From 43b4e7f8afabc28db10878caff302f343ed0e128 Mon Sep 17 00:00:00 2001 From: "N. L." Date: Fri, 15 Dec 2023 12:14:56 +0100 Subject: [PATCH] docs(notebook-link): update link to example notebooks --- README.md | 6 +- .../battery_water_level_analysis.ipynb | 6293 +-- .../extreme_anomaly_df_analysis.ipynb | 32304 +--------------- pyproject.toml | 2 +- src/anomalytics/__init__.py | 2 +- tests/test_version.py | 2 +- 6 files changed, 171 insertions(+), 38438 deletions(-) diff --git a/README.md b/README.md index 3edebeb..a55ce74 100644 --- a/README.md +++ b/README.md @@ -78,8 +78,8 @@ $ pip3 install "anomalytics[codequality,docs,security,testcov,extra]" `anomalytics` can be used to analyze anomalies in your dataset (both as `pandas.DataFrame` or `pandas.Series`). To start, let's follow along with this minimum example where we want to detect extremely high anomalies in our dataset. Read the walkthrough below, or the concrete examples here: -* [Extreme Anomaly Analysis - DataFrame](docs/examples/extreme_anomaly_df_analysis.ipynb) -* [Battery Water Level Analysis - Time Series](docs/examples/battery_water_level_analysis.ipynb) +* [Extreme Anomaly Analysis - DataFrame](https://github.com/Aeternalis-Ingenium/anomalytics/blob/trunk/docs/examples/extreme_anomaly_df_analysis.ipynb) +* [Battery Water Level Analysis - Time Series](https://github.com/Aeternalis-Ingenium/anomalytics/blob/trunk/docs/examples/battery_water_level_analysis.ipynb) ### Anomaly Detection via the `Detector` Instance @@ -142,7 +142,7 @@ Read the walkthrough below, or the concrete examples here: T2: 10000 ``` - ![Ad Impressions Hist]([docs/assets/readme/02-AdImpressionsNormDistributions.png](https://github.com/Aeternalis-Ingenium/anomalytics/raw/trunk/docs/assets/readme/02-AdImpressionsNormDistributions.png)) + ![Ad Impressions Hist](https://github.com/Aeternalis-Ingenium/anomalytics/raw/trunk/docs/assets/readme/02-AdImpressionsNormDistributions.png) 4. Now, we can extract exceedances by giving the expected `q`uantile: diff --git a/docs/examples/battery_water_level_analysis.ipynb b/docs/examples/battery_water_level_analysis.ipynb index 603e3b7..1d20714 100644 --- a/docs/examples/battery_water_level_analysis.ipynb +++ b/docs/examples/battery_water_level_analysis.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 40, "metadata": {}, "outputs": [ { @@ -10,6 +10,8 @@ "output_type": "stream", "text": [ "Requirement already satisfied: anomalytics in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (0.1.8)\n", + "Collecting anomalytics\n", + " Downloading anomalytics-0.1.9-py3-none-any.whl.metadata (24 kB)\n", "Requirement already satisfied: matplotlib>=3.7.2 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from anomalytics) (3.8.2)\n", "Requirement already satisfied: numpy>=1.25.2 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from anomalytics) (1.26.2)\n", "Requirement already satisfied: pandas>=2.0.3 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from anomalytics) (2.1.3)\n", @@ -25,173 +27,25 @@ "Requirement already satisfied: pytz>=2020.1 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from pandas>=2.0.3->anomalytics) (2023.3.post1)\n", "Requirement already satisfied: tzdata>=2022.1 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from pandas>=2.0.3->anomalytics) (2023.3)\n", "Requirement already satisfied: six>=1.5 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from python-dateutil>=2.7->matplotlib>=3.7.2->anomalytics) (1.16.0)\n", - "Note: you may need to restart the kernel to use updated packages.\n", - "Package Version\n", - "------------------------- ------------\n", - "anomalytics 0.1.8\n", - "anyio 4.1.0\n", - "appnope 0.1.3\n", - "argon2-cffi 23.1.0\n", - "argon2-cffi-bindings 21.2.0\n", - "arrow 1.3.0\n", - "asttokens 2.4.1\n", - "async-lru 2.0.4\n", - "attrs 23.1.0\n", - "Babel 2.13.1\n", - "beautifulsoup4 4.12.2\n", - "bleach 6.1.0\n", - "blinker 1.7.0\n", - "boto3 1.33.6\n", - "botocore 1.33.6\n", - "Brotli 1.1.0\n", - "cached-property 1.5.2\n", - "certifi 2023.11.17\n", - "cffi 1.16.0\n", - "charset-normalizer 3.3.2\n", - "click 8.1.7\n", - "cloudpickle 3.0.0\n", - "colorama 0.4.6\n", - "comm 0.1.4\n", - "contourpy 1.2.0\n", - "cycler 0.12.1\n", - "debugpy 1.8.0\n", - "decorator 5.1.1\n", - "defusedxml 0.7.1\n", - "entrypoints 0.4\n", - "et-xmlfile 1.1.0\n", - "exceptiongroup 1.2.0\n", - "executing 2.0.1\n", - "fastjsonschema 2.19.0\n", - "Flask 3.0.0\n", - "fonttools 4.46.0\n", - "fqdn 1.5.1\n", - "gym 0.26.2\n", - "gym-notices 0.0.8\n", - "h5py 3.10.0\n", - "idna 3.6\n", - "importlib-metadata 7.0.0\n", - "importlib-resources 6.1.1\n", - "ipykernel 6.26.0\n", - "ipython 8.18.1\n", - "ipywidgets 8.1.1\n", - "isoduration 20.11.0\n", - "itsdangerous 2.1.2\n", - "jedi 0.19.1\n", - "Jinja2 3.1.2\n", - "jmespath 1.0.1\n", - "joblib 1.3.2\n", - "json5 0.9.14\n", - "jsonpointer 2.4\n", - "jsonschema 4.20.0\n", - "jsonschema-specifications 2023.11.2\n", - "jupyter 1.0.0\n", - "jupyter_client 8.6.0\n", - "jupyter-console 6.6.3\n", - "jupyter_core 5.5.0\n", - "jupyter-events 0.9.0\n", - "jupyter-lsp 2.2.1\n", - "jupyter_server 2.11.1\n", - "jupyter_server_terminals 0.4.4\n", - "jupyterlab 4.0.9\n", - "jupyterlab_pygments 0.3.0\n", - "jupyterlab_server 2.25.2\n", - "jupyterlab-widgets 3.0.9\n", - "kaggle 1.5.16\n", - "kiwisolver 1.4.5\n", - "lxml 4.9.3\n", - "MarkupSafe 2.1.3\n", - "matplotlib 3.8.2\n", - "matplotlib-inline 0.1.6\n", - "mistune 3.0.2\n", - "munkres 1.1.4\n", - "nbclient 0.8.0\n", - "nbconvert 7.11.0\n", - "nbformat 5.9.2\n", - "nest-asyncio 1.5.8\n", - "notebook 7.0.6\n", - "notebook_shim 0.2.3\n", - "numpy 1.26.2\n", - "openpyxl 3.1.2\n", - "overrides 7.4.0\n", - "packaging 23.2\n", - "pandas 2.1.3\n", - "pandas-datareader 0.10.0\n", - "pandocfilters 1.5.0\n", - "parso 0.8.3\n", - "pexpect 4.8.0\n", - "pickleshare 0.7.5\n", - "Pillow 10.1.0\n", - "pip 23.3.1\n", - "pkgutil_resolve_name 1.3.10\n", - "platformdirs 4.0.0\n", - "prometheus-client 0.19.0\n", - "prompt-toolkit 3.0.41\n", - "psutil 5.9.5\n", - "ptyprocess 0.7.0\n", - "pure-eval 0.2.2\n", - "pycparser 2.21\n", - "Pygments 2.17.2\n", - "pyobjc-core 10.0\n", - "pyobjc-framework-Cocoa 10.0\n", - "pyparsing 3.1.1\n", - "PySocks 1.7.1\n", - "python-dateutil 2.8.2\n", - "python-json-logger 2.0.7\n", - "python-slugify 8.0.1\n", - "pytz 2023.3.post1\n", - "PyYAML 6.0.1\n", - "pyzmq 25.1.1\n", - "qtconsole 5.5.1\n", - "QtPy 2.4.1\n", - "referencing 0.31.1\n", - "requests 2.31.0\n", - "rfc3339-validator 0.1.4\n", - "rfc3986-validator 0.1.1\n", - "rpds-py 0.13.2\n", - "s3transfer 0.8.2\n", - "scikit-learn 1.3.2\n", - "SciPy 1.11.4\n", - "seaborn 0.13.0\n", - "Send2Trash 1.8.2\n", - "setuptools 68.2.2\n", - "six 1.16.0\n", - "sniffio 1.3.0\n", - "soupsieve 2.5\n", - "stack-data 0.6.2\n", - "terminado 0.18.0\n", - "text-unidecode 1.3\n", - "threadpoolctl 3.2.0\n", - "tinycss2 1.2.1\n", - "tomli 2.0.1\n", - "tornado 6.3.3\n", - "tqdm 4.66.1\n", - "traitlets 5.14.0\n", - "types-python-dateutil 2.8.19.14\n", - "typing_extensions 4.8.0\n", - "typing-utils 0.1.0\n", - "tzdata 2023.3\n", - "uri-template 1.3.0\n", - "urllib3 1.26.18\n", - "wcwidth 0.2.12\n", - "webcolors 1.13\n", - "webencodings 0.5.1\n", - "websocket-client 1.7.0\n", - "Werkzeug 3.0.1\n", - "wheel 0.42.0\n", - "widgetsnbextension 4.0.9\n", - "zipp 3.17.0\n", + "Downloading anomalytics-0.1.9-py3-none-any.whl (49 kB)\n", + "\u001b[2K \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.6/49.6 kB\u001b[0m \u001b[31m2.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hInstalling collected packages: anomalytics\n", + " Attempting uninstall: anomalytics\n", + " Found existing installation: anomalytics 0.1.8\n", + " Uninstalling anomalytics-0.1.8:\n", + " Successfully uninstalled anomalytics-0.1.8\n", + "Successfully installed anomalytics-0.1.9\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } ], "source": [ - "%pip install --upgrade anomalytics\n", - "%pip list" + "%pip install --upgrade anomalytics" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ @@ -232,7 +86,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 42, "metadata": {}, "outputs": [ { @@ -246,7 +100,7 @@ "Name: Water Level, dtype: float64" ] }, - "execution_count": 4, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } @@ -270,7 +124,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 43, "metadata": {}, "outputs": [ { @@ -287,7 +141,7 @@ "Name: Water Level, dtype: float64" ] }, - "execution_count": 5, + "execution_count": 43, "metadata": {}, "output_type": "execute_result" } @@ -298,7 +152,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 44, "metadata": {}, "outputs": [ { @@ -331,7 +185,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 45, "metadata": {}, "outputs": [ { @@ -340,7 +194,7 @@ "'POT'" ] }, - "execution_count": 7, + "execution_count": 45, "metadata": {}, "output_type": "execute_result" } @@ -356,7 +210,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 46, "metadata": {}, "outputs": [ { @@ -376,7 +230,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 47, "metadata": {}, "outputs": [], "source": [ @@ -391,7 +245,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 48, "metadata": {}, "outputs": [ { @@ -412,7 +266,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 49, "metadata": {}, "outputs": [ { @@ -439,7 +293,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 50, "metadata": {}, "outputs": [ { @@ -468,7 +322,7 @@ "Name: Water Level, dtype: float64" ] }, - "execution_count": 12, + "execution_count": 50, "metadata": {}, "output_type": "execute_result" } @@ -480,7 +334,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 51, "metadata": {}, "outputs": [ { @@ -518,7 +372,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 52, "metadata": {}, "outputs": [ { @@ -547,7 +401,7 @@ "Name: anomaly scores, dtype: float64" ] }, - "execution_count": 14, + "execution_count": 52, "metadata": {}, "output_type": "execute_result" } @@ -559,7 +413,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 53, "metadata": {}, "outputs": [ { @@ -579,6027 +433,32 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{0: {'index': Timestamp('2016-04-03 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 1: {'index': Timestamp('2016-04-03 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 2: {'index': Timestamp('2016-04-03 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 3: {'index': Timestamp('2016-04-03 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 4: {'index': Timestamp('2016-04-03 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 5: {'index': Timestamp('2016-04-03 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 6: {'index': Timestamp('2016-04-03 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 7: {'index': Timestamp('2016-04-03 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 8: {'index': Timestamp('2016-04-03 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 9: {'index': Timestamp('2016-04-04 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 10: {'index': Timestamp('2016-04-04 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 11: {'index': Timestamp('2016-04-04 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 12: {'index': Timestamp('2016-04-04 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 13: {'index': Timestamp('2016-04-04 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 14: {'index': Timestamp('2016-04-04 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 15: {'index': Timestamp('2016-04-04 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 16: {'index': Timestamp('2016-04-04 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 17: {'index': Timestamp('2016-04-04 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 18: {'index': Timestamp('2016-04-04 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 19: {'index': Timestamp('2016-04-04 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 20: {'index': Timestamp('2016-04-04 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 21: {'index': Timestamp('2016-04-04 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 22: {'index': Timestamp('2016-04-04 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 23: {'index': Timestamp('2016-04-04 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 24: {'index': Timestamp('2016-04-04 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 25: {'index': Timestamp('2016-04-04 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 26: {'index': Timestamp('2016-04-04 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 27: {'index': Timestamp('2016-04-04 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 28: {'index': Timestamp('2016-04-04 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 29: {'index': Timestamp('2016-04-04 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 30: {'index': Timestamp('2016-04-04 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 31: {'index': Timestamp('2016-04-04 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 32: {'index': Timestamp('2016-04-04 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 33: {'index': Timestamp('2016-04-05 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 34: {'index': Timestamp('2016-04-05 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 35: {'index': Timestamp('2016-04-05 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 36: {'index': Timestamp('2016-04-05 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 37: {'index': Timestamp('2016-04-05 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 38: {'index': Timestamp('2016-04-05 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 39: {'index': Timestamp('2016-04-05 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 40: {'index': Timestamp('2016-04-05 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 41: {'index': Timestamp('2016-04-05 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 42: {'index': Timestamp('2016-04-05 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 43: {'index': Timestamp('2016-04-05 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 44: {'index': Timestamp('2016-04-05 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 45: {'index': Timestamp('2016-04-05 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 46: {'index': Timestamp('2016-04-05 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 47: {'index': Timestamp('2016-04-05 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 48: {'index': Timestamp('2016-04-05 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 49: {'index': Timestamp('2016-04-05 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 50: {'index': Timestamp('2016-04-05 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 51: {'index': Timestamp('2016-04-05 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 52: {'index': Timestamp('2016-04-05 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 53: {'index': Timestamp('2016-04-05 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 54: {'index': Timestamp('2016-04-05 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 55: {'index': Timestamp('2016-04-05 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 56: {'index': Timestamp('2016-04-05 23:00:00'),\n", - " 'c': 0.030115819897238248,\n", - " 'loc': 0,\n", - " 'scale': 0.13738043918486165,\n", - " 'p_value': 0.5195442432679798,\n", - " 'anomaly_score': 1.9247638925029955},\n", - " 57: {'index': Timestamp('2016-04-06 00:00:00'),\n", - " 'c': 0.03011614384167466,\n", - " 'loc': 0,\n", - " 'scale': 0.13738660684242116,\n", - " 'p_value': 0.5190035252524193,\n", - " 'anomaly_score': 1.9267691862278704},\n", - " 58: {'index': Timestamp('2016-04-06 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 59: {'index': Timestamp('2016-04-06 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 60: {'index': Timestamp('2016-04-06 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 61: {'index': Timestamp('2016-04-06 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 62: {'index': Timestamp('2016-04-06 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 63: {'index': Timestamp('2016-04-06 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 64: {'index': Timestamp('2016-04-06 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 65: {'index': Timestamp('2016-04-06 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 66: {'index': Timestamp('2016-04-06 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 67: {'index': Timestamp('2016-04-06 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 68: {'index': Timestamp('2016-04-06 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 69: {'index': Timestamp('2016-04-06 12:00:00'),\n", - " 'c': 0.030047368988989326,\n", - " 'loc': 0,\n", - " 'scale': 0.13737083220828827,\n", - " 'p_value': 0.5079666517939416,\n", - " 'anomaly_score': 1.9686331700484412},\n", - " 70: {'index': Timestamp('2016-04-06 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 71: {'index': Timestamp('2016-04-06 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 72: {'index': Timestamp('2016-04-06 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 73: {'index': Timestamp('2016-04-06 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 74: {'index': Timestamp('2016-04-06 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 75: {'index': Timestamp('2016-04-06 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 76: {'index': Timestamp('2016-04-06 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 77: {'index': Timestamp('2016-04-06 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 78: {'index': Timestamp('2016-04-06 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 79: {'index': Timestamp('2016-04-06 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 80: {'index': Timestamp('2016-04-06 23:00:00'),\n", - " 'c': 0.030046930110468616,\n", - " 'loc': 0,\n", - " 'scale': 0.13734438566103221,\n", - " 'p_value': 0.8966983997441095,\n", - " 'anomaly_score': 1.1152021686281248},\n", - " 81: {'index': Timestamp('2016-04-07 00:00:00'),\n", - " 'c': 0.03016532279231214,\n", - " 'loc': 0,\n", - " 'scale': 0.1373167332843332,\n", - " 'p_value': 0.30934182350176403,\n", - " 'anomaly_score': 3.2326698946814005},\n", - " 82: {'index': Timestamp('2016-04-07 01:00:00'),\n", - " 'c': 0.030090021594412285,\n", - " 'loc': 0,\n", - " 'scale': 0.13732031883456136,\n", - " 'p_value': 0.28434182742226083,\n", - " 'anomaly_score': 3.516893765034975},\n", - " 83: {'index': Timestamp('2016-04-07 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 84: {'index': Timestamp('2016-04-07 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 85: {'index': Timestamp('2016-04-07 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 86: {'index': Timestamp('2016-04-07 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 87: {'index': Timestamp('2016-04-07 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 88: {'index': Timestamp('2016-04-07 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 89: {'index': Timestamp('2016-04-07 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 90: {'index': Timestamp('2016-04-07 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 91: {'index': Timestamp('2016-04-07 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 92: {'index': Timestamp('2016-04-07 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 93: {'index': Timestamp('2016-04-07 12:00:00'),\n", - " 'c': 0.029928832388606705,\n", - " 'loc': 0,\n", - " 'scale': 0.13734640264084272,\n", - " 'p_value': 0.5188840943100294,\n", - " 'anomaly_score': 1.9272126684278503},\n", - " 94: {'index': Timestamp('2016-04-07 13:00:00'),\n", - " 'c': 0.029960411929126195,\n", - " 'loc': 0,\n", - " 'scale': 0.1373295081141871,\n", - " 'p_value': 0.43732892610401514,\n", - " 'anomaly_score': 2.2866084091637653},\n", - " 95: {'index': Timestamp('2016-04-07 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 96: {'index': Timestamp('2016-04-07 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 97: {'index': Timestamp('2016-04-07 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 98: {'index': Timestamp('2016-04-07 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 99: {'index': Timestamp('2016-04-07 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 100: {'index': Timestamp('2016-04-07 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 101: {'index': Timestamp('2016-04-07 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 102: {'index': Timestamp('2016-04-07 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 103: {'index': Timestamp('2016-04-07 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 104: {'index': Timestamp('2016-04-07 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 105: {'index': Timestamp('2016-04-08 00:00:00'),\n", - " 'c': 0.02985435533427018,\n", - " 'loc': 0,\n", - " 'scale': 0.13734401699810536,\n", - " 'p_value': 0.36636112818248295,\n", - " 'anomaly_score': 2.7295472228754143},\n", - " 106: {'index': Timestamp('2016-04-08 01:00:00'),\n", - " 'c': 0.029818992458448133,\n", - " 'loc': 0,\n", - " 'scale': 0.13733317176917975,\n", - " 'p_value': 0.052509615390933295,\n", - " 'anomaly_score': 19.044131109226665},\n", - " 107: {'index': Timestamp('2016-04-08 02:00:00'),\n", - " 'c': 0.029730060728011414,\n", - " 'loc': 0,\n", - " 'scale': 0.13745136295349106,\n", - " 'p_value': 0.07974752698759212,\n", - " 'anomaly_score': 12.539573799643838},\n", - " 108: {'index': Timestamp('2016-04-08 03:00:00'),\n", - " 'c': 0.029629626925736292,\n", - " 'loc': 0,\n", - " 'scale': 0.1375268777909746,\n", - " 'p_value': 0.676796923608791,\n", - " 'anomaly_score': 1.4775480873462572},\n", - " 109: {'index': Timestamp('2016-04-08 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 110: {'index': Timestamp('2016-04-08 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 111: {'index': Timestamp('2016-04-08 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 112: {'index': Timestamp('2016-04-08 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 113: {'index': Timestamp('2016-04-08 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 114: {'index': Timestamp('2016-04-08 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 115: {'index': Timestamp('2016-04-08 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 116: {'index': Timestamp('2016-04-08 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 117: {'index': Timestamp('2016-04-08 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 118: {'index': Timestamp('2016-04-08 13:00:00'),\n", - " 'c': 0.0296402012631307,\n", - " 'loc': 0,\n", - " 'scale': 0.13748292529779288,\n", - " 'p_value': 0.7816083774361311,\n", - " 'anomaly_score': 1.279413103631575},\n", - " 119: {'index': Timestamp('2016-04-08 14:00:00'),\n", - " 'c': 0.02973814611783518,\n", - " 'loc': 0,\n", - " 'scale': 0.1374414242536956,\n", - " 'p_value': 0.5903826613252281,\n", - " 'anomaly_score': 1.693816681125605},\n", - " 120: {'index': Timestamp('2016-04-08 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 121: {'index': Timestamp('2016-04-08 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 122: {'index': Timestamp('2016-04-08 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 123: {'index': Timestamp('2016-04-08 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 124: {'index': Timestamp('2016-04-08 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 125: {'index': Timestamp('2016-04-08 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 126: {'index': Timestamp('2016-04-08 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 127: {'index': Timestamp('2016-04-08 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 128: {'index': Timestamp('2016-04-08 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 129: {'index': Timestamp('2016-04-09 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 130: {'index': Timestamp('2016-04-09 01:00:00'),\n", - " 'c': 0.02977649220384756,\n", - " 'loc': 0,\n", - " 'scale': 0.13742512296489268,\n", - " 'p_value': 0.9434960283342338,\n", - " 'anomaly_score': 1.0598878744254232},\n", - " 131: {'index': Timestamp('2016-04-09 02:00:00'),\n", - " 'c': 0.029871280734027443,\n", - " 'loc': 0,\n", - " 'scale': 0.1373588981195223,\n", - " 'p_value': 0.305071072258564,\n", - " 'anomaly_score': 3.2779246901274424},\n", - " 132: {'index': Timestamp('2016-04-09 03:00:00'),\n", - " 'c': 0.029798339805772234,\n", - " 'loc': 0,\n", - " 'scale': 0.13737888978387697,\n", - " 'p_value': 0.5007635531749924,\n", - " 'anomaly_score': 1.9969504442959105},\n", - " 133: {'index': Timestamp('2016-04-09 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 134: {'index': Timestamp('2016-04-09 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 135: {'index': Timestamp('2016-04-09 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 136: {'index': Timestamp('2016-04-09 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 137: {'index': Timestamp('2016-04-09 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 138: {'index': Timestamp('2016-04-09 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 139: {'index': Timestamp('2016-04-09 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 140: {'index': Timestamp('2016-04-09 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 141: {'index': Timestamp('2016-04-09 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 142: {'index': Timestamp('2016-04-09 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 143: {'index': Timestamp('2016-04-09 14:00:00'),\n", - " 'c': 0.029711210852800388,\n", - " 'loc': 0,\n", - " 'scale': 0.13737416160889354,\n", - " 'p_value': 0.4017145002154631,\n", - " 'anomaly_score': 2.4893301074858916},\n", - " 144: {'index': Timestamp('2016-04-09 15:00:00'),\n", - " 'c': 0.029704350719657872,\n", - " 'loc': 0,\n", - " 'scale': 0.13738262676851443,\n", - " 'p_value': 0.4500397965909572,\n", - " 'anomaly_score': 2.222025713225765},\n", - " 145: {'index': Timestamp('2016-04-09 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 146: {'index': Timestamp('2016-04-09 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 147: {'index': Timestamp('2016-04-09 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 148: {'index': Timestamp('2016-04-09 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 149: {'index': Timestamp('2016-04-09 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 150: {'index': Timestamp('2016-04-09 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 151: {'index': Timestamp('2016-04-09 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 152: {'index': Timestamp('2016-04-09 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 153: {'index': Timestamp('2016-04-10 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 154: {'index': Timestamp('2016-04-10 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 155: {'index': Timestamp('2016-04-10 02:00:00'),\n", - " 'c': 0.029605507615101667,\n", - " 'loc': 0,\n", - " 'scale': 0.13737045856183255,\n", - " 'p_value': 0.2965918395076433,\n", - " 'anomaly_score': 3.3716369326278435},\n", - " 156: {'index': Timestamp('2016-04-10 03:00:00'),\n", - " 'c': 0.029526375458111292,\n", - " 'loc': 0,\n", - " 'scale': 0.13739766888535238,\n", - " 'p_value': 0.21810676782662128,\n", - " 'anomaly_score': 4.584910454474874},\n", - " 157: {'index': Timestamp('2016-04-10 04:00:00'),\n", - " 'c': 0.029401245313211897,\n", - " 'loc': 0,\n", - " 'scale': 0.1374514702153667,\n", - " 'p_value': 0.4193240244473115,\n", - " 'anomaly_score': 2.384790619421452},\n", - " 158: {'index': Timestamp('2016-04-10 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 159: {'index': Timestamp('2016-04-10 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 160: {'index': Timestamp('2016-04-10 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 161: {'index': Timestamp('2016-04-10 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 162: {'index': Timestamp('2016-04-10 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 163: {'index': Timestamp('2016-04-10 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 164: {'index': Timestamp('2016-04-10 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 165: {'index': Timestamp('2016-04-10 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 166: {'index': Timestamp('2016-04-10 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 167: {'index': Timestamp('2016-04-10 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 168: {'index': Timestamp('2016-04-10 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 169: {'index': Timestamp('2016-04-10 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 170: {'index': Timestamp('2016-04-10 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 171: {'index': Timestamp('2016-04-10 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 172: {'index': Timestamp('2016-04-10 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 173: {'index': Timestamp('2016-04-10 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 174: {'index': Timestamp('2016-04-10 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 175: {'index': Timestamp('2016-04-10 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 176: {'index': Timestamp('2016-04-10 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 177: {'index': Timestamp('2016-04-11 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 178: {'index': Timestamp('2016-04-11 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 179: {'index': Timestamp('2016-04-11 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 180: {'index': Timestamp('2016-04-11 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 181: {'index': Timestamp('2016-04-11 04:00:00'),\n", - " 'c': 0.029357673217943976,\n", - " 'loc': 0,\n", - " 'scale': 0.13743491902425997,\n", - " 'p_value': 0.8161754482420212,\n", - " 'anomaly_score': 1.2252267599496196},\n", - " 182: {'index': Timestamp('2016-04-11 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 183: {'index': Timestamp('2016-04-11 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 184: {'index': Timestamp('2016-04-11 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 185: {'index': Timestamp('2016-04-11 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 186: {'index': Timestamp('2016-04-11 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 187: {'index': Timestamp('2016-04-11 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 188: {'index': Timestamp('2016-04-11 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 189: {'index': Timestamp('2016-04-11 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 190: {'index': Timestamp('2016-04-11 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 191: {'index': Timestamp('2016-04-11 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 192: {'index': Timestamp('2016-04-11 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 193: {'index': Timestamp('2016-04-11 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 194: {'index': Timestamp('2016-04-11 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 195: {'index': Timestamp('2016-04-11 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 196: {'index': Timestamp('2016-04-11 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 197: {'index': Timestamp('2016-04-11 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 198: {'index': Timestamp('2016-04-11 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 199: {'index': Timestamp('2016-04-11 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 200: {'index': Timestamp('2016-04-11 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 201: {'index': Timestamp('2016-04-12 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 202: {'index': Timestamp('2016-04-12 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 203: {'index': Timestamp('2016-04-12 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 204: {'index': Timestamp('2016-04-12 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 205: {'index': Timestamp('2016-04-12 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 206: {'index': Timestamp('2016-04-12 05:00:00'),\n", - " 'c': 0.02945304955926311,\n", - " 'loc': 0,\n", - " 'scale': 0.13740597885461447,\n", - " 'p_value': 0.7814964948541101,\n", - " 'anomaly_score': 1.2795962702131891},\n", - " 207: {'index': Timestamp('2016-04-12 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 208: {'index': Timestamp('2016-04-12 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 209: {'index': Timestamp('2016-04-12 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 210: {'index': Timestamp('2016-04-12 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 211: {'index': Timestamp('2016-04-12 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 212: {'index': Timestamp('2016-04-12 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 213: {'index': Timestamp('2016-04-12 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 214: {'index': Timestamp('2016-04-12 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 215: {'index': Timestamp('2016-04-12 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 216: {'index': Timestamp('2016-04-12 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 217: {'index': Timestamp('2016-04-12 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 218: {'index': Timestamp('2016-04-12 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 219: {'index': Timestamp('2016-04-12 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 220: {'index': Timestamp('2016-04-12 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 221: {'index': Timestamp('2016-04-12 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 222: {'index': Timestamp('2016-04-12 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 223: {'index': Timestamp('2016-04-12 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 224: {'index': Timestamp('2016-04-12 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 225: {'index': Timestamp('2016-04-13 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 226: {'index': Timestamp('2016-04-13 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 227: {'index': Timestamp('2016-04-13 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 228: {'index': Timestamp('2016-04-13 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 229: {'index': Timestamp('2016-04-13 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 230: {'index': Timestamp('2016-04-13 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 231: {'index': Timestamp('2016-04-13 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 232: {'index': Timestamp('2016-04-13 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 233: {'index': Timestamp('2016-04-13 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 234: {'index': Timestamp('2016-04-13 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 235: {'index': Timestamp('2016-04-13 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 236: {'index': Timestamp('2016-04-13 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 237: {'index': Timestamp('2016-04-13 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 238: {'index': Timestamp('2016-04-13 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 239: {'index': Timestamp('2016-04-13 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 240: {'index': Timestamp('2016-04-13 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 241: {'index': Timestamp('2016-04-13 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 242: {'index': Timestamp('2016-04-13 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 243: {'index': Timestamp('2016-04-13 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 244: {'index': Timestamp('2016-04-13 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 245: {'index': Timestamp('2016-04-13 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 246: {'index': Timestamp('2016-04-13 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 247: {'index': Timestamp('2016-04-13 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 248: {'index': Timestamp('2016-04-13 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 249: {'index': Timestamp('2016-04-14 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 250: {'index': Timestamp('2016-04-14 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 251: {'index': Timestamp('2016-04-14 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 252: {'index': Timestamp('2016-04-14 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 253: {'index': Timestamp('2016-04-14 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 254: {'index': Timestamp('2016-04-14 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 255: {'index': Timestamp('2016-04-14 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 256: {'index': Timestamp('2016-04-14 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 257: {'index': Timestamp('2016-04-14 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 258: {'index': Timestamp('2016-04-14 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 259: {'index': Timestamp('2016-04-14 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 260: {'index': Timestamp('2016-04-14 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 261: {'index': Timestamp('2016-04-14 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 262: {'index': Timestamp('2016-04-14 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 263: {'index': Timestamp('2016-04-14 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 264: {'index': Timestamp('2016-04-14 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 265: {'index': Timestamp('2016-04-14 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 266: {'index': Timestamp('2016-04-14 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 267: {'index': Timestamp('2016-04-14 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 268: {'index': Timestamp('2016-04-14 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 269: {'index': Timestamp('2016-04-14 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 270: {'index': Timestamp('2016-04-14 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 271: {'index': Timestamp('2016-04-14 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 272: {'index': Timestamp('2016-04-14 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 273: {'index': Timestamp('2016-04-15 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 274: {'index': Timestamp('2016-04-15 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 275: {'index': Timestamp('2016-04-15 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 276: {'index': Timestamp('2016-04-15 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 277: {'index': Timestamp('2016-04-15 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 278: {'index': Timestamp('2016-04-15 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 279: {'index': Timestamp('2016-04-15 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 280: {'index': Timestamp('2016-04-15 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 281: {'index': Timestamp('2016-04-15 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 282: {'index': Timestamp('2016-04-15 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 283: {'index': Timestamp('2016-04-15 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 284: {'index': Timestamp('2016-04-15 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 285: {'index': Timestamp('2016-04-15 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 286: {'index': Timestamp('2016-04-15 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 287: {'index': Timestamp('2016-04-15 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 288: {'index': Timestamp('2016-04-15 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 289: {'index': Timestamp('2016-04-15 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 290: {'index': Timestamp('2016-04-15 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 291: {'index': Timestamp('2016-04-15 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 292: {'index': Timestamp('2016-04-15 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 293: {'index': Timestamp('2016-04-15 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 294: {'index': Timestamp('2016-04-15 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 295: {'index': Timestamp('2016-04-15 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 296: {'index': Timestamp('2016-04-15 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 297: {'index': Timestamp('2016-04-16 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 298: {'index': Timestamp('2016-04-16 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 299: {'index': Timestamp('2016-04-16 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 300: {'index': Timestamp('2016-04-16 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 301: {'index': Timestamp('2016-04-16 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 302: {'index': Timestamp('2016-04-16 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 303: {'index': Timestamp('2016-04-16 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 304: {'index': Timestamp('2016-04-16 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 305: {'index': Timestamp('2016-04-16 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 306: {'index': Timestamp('2016-04-16 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 307: {'index': Timestamp('2016-04-16 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 308: {'index': Timestamp('2016-04-16 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 309: {'index': Timestamp('2016-04-16 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 310: {'index': Timestamp('2016-04-16 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 311: {'index': Timestamp('2016-04-16 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 312: {'index': Timestamp('2016-04-16 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 313: {'index': Timestamp('2016-04-16 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 314: {'index': Timestamp('2016-04-16 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 315: {'index': Timestamp('2016-04-16 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 316: {'index': Timestamp('2016-04-16 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 317: {'index': Timestamp('2016-04-16 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 318: {'index': Timestamp('2016-04-16 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 319: {'index': Timestamp('2016-04-16 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 320: {'index': Timestamp('2016-04-16 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 321: {'index': Timestamp('2016-04-17 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 322: {'index': Timestamp('2016-04-17 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 323: {'index': Timestamp('2016-04-17 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 324: {'index': Timestamp('2016-04-17 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 325: {'index': Timestamp('2016-04-17 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 326: {'index': Timestamp('2016-04-17 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 327: {'index': Timestamp('2016-04-17 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 328: {'index': Timestamp('2016-04-17 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 329: {'index': Timestamp('2016-04-17 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 330: {'index': Timestamp('2016-04-17 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 331: {'index': Timestamp('2016-04-17 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 332: {'index': Timestamp('2016-04-17 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 333: {'index': Timestamp('2016-04-17 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 334: {'index': Timestamp('2016-04-17 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 335: {'index': Timestamp('2016-04-17 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 336: {'index': Timestamp('2016-04-17 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 337: {'index': Timestamp('2016-04-17 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 338: {'index': Timestamp('2016-04-17 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 339: {'index': Timestamp('2016-04-17 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 340: {'index': Timestamp('2016-04-17 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 341: {'index': Timestamp('2016-04-17 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 342: {'index': Timestamp('2016-04-17 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 343: {'index': Timestamp('2016-04-17 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 344: {'index': Timestamp('2016-04-17 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 345: {'index': Timestamp('2016-04-18 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 346: {'index': Timestamp('2016-04-18 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 347: {'index': Timestamp('2016-04-18 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 348: {'index': Timestamp('2016-04-18 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 349: {'index': Timestamp('2016-04-18 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 350: {'index': Timestamp('2016-04-18 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 351: {'index': Timestamp('2016-04-18 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 352: {'index': Timestamp('2016-04-18 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 353: {'index': Timestamp('2016-04-18 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 354: {'index': Timestamp('2016-04-18 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 355: {'index': Timestamp('2016-04-18 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 356: {'index': Timestamp('2016-04-18 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 357: {'index': Timestamp('2016-04-18 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 358: {'index': Timestamp('2016-04-18 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 359: {'index': Timestamp('2016-04-18 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 360: {'index': Timestamp('2016-04-18 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 361: {'index': Timestamp('2016-04-18 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 362: {'index': Timestamp('2016-04-18 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 363: {'index': Timestamp('2016-04-18 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 364: {'index': Timestamp('2016-04-18 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 365: {'index': Timestamp('2016-04-18 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 366: {'index': Timestamp('2016-04-18 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 367: {'index': Timestamp('2016-04-18 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 368: {'index': Timestamp('2016-04-18 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 369: {'index': Timestamp('2016-04-19 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 370: {'index': Timestamp('2016-04-19 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 371: {'index': Timestamp('2016-04-19 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 372: {'index': Timestamp('2016-04-19 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 373: {'index': Timestamp('2016-04-19 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 374: {'index': Timestamp('2016-04-19 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 375: {'index': Timestamp('2016-04-19 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 376: {'index': Timestamp('2016-04-19 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 377: {'index': Timestamp('2016-04-19 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 378: {'index': Timestamp('2016-04-19 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 379: {'index': Timestamp('2016-04-19 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 380: {'index': Timestamp('2016-04-19 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 381: {'index': Timestamp('2016-04-19 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 382: {'index': Timestamp('2016-04-19 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 383: {'index': Timestamp('2016-04-19 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 384: {'index': Timestamp('2016-04-19 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 385: {'index': Timestamp('2016-04-19 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 386: {'index': Timestamp('2016-04-19 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 387: {'index': Timestamp('2016-04-19 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 388: {'index': Timestamp('2016-04-19 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 389: {'index': Timestamp('2016-04-19 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 390: {'index': Timestamp('2016-04-19 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 391: {'index': Timestamp('2016-04-19 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 392: {'index': Timestamp('2016-04-19 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 393: {'index': Timestamp('2016-04-20 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 394: {'index': Timestamp('2016-04-20 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 395: {'index': Timestamp('2016-04-20 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 396: {'index': Timestamp('2016-04-20 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 397: {'index': Timestamp('2016-04-20 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 398: {'index': Timestamp('2016-04-20 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 399: {'index': Timestamp('2016-04-20 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 400: {'index': Timestamp('2016-04-20 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 401: {'index': Timestamp('2016-04-20 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 402: {'index': Timestamp('2016-04-20 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 403: {'index': Timestamp('2016-04-20 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 404: {'index': Timestamp('2016-04-20 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 405: {'index': Timestamp('2016-04-20 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 406: {'index': Timestamp('2016-04-20 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 407: {'index': Timestamp('2016-04-20 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 408: {'index': Timestamp('2016-04-20 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 409: {'index': Timestamp('2016-04-20 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 410: {'index': Timestamp('2016-04-20 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 411: {'index': Timestamp('2016-04-20 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 412: {'index': Timestamp('2016-04-20 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 413: {'index': Timestamp('2016-04-20 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 414: {'index': Timestamp('2016-04-20 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 415: {'index': Timestamp('2016-04-20 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 416: {'index': Timestamp('2016-04-20 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 417: {'index': Timestamp('2016-04-21 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 418: {'index': Timestamp('2016-04-21 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 419: {'index': Timestamp('2016-04-21 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 420: {'index': Timestamp('2016-04-21 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 421: {'index': Timestamp('2016-04-21 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 422: {'index': Timestamp('2016-04-21 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 423: {'index': Timestamp('2016-04-21 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 424: {'index': Timestamp('2016-04-21 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 425: {'index': Timestamp('2016-04-21 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 426: {'index': Timestamp('2016-04-21 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 427: {'index': Timestamp('2016-04-21 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 428: {'index': Timestamp('2016-04-21 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 429: {'index': Timestamp('2016-04-21 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 430: {'index': Timestamp('2016-04-21 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 431: {'index': Timestamp('2016-04-21 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 432: {'index': Timestamp('2016-04-21 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 433: {'index': Timestamp('2016-04-21 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 434: {'index': Timestamp('2016-04-21 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 435: {'index': Timestamp('2016-04-21 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 436: {'index': Timestamp('2016-04-21 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 437: {'index': Timestamp('2016-04-21 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 438: {'index': Timestamp('2016-04-21 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 439: {'index': Timestamp('2016-04-21 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 440: {'index': Timestamp('2016-04-21 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 441: {'index': Timestamp('2016-04-22 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 442: {'index': Timestamp('2016-04-22 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 443: {'index': Timestamp('2016-04-22 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 444: {'index': Timestamp('2016-04-22 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 445: {'index': Timestamp('2016-04-22 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 446: {'index': Timestamp('2016-04-22 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 447: {'index': Timestamp('2016-04-22 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 448: {'index': Timestamp('2016-04-22 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 449: {'index': Timestamp('2016-04-22 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 450: {'index': Timestamp('2016-04-22 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 451: {'index': Timestamp('2016-04-22 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 452: {'index': Timestamp('2016-04-22 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 453: {'index': Timestamp('2016-04-22 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 454: {'index': Timestamp('2016-04-22 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 455: {'index': Timestamp('2016-04-22 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 456: {'index': Timestamp('2016-04-22 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 457: {'index': Timestamp('2016-04-22 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 458: {'index': Timestamp('2016-04-22 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 459: {'index': Timestamp('2016-04-22 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 460: {'index': Timestamp('2016-04-22 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 461: {'index': Timestamp('2016-04-22 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 462: {'index': Timestamp('2016-04-22 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 463: {'index': Timestamp('2016-04-22 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 464: {'index': Timestamp('2016-04-22 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 465: {'index': Timestamp('2016-04-23 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 466: {'index': Timestamp('2016-04-23 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 467: {'index': Timestamp('2016-04-23 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 468: {'index': Timestamp('2016-04-23 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 469: {'index': Timestamp('2016-04-23 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 470: {'index': Timestamp('2016-04-23 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 471: {'index': Timestamp('2016-04-23 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 472: {'index': Timestamp('2016-04-23 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 473: {'index': Timestamp('2016-04-23 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 474: {'index': Timestamp('2016-04-23 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 475: {'index': Timestamp('2016-04-23 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 476: {'index': Timestamp('2016-04-23 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 477: {'index': Timestamp('2016-04-23 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 478: {'index': Timestamp('2016-04-23 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 479: {'index': Timestamp('2016-04-23 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 480: {'index': Timestamp('2016-04-23 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 481: {'index': Timestamp('2016-04-23 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 482: {'index': Timestamp('2016-04-23 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 483: {'index': Timestamp('2016-04-23 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 484: {'index': Timestamp('2016-04-23 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 485: {'index': Timestamp('2016-04-23 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 486: {'index': Timestamp('2016-04-23 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 487: {'index': Timestamp('2016-04-23 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 488: {'index': Timestamp('2016-04-23 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 489: {'index': Timestamp('2016-04-24 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 490: {'index': Timestamp('2016-04-24 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 491: {'index': Timestamp('2016-04-24 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 492: {'index': Timestamp('2016-04-24 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 493: {'index': Timestamp('2016-04-24 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 494: {'index': Timestamp('2016-04-24 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 495: {'index': Timestamp('2016-04-24 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 496: {'index': Timestamp('2016-04-24 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 497: {'index': Timestamp('2016-04-24 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 498: {'index': Timestamp('2016-04-24 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 499: {'index': Timestamp('2016-04-24 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 500: {'index': Timestamp('2016-04-24 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 501: {'index': Timestamp('2016-04-24 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 502: {'index': Timestamp('2016-04-24 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 503: {'index': Timestamp('2016-04-24 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 504: {'index': Timestamp('2016-04-24 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 505: {'index': Timestamp('2016-04-24 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 506: {'index': Timestamp('2016-04-24 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 507: {'index': Timestamp('2016-04-24 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 508: {'index': Timestamp('2016-04-24 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 509: {'index': Timestamp('2016-04-24 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 510: {'index': Timestamp('2016-04-24 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 511: {'index': Timestamp('2016-04-24 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 512: {'index': Timestamp('2016-04-24 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 513: {'index': Timestamp('2016-04-25 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 514: {'index': Timestamp('2016-04-25 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 515: {'index': Timestamp('2016-04-25 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 516: {'index': Timestamp('2016-04-25 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 517: {'index': Timestamp('2016-04-25 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 518: {'index': Timestamp('2016-04-25 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 519: {'index': Timestamp('2016-04-25 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 520: {'index': Timestamp('2016-04-25 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 521: {'index': Timestamp('2016-04-25 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 522: {'index': Timestamp('2016-04-25 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 523: {'index': Timestamp('2016-04-25 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 524: {'index': Timestamp('2016-04-25 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 525: {'index': Timestamp('2016-04-25 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 526: {'index': Timestamp('2016-04-25 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 527: {'index': Timestamp('2016-04-25 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 528: {'index': Timestamp('2016-04-25 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 529: {'index': Timestamp('2016-04-25 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 530: {'index': Timestamp('2016-04-25 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 531: {'index': Timestamp('2016-04-25 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 532: {'index': Timestamp('2016-04-25 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 533: {'index': Timestamp('2016-04-25 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 534: {'index': Timestamp('2016-04-25 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 535: {'index': Timestamp('2016-04-25 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 536: {'index': Timestamp('2016-04-25 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 537: {'index': Timestamp('2016-04-26 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 538: {'index': Timestamp('2016-04-26 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 539: {'index': Timestamp('2016-04-26 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 540: {'index': Timestamp('2016-04-26 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 541: {'index': Timestamp('2016-04-26 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 542: {'index': Timestamp('2016-04-26 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 543: {'index': Timestamp('2016-04-26 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 544: {'index': Timestamp('2016-04-26 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 545: {'index': Timestamp('2016-04-26 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 546: {'index': Timestamp('2016-04-26 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 547: {'index': Timestamp('2016-04-26 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 548: {'index': Timestamp('2016-04-26 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 549: {'index': Timestamp('2016-04-26 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 550: {'index': Timestamp('2016-04-26 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 551: {'index': Timestamp('2016-04-26 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 552: {'index': Timestamp('2016-04-26 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 553: {'index': Timestamp('2016-04-26 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 554: {'index': Timestamp('2016-04-26 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 555: {'index': Timestamp('2016-04-26 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 556: {'index': Timestamp('2016-04-26 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 557: {'index': Timestamp('2016-04-26 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 558: {'index': Timestamp('2016-04-26 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 559: {'index': Timestamp('2016-04-26 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 560: {'index': Timestamp('2016-04-26 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 561: {'index': Timestamp('2016-04-27 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 562: {'index': Timestamp('2016-04-27 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 563: {'index': Timestamp('2016-04-27 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 564: {'index': Timestamp('2016-04-27 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 565: {'index': Timestamp('2016-04-27 04:00:00'),\n", - " 'c': 0.029464654211810028,\n", - " 'loc': 0,\n", - " 'scale': 0.1373629132177982,\n", - " 'p_value': 0.5859692041615487,\n", - " 'anomaly_score': 1.7065743265994318},\n", - " 566: {'index': Timestamp('2016-04-27 05:00:00'),\n", - " 'c': 0.029518732648952883,\n", - " 'loc': 0,\n", - " 'scale': 0.13734294114141812,\n", - " 'p_value': 0.8710480479361675,\n", - " 'anomaly_score': 1.1480422949909215},\n", - " 567: {'index': Timestamp('2016-04-27 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 568: {'index': Timestamp('2016-04-27 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 569: {'index': Timestamp('2016-04-27 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 570: {'index': Timestamp('2016-04-27 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 571: {'index': Timestamp('2016-04-27 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 572: {'index': Timestamp('2016-04-27 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 573: {'index': Timestamp('2016-04-27 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 574: {'index': Timestamp('2016-04-27 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 575: {'index': Timestamp('2016-04-27 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 576: {'index': Timestamp('2016-04-27 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 577: {'index': Timestamp('2016-04-27 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 578: {'index': Timestamp('2016-04-27 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 579: {'index': Timestamp('2016-04-27 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 580: {'index': Timestamp('2016-04-27 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 581: {'index': Timestamp('2016-04-27 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 582: {'index': Timestamp('2016-04-27 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 583: {'index': Timestamp('2016-04-27 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 584: {'index': Timestamp('2016-04-27 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 585: {'index': Timestamp('2016-04-28 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 586: {'index': Timestamp('2016-04-28 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 587: {'index': Timestamp('2016-04-28 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 588: {'index': Timestamp('2016-04-28 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 589: {'index': Timestamp('2016-04-28 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 590: {'index': Timestamp('2016-04-28 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 591: {'index': Timestamp('2016-04-28 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 592: {'index': Timestamp('2016-04-28 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 593: {'index': Timestamp('2016-04-28 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 594: {'index': Timestamp('2016-04-28 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 595: {'index': Timestamp('2016-04-28 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 596: {'index': Timestamp('2016-04-28 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 597: {'index': Timestamp('2016-04-28 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 598: {'index': Timestamp('2016-04-28 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 599: {'index': Timestamp('2016-04-28 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 600: {'index': Timestamp('2016-04-28 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 601: {'index': Timestamp('2016-04-28 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 602: {'index': Timestamp('2016-04-28 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 603: {'index': Timestamp('2016-04-28 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 604: {'index': Timestamp('2016-04-28 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 605: {'index': Timestamp('2016-04-28 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 606: {'index': Timestamp('2016-04-28 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 607: {'index': Timestamp('2016-04-28 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 608: {'index': Timestamp('2016-04-28 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 609: {'index': Timestamp('2016-04-29 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 610: {'index': Timestamp('2016-04-29 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 611: {'index': Timestamp('2016-04-29 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 612: {'index': Timestamp('2016-04-29 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 613: {'index': Timestamp('2016-04-29 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 614: {'index': Timestamp('2016-04-29 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 615: {'index': Timestamp('2016-04-29 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 616: {'index': Timestamp('2016-04-29 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 617: {'index': Timestamp('2016-04-29 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 618: {'index': Timestamp('2016-04-29 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 619: {'index': Timestamp('2016-04-29 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 620: {'index': Timestamp('2016-04-29 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 621: {'index': Timestamp('2016-04-29 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 622: {'index': Timestamp('2016-04-29 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 623: {'index': Timestamp('2016-04-29 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 624: {'index': Timestamp('2016-04-29 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 625: {'index': Timestamp('2016-04-29 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 626: {'index': Timestamp('2016-04-29 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 627: {'index': Timestamp('2016-04-29 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 628: {'index': Timestamp('2016-04-29 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 629: {'index': Timestamp('2016-04-29 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 630: {'index': Timestamp('2016-04-29 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 631: {'index': Timestamp('2016-04-29 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 632: {'index': Timestamp('2016-04-29 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 633: {'index': Timestamp('2016-04-30 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 634: {'index': Timestamp('2016-04-30 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 635: {'index': Timestamp('2016-04-30 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 636: {'index': Timestamp('2016-04-30 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 637: {'index': Timestamp('2016-04-30 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 638: {'index': Timestamp('2016-04-30 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 639: {'index': Timestamp('2016-04-30 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 640: {'index': Timestamp('2016-04-30 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 641: {'index': Timestamp('2016-04-30 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 642: {'index': Timestamp('2016-04-30 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 643: {'index': Timestamp('2016-04-30 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 644: {'index': Timestamp('2016-04-30 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 645: {'index': Timestamp('2016-04-30 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 646: {'index': Timestamp('2016-04-30 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 647: {'index': Timestamp('2016-04-30 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 648: {'index': Timestamp('2016-04-30 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 649: {'index': Timestamp('2016-04-30 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 650: {'index': Timestamp('2016-04-30 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 651: {'index': Timestamp('2016-04-30 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 652: {'index': Timestamp('2016-04-30 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 653: {'index': Timestamp('2016-04-30 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 654: {'index': Timestamp('2016-04-30 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 655: {'index': Timestamp('2016-04-30 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 656: {'index': Timestamp('2016-04-30 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 657: {'index': Timestamp('2016-05-01 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 658: {'index': Timestamp('2016-05-01 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 659: {'index': Timestamp('2016-05-01 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 660: {'index': Timestamp('2016-05-01 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 661: {'index': Timestamp('2016-05-01 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 662: {'index': Timestamp('2016-05-01 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 663: {'index': Timestamp('2016-05-01 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 664: {'index': Timestamp('2016-05-01 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 665: {'index': Timestamp('2016-05-01 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 666: {'index': Timestamp('2016-05-01 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 667: {'index': Timestamp('2016-05-01 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 668: {'index': Timestamp('2016-05-01 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 669: {'index': Timestamp('2016-05-01 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 670: {'index': Timestamp('2016-05-01 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 671: {'index': Timestamp('2016-05-01 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 672: {'index': Timestamp('2016-05-01 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 673: {'index': Timestamp('2016-05-01 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 674: {'index': Timestamp('2016-05-01 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 675: {'index': Timestamp('2016-05-01 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 676: {'index': Timestamp('2016-05-01 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 677: {'index': Timestamp('2016-05-01 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 678: {'index': Timestamp('2016-05-01 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 679: {'index': Timestamp('2016-05-01 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 680: {'index': Timestamp('2016-05-01 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 681: {'index': Timestamp('2016-05-02 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 682: {'index': Timestamp('2016-05-02 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 683: {'index': Timestamp('2016-05-02 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 684: {'index': Timestamp('2016-05-02 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 685: {'index': Timestamp('2016-05-02 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 686: {'index': Timestamp('2016-05-02 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 687: {'index': Timestamp('2016-05-02 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 688: {'index': Timestamp('2016-05-02 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 689: {'index': Timestamp('2016-05-02 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 690: {'index': Timestamp('2016-05-02 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 691: {'index': Timestamp('2016-05-02 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 692: {'index': Timestamp('2016-05-02 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 693: {'index': Timestamp('2016-05-02 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 694: {'index': Timestamp('2016-05-02 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 695: {'index': Timestamp('2016-05-02 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 696: {'index': Timestamp('2016-05-02 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 697: {'index': Timestamp('2016-05-02 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 698: {'index': Timestamp('2016-05-02 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 699: {'index': Timestamp('2016-05-02 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 700: {'index': Timestamp('2016-05-02 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 701: {'index': Timestamp('2016-05-02 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 702: {'index': Timestamp('2016-05-02 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 703: {'index': Timestamp('2016-05-02 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 704: {'index': Timestamp('2016-05-02 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 705: {'index': Timestamp('2016-05-03 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 706: {'index': Timestamp('2016-05-03 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 707: {'index': Timestamp('2016-05-03 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 708: {'index': Timestamp('2016-05-03 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 709: {'index': Timestamp('2016-05-03 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 710: {'index': Timestamp('2016-05-03 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 711: {'index': Timestamp('2016-05-03 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 712: {'index': Timestamp('2016-05-03 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 713: {'index': Timestamp('2016-05-03 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 714: {'index': Timestamp('2016-05-03 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 715: {'index': Timestamp('2016-05-03 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 716: {'index': Timestamp('2016-05-03 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 717: {'index': Timestamp('2016-05-03 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 718: {'index': Timestamp('2016-05-03 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 719: {'index': Timestamp('2016-05-03 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 720: {'index': Timestamp('2016-05-03 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 721: {'index': Timestamp('2016-05-03 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 722: {'index': Timestamp('2016-05-03 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 723: {'index': Timestamp('2016-05-03 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 724: {'index': Timestamp('2016-05-03 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 725: {'index': Timestamp('2016-05-03 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 726: {'index': Timestamp('2016-05-03 21:00:00'),\n", - " 'c': 0.02964189562589155,\n", - " 'loc': 0,\n", - " 'scale': 0.13728074993439215,\n", - " 'p_value': 0.9642525223797351,\n", - " 'anomaly_score': 1.0370727343621997},\n", - " 727: {'index': Timestamp('2016-05-03 22:00:00'),\n", - " 'c': 0.029733133211110697,\n", - " 'loc': 0,\n", - " 'scale': 0.13722991818472785,\n", - " 'p_value': 0.41583274965446615,\n", - " 'anomaly_score': 2.404812994721903},\n", - " 728: {'index': Timestamp('2016-05-03 23:00:00'),\n", - " 'c': 0.029642940254280326,\n", - " 'loc': 0,\n", - " 'scale': 0.13723224099691672,\n", - " 'p_value': 0.6027418307797329,\n", - " 'anomaly_score': 1.6590851156063895},\n", - " 729: {'index': Timestamp('2016-05-04 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 730: {'index': Timestamp('2016-05-04 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 731: {'index': Timestamp('2016-05-04 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 732: {'index': Timestamp('2016-05-04 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 733: {'index': Timestamp('2016-05-04 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 734: {'index': Timestamp('2016-05-04 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 735: {'index': Timestamp('2016-05-04 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 736: {'index': Timestamp('2016-05-04 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 737: {'index': Timestamp('2016-05-04 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 738: {'index': Timestamp('2016-05-04 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 739: {'index': Timestamp('2016-05-04 10:00:00'),\n", - " 'c': 0.029664773511078928,\n", - " 'loc': 0,\n", - " 'scale': 0.13721306642952552,\n", - " 'p_value': 0.7111979985432318,\n", - " 'anomaly_score': 1.4060781977006824},\n", - " 740: {'index': Timestamp('2016-05-04 11:00:00'),\n", - " 'c': 0.029785618044357663,\n", - " 'loc': 0,\n", - " 'scale': 0.13716184053093286,\n", - " 'p_value': 0.5221347979795703,\n", - " 'anomaly_score': 1.915214239444595},\n", - " 741: {'index': Timestamp('2016-05-04 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 742: {'index': Timestamp('2016-05-04 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 743: {'index': Timestamp('2016-05-04 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 744: {'index': Timestamp('2016-05-04 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 745: {'index': Timestamp('2016-05-04 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 746: {'index': Timestamp('2016-05-04 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 747: {'index': Timestamp('2016-05-04 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 748: {'index': Timestamp('2016-05-04 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 749: {'index': Timestamp('2016-05-04 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 750: {'index': Timestamp('2016-05-04 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 751: {'index': Timestamp('2016-05-04 22:00:00'),\n", - " 'c': 0.029699014217528737,\n", - " 'loc': 0,\n", - " 'scale': 0.13715033793659717,\n", - " 'p_value': 0.18413530934239578,\n", - " 'anomaly_score': 5.430788932178786},\n", - " 752: {'index': Timestamp('2016-05-04 23:00:00'),\n", - " 'c': 0.029556912634663528,\n", - " 'loc': 0,\n", - " 'scale': 0.13721012745813166,\n", - " 'p_value': 0.1193699181642402,\n", - " 'anomaly_score': 8.37731997624483},\n", - " 753: {'index': Timestamp('2016-05-05 00:00:00'),\n", - " 'c': 0.029425686093983598,\n", - " 'loc': 0,\n", - " 'scale': 0.13727144042560308,\n", - " 'p_value': 0.18951699470149713,\n", - " 'anomaly_score': 5.276571642427487},\n", - " 754: {'index': Timestamp('2016-05-05 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 755: {'index': Timestamp('2016-05-05 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 756: {'index': Timestamp('2016-05-05 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 757: {'index': Timestamp('2016-05-05 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 758: {'index': Timestamp('2016-05-05 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 759: {'index': Timestamp('2016-05-05 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 760: {'index': Timestamp('2016-05-05 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 761: {'index': Timestamp('2016-05-05 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 762: {'index': Timestamp('2016-05-05 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 763: {'index': Timestamp('2016-05-05 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 764: {'index': Timestamp('2016-05-05 11:00:00'),\n", - " 'c': 0.029293313005478543,\n", - " 'loc': 0,\n", - " 'scale': 0.13732404555527816,\n", - " 'p_value': 0.2705599289326875,\n", - " 'anomaly_score': 3.696038818256748},\n", - " 765: {'index': Timestamp('2016-05-05 12:00:00'),\n", - " 'c': 0.029182019885684092,\n", - " 'loc': 0,\n", - " 'scale': 0.13735888488627657,\n", - " 'p_value': 0.1806691109952622,\n", - " 'anomaly_score': 5.534980465068119},\n", - " 766: {'index': Timestamp('2016-05-05 13:00:00'),\n", - " 'c': 0.029051205830514945,\n", - " 'loc': 0,\n", - " 'scale': 0.13740898403316945,\n", - " 'p_value': 0.8440761253417608,\n", - " 'anomaly_score': 1.1847272656777335},\n", - " 767: {'index': Timestamp('2016-05-05 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 768: {'index': Timestamp('2016-05-05 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 769: {'index': Timestamp('2016-05-05 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 770: {'index': Timestamp('2016-05-05 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 771: {'index': Timestamp('2016-05-05 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 772: {'index': Timestamp('2016-05-05 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 773: {'index': Timestamp('2016-05-05 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 774: {'index': Timestamp('2016-05-05 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 775: {'index': Timestamp('2016-05-05 22:00:00'),\n", - " 'c': 0.029167456681161042,\n", - " 'loc': 0,\n", - " 'scale': 0.13733773622806586,\n", - " 'p_value': 0.39869206186842365,\n", - " 'anomaly_score': 2.508201430732323},\n", - " 776: {'index': Timestamp('2016-05-05 23:00:00'),\n", - " 'c': 0.02907181640528729,\n", - " 'loc': 0,\n", - " 'scale': 0.13736454789277955,\n", - " 'p_value': 0.06758147106094771,\n", - " 'anomaly_score': 14.796955205342593},\n", - " 777: {'index': Timestamp('2016-05-06 00:00:00'),\n", - " 'c': 0.029009287624509553,\n", - " 'loc': 0,\n", - " 'scale': 0.13743868302290102,\n", - " 'p_value': 0.028334362794044,\n", - " 'anomaly_score': 35.29283532044716},\n", - " 778: {'index': Timestamp('2016-05-06 01:00:00'),\n", - " 'c': 0.029119159522481668,\n", - " 'loc': 0,\n", - " 'scale': 0.13754419625660008,\n", - " 'p_value': 0.06691637247082739,\n", - " 'anomaly_score': 14.944025850115473},\n", - " 779: {'index': Timestamp('2016-05-06 02:00:00'),\n", - " 'c': 0.02889624741607609,\n", - " 'loc': 0,\n", - " 'scale': 0.13762282042220025,\n", - " 'p_value': 0.8163934254810028,\n", - " 'anomaly_score': 1.2248996241129941},\n", - " 780: {'index': Timestamp('2016-05-06 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 781: {'index': Timestamp('2016-05-06 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 782: {'index': Timestamp('2016-05-06 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 783: {'index': Timestamp('2016-05-06 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 784: {'index': Timestamp('2016-05-06 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 785: {'index': Timestamp('2016-05-06 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 786: {'index': Timestamp('2016-05-06 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 787: {'index': Timestamp('2016-05-06 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 788: {'index': Timestamp('2016-05-06 11:00:00'),\n", - " 'c': 0.029033401834451605,\n", - " 'loc': 0,\n", - " 'scale': 0.13758059962803681,\n", - " 'p_value': 0.5948811316992879,\n", - " 'anomaly_score': 1.6810080984473037},\n", - " 789: {'index': Timestamp('2016-05-06 12:00:00'),\n", - " 'c': 0.02903954346929158,\n", - " 'loc': 0,\n", - " 'scale': 0.13757407280595563,\n", - " 'p_value': 0.12153592441877152,\n", - " 'anomaly_score': 8.228019861471902},\n", - " 790: {'index': Timestamp('2016-05-06 13:00:00'),\n", - " 'c': 0.02889624741607609,\n", - " 'loc': 0,\n", - " 'scale': 0.13762282042220025,\n", - " 'p_value': 0.09449747594975116,\n", - " 'anomaly_score': 10.582293230051434},\n", - " 791: {'index': Timestamp('2016-05-06 14:00:00'),\n", - " 'c': 0.02878661517623602,\n", - " 'loc': 0,\n", - " 'scale': 0.13771927085068897,\n", - " 'p_value': 0.364574386836468,\n", - " 'anomaly_score': 2.7429244513783027},\n", - " 792: {'index': Timestamp('2016-05-06 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 793: {'index': Timestamp('2016-05-06 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 794: {'index': Timestamp('2016-05-06 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 795: {'index': Timestamp('2016-05-06 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 796: {'index': Timestamp('2016-05-06 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 797: {'index': Timestamp('2016-05-06 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 798: {'index': Timestamp('2016-05-06 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 799: {'index': Timestamp('2016-05-06 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 800: {'index': Timestamp('2016-05-06 23:00:00'),\n", - " 'c': 0.028716702306882558,\n", - " 'loc': 0,\n", - " 'scale': 0.13772595222440048,\n", - " 'p_value': 0.325730781405035,\n", - " 'anomaly_score': 3.0700199584654375},\n", - " 801: {'index': Timestamp('2016-05-07 00:00:00'),\n", - " 'c': 0.028614129434459255,\n", - " 'loc': 0,\n", - " 'scale': 0.13775230484643408,\n", - " 'p_value': 0.046740350353963345,\n", - " 'anomaly_score': 21.39479042041894},\n", - " 802: {'index': Timestamp('2016-05-07 01:00:00'),\n", - " 'c': 0.028543573043284844,\n", - " 'loc': 0,\n", - " 'scale': 0.13782849285040732,\n", - " 'p_value': 0.0222557462999383,\n", - " 'anomaly_score': 44.932216000448044},\n", - " 803: {'index': Timestamp('2016-05-07 02:00:00'),\n", - " 'c': 0.028721084029659973,\n", - " 'loc': 0,\n", - " 'scale': 0.1379308672032084,\n", - " 'p_value': 0.045711046231713,\n", - " 'anomaly_score': 21.876550252884584},\n", - " 804: {'index': Timestamp('2016-05-07 03:00:00'),\n", - " 'c': 0.028641663755329283,\n", - " 'loc': 0,\n", - " 'scale': 0.1380264750344093,\n", - " 'p_value': 0.7936813412129591,\n", - " 'anomaly_score': 1.2599515045568923},\n", - " 805: {'index': Timestamp('2016-05-07 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 806: {'index': Timestamp('2016-05-07 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 807: {'index': Timestamp('2016-05-07 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 808: {'index': Timestamp('2016-05-07 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 809: {'index': Timestamp('2016-05-07 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 810: {'index': Timestamp('2016-05-07 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 811: {'index': Timestamp('2016-05-07 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 812: {'index': Timestamp('2016-05-07 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 813: {'index': Timestamp('2016-05-07 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 814: {'index': Timestamp('2016-05-07 13:00:00'),\n", - " 'c': 0.02870636305433881,\n", - " 'loc': 0,\n", - " 'scale': 0.1379839491333027,\n", - " 'p_value': 0.26645332963773055,\n", - " 'anomaly_score': 3.753002453974203},\n", - " 815: {'index': Timestamp('2016-05-07 14:00:00'),\n", - " 'c': 0.02860703213104249,\n", - " 'loc': 0,\n", - " 'scale': 0.1380164502411313,\n", - " 'p_value': 0.3065034907097339,\n", - " 'anomaly_score': 3.262605583004677},\n", - " 816: {'index': Timestamp('2016-05-07 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 817: {'index': Timestamp('2016-05-07 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 818: {'index': Timestamp('2016-05-07 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 819: {'index': Timestamp('2016-05-07 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 820: {'index': Timestamp('2016-05-07 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 821: {'index': Timestamp('2016-05-07 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 822: {'index': Timestamp('2016-05-07 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 823: {'index': Timestamp('2016-05-07 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 824: {'index': Timestamp('2016-05-07 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 825: {'index': Timestamp('2016-05-08 00:00:00'),\n", - " 'c': 0.028551194982261156,\n", - " 'loc': 0,\n", - " 'scale': 0.13803856398669123,\n", - " 'p_value': 0.37580879143665574,\n", - " 'anomaly_score': 2.6609276386993583},\n", - " 826: {'index': Timestamp('2016-05-08 01:00:00'),\n", - " 'c': 0.028474680617117422,\n", - " 'loc': 0,\n", - " 'scale': 0.1380512017023322,\n", - " 'p_value': 0.08473565967849182,\n", - " 'anomaly_score': 11.801406914093178},\n", - " 827: {'index': Timestamp('2016-05-08 02:00:00'),\n", - " 'c': 0.028347231745694403,\n", - " 'loc': 0,\n", - " 'scale': 0.1381164044208183,\n", - " 'p_value': 0.05267698290583189,\n", - " 'anomaly_score': 18.983623298768872},\n", - " 828: {'index': Timestamp('2016-05-08 03:00:00'),\n", - " 'c': 0.028232300074835008,\n", - " 'loc': 0,\n", - " 'scale': 0.1382242852379451,\n", - " 'p_value': 0.19266846583435132,\n", - " 'anomaly_score': 5.190262950761025},\n", - " 829: {'index': Timestamp('2016-05-08 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 830: {'index': Timestamp('2016-05-08 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 831: {'index': Timestamp('2016-05-08 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 832: {'index': Timestamp('2016-05-08 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 833: {'index': Timestamp('2016-05-08 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 834: {'index': Timestamp('2016-05-08 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 835: {'index': Timestamp('2016-05-08 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 836: {'index': Timestamp('2016-05-08 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 837: {'index': Timestamp('2016-05-08 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 838: {'index': Timestamp('2016-05-08 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 839: {'index': Timestamp('2016-05-08 14:00:00'),\n", - " 'c': 0.028163079925753186,\n", - " 'loc': 0,\n", - " 'scale': 0.13826369443097442,\n", - " 'p_value': 0.2688965160769437,\n", - " 'anomaly_score': 3.718902775645683},\n", - " 840: {'index': Timestamp('2016-05-08 15:00:00'),\n", - " 'c': 0.02799290856776331,\n", - " 'loc': 0,\n", - " 'scale': 0.1383074204074507,\n", - " 'p_value': 0.3711569612106954,\n", - " 'anomaly_score': 2.694277905331615},\n", - " 841: {'index': Timestamp('2016-05-08 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 842: {'index': Timestamp('2016-05-08 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 843: {'index': Timestamp('2016-05-08 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 844: {'index': Timestamp('2016-05-08 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 845: {'index': Timestamp('2016-05-08 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 846: {'index': Timestamp('2016-05-08 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 847: {'index': Timestamp('2016-05-08 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 848: {'index': Timestamp('2016-05-08 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 849: {'index': Timestamp('2016-05-09 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 850: {'index': Timestamp('2016-05-09 01:00:00'),\n", - " 'c': 0.027953012006308123,\n", - " 'loc': 0,\n", - " 'scale': 0.1383108513388425,\n", - " 'p_value': 0.7940427586359905,\n", - " 'anomaly_score': 1.2593780235686598},\n", - " 851: {'index': Timestamp('2016-05-09 02:00:00'),\n", - " 'c': 0.02801768909677567,\n", - " 'loc': 0,\n", - " 'scale': 0.1382564024004524,\n", - " 'p_value': 0.14977883609118903,\n", - " 'anomaly_score': 6.676510688006519},\n", - " 852: {'index': Timestamp('2016-05-09 03:00:00'),\n", - " 'c': 0.027904812323713044,\n", - " 'loc': 0,\n", - " 'scale': 0.13831194341976474,\n", - " 'p_value': 0.08789135243722149,\n", - " 'anomaly_score': 11.377683609024837},\n", - " 853: {'index': Timestamp('2016-05-09 04:00:00'),\n", - " 'c': 0.02773991613000018,\n", - " 'loc': 0,\n", - " 'scale': 0.1383951786196972,\n", - " 'p_value': 0.6639628774656695,\n", - " 'anomaly_score': 1.506108299031681},\n", - " 854: {'index': Timestamp('2016-05-09 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 855: {'index': Timestamp('2016-05-09 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 856: {'index': Timestamp('2016-05-09 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 857: {'index': Timestamp('2016-05-09 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 858: {'index': Timestamp('2016-05-09 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 859: {'index': Timestamp('2016-05-09 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 860: {'index': Timestamp('2016-05-09 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 861: {'index': Timestamp('2016-05-09 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 862: {'index': Timestamp('2016-05-09 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 863: {'index': Timestamp('2016-05-09 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 864: {'index': Timestamp('2016-05-09 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 865: {'index': Timestamp('2016-05-09 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 866: {'index': Timestamp('2016-05-09 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 867: {'index': Timestamp('2016-05-09 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 868: {'index': Timestamp('2016-05-09 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 869: {'index': Timestamp('2016-05-09 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 870: {'index': Timestamp('2016-05-09 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 871: {'index': Timestamp('2016-05-09 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 872: {'index': Timestamp('2016-05-09 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 873: {'index': Timestamp('2016-05-10 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 874: {'index': Timestamp('2016-05-10 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 875: {'index': Timestamp('2016-05-10 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 876: {'index': Timestamp('2016-05-10 03:00:00'),\n", - " 'c': 0.02780281701881265,\n", - " 'loc': 0,\n", - " 'scale': 0.13835704743263222,\n", - " 'p_value': 0.8290868332663486,\n", - " 'anomaly_score': 1.2061462803121668},\n", - " 877: {'index': Timestamp('2016-05-10 04:00:00'),\n", - " 'c': 0.0279155693137114,\n", - " 'loc': 0,\n", - " 'scale': 0.13831860133245807,\n", - " 'p_value': 0.5284899291963157,\n", - " 'anomaly_score': 1.8921836439167694},\n", - " 878: {'index': Timestamp('2016-05-10 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 879: {'index': Timestamp('2016-05-10 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 880: {'index': Timestamp('2016-05-10 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 881: {'index': Timestamp('2016-05-10 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 882: {'index': Timestamp('2016-05-10 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 883: {'index': Timestamp('2016-05-10 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 884: {'index': Timestamp('2016-05-10 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 885: {'index': Timestamp('2016-05-10 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 886: {'index': Timestamp('2016-05-10 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 887: {'index': Timestamp('2016-05-10 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 888: {'index': Timestamp('2016-05-10 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 889: {'index': Timestamp('2016-05-10 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 890: {'index': Timestamp('2016-05-10 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 891: {'index': Timestamp('2016-05-10 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 892: {'index': Timestamp('2016-05-10 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 893: {'index': Timestamp('2016-05-10 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 894: {'index': Timestamp('2016-05-10 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 895: {'index': Timestamp('2016-05-10 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 896: {'index': Timestamp('2016-05-10 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 897: {'index': Timestamp('2016-05-11 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 898: {'index': Timestamp('2016-05-11 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 899: {'index': Timestamp('2016-05-11 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 900: {'index': Timestamp('2016-05-11 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 901: {'index': Timestamp('2016-05-11 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 902: {'index': Timestamp('2016-05-11 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 903: {'index': Timestamp('2016-05-11 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 904: {'index': Timestamp('2016-05-11 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 905: {'index': Timestamp('2016-05-11 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 906: {'index': Timestamp('2016-05-11 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 907: {'index': Timestamp('2016-05-11 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 908: {'index': Timestamp('2016-05-11 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 909: {'index': Timestamp('2016-05-11 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 910: {'index': Timestamp('2016-05-11 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 911: {'index': Timestamp('2016-05-11 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 912: {'index': Timestamp('2016-05-11 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 913: {'index': Timestamp('2016-05-11 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 914: {'index': Timestamp('2016-05-11 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 915: {'index': Timestamp('2016-05-11 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 916: {'index': Timestamp('2016-05-11 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 917: {'index': Timestamp('2016-05-11 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 918: {'index': Timestamp('2016-05-11 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 919: {'index': Timestamp('2016-05-11 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 920: {'index': Timestamp('2016-05-11 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 921: {'index': Timestamp('2016-05-12 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 922: {'index': Timestamp('2016-05-12 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 923: {'index': Timestamp('2016-05-12 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 924: {'index': Timestamp('2016-05-12 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 925: {'index': Timestamp('2016-05-12 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 926: {'index': Timestamp('2016-05-12 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 927: {'index': Timestamp('2016-05-12 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 928: {'index': Timestamp('2016-05-12 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 929: {'index': Timestamp('2016-05-12 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 930: {'index': Timestamp('2016-05-12 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 931: {'index': Timestamp('2016-05-12 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 932: {'index': Timestamp('2016-05-12 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 933: {'index': Timestamp('2016-05-12 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 934: {'index': Timestamp('2016-05-12 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 935: {'index': Timestamp('2016-05-12 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 936: {'index': Timestamp('2016-05-12 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 937: {'index': Timestamp('2016-05-12 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 938: {'index': Timestamp('2016-05-12 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 939: {'index': Timestamp('2016-05-12 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 940: {'index': Timestamp('2016-05-12 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 941: {'index': Timestamp('2016-05-12 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 942: {'index': Timestamp('2016-05-12 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 943: {'index': Timestamp('2016-05-12 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 944: {'index': Timestamp('2016-05-12 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 945: {'index': Timestamp('2016-05-13 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 946: {'index': Timestamp('2016-05-13 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 947: {'index': Timestamp('2016-05-13 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 948: {'index': Timestamp('2016-05-13 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 949: {'index': Timestamp('2016-05-13 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 950: {'index': Timestamp('2016-05-13 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 951: {'index': Timestamp('2016-05-13 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 952: {'index': Timestamp('2016-05-13 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 953: {'index': Timestamp('2016-05-13 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 954: {'index': Timestamp('2016-05-13 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 955: {'index': Timestamp('2016-05-13 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 956: {'index': Timestamp('2016-05-13 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 957: {'index': Timestamp('2016-05-13 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 958: {'index': Timestamp('2016-05-13 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 959: {'index': Timestamp('2016-05-13 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 960: {'index': Timestamp('2016-05-13 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 961: {'index': Timestamp('2016-05-13 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 962: {'index': Timestamp('2016-05-13 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 963: {'index': Timestamp('2016-05-13 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 964: {'index': Timestamp('2016-05-13 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 965: {'index': Timestamp('2016-05-13 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 966: {'index': Timestamp('2016-05-13 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 967: {'index': Timestamp('2016-05-13 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 968: {'index': Timestamp('2016-05-13 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 969: {'index': Timestamp('2016-05-14 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 970: {'index': Timestamp('2016-05-14 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 971: {'index': Timestamp('2016-05-14 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 972: {'index': Timestamp('2016-05-14 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 973: {'index': Timestamp('2016-05-14 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 974: {'index': Timestamp('2016-05-14 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 975: {'index': Timestamp('2016-05-14 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 976: {'index': Timestamp('2016-05-14 07:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 977: {'index': Timestamp('2016-05-14 08:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 978: {'index': Timestamp('2016-05-14 09:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 979: {'index': Timestamp('2016-05-14 10:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 980: {'index': Timestamp('2016-05-14 11:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 981: {'index': Timestamp('2016-05-14 12:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 982: {'index': Timestamp('2016-05-14 13:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 983: {'index': Timestamp('2016-05-14 14:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 984: {'index': Timestamp('2016-05-14 15:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 985: {'index': Timestamp('2016-05-14 16:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 986: {'index': Timestamp('2016-05-14 17:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 987: {'index': Timestamp('2016-05-14 18:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 988: {'index': Timestamp('2016-05-14 19:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 989: {'index': Timestamp('2016-05-14 20:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 990: {'index': Timestamp('2016-05-14 21:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 991: {'index': Timestamp('2016-05-14 22:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 992: {'index': Timestamp('2016-05-14 23:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 993: {'index': Timestamp('2016-05-15 00:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 994: {'index': Timestamp('2016-05-15 01:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 995: {'index': Timestamp('2016-05-15 02:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 996: {'index': Timestamp('2016-05-15 03:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 997: {'index': Timestamp('2016-05-15 04:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 998: {'index': Timestamp('2016-05-15 05:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 999: {'index': Timestamp('2016-05-15 06:00:00'),\n", - " 'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " ...}" + "{'index': Timestamp('2016-04-03 15:00:00'),\n", + " 'c': 0.0,\n", + " 'loc': 0.0,\n", + " 'scale': 0.0,\n", + " 'p_value': 0.0,\n", + " 'anomaly_score': 0.0}" ] }, - "execution_count": 16, + "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pot_detector.params" + "pot_detector.params[0]" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 55, "metadata": {}, "outputs": [ { @@ -6619,7 +478,7 @@ "Name: anomaly scores, Length: 35001, dtype: float64" ] }, - "execution_count": 17, + "execution_count": 55, "metadata": {}, "output_type": "execute_result" } @@ -6644,7 +503,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 56, "metadata": {}, "outputs": [ { @@ -6663,7 +522,7 @@ "Name: detected data, dtype: bool" ] }, - "execution_count": 18, + "execution_count": 56, "metadata": {}, "output_type": "execute_result" } @@ -6675,7 +534,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 57, "metadata": {}, "outputs": [ { @@ -6695,7 +554,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 58, "metadata": {}, "outputs": [ { @@ -6862,7 +721,7 @@ "2019-12-30 16:00:00 97786 1.282 18.412294 15.110118" ] }, - "execution_count": 20, + "execution_count": 58, "metadata": {}, "output_type": "execute_result" } @@ -6896,7 +755,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 59, "metadata": {}, "outputs": [ { @@ -6950,7 +809,7 @@ "0 0.140923 " ] }, - "execution_count": 21, + "execution_count": 59, "metadata": {}, "output_type": "execute_result" } @@ -6980,7 +839,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 60, "metadata": {}, "outputs": [ { @@ -7011,12 +870,12 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 61, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -7040,7 +899,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 62, "metadata": {}, "outputs": [], "source": [ @@ -7061,7 +920,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 63, "metadata": {}, "outputs": [ { @@ -7082,7 +941,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 64, "metadata": {}, "outputs": [ { @@ -7102,7 +961,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 65, "metadata": {}, "outputs": [ { @@ -7131,7 +990,7 @@ "Name: Water Level, dtype: float64" ] }, - "execution_count": 27, + "execution_count": 65, "metadata": {}, "output_type": "execute_result" } @@ -7143,7 +1002,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 66, "metadata": {}, "outputs": [ { @@ -7157,7 +1016,7 @@ "Name: exceedances, dtype: float64" ] }, - "execution_count": 28, + "execution_count": 66, "metadata": {}, "output_type": "execute_result" } @@ -7168,7 +1027,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 67, "metadata": {}, "outputs": [ { @@ -7188,7 +1047,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 68, "metadata": {}, "outputs": [ { @@ -7217,7 +1076,7 @@ "Name: anomaly scores, dtype: float64" ] }, - "execution_count": 30, + "execution_count": 68, "metadata": {}, "output_type": "execute_result" } @@ -7229,7 +1088,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 69, "metadata": {}, "outputs": [ { @@ -7249,7 +1108,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 70, "metadata": {}, "outputs": [ { @@ -13258,7 +7117,7 @@ " ...}" ] }, - "execution_count": 32, + "execution_count": 70, "metadata": {}, "output_type": "execute_result" } @@ -13269,7 +7128,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 71, "metadata": {}, "outputs": [ { @@ -13298,7 +7157,7 @@ "Name: detected data, dtype: bool" ] }, - "execution_count": 33, + "execution_count": 71, "metadata": {}, "output_type": "execute_result" } @@ -13310,7 +7169,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 72, "metadata": {}, "outputs": [ { @@ -13330,7 +7189,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 73, "metadata": {}, "outputs": [ { @@ -13353,7 +7212,7 @@ "Name: Water Level, dtype: float64" ] }, - "execution_count": 35, + "execution_count": 73, "metadata": {}, "output_type": "execute_result" } @@ -13364,7 +7223,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 74, "metadata": {}, "outputs": [ { @@ -13515,7 +7374,7 @@ "2020-02-08 19:00:00 98749 -1.431 92.154635 24.606906" ] }, - "execution_count": 36, + "execution_count": 74, "metadata": {}, "output_type": "execute_result" } @@ -13526,7 +7385,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 75, "metadata": {}, "outputs": [ { @@ -13580,7 +7439,7 @@ "0 0.159542 " ] }, - "execution_count": 37, + "execution_count": 75, "metadata": {}, "output_type": "execute_result" } @@ -13592,7 +7451,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 76, "metadata": {}, "outputs": [ { @@ -13612,12 +7471,12 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 77, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] diff --git a/docs/examples/extreme_anomaly_df_analysis.ipynb b/docs/examples/extreme_anomaly_df_analysis.ipynb index 5bed0cb..a7fc813 100644 --- a/docs/examples/extreme_anomaly_df_analysis.ipynb +++ b/docs/examples/extreme_anomaly_df_analysis.ipynb @@ -2,14 +2,14 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 40, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Requirement already satisfied: anomalytics in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (0.1.8)\n", + "Requirement already satisfied: anomalytics in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (0.1.9)\n", "Requirement already satisfied: matplotlib>=3.7.2 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from anomalytics) (3.8.2)\n", "Requirement already satisfied: numpy>=1.25.2 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from anomalytics) (1.26.2)\n", "Requirement already satisfied: pandas>=2.0.3 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from anomalytics) (2.1.3)\n", @@ -25,173 +25,17 @@ "Requirement already satisfied: pytz>=2020.1 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from pandas>=2.0.3->anomalytics) (2023.3.post1)\n", "Requirement already satisfied: tzdata>=2022.1 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from pandas>=2.0.3->anomalytics) (2023.3)\n", "Requirement already satisfied: six>=1.5 in /Users/ninovation/miniconda3/envs/anomalytics/lib/python3.12/site-packages (from python-dateutil>=2.7->matplotlib>=3.7.2->anomalytics) (1.16.0)\n", - "Note: you may need to restart the kernel to use updated packages.\n", - "Package Version\n", - "------------------------- ------------\n", - "anomalytics 0.1.8\n", - "anyio 4.1.0\n", - "appnope 0.1.3\n", - "argon2-cffi 23.1.0\n", - "argon2-cffi-bindings 21.2.0\n", - "arrow 1.3.0\n", - "asttokens 2.4.1\n", - "async-lru 2.0.4\n", - "attrs 23.1.0\n", - "Babel 2.13.1\n", - "beautifulsoup4 4.12.2\n", - "bleach 6.1.0\n", - "blinker 1.7.0\n", - "boto3 1.33.6\n", - "botocore 1.33.6\n", - "Brotli 1.1.0\n", - "cached-property 1.5.2\n", - "certifi 2023.11.17\n", - "cffi 1.16.0\n", - "charset-normalizer 3.3.2\n", - "click 8.1.7\n", - "cloudpickle 3.0.0\n", - "colorama 0.4.6\n", - "comm 0.1.4\n", - "contourpy 1.2.0\n", - "cycler 0.12.1\n", - "debugpy 1.8.0\n", - "decorator 5.1.1\n", - "defusedxml 0.7.1\n", - "entrypoints 0.4\n", - "et-xmlfile 1.1.0\n", - "exceptiongroup 1.2.0\n", - "executing 2.0.1\n", - "fastjsonschema 2.19.0\n", - "Flask 3.0.0\n", - "fonttools 4.46.0\n", - "fqdn 1.5.1\n", - "gym 0.26.2\n", - "gym-notices 0.0.8\n", - "h5py 3.10.0\n", - "idna 3.6\n", - "importlib-metadata 7.0.0\n", - "importlib-resources 6.1.1\n", - "ipykernel 6.26.0\n", - "ipython 8.18.1\n", - "ipywidgets 8.1.1\n", - "isoduration 20.11.0\n", - "itsdangerous 2.1.2\n", - "jedi 0.19.1\n", - "Jinja2 3.1.2\n", - "jmespath 1.0.1\n", - "joblib 1.3.2\n", - "json5 0.9.14\n", - "jsonpointer 2.4\n", - "jsonschema 4.20.0\n", - "jsonschema-specifications 2023.11.2\n", - "jupyter 1.0.0\n", - "jupyter_client 8.6.0\n", - "jupyter-console 6.6.3\n", - "jupyter_core 5.5.0\n", - "jupyter-events 0.9.0\n", - "jupyter-lsp 2.2.1\n", - "jupyter_server 2.11.1\n", - "jupyter_server_terminals 0.4.4\n", - "jupyterlab 4.0.9\n", - "jupyterlab_pygments 0.3.0\n", - "jupyterlab_server 2.25.2\n", - "jupyterlab-widgets 3.0.9\n", - "kaggle 1.5.16\n", - "kiwisolver 1.4.5\n", - "lxml 4.9.3\n", - "MarkupSafe 2.1.3\n", - "matplotlib 3.8.2\n", - "matplotlib-inline 0.1.6\n", - "mistune 3.0.2\n", - "munkres 1.1.4\n", - "nbclient 0.8.0\n", - "nbconvert 7.11.0\n", - "nbformat 5.9.2\n", - "nest-asyncio 1.5.8\n", - "notebook 7.0.6\n", - "notebook_shim 0.2.3\n", - "numpy 1.26.2\n", - "openpyxl 3.1.2\n", - "overrides 7.4.0\n", - "packaging 23.2\n", - "pandas 2.1.3\n", - "pandas-datareader 0.10.0\n", - "pandocfilters 1.5.0\n", - "parso 0.8.3\n", - "pexpect 4.8.0\n", - "pickleshare 0.7.5\n", - "Pillow 10.1.0\n", - "pip 23.3.1\n", - "pkgutil_resolve_name 1.3.10\n", - "platformdirs 4.0.0\n", - "prometheus-client 0.19.0\n", - "prompt-toolkit 3.0.41\n", - "psutil 5.9.5\n", - "ptyprocess 0.7.0\n", - "pure-eval 0.2.2\n", - "pycparser 2.21\n", - "Pygments 2.17.2\n", - "pyobjc-core 10.0\n", - "pyobjc-framework-Cocoa 10.0\n", - "pyparsing 3.1.1\n", - "PySocks 1.7.1\n", - "python-dateutil 2.8.2\n", - "python-json-logger 2.0.7\n", - "python-slugify 8.0.1\n", - "pytz 2023.3.post1\n", - "PyYAML 6.0.1\n", - "pyzmq 25.1.1\n", - "qtconsole 5.5.1\n", - "QtPy 2.4.1\n", - "referencing 0.31.1\n", - "requests 2.31.0\n", - "rfc3339-validator 0.1.4\n", - "rfc3986-validator 0.1.1\n", - "rpds-py 0.13.2\n", - "s3transfer 0.8.2\n", - "scikit-learn 1.3.2\n", - "SciPy 1.11.4\n", - "seaborn 0.13.0\n", - "Send2Trash 1.8.2\n", - "setuptools 68.2.2\n", - "six 1.16.0\n", - "sniffio 1.3.0\n", - "soupsieve 2.5\n", - "stack-data 0.6.2\n", - "terminado 0.18.0\n", - "text-unidecode 1.3\n", - "threadpoolctl 3.2.0\n", - "tinycss2 1.2.1\n", - "tomli 2.0.1\n", - "tornado 6.3.3\n", - "tqdm 4.66.1\n", - "traitlets 5.14.0\n", - "types-python-dateutil 2.8.19.14\n", - "typing_extensions 4.8.0\n", - "typing-utils 0.1.0\n", - "tzdata 2023.3\n", - "uri-template 1.3.0\n", - "urllib3 1.26.18\n", - "wcwidth 0.2.12\n", - "webcolors 1.13\n", - "webencodings 0.5.1\n", - "websocket-client 1.7.0\n", - "Werkzeug 3.0.1\n", - "wheel 0.42.0\n", - "widgetsnbextension 4.0.9\n", - "zipp 3.17.0\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } ], "source": [ - "%pip install --upgrade anomalytics\n", - "%pip list" + "%pip install --upgrade anomalytics" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ @@ -239,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 42, "metadata": {}, "outputs": [ { @@ -318,7 +162,7 @@ "4 2023-10-18 09:05:00 48.829233 76.445099 26.710413" ] }, - "execution_count": 3, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } @@ -356,7 +200,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 43, "metadata": {}, "outputs": [], "source": [ @@ -369,7 +213,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 44, "metadata": {}, "outputs": [ { @@ -414,7 +258,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 45, "metadata": {}, "outputs": [], "source": [ @@ -428,7 +272,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 46, "metadata": {}, "outputs": [ { @@ -449,7 +293,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 47, "metadata": {}, "outputs": [ { @@ -478,7 +322,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 48, "metadata": {}, "outputs": [ { @@ -677,7 +521,7 @@ "19 58.224653 85.177029 60.362306 2023-10-18 09:20:00" ] }, - "execution_count": 9, + "execution_count": 48, "metadata": {}, "output_type": "execute_result" } @@ -689,7 +533,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 49, "metadata": {}, "outputs": [ { @@ -768,7 +612,7 @@ "65699 0.0 0.0 0.0 2023-12-03 00:00:00" ] }, - "execution_count": 10, + "execution_count": 49, "metadata": {}, "output_type": "execute_result" } @@ -779,7 +623,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 50, "metadata": {}, "outputs": [ { @@ -816,7 +660,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 51, "metadata": {}, "outputs": [], "source": [ @@ -825,7 +669,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 52, "metadata": {}, "outputs": [ { @@ -845,7 +689,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 53, "metadata": {}, "outputs": [ { @@ -1087,7 +931,7 @@ "19 0.000000 2023-11-17 01:05:00 " ] }, - "execution_count": 14, + "execution_count": 53, "metadata": {}, "output_type": "execute_result" } @@ -1098,16022 +942,37 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{0: {'xandr': {'c': -0.11675297447288158,\n", - " 'loc': 0,\n", - " 'scale': 2.3129766056305603,\n", - " 'p_value': 0.9198385927065513,\n", - " 'anomaly_score': 1.0871472537998},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.0871472537998},\n", - " 1: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 2: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 3: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12551636173415356,\n", - " 'loc': 0,\n", - " 'scale': 3.7839550066256016,\n", - " 'p_value': 0.5506986257362975,\n", - " 'anomaly_score': 1.8158752414952473},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.8158752414952473},\n", - " 4: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 5: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 6: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 7: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 8: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 9: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 10: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13161034170526126,\n", - " 'loc': 0,\n", - " 'scale': 6.085878530787276,\n", - " 'p_value': 0.8860384017726413,\n", - " 'anomaly_score': 1.1286192539729236},\n", - " 'total_anomaly_score': 1.1286192539729236},\n", - " 11: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 12: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 13: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 14: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 15: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 16: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 17: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 18: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 19: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 20: {'xandr': {'c': -0.1164822074244576,\n", - " 'loc': 0,\n", - " 'scale': 2.311478113762001,\n", - " 'p_value': 0.5063583264515152,\n", - " 'anomaly_score': 1.9748860594588284},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.9748860594588284},\n", - " 21: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 22: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 23: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 24: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 25: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1254872355207557,\n", - " 'loc': 0,\n", - " 'scale': 3.7831752431590724,\n", - " 'p_value': 0.09262374989667296,\n", - " 'anomaly_score': 10.796367034540888},\n", - " 'adobe': {'c': -0.13142739011640972,\n", - " 'loc': 0,\n", - " 'scale': 6.082596903002937,\n", - " 'p_value': 0.018604000827020465,\n", - " 'anomaly_score': 53.75187892636509},\n", - " 'total_anomaly_score': 64.54824596090597},\n", - " 26: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 27: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 28: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 29: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 30: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 31: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 32: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 33: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 34: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 35: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 36: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 37: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 38: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 39: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 40: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 41: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 42: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 43: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 44: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 45: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 46: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 47: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 48: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 49: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 50: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 51: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 52: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 53: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 54: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 55: {'xandr': {'c': -0.11650143424146539,\n", - " 'loc': 0,\n", - " 'scale': 2.311227021439011,\n", - " 'p_value': 0.5488701207334602,\n", - " 'anomaly_score': 1.821924645239735},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.821924645239735},\n", - " 56: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 57: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 58: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 59: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13148902720118152,\n", - " 'loc': 0,\n", - " 'scale': 6.090361768363298,\n", - " 'p_value': 0.2745294160148301,\n", - " 'anomaly_score': 3.6425969009673627},\n", - " 'total_anomaly_score': 3.6425969009673627},\n", - " 60: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 61: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 62: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 63: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 64: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 65: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 66: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 67: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13162507992341044,\n", - " 'loc': 0,\n", - " 'scale': 6.091907321587656,\n", - " 'p_value': 0.8860890890484872,\n", - " 'anomaly_score': 1.1285546931560058},\n", - " 'total_anomaly_score': 1.1285546931560058},\n", - " 68: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 69: {'xandr': {'c': -0.11646322364308334,\n", - " 'loc': 0,\n", - " 'scale': 2.310762195484766,\n", - " 'p_value': 0.44817347584949707,\n", - " 'anomaly_score': 2.2312788549222713},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.2312788549222713},\n", - " 70: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12590538469761708,\n", - " 'loc': 0,\n", - " 'scale': 3.7868825918650275,\n", - " 'p_value': 0.3865306400670228,\n", - " 'anomaly_score': 2.587117026030858},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.587117026030858},\n", - " 71: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 72: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 73: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 74: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 75: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 76: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 77: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 78: {'xandr': {'c': -0.11653358955494175,\n", - " 'loc': 0,\n", - " 'scale': 2.310730051809077,\n", - " 'p_value': 0.07027851888999333,\n", - " 'anomaly_score': 14.229098959317794},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 14.229098959317794},\n", - " 79: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 80: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 81: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 82: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 83: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 84: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 85: {'xandr': {'c': -0.11687722098686859,\n", - " 'loc': 0,\n", - " 'scale': 2.3131495902767076,\n", - " 'p_value': 0.014372526581000394,\n", - " 'anomaly_score': 69.57718911593034},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 69.57718911593034},\n", - " 86: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13144945404763403,\n", - " 'loc': 0,\n", - " 'scale': 6.08862957729078,\n", - " 'p_value': 0.5153799581949171,\n", - " 'anomaly_score': 1.940316040814686},\n", - " 'total_anomaly_score': 1.940316040814686},\n", - " 87: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 88: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 89: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 90: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 91: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 92: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 93: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 94: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 95: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 96: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 97: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 98: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 99: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 100: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 101: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 102: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 103: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 104: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 105: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 106: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 107: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 108: {'xandr': {'c': -0.11667796717855528,\n", - " 'loc': 0,\n", - " 'scale': 2.315815609624986,\n", - " 'p_value': 0.1853824402697661,\n", - " 'anomaly_score': 5.394254162070653},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 5.394254162070653},\n", - " 109: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 110: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13143331854721801,\n", - " 'loc': 0,\n", - " 'scale': 6.087689496025867,\n", - " 'p_value': 0.45690027682085693,\n", - " 'anomaly_score': 2.188661401034965},\n", - " 'total_anomaly_score': 2.188661401034965},\n", - " 111: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 112: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13145904601805863,\n", - " 'loc': 0,\n", - " 'scale': 6.087366799428139,\n", - " 'p_value': 0.3690128009518503,\n", - " 'anomaly_score': 2.7099330901815586},\n", - " 'total_anomaly_score': 2.7099330901815586},\n", - " 113: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 114: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 115: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 116: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 117: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 118: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1260533072133096,\n", - " 'loc': 0,\n", - " 'scale': 3.7873806848102807,\n", - " 'p_value': 0.32707547282990096,\n", - " 'anomaly_score': 3.0573983165043392},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.0573983165043392},\n", - " 119: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 120: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 121: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 122: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 123: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 124: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 125: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 126: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 127: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 128: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 129: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 130: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 131: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 132: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 133: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 134: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 135: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 136: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 137: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 138: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 139: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 140: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 141: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13153892811178536,\n", - " 'loc': 0,\n", - " 'scale': 6.087805061381914,\n", - " 'p_value': 0.7999032737618709,\n", - " 'anomaly_score': 1.250151153022656},\n", - " 'total_anomaly_score': 1.250151153022656},\n", - " 142: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 143: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 144: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 145: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 146: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 147: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 148: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 149: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 150: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 151: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 152: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 153: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 154: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1262461786273018,\n", - " 'loc': 0,\n", - " 'scale': 3.7882794896596934,\n", - " 'p_value': 0.015505840497919709,\n", - " 'anomaly_score': 64.49182810400777},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 64.49182810400777},\n", - " 155: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12605441362468953,\n", - " 'loc': 0,\n", - " 'scale': 3.792456556376073,\n", - " 'p_value': 0.9142620899339753,\n", - " 'anomaly_score': 1.093778262283867},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.093778262283867},\n", - " 156: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 157: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 158: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 159: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 160: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 161: {'xandr': {'c': -0.11697703993035957,\n", - " 'loc': 0,\n", - " 'scale': 2.317106470812306,\n", - " 'p_value': 0.4084271447669645,\n", - " 'anomaly_score': 2.448417086897023},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.448417086897023},\n", - " 162: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 163: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 164: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12573916957132553,\n", - " 'loc': 0,\n", - " 'scale': 3.7898587499108665,\n", - " 'p_value': 0.1733945716108777,\n", - " 'anomaly_score': 5.7671932328086},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 5.7671932328086},\n", - " 165: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 166: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 167: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 168: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13139356212721204,\n", - " 'loc': 0,\n", - " 'scale': 6.085024620294279,\n", - " 'p_value': 0.7369366651745635,\n", - " 'anomaly_score': 1.3569687155722165},\n", - " 'total_anomaly_score': 1.3569687155722165},\n", - " 169: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 170: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 171: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 172: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 173: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 174: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 175: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 176: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 177: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 178: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 179: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 180: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12610889420539093,\n", - " 'loc': 0,\n", - " 'scale': 3.7923974070455646,\n", - " 'p_value': 0.7102652916965964,\n", - " 'anomaly_score': 1.4079246327964585},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.4079246327964585},\n", - " 181: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 182: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12593817791720419,\n", - " 'loc': 0,\n", - " 'scale': 3.7907513573080203,\n", - " 'p_value': 0.9363632262636357,\n", - " 'anomaly_score': 1.067961632784634},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.067961632784634},\n", - " 183: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 184: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 185: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 186: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 187: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 188: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 189: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 190: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 191: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 192: {'xandr': {'c': -0.11708042535694346,\n", - " 'loc': 0,\n", - " 'scale': 2.3172053390388614,\n", - " 'p_value': 0.9288393484277615,\n", - " 'anomaly_score': 1.0766124429296535},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.0766124429296535},\n", - " 193: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 194: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1312721780863085,\n", - " 'loc': 0,\n", - " 'scale': 6.0825718636567085,\n", - " 'p_value': 0.6350572546214351,\n", - " 'anomaly_score': 1.5746611706626537},\n", - " 'total_anomaly_score': 1.5746611706626537},\n", - " 195: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 196: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 197: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 198: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 199: {'xandr': {'c': -0.11680778935777784,\n", - " 'loc': 0,\n", - " 'scale': 2.3157453991027674,\n", - " 'p_value': 0.22711104522579342,\n", - " 'anomaly_score': 4.403132392816041},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 4.403132392816041},\n", - " 200: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 201: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 202: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 203: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 204: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 205: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 206: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 207: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 208: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 209: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 210: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 211: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 212: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 213: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12560362258816704,\n", - " 'loc': 0,\n", - " 'scale': 3.7880211618903337,\n", - " 'p_value': 0.6017536629226964,\n", - " 'anomaly_score': 1.6618095769339154},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.6618095769339154},\n", - " 214: {'xandr': {'c': -0.1170890524487687,\n", - " 'loc': 0,\n", - " 'scale': 2.316825925024685,\n", - " 'p_value': 0.7838510090665026,\n", - " 'anomaly_score': 1.2757526474207284},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.2757526474207284},\n", - " 215: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 216: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 217: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 218: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 219: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 220: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 221: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 222: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 223: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 224: {'xandr': {'c': -0.11687449510468396,\n", - " 'loc': 0,\n", - " 'scale': 2.315610190722367,\n", - " 'p_value': 0.9152142726336686,\n", - " 'anomaly_score': 1.0926403028247664},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.0926403028247664},\n", - " 225: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 226: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 227: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 228: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 229: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 230: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 231: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 232: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 233: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 234: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 235: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 236: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13119312638532948,\n", - " 'loc': 0,\n", - " 'scale': 6.080745973899562,\n", - " 'p_value': 0.5402789221480664,\n", - " 'anomaly_score': 1.8508958225209913},\n", - " 'total_anomaly_score': 1.8508958225209913},\n", - " 237: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 238: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 239: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 240: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 241: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12552869064405683,\n", - " 'loc': 0,\n", - " 'scale': 3.7870004718852033,\n", - " 'p_value': 0.08142711525631458,\n", - " 'anomaly_score': 12.280921371857776},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 12.280921371857776},\n", - " 242: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 243: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 244: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 245: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 246: {'xandr': {'c': -0.11657803400903363,\n", - " 'loc': 0,\n", - " 'scale': 2.3140758216563366,\n", - " 'p_value': 0.19895445351859298,\n", - " 'anomaly_score': 5.026276026068181},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 5.026276026068181},\n", - " 247: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 248: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 249: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 250: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 251: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 252: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 253: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 254: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 255: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 256: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 257: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 258: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 259: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 260: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 261: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 262: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 263: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12592856605237196,\n", - " 'loc': 0,\n", - " 'scale': 3.7908677370305224,\n", - " 'p_value': 0.5786182499051268,\n", - " 'anomaly_score': 1.7282552013593853},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.7282552013593853},\n", - " 264: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 265: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 266: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 267: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 268: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 269: {'xandr': {'c': -0.1168995161528846,\n", - " 'loc': 0,\n", - " 'scale': 2.315399341300343,\n", - " 'p_value': 0.017828553952095393,\n", - " 'anomaly_score': 56.08979857182808},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 56.08979857182808},\n", - " 270: {'xandr': {'c': -0.11680851756442086,\n", - " 'loc': 0,\n", - " 'scale': 2.318036342454149,\n", - " 'p_value': 0.6264761925494102,\n", - " 'anomaly_score': 1.5962298518169626},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.5962298518169626},\n", - " 271: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13117650054908397,\n", - " 'loc': 0,\n", - " 'scale': 6.079715370686937,\n", - " 'p_value': 0.5045806314555685,\n", - " 'anomaly_score': 1.9818438078276817},\n", - " 'total_anomaly_score': 1.9818438078276817},\n", - " 272: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 273: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 274: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 275: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 276: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 277: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 278: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 279: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 280: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 281: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 282: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 283: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 284: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 285: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 286: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 287: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 288: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 289: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 290: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12588027089244885,\n", - " 'loc': 0,\n", - " 'scale': 3.7899538792391603,\n", - " 'p_value': 0.13474841517142658,\n", - " 'anomaly_score': 7.42123756133089},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 7.42123756133089},\n", - " 291: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 292: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 293: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 294: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 295: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 296: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 297: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 298: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 299: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 300: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 301: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 302: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 303: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 304: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 305: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 306: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 307: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 308: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 309: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 310: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12629354986409635,\n", - " 'loc': 0,\n", - " 'scale': 3.7931055046455455,\n", - " 'p_value': 0.618785661058276,\n", - " 'anomaly_score': 1.616068475616829},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.616068475616829},\n", - " 311: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 312: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 313: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 314: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 315: {'xandr': {'c': -0.11674717015159344,\n", - " 'loc': 0,\n", - " 'scale': 2.3174007532270897,\n", - " 'p_value': 0.4582281018012466,\n", - " 'anomaly_score': 2.1823192337377493},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.1823192337377493},\n", - " 316: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 317: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 318: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 319: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 320: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 321: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 322: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 323: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 324: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 325: {'xandr': {'c': -0.11677767095107505,\n", - " 'loc': 0,\n", - " 'scale': 2.317264822860332,\n", - " 'p_value': 0.42575085670683016,\n", - " 'anomaly_score': 2.348791515617771},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.348791515617771},\n", - " 326: {'xandr': {'c': -0.11685521220198902,\n", - " 'loc': 0,\n", - " 'scale': 2.3173198676952356,\n", - " 'p_value': 0.7227427526101917,\n", - " 'anomaly_score': 1.3836181634315825},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.3836181634315825},\n", - " 327: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 328: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 329: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 330: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 331: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12620266886468956,\n", - " 'loc': 0,\n", - " 'scale': 3.791924912891103,\n", - " 'p_value': 0.6816328075443503,\n", - " 'anomaly_score': 1.467065535772257},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.467065535772257},\n", - " 332: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 333: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 334: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 335: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 336: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 337: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 338: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 339: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 340: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 341: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 342: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 343: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 344: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 345: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12605899193249331,\n", - " 'loc': 0,\n", - " 'scale': 3.7904110905371446,\n", - " 'p_value': 0.2415259872392974,\n", - " 'anomaly_score': 4.140341217234016},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 4.140341217234016},\n", - " 346: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 347: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 348: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 349: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 350: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 351: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 352: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 353: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 354: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 355: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 356: {'xandr': {'c': -0.11671257674084633,\n", - " 'loc': 0,\n", - " 'scale': 2.316350175810169,\n", - " 'p_value': 0.8445871136659668,\n", - " 'anomaly_score': 1.1840104872775725},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.1840104872775725},\n", - " 357: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 358: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 359: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 360: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 361: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 362: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 363: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 364: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 365: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 366: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 367: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 368: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 369: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 370: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 371: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13117018239822476,\n", - " 'loc': 0,\n", - " 'scale': 6.078910774309276,\n", - " 'p_value': 0.5453204202494675,\n", - " 'anomaly_score': 1.8337842539300664},\n", - " 'total_anomaly_score': 1.8337842539300664},\n", - " 372: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 373: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 374: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12634981037169557,\n", - " 'loc': 0,\n", - " 'scale': 3.7921859639640414,\n", - " 'p_value': 0.9634175766041787,\n", - " 'anomaly_score': 1.0379715133750889},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.0379715133750889},\n", - " 375: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 376: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 377: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 378: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 379: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 380: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 381: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 382: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 383: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 384: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 385: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 386: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 387: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 388: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 389: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 390: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 391: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 392: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 393: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 394: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 395: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 396: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 397: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.131142878464863,\n", - " 'loc': 0,\n", - " 'scale': 6.077772746659931,\n", - " 'p_value': 0.3832865547191108,\n", - " 'anomaly_score': 2.6090140332025054},\n", - " 'total_anomaly_score': 2.6090140332025054},\n", - " 398: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 399: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 400: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 401: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12599708780073957,\n", - " 'loc': 0,\n", - " 'scale': 3.789373731798622,\n", - " 'p_value': 0.006114259824778871,\n", - " 'anomaly_score': 163.5520943920904},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 163.5520943920904},\n", - " 402: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 403: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 404: {'xandr': {'c': -0.11646858497846022,\n", - " 'loc': 0,\n", - " 'scale': 2.314963235525026,\n", - " 'p_value': 0.34252342247731327,\n", - " 'anomaly_score': 2.91950837337623},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13121683032371897,\n", - " 'loc': 0,\n", - " 'scale': 6.0781116138694316,\n", - " 'p_value': 0.30729348995612116,\n", - " 'anomaly_score': 3.254217979504842},\n", - " 'total_anomaly_score': 6.173726352881072},\n", - " 405: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 406: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 407: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 408: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 409: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 410: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 411: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 412: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 413: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.124972072803778,\n", - " 'loc': 0,\n", - " 'scale': 3.7917978622392035,\n", - " 'p_value': 0.0850096309982364,\n", - " 'anomaly_score': 11.763373023237166},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 11.763373023237166},\n", - " 414: {'xandr': {'c': -0.11662301555207502,\n", - " 'loc': 0,\n", - " 'scale': 2.315455819861299,\n", - " 'p_value': 0.38199000918259496,\n", - " 'anomaly_score': 2.617869514807101},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.617869514807101},\n", - " 415: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 416: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 417: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 418: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 419: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 420: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 421: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 422: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 423: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 424: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 425: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 426: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 427: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 428: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 429: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 430: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 431: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 432: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 433: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12541623494610538,\n", - " 'loc': 0,\n", - " 'scale': 3.7957089433459026,\n", - " 'p_value': 0.6317814764332443,\n", - " 'anomaly_score': 1.5828257669812555},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.5828257669812555},\n", - " 434: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 435: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 436: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 437: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 438: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 439: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 440: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1313308164472492,\n", - " 'loc': 0,\n", - " 'scale': 6.079219587714341,\n", - " 'p_value': 0.45627020973147053,\n", - " 'anomaly_score': 2.1916837406249505},\n", - " 'total_anomaly_score': 2.1916837406249505},\n", - " 441: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 442: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 443: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 444: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 445: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 446: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 447: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 448: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 449: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 450: {'xandr': {'c': -0.11672517394055977,\n", - " 'loc': 0,\n", - " 'scale': 2.315608407701226,\n", - " 'p_value': 0.07412886641660649,\n", - " 'anomaly_score': 13.490021476653501},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 13.490021476653501},\n", - " 451: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 452: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 453: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 454: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13136040830750598,\n", - " 'loc': 0,\n", - " 'scale': 6.078880349510408,\n", - " 'p_value': 0.11736113601705746,\n", - " 'anomaly_score': 8.520708250938014},\n", - " 'total_anomaly_score': 8.520708250938014},\n", - " 455: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 456: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 457: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 458: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 459: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 460: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 461: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 462: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12531268047772356,\n", - " 'loc': 0,\n", - " 'scale': 3.794468306742914,\n", - " 'p_value': 0.8806777567687423,\n", - " 'anomaly_score': 1.1354891074677054},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.1354891074677054},\n", - " 463: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 464: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 465: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 466: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 467: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 468: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 469: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 470: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 471: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13160851288152975,\n", - " 'loc': 0,\n", - " 'scale': 6.083221775227267,\n", - " 'p_value': 0.7884791278814492,\n", - " 'anomaly_score': 1.2682643898093822},\n", - " 'total_anomaly_score': 1.2682643898093822},\n", - " 472: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 473: {'xandr': {'c': -0.11708612777880173,\n", - " 'loc': 0,\n", - " 'scale': 2.3179463972367964,\n", - " 'p_value': 0.4666444155315666,\n", - " 'anomaly_score': 2.142959321308655},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.142959321308655},\n", - " 474: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 475: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 476: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 477: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 478: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 479: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 480: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 481: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 482: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 483: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 484: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 485: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 486: {'xandr': {'c': -0.11714703595723078,\n", - " 'loc': 0,\n", - " 'scale': 2.3178598187786754,\n", - " 'p_value': 0.1471686369703016,\n", - " 'anomaly_score': 6.79492601539687},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 6.79492601539687},\n", - " 487: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 488: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 489: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 490: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 491: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 492: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1314688743087321,\n", - " 'loc': 0,\n", - " 'scale': 6.080428637661777,\n", - " 'p_value': 0.1432736714016492,\n", - " 'anomaly_score': 6.979649437450579},\n", - " 'total_anomaly_score': 6.979649437450579},\n", - " 493: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 494: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 495: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 496: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 497: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 498: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 499: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 500: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 501: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 502: {'xandr': {'c': -0.11747801894618835,\n", - " 'loc': 0,\n", - " 'scale': 2.31950632030369,\n", - " 'p_value': 0.49490237824548555,\n", - " 'anomaly_score': 2.0206005142775285},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.0206005142775285},\n", - " 503: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 504: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 505: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 506: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 507: {'xandr': {'c': -0.11749255649254653,\n", - " 'loc': 0,\n", - " 'scale': 2.3192605870575758,\n", - " 'p_value': 0.5409411439413372,\n", - " 'anomaly_score': 1.8486299502269803},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.8486299502269803},\n", - " 508: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 509: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 510: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 511: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 512: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 513: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 514: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12501151538072788,\n", - " 'loc': 0,\n", - " 'scale': 3.79201692697768,\n", - " 'p_value': 0.11368909796865474,\n", - " 'anomaly_score': 8.7959181475405},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 8.7959181475405},\n", - " 515: {'xandr': {'c': -0.11746735961803044,\n", - " 'loc': 0,\n", - " 'scale': 2.3188598556215916,\n", - " 'p_value': 0.06773000585926768,\n", - " 'anomaly_score': 14.764504850004634},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 14.764504850004634},\n", - " 516: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 517: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 518: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 519: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 520: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 521: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 522: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 523: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 524: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 525: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 526: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12542997050786078,\n", - " 'loc': 0,\n", - " 'scale': 3.7954270352505923,\n", - " 'p_value': 0.5168297472541313,\n", - " 'anomaly_score': 1.9348731479039423},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.9348731479039423},\n", - " 527: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 528: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 529: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 530: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 531: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 532: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 533: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 534: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 535: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13170126603394391,\n", - " 'loc': 0,\n", - " 'scale': 6.084182183805523,\n", - " 'p_value': 0.8265114622071345,\n", - " 'anomaly_score': 1.2099045757085787},\n", - " 'total_anomaly_score': 1.2099045757085787},\n", - " 536: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 537: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 538: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 539: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13154657518150298,\n", - " 'loc': 0,\n", - " 'scale': 6.081290621483767,\n", - " 'p_value': 0.6454620767618272,\n", - " 'anomaly_score': 1.5492776973309244},\n", - " 'total_anomaly_score': 1.5492776973309244},\n", - " 540: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 541: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 542: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 543: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 544: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 545: {'xandr': {'c': -0.11783601909334855,\n", - " 'loc': 0,\n", - " 'scale': 2.3212959659051133,\n", - " 'p_value': 0.40065642432487303,\n", - " 'anomaly_score': 2.4959040696403463},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.4959040696403463},\n", - " 546: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 547: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 548: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 549: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1254265950854027,\n", - " 'loc': 0,\n", - " 'scale': 3.7948498845101506,\n", - " 'p_value': 0.01955431290221901,\n", - " 'anomaly_score': 51.13961329147601},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 51.13961329147601},\n", - " 550: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 551: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 552: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 553: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 554: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12538848962294363,\n", - " 'loc': 0,\n", - " 'scale': 3.799256929774843,\n", - " 'p_value': 0.21476636871483926,\n", - " 'anomaly_score': 4.656222508132881},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 4.656222508132881},\n", - " 555: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 556: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13146508667887313,\n", - " 'loc': 0,\n", - " 'scale': 6.079405556153603,\n", - " 'p_value': 0.746681192126076,\n", - " 'anomaly_score': 1.3392596606761076},\n", - " 'total_anomaly_score': 1.3392596606761076},\n", - " 557: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 558: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12572353853527068,\n", - " 'loc': 0,\n", - " 'scale': 3.801285649429541,\n", - " 'p_value': 0.2706042671149182,\n", - " 'anomaly_score': 3.6954332267618213},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.6954332267618213},\n", - " 559: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 560: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 561: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 562: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 563: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 564: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 565: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 566: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 567: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12598397167312125,\n", - " 'loc': 0,\n", - " 'scale': 3.8028034566088955,\n", - " 'p_value': 0.8108152308285005,\n", - " 'anomaly_score': 1.2333266100319653},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.2333266100319653},\n", - " 568: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 569: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 570: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 571: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 572: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 573: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 574: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 575: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 576: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 577: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 578: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 579: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 580: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 581: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 582: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 583: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 584: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 585: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 586: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 587: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 588: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 589: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 590: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 591: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12573755831386751,\n", - " 'loc': 0,\n", - " 'scale': 3.800647003740279,\n", - " 'p_value': 0.06266100835208603,\n", - " 'anomaly_score': 15.95888777245809},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 15.95888777245809},\n", - " 592: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 593: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 594: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 595: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 596: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 597: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 598: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 599: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 600: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1313420151659499,\n", - " 'loc': 0,\n", - " 'scale': 6.076911791592497,\n", - " 'p_value': 0.8075034040209786,\n", - " 'anomaly_score': 1.2383848724605753},\n", - " 'total_anomaly_score': 1.2383848724605753},\n", - " 601: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 602: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 603: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 604: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 605: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 606: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 607: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 608: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 609: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 610: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 611: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 612: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 613: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 614: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12613391030930501,\n", - " 'loc': 0,\n", - " 'scale': 3.804840950448952,\n", - " 'p_value': 0.8274101101935922,\n", - " 'anomaly_score': 1.2085905014697322},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.2085905014697322},\n", - " 615: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 616: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 617: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13119746760969095,\n", - " 'loc': 0,\n", - " 'scale': 6.074151677912544,\n", - " 'p_value': 0.2423580437780692,\n", - " 'anomaly_score': 4.126126719011293},\n", - " 'total_anomaly_score': 4.126126719011293},\n", - " 618: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 619: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 620: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 621: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 622: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 623: {'xandr': {'c': -0.11793203855370415,\n", - " 'loc': 0,\n", - " 'scale': 2.321451811053885,\n", - " 'p_value': 0.38732334772747673,\n", - " 'anomaly_score': 2.581822154195586},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.581822154195586},\n", - " 624: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 625: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 626: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 627: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 628: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 629: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 630: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 631: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 632: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13135566042821153,\n", - " 'loc': 0,\n", - " 'scale': 6.076097423763482,\n", - " 'p_value': 0.2781873091600072,\n", - " 'anomaly_score': 3.594700286722361},\n", - " 'total_anomaly_score': 3.594700286722361},\n", - " 633: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 634: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 635: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 636: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 637: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 638: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 639: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 640: {'xandr': {'c': -0.11804091709862731,\n", - " 'loc': 0,\n", - " 'scale': 2.321635361854943,\n", - " 'p_value': 0.034595079364406776,\n", - " 'anomaly_score': 28.90584494593911},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 28.90584494593911},\n", - " 641: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 642: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 643: {'xandr': {'c': -0.11825169549941877,\n", - " 'loc': 0,\n", - " 'scale': 2.3243792886426116,\n", - " 'p_value': 0.5553826891685897,\n", - " 'anomaly_score': 1.8005602614244323},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.8005602614244323},\n", - " 644: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 645: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 646: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 647: {'xandr': {'c': -0.1182194726487423,\n", - " 'loc': 0,\n", - " 'scale': 2.3238664454874414,\n", - " 'p_value': 0.7198030329937758,\n", - " 'anomaly_score': 1.3892689446456488},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.3892689446456488},\n", - " 648: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 649: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 650: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13150071156695775,\n", - " 'loc': 0,\n", - " 'scale': 6.0776754870618435,\n", - " 'p_value': 0.5021804018603774,\n", - " 'anomaly_score': 1.9913162606413954},\n", - " 'total_anomaly_score': 1.9913162606413954},\n", - " 651: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 652: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 653: {'xandr': {'c': -0.11805224279139628,\n", - " 'loc': 0,\n", - " 'scale': 2.3228987322496732,\n", - " 'p_value': 0.41964982394714706,\n", - " 'anomaly_score': 2.3829391624526104},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.3829391624526104},\n", - " 654: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12587824364237715,\n", - " 'loc': 0,\n", - " 'scale': 3.8026497073422565,\n", - " 'p_value': 0.5425782437086546,\n", - " 'anomaly_score': 1.843052152560995},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.843052152560995},\n", - " 655: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 656: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 657: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 658: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12585274605980112,\n", - " 'loc': 0,\n", - " 'scale': 3.8019131362133116,\n", - " 'p_value': 0.13816044677550757,\n", - " 'anomaly_score': 7.237961539201358},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 7.237961539201358},\n", - " 659: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 660: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 661: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 662: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 663: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1314906271534384,\n", - " 'loc': 0,\n", - " 'scale': 6.076846833605156,\n", - " 'p_value': 0.7563397895638757,\n", - " 'anomaly_score': 1.3221570698754654},\n", - " 'total_anomaly_score': 1.3221570698754654},\n", - " 664: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 665: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 666: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 667: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 668: {'xandr': {'c': -0.1181553276822582,\n", - " 'loc': 0,\n", - " 'scale': 2.3230016699769873,\n", - " 'p_value': 0.8258042992984763,\n", - " 'anomaly_score': 1.2109406560967333},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.2109406560967333},\n", - " 669: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 670: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12626128136310333,\n", - " 'loc': 0,\n", - " 'scale': 3.8050085221318954,\n", - " 'p_value': 0.2995961367345242,\n", - " 'anomaly_score': 3.3378267520389033},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.3378267520389033},\n", - " 671: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 672: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 673: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 674: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 675: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 676: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13137017465376427,\n", - " 'loc': 0,\n", - " 'scale': 6.074358665828491,\n", - " 'p_value': 0.5296118101950451,\n", - " 'anomaly_score': 1.8881754159366662},\n", - " 'total_anomaly_score': 1.8881754159366662},\n", - " 677: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 678: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 679: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 680: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 681: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 682: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1313465374208677,\n", - " 'loc': 0,\n", - " 'scale': 6.073340941609844,\n", - " 'p_value': 0.857715787064551,\n", - " 'anomaly_score': 1.1658873662829536},\n", - " 'total_anomaly_score': 1.1658873662829536},\n", - " 683: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 684: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 685: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 686: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 687: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 688: {'xandr': {'c': -0.11791375005253624,\n", - " 'loc': 0,\n", - " 'scale': 2.321704900644031,\n", - " 'p_value': 0.787087616206025,\n", - " 'anomaly_score': 1.270506585810955},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.270506585810955},\n", - " 689: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 690: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 691: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 692: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 693: {'xandr': {'c': -0.11773128042906798,\n", - " 'loc': 0,\n", - " 'scale': 2.320535741654211,\n", - " 'p_value': 0.2399518459449923,\n", - " 'anomaly_score': 4.167502842337978},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 4.167502842337978},\n", - " 694: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 695: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 696: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 697: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 698: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 699: {'xandr': {'c': -0.11797124001337378,\n", - " 'loc': 0,\n", - " 'scale': 2.32146298328335,\n", - " 'p_value': 0.8809517065866561,\n", - " 'anomaly_score': 1.1351360040774647},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.1351360040774647},\n", - " 700: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 701: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12648334963523844,\n", - " 'loc': 0,\n", - " 'scale': 3.8061881388827876,\n", - " 'p_value': 0.6239056475538102,\n", - " 'anomaly_score': 1.6028064562658935},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.6028064562658935},\n", - " 702: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 703: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 704: {'xandr': {'c': -0.11770719046036655,\n", - " 'loc': 0,\n", - " 'scale': 2.3200591377552637,\n", - " 'p_value': 0.5522511694029589,\n", - " 'anomaly_score': 1.8107702715796947},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.8107702715796947},\n", - " 705: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 706: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 707: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 708: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 709: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 710: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 711: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13117827190310016,\n", - " 'loc': 0,\n", - " 'scale': 6.070250033970024,\n", - " 'p_value': 0.6401113570495076,\n", - " 'anomaly_score': 1.5622281794988646},\n", - " 'total_anomaly_score': 1.5622281794988646},\n", - " 712: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 713: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 714: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 715: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 716: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 717: {'xandr': {'c': -0.11769333338170956,\n", - " 'loc': 0,\n", - " 'scale': 2.3195874081941747,\n", - " 'p_value': 0.7259287363980537,\n", - " 'anomaly_score': 1.3775456871453329},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.3775456871453329},\n", - " 718: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13110881842911817,\n", - " 'loc': 0,\n", - " 'scale': 6.068496998120684,\n", - " 'p_value': 0.2524649393750749,\n", - " 'anomaly_score': 3.960946032646333},\n", - " 'total_anomaly_score': 3.960946032646333},\n", - " 719: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 720: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 721: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 722: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 723: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13126137855186534,\n", - " 'loc': 0,\n", - " 'scale': 6.070335933470888,\n", - " 'p_value': 0.6263902354792867,\n", - " 'anomaly_score': 1.5964488961658911},\n", - " 'total_anomaly_score': 1.5964488961658911},\n", - " 724: {'xandr': {'c': -0.11752492152212132,\n", - " 'loc': 0,\n", - " 'scale': 2.3186473241971175,\n", - " 'p_value': 0.9372958762882128,\n", - " 'anomaly_score': 1.0668989646685547},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.0668989646685547},\n", - " 725: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 726: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 727: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13119436219976888,\n", - " 'loc': 0,\n", - " 'scale': 6.068584787499287,\n", - " 'p_value': 0.6124957911207232,\n", - " 'anomaly_score': 1.63266428030507},\n", - " 'total_anomaly_score': 1.63266428030507},\n", - " 728: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 729: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13114049798072092,\n", - " 'loc': 0,\n", - " 'scale': 6.067058230304426,\n", - " 'p_value': 0.9573296405704705,\n", - " 'anomaly_score': 1.0445722743987143},\n", - " 'total_anomaly_score': 1.0445722743987143},\n", - " 730: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 731: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 732: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 733: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 734: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 735: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 736: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 737: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 738: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 739: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 740: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 741: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 742: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 743: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 744: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 745: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 746: {'xandr': {'c': -0.1172559577281596,\n", - " 'loc': 0,\n", - " 'scale': 2.3171344763187003,\n", - " 'p_value': 0.763250046980626,\n", - " 'anomaly_score': 1.3101866209585487},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.3101866209585487},\n", - " 747: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 748: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 749: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 750: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 751: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 752: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13093042019817674,\n", - " 'loc': 0,\n", - " 'scale': 6.0634847985432945,\n", - " 'p_value': 0.4758562819168018,\n", - " 'anomaly_score': 2.1014748317956196},\n", - " 'total_anomaly_score': 2.1014748317956196},\n", - " 753: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1263934579478136,\n", - " 'loc': 0,\n", - " 'scale': 3.805025039677073,\n", - " 'p_value': 0.4679137061210201,\n", - " 'anomaly_score': 2.137146202213111},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.137146202213111},\n", - " 754: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 755: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 756: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13094251995540654,\n", - " 'loc': 0,\n", - " 'scale': 6.0629378775103095,\n", - " 'p_value': 0.7003592321702872,\n", - " 'anomaly_score': 1.4278386777328258},\n", - " 'total_anomaly_score': 1.4278386777328258},\n", - " 757: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 758: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 759: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 760: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 761: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 762: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 763: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 764: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 765: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 766: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 767: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 768: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 769: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 770: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 771: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 772: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 773: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 774: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 775: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 776: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 777: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 778: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 779: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 780: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 781: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 782: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 783: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 784: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 785: {'xandr': {'c': -0.11703582950124777,\n", - " 'loc': 0,\n", - " 'scale': 2.3159094267277665,\n", - " 'p_value': 0.6856722787487589,\n", - " 'anomaly_score': 1.458422676537016},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.458422676537016},\n", - " 786: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 787: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 788: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 789: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 790: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 791: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1308405869082695,\n", - " 'loc': 0,\n", - " 'scale': 6.060737647918087,\n", - " 'p_value': 0.8859852545991735,\n", - " 'anomaly_score': 1.1286869559159962},\n", - " 'total_anomaly_score': 1.1286869559159962},\n", - " 792: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 793: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 794: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 795: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 796: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13065972255899255,\n", - " 'loc': 0,\n", - " 'scale': 6.05745856964799,\n", - " 'p_value': 0.5106987735449248,\n", - " 'anomaly_score': 1.958101432393655},\n", - " 'total_anomaly_score': 1.958101432393655},\n", - " 797: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13065187540330503,\n", - " 'loc': 0,\n", - " 'scale': 6.0566119056896675,\n", - " 'p_value': 0.9457250820735643,\n", - " 'anomaly_score': 1.0573897414325042},\n", - " 'total_anomaly_score': 1.0573897414325042},\n", - " 798: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 799: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 800: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 801: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 802: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 803: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 804: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 805: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13045187584862375,\n", - " 'loc': 0,\n", - " 'scale': 6.053195617736527,\n", - " 'p_value': 0.012799108177886296,\n", - " 'anomaly_score': 78.130443629483},\n", - " 'total_anomaly_score': 78.130443629483},\n", - " 806: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 807: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 808: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 809: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 810: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 811: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 812: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 813: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 814: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 815: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 816: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 817: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 818: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 819: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 820: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 821: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1303899085738655,\n", - " 'loc': 0,\n", - " 'scale': 6.060910489939866,\n", - " 'p_value': 0.7527827522386541,\n", - " 'anomaly_score': 1.3284045058500102},\n", - " 'total_anomaly_score': 1.3284045058500102},\n", - " 822: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 823: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 824: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 825: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 826: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 827: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 828: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 829: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 830: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 831: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 832: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12644114053212674,\n", - " 'loc': 0,\n", - " 'scale': 3.804845797604602,\n", - " 'p_value': 0.18811407054274995,\n", - " 'anomaly_score': 5.315923455990202},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 5.315923455990202},\n", - " 833: {'xandr': {'c': -0.11695028472348781,\n", - " 'loc': 0,\n", - " 'scale': 2.315116748626842,\n", - " 'p_value': 0.43766579131337624,\n", - " 'anomaly_score': 2.284848438803349},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.284848438803349},\n", - " 834: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 835: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 836: {'xandr': {'c': -0.11700124282984037,\n", - " 'loc': 0,\n", - " 'scale': 2.3150615294466625,\n", - " 'p_value': 0.39046305722133734,\n", - " 'anomaly_score': 2.5610617483669946},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.5610617483669946},\n", - " 837: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 838: {'xandr': {'c': -0.11711541322171468,\n", - " 'loc': 0,\n", - " 'scale': 2.3152745186608046,\n", - " 'p_value': 0.8391856749850332,\n", - " 'anomaly_score': 1.1916313991153804},\n", - " 'gam': {'c': -0.12680598712338154,\n", - " 'loc': 0,\n", - " 'scale': 3.8072648749550133,\n", - " 'p_value': 0.6799409903818439,\n", - " 'anomaly_score': 1.4707158623256646},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.6623472614410453},\n", - " 839: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 840: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 841: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 842: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 843: {'xandr': {'c': -0.1168920695295344,\n", - " 'loc': 0,\n", - " 'scale': 2.314022513199577,\n", - " 'p_value': 0.7549537213017742,\n", - " 'anomaly_score': 1.3245845033728558},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.3245845033728558},\n", - " 844: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 845: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 846: {'xandr': {'c': -0.11670640735740687,\n", - " 'loc': 0,\n", - " 'scale': 2.3128923340209893,\n", - " 'p_value': 0.25063315388950114,\n", - " 'anomaly_score': 3.989895129520171},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.989895129520171},\n", - " 847: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 848: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 849: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 850: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 851: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 852: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 853: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 854: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 855: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 856: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 857: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 858: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 859: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 860: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 861: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 862: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 863: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 864: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 865: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13025968361363932,\n", - " 'loc': 0,\n", - " 'scale': 6.058360786635491,\n", - " 'p_value': 0.6229513039221318,\n", - " 'anomaly_score': 1.6052619100465015},\n", - " 'total_anomaly_score': 1.6052619100465015},\n", - " 866: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 867: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 868: {'xandr': {'c': -0.11694103309766736,\n", - " 'loc': 0,\n", - " 'scale': 2.313801948528959,\n", - " 'p_value': 0.1978322159222801,\n", - " 'anomaly_score': 5.054788449586278},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13019204541484974,\n", - " 'loc': 0,\n", - " 'scale': 6.056669125952222,\n", - " 'p_value': 0.12164206667421076,\n", - " 'anomaly_score': 8.22084026801568},\n", - " 'total_anomaly_score': 13.275628717601958},\n", - " 869: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 870: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 871: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 872: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 873: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 874: {'xandr': {'c': -0.11724965228819181,\n", - " 'loc': 0,\n", - " 'scale': 2.3150739083942558,\n", - " 'p_value': 0.8740894991864532,\n", - " 'anomaly_score': 1.144047607173792},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.144047607173792},\n", - " 875: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 876: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 877: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 878: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 879: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 880: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 881: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 882: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 883: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 884: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 885: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 886: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 887: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 888: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 889: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 890: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 891: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 892: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 893: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 894: {'xandr': {'c': -0.11700437416609302,\n", - " 'loc': 0,\n", - " 'scale': 2.313706171469617,\n", - " 'p_value': 0.0129494400496827,\n", - " 'anomaly_score': 77.22341631478521},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 77.22341631478521},\n", - " 895: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12664797360369773,\n", - " 'loc': 0,\n", - " 'scale': 3.8057141003545416,\n", - " 'p_value': 0.6471430173406004,\n", - " 'anomaly_score': 1.545253480613059},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.545253480613059},\n", - " 896: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 897: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 898: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 899: {'xandr': {'c': -0.11674414438337494,\n", - " 'loc': 0,\n", - " 'scale': 2.316250628846406,\n", - " 'p_value': 0.968440537588642,\n", - " 'anomaly_score': 1.0325879196361805},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.0325879196361805},\n", - " 900: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 901: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 902: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 903: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 904: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 905: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 906: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 907: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12652597243811536,\n", - " 'loc': 0,\n", - " 'scale': 3.804395945502864,\n", - " 'p_value': 0.05494517617877667,\n", - " 'anomaly_score': 18.19995984263062},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 18.19995984263062},\n", - " 908: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 909: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 910: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13043940477898364,\n", - " 'loc': 0,\n", - " 'scale': 6.0608500145209625,\n", - " 'p_value': 0.21967684619713043,\n", - " 'anomaly_score': 4.552141098669245},\n", - " 'total_anomaly_score': 4.552141098669245},\n", - " 911: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 912: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 913: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 914: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 915: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 916: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 917: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 918: {'xandr': {'c': -0.11643100888619715,\n", - " 'loc': 0,\n", - " 'scale': 2.314572353006458,\n", - " 'p_value': 0.16387872221339014,\n", - " 'anomaly_score': 6.102073450986991},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 6.102073450986991},\n", - " 919: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 920: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 921: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 922: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 923: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 924: {'xandr': {'c': -0.11674617032342366,\n", - " 'loc': 0,\n", - " 'scale': 2.3160995685206327,\n", - " 'p_value': 0.4539227621626807,\n", - " 'anomaly_score': 2.2030179655137268},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.2030179655137268},\n", - " 925: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13062492240903706,\n", - " 'loc': 0,\n", - " 'scale': 6.063247212327358,\n", - " 'p_value': 0.19346343401370283,\n", - " 'anomaly_score': 5.168935437841815},\n", - " 'total_anomaly_score': 5.168935437841815},\n", - " 926: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 927: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1268982016062742,\n", - " 'loc': 0,\n", - " 'scale': 3.8086853021341076,\n", - " 'p_value': 0.28823784162604554,\n", - " 'anomaly_score': 3.4693570919025323},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.4693570919025323},\n", - " 928: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 929: {'xandr': {'c': -0.11682058785485758,\n", - " 'loc': 0,\n", - " 'scale': 2.316084424625231,\n", - " 'p_value': 0.8661562994999003,\n", - " 'anomaly_score': 1.1545260371336885},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.1545260371336885},\n", - " 930: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 931: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13082417114865594,\n", - " 'loc': 0,\n", - " 'scale': 6.066022329638463,\n", - " 'p_value': 0.23280702854868973,\n", - " 'anomaly_score': 4.295402961989431},\n", - " 'total_anomaly_score': 4.295402961989431},\n", - " 932: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 933: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 934: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 935: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 936: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 937: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 938: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 939: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 940: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12713728107072889,\n", - " 'loc': 0,\n", - " 'scale': 3.8099945462223532,\n", - " 'p_value': 0.05860024124829208,\n", - " 'anomaly_score': 17.06477616300164},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 17.06477616300164},\n", - " 941: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 942: {'xandr': {'c': -0.11656361031888095,\n", - " 'loc': 0,\n", - " 'scale': 2.3146998800521965,\n", - " 'p_value': 0.9238373734370057,\n", - " 'anomaly_score': 1.0824415949742778},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.0824415949742778},\n", - " 943: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 944: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 945: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 946: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 947: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 948: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13098817888238595,\n", - " 'loc': 0,\n", - " 'scale': 6.06813706970352,\n", - " 'p_value': 0.5781174606309192,\n", - " 'anomaly_score': 1.7297522875518516},\n", - " 'total_anomaly_score': 1.7297522875518516},\n", - " 949: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 950: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 951: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 952: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 953: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 954: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1309521079980444,\n", - " 'loc': 0,\n", - " 'scale': 6.066757101307866,\n", - " 'p_value': 0.929725036736127,\n", - " 'anomaly_score': 1.0755868245848028},\n", - " 'total_anomaly_score': 1.0755868245848028},\n", - " 955: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 956: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 957: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 958: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12751927259900864,\n", - " 'loc': 0,\n", - " 'scale': 3.814235825486441,\n", - " 'p_value': 0.17227440752759154,\n", - " 'anomaly_score': 5.804692724540873},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 5.804692724540873},\n", - " 959: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 960: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 961: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 962: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 963: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 964: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 965: {'xandr': {'c': -0.1162586584495327,\n", - " 'loc': 0,\n", - " 'scale': 2.3130992414552924,\n", - " 'p_value': 0.9948922336738474,\n", - " 'anomaly_score': 1.0051339895450697},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.0051339895450697},\n", - " 966: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 967: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 968: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 969: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 970: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 971: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 972: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 973: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 974: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 975: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 976: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 977: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 978: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 979: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 980: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 981: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 982: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 983: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 984: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12789007658393864,\n", - " 'loc': 0,\n", - " 'scale': 3.816797426197956,\n", - " 'p_value': 0.5345353905769706,\n", - " 'anomaly_score': 1.870783520845295},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.870783520845295},\n", - " 985: {'xandr': {'c': -0.11594688842316264,\n", - " 'loc': 0,\n", - " 'scale': 2.311451283960828,\n", - " 'p_value': 0.3286238696094714,\n", - " 'anomaly_score': 3.042992589638652},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.042992589638652},\n", - " 986: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 987: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.13075424353624307,\n", - " 'loc': 0,\n", - " 'scale': 6.06337398826298,\n", - " 'p_value': 0.1974377564537105,\n", - " 'anomaly_score': 5.064887374945688},\n", - " 'total_anomaly_score': 5.064887374945688},\n", - " 988: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 989: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 990: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 991: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 992: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 993: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 994: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 995: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12788420712993306,\n", - " 'loc': 0,\n", - " 'scale': 3.8162055130033496,\n", - " 'p_value': 0.06957468260226762,\n", - " 'anomaly_score': 14.373044368978658},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 14.373044368978658},\n", - " 996: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 997: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 998: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 999: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " ...}" + "{'xandr': {'c': -0.11675297447288158,\n", + " 'loc': 0,\n", + " 'scale': 2.3129766056305603,\n", + " 'p_value': 0.9198385927065513,\n", + " 'anomaly_score': 1.0871472537998},\n", + " 'gam': {'c': 0.0,\n", + " 'loc': 0.0,\n", + " 'scale': 0.0,\n", + " 'p_value': 0.0,\n", + " 'anomaly_score': 0.0},\n", + " 'adobe': {'c': 0.0,\n", + " 'loc': 0.0,\n", + " 'scale': 0.0,\n", + " 'p_value': 0.0,\n", + " 'anomaly_score': 0.0},\n", + " 'total_anomaly_score': 1.0871472537998}" ] }, - "execution_count": 15, + "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pot_detector.params" + "pot_detector.params[0]" ] }, { @@ -17127,7 +986,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 55, "metadata": {}, "outputs": [], "source": [ @@ -17136,7 +995,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 56, "metadata": {}, "outputs": [ { @@ -17156,7 +1015,7 @@ "Name: detected data, Length: 6570, dtype: bool" ] }, - "execution_count": 17, + "execution_count": 56, "metadata": {}, "output_type": "execute_result" } @@ -17167,7 +1026,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 57, "metadata": {}, "outputs": [ { @@ -17187,7 +1046,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 58, "metadata": {}, "outputs": [ { @@ -17378,7 +1237,7 @@ "[6570 rows x 8 columns]" ] }, - "execution_count": 19, + "execution_count": 58, "metadata": {}, "output_type": "execute_result" } @@ -17389,7 +1248,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 59, "metadata": {}, "outputs": [ { @@ -18351,7 +2210,7 @@ "2023-12-02 23:04:00 19.689885 " ] }, - "execution_count": 20, + "execution_count": 59, "metadata": {}, "output_type": "execute_result" } @@ -18382,7 +2241,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 60, "metadata": {}, "outputs": [ { @@ -18462,7 +2321,7 @@ "2 6.007833 " ] }, - "execution_count": 21, + "execution_count": 60, "metadata": {}, "output_type": "execute_result" } @@ -18483,7 +2342,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 61, "metadata": {}, "outputs": [ { @@ -18503,7 +2362,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 62, "metadata": {}, "outputs": [ { @@ -18534,7 +2393,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 63, "metadata": {}, "outputs": [], "source": [ @@ -18543,7 +2402,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 64, "metadata": {}, "outputs": [], "source": [ @@ -18552,7 +2411,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 65, "metadata": {}, "outputs": [], "source": [ @@ -18568,7 +2427,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 66, "metadata": {}, "outputs": [ { @@ -18593,7 +2452,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 67, "metadata": {}, "outputs": [ { @@ -18620,7 +2479,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 68, "metadata": {}, "outputs": [ { @@ -18640,7 +2499,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 69, "metadata": {}, "outputs": [ { @@ -18664,7 +2523,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 70, "metadata": {}, "outputs": [ { @@ -18906,7 +2765,7 @@ "19 4.895357 2023-11-17 01:05:00 " ] }, - "execution_count": 31, + "execution_count": 70, "metadata": {}, "output_type": "execute_result" } @@ -18918,7 +2777,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 71, "metadata": {}, "outputs": [ { @@ -18938,16027 +2797,42 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 72, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{0: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 1: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 2: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 3: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.151891303024639,\n", - " 'loc': 0,\n", - " 'scale': 6.103864019736434,\n", - " 'p_value': 0.6178198433105214,\n", - " 'anomaly_score': 1.6185948231147889},\n", - " 'total_anomaly_score': 1.6185948231147889},\n", - " 4: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 5: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 6: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 7: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 8: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 9: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 10: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 11: {'xandr': {'c': -0.12934489757290532,\n", - " 'loc': 0,\n", - " 'scale': 2.442840763347193,\n", - " 'p_value': 0.042754418793203665,\n", - " 'anomaly_score': 23.3893952537828},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 23.3893952537828},\n", - " 12: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 13: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1277867854778989,\n", - " 'loc': 0,\n", - " 'scale': 3.6487125799713134,\n", - " 'p_value': 0.631284519956178,\n", - " 'anomaly_score': 1.5840717907504167},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.5840717907504167},\n", - " 14: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 15: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 16: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 17: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 18: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 19: {'xandr': {'c': -0.12962431310550215,\n", - " 'loc': 0,\n", - " 'scale': 2.4456411034273526,\n", - " 'p_value': 0.2042751806189,\n", - " 'anomaly_score': 4.8953573163918565},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 4.8953573163918565},\n", - " 20: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 21: {'xandr': {'c': -0.12991640242734875,\n", - " 'loc': 0,\n", - " 'scale': 2.4469278904212013,\n", - " 'p_value': 0.5571512039467685,\n", - " 'anomaly_score': 1.7948449055052966},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.7948449055052966},\n", - " 22: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 23: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 24: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 25: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 26: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 27: {'xandr': {'c': -0.12989882181443052,\n", - " 'loc': 0,\n", - " 'scale': 2.446462672065266,\n", - " 'p_value': 0.46670412047591475,\n", - " 'anomaly_score': 2.142685174881817},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.142685174881817},\n", - " 28: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15180252426416574,\n", - " 'loc': 0,\n", - " 'scale': 6.102040488968139,\n", - " 'p_value': 0.2476720315267948,\n", - " 'anomaly_score': 4.0375975996781595},\n", - " 'total_anomaly_score': 4.0375975996781595},\n", - " 29: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 30: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 31: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 32: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 33: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 34: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15206845340230812,\n", - " 'loc': 0,\n", - " 'scale': 6.104639599116176,\n", - " 'p_value': 0.6959562174245962,\n", - " 'anomaly_score': 1.4368719970640187},\n", - " 'total_anomaly_score': 1.4368719970640187},\n", - " 35: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 36: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 37: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 38: {'xandr': {'c': -0.1299237997607207,\n", - " 'loc': 0,\n", - " 'scale': 2.446301760651592,\n", - " 'p_value': 0.6404016218039523,\n", - " 'anomaly_score': 1.561520092942757},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.561520092942757},\n", - " 39: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 40: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 41: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 42: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 43: {'xandr': {'c': -0.12982951699796022,\n", - " 'loc': 0,\n", - " 'scale': 2.445547013774596,\n", - " 'p_value': 0.4518865583031705,\n", - " 'anomaly_score': 2.212944779227313},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.212944779227313},\n", - " 44: {'xandr': {'c': -0.12989053333180517,\n", - " 'loc': 0,\n", - " 'scale': 2.445419315309044,\n", - " 'p_value': 0.03268133474205583,\n", - " 'anomaly_score': 30.598505473925897},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 30.598505473925897},\n", - " 45: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 46: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 47: {'xandr': {'c': -0.1301021684421938,\n", - " 'loc': 0,\n", - " 'scale': 2.4484076546170206,\n", - " 'p_value': 0.8495479055639232,\n", - " 'anomaly_score': 1.1770966574700785},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.1770966574700785},\n", - " 48: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 49: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 50: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 51: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 52: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 53: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 54: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 55: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 56: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 57: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 58: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 59: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 60: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 61: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 62: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 63: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 64: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 65: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 66: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 67: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 68: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 69: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 70: {'xandr': {'c': -0.1298511737969436,\n", - " 'loc': 0,\n", - " 'scale': 2.446979599353888,\n", - " 'p_value': 0.5401833082276416,\n", - " 'anomaly_score': 1.851223436135099},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.851223436135099},\n", - " 71: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 72: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 73: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 74: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 75: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 76: {'xandr': {'c': -0.12982434720836944,\n", - " 'loc': 0,\n", - " 'scale': 2.446495909898654,\n", - " 'p_value': 0.9807514297677248,\n", - " 'anomaly_score': 1.0196263493970474},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.0196263493970474},\n", - " 77: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 78: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 79: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 80: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 81: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 82: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 83: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 84: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 85: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 86: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 87: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 88: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1519158713045726,\n", - " 'loc': 0,\n", - " 'scale': 6.1021581607748265,\n", - " 'p_value': 0.31340811148543146,\n", - " 'anomaly_score': 3.190727882760891},\n", - " 'total_anomaly_score': 3.190727882760891},\n", - " 89: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 90: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15212260999210062,\n", - " 'loc': 0,\n", - " 'scale': 6.1038150134049864,\n", - " 'p_value': 0.9852471645455253,\n", - " 'anomaly_score': 1.0149737405854702},\n", - " 'total_anomaly_score': 1.0149737405854702},\n", - " 91: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 92: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 93: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 94: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 95: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 96: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 97: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 98: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 99: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 100: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 101: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 102: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 103: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 104: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 105: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 106: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 107: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 108: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 109: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 110: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 111: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 112: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 113: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 114: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 115: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 116: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 117: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 118: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 119: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 120: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 121: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 122: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 123: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 124: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 125: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 126: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 127: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 128: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 129: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 130: {'xandr': {'c': -0.1295020542027605,\n", - " 'loc': 0,\n", - " 'scale': 2.4447020840785774,\n", - " 'p_value': 0.805296731158449,\n", - " 'anomaly_score': 1.241778292780927},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.241778292780927},\n", - " 131: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 132: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 133: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 134: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 135: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 136: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 137: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 138: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12771322874666885,\n", - " 'loc': 0,\n", - " 'scale': 3.647605426401552,\n", - " 'p_value': 0.3173640890869698,\n", - " 'anomaly_score': 3.1509551155485713},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.1509551155485713},\n", - " 139: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15175400144466694,\n", - " 'loc': 0,\n", - " 'scale': 6.099145543266452,\n", - " 'p_value': 0.10749778788666182,\n", - " 'anomaly_score': 9.302517006715807},\n", - " 'total_anomaly_score': 9.302517006715807},\n", - " 140: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 141: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 142: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 143: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 144: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 145: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 146: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 147: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 148: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 149: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 150: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 151: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15218279407791382,\n", - " 'loc': 0,\n", - " 'scale': 6.104712889077961,\n", - " 'p_value': 0.3696545958360906,\n", - " 'anomaly_score': 2.7052281001354364},\n", - " 'total_anomaly_score': 2.7052281001354364},\n", - " 152: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 153: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 154: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 155: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 156: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 157: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 158: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 159: {'xandr': {'c': -0.12928954213387683,\n", - " 'loc': 0,\n", - " 'scale': 2.443415670958028,\n", - " 'p_value': 0.23804462645093716,\n", - " 'anomaly_score': 4.2008929792250855},\n", - " 'gam': {'c': -0.12785521209779144,\n", - " 'loc': 0,\n", - " 'scale': 3.6483350516332917,\n", - " 'p_value': 0.28896109552674615,\n", - " 'anomaly_score': 3.460673479857569},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 7.661566459082655},\n", - " 160: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 161: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 162: {'xandr': {'c': -0.12956082931497687,\n", - " 'loc': 0,\n", - " 'scale': 2.44453862991353,\n", - " 'p_value': 0.4625167035843187,\n", - " 'anomaly_score': 2.1620840766406957},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.1620840766406957},\n", - " 163: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.152317025396734,\n", - " 'loc': 0,\n", - " 'scale': 6.1055839581746705,\n", - " 'p_value': 0.5728448264950441,\n", - " 'anomaly_score': 1.745673442000879},\n", - " 'total_anomaly_score': 1.745673442000879},\n", - " 164: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 165: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 166: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 167: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15225487613196315,\n", - " 'loc': 0,\n", - " 'scale': 6.104116266990193,\n", - " 'p_value': 0.05442492692492425,\n", - " 'anomaly_score': 18.37393371936791},\n", - " 'total_anomaly_score': 18.37393371936791},\n", - " 168: {'xandr': {'c': -0.12960165538675983,\n", - " 'loc': 0,\n", - " 'scale': 2.4443796754801888,\n", - " 'p_value': 0.5111002076976614,\n", - " 'anomaly_score': 1.9565634780401902},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.9565634780401902},\n", - " 169: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 170: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 171: {'xandr': {'c': -0.12959123240447343,\n", - " 'loc': 0,\n", - " 'scale': 2.4440388735171887,\n", - " 'p_value': 0.2634478474355745,\n", - " 'anomaly_score': 3.7958176911828727},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.7958176911828727},\n", - " 172: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 173: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 174: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 175: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 176: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 177: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 178: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 179: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15264344335123062,\n", - " 'loc': 0,\n", - " 'scale': 6.111059933290393,\n", - " 'p_value': 0.21114839396745114,\n", - " 'anomaly_score': 4.736005712428727},\n", - " 'total_anomaly_score': 4.736005712428727},\n", - " 180: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 181: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 182: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 183: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 184: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 185: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 186: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15295623489036453,\n", - " 'loc': 0,\n", - " 'scale': 6.1143367091738945,\n", - " 'p_value': 0.5227238551326588,\n", - " 'anomaly_score': 1.9130559858344636},\n", - " 'total_anomaly_score': 1.9130559858344636},\n", - " 187: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 188: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 189: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 190: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 191: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 192: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 193: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 194: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 195: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 196: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 197: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 198: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 199: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 200: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 201: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 202: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 203: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 204: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 205: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 206: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 207: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 208: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 209: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 210: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 211: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 212: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 213: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 214: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 215: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12801005476998767,\n", - " 'loc': 0,\n", - " 'scale': 3.6493009425201084,\n", - " 'p_value': 0.08819305347182654,\n", - " 'anomaly_score': 11.338761508234343},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 11.338761508234343},\n", - " 216: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 217: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 218: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 219: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 220: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 221: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 222: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 223: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 224: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 225: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 226: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 227: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 228: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 229: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 230: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 231: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 232: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 233: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 234: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 235: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 236: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 237: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 238: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 239: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 240: {'xandr': {'c': -0.12982911972706007,\n", - " 'loc': 0,\n", - " 'scale': 2.4449419967256802,\n", - " 'p_value': 0.39482861474948017,\n", - " 'anomaly_score': 2.5327444937963848},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.5327444937963848},\n", - " 241: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 242: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 243: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15294705924400587,\n", - " 'loc': 0,\n", - " 'scale': 6.113416784244169,\n", - " 'p_value': 0.9247722983765189,\n", - " 'anomaly_score': 1.081347269760942},\n", - " 'total_anomaly_score': 1.081347269760942},\n", - " 244: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 245: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 246: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 247: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 248: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 249: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 250: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 251: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 252: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 253: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 254: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 255: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 256: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 257: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 258: {'xandr': {'c': -0.12992685822171235,\n", - " 'loc': 0,\n", - " 'scale': 2.4451236895995563,\n", - " 'p_value': 0.34089927705369466,\n", - " 'anomaly_score': 2.9334177785378266},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.9334177785378266},\n", - " 259: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 260: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 261: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 262: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 263: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15262487107047235,\n", - " 'loc': 0,\n", - " 'scale': 6.109276379063809,\n", - " 'p_value': 0.291525788303438,\n", - " 'anomaly_score': 3.430228268379257},\n", - " 'total_anomaly_score': 3.430228268379257},\n", - " 264: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 265: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 266: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 267: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 268: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 269: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 270: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 271: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 272: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 273: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 274: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 275: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 276: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 277: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 278: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 279: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 280: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 281: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 282: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 283: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 284: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 285: {'xandr': {'c': -0.13007733432516103,\n", - " 'loc': 0,\n", - " 'scale': 2.4455714029854065,\n", - " 'p_value': 0.5953952160767216,\n", - " 'anomaly_score': 1.6795566591706401},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1528546144003171,\n", - " 'loc': 0,\n", - " 'scale': 6.111220805749946,\n", - " 'p_value': 0.47027593130662937,\n", - " 'anomaly_score': 2.126411184220227},\n", - " 'total_anomaly_score': 3.8059678433908672},\n", - " 286: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 287: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 288: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 289: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 290: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 291: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 292: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12831713210757323,\n", - " 'loc': 0,\n", - " 'scale': 3.652513511370956,\n", - " 'p_value': 0.8679132929720648,\n", - " 'anomaly_score': 1.1521888281899915},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.1521888281899915},\n", - " 293: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 294: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 295: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 296: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 297: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 298: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 299: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 300: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1281113402450612,\n", - " 'loc': 0,\n", - " 'scale': 3.6504941045317416,\n", - " 'p_value': 0.32115311343718805,\n", - " 'anomaly_score': 3.1137795592182},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.1137795592182},\n", - " 301: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 302: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 303: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 304: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 305: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 306: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 307: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 308: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 309: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 310: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 311: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 312: {'xandr': {'c': -0.130025696355538,\n", - " 'loc': 0,\n", - " 'scale': 2.444960486454352,\n", - " 'p_value': 0.41707405726533286,\n", - " 'anomaly_score': 2.397655722239811},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.397655722239811},\n", - " 313: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15289070364105622,\n", - " 'loc': 0,\n", - " 'scale': 6.110831675695917,\n", - " 'p_value': 0.7129860655650125,\n", - " 'anomaly_score': 1.4025519547952743},\n", - " 'total_anomaly_score': 1.4025519547952743},\n", - " 314: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 315: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 316: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 317: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 318: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 319: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 320: {'xandr': {'c': -0.13009707298996148,\n", - " 'loc': 0,\n", - " 'scale': 2.44500399080863,\n", - " 'p_value': 0.20056549406683286,\n", - " 'anomaly_score': 4.985902508567989},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 4.985902508567989},\n", - " 321: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 322: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 323: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 324: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 325: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 326: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 327: {'xandr': {'c': -0.13039704604538807,\n", - " 'loc': 0,\n", - " 'scale': 2.4463273447714835,\n", - " 'p_value': 0.22026566611865564,\n", - " 'anomaly_score': 4.539972196398992},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 4.539972196398992},\n", - " 328: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 329: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 330: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1282371258148623,\n", - " 'loc': 0,\n", - " 'scale': 3.651135658382477,\n", - " 'p_value': 0.642912309081812,\n", - " 'anomaly_score': 1.5554220783673747},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.5554220783673747},\n", - " 331: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 332: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 333: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 334: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 335: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 336: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 337: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 338: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 339: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 340: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1527119159293241,\n", - " 'loc': 0,\n", - " 'scale': 6.108141248461992,\n", - " 'p_value': 0.5055836181098189,\n", - " 'anomaly_score': 1.9779121873818069},\n", - " 'total_anomaly_score': 1.9779121873818069},\n", - " 341: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 342: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 343: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12815203358627994,\n", - " 'loc': 0,\n", - " 'scale': 3.650024239478535,\n", - " 'p_value': 0.06038018470524125,\n", - " 'anomaly_score': 16.56172475923539},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 16.56172475923539},\n", - " 344: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 345: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 346: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 347: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12844307651999007,\n", - " 'loc': 0,\n", - " 'scale': 3.6537868482310922,\n", - " 'p_value': 0.5483064829747232,\n", - " 'anomaly_score': 1.8237975129797979},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.8237975129797979},\n", - " 348: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.128410173364306,\n", - " 'loc': 0,\n", - " 'scale': 3.6530480146104054,\n", - " 'p_value': 0.9021469596146752,\n", - " 'anomaly_score': 1.1084668515949108},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.1084668515949108},\n", - " 349: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 350: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 351: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15271530768785196,\n", - " 'loc': 0,\n", - " 'scale': 6.1074310761810775,\n", - " 'p_value': 0.4563797805996072,\n", - " 'anomaly_score': 2.1911575457750696},\n", - " 'total_anomaly_score': 2.1911575457750696},\n", - " 352: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 353: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 354: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 355: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 356: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 357: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 358: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 359: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 360: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 361: {'xandr': {'c': -0.13066712376137618,\n", - " 'loc': 0,\n", - " 'scale': 2.4475665412804872,\n", - " 'p_value': 0.1732199821581531,\n", - " 'anomaly_score': 5.77300602125095},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15277120349709203,\n", - " 'loc': 0,\n", - " 'scale': 6.1072595858092615,\n", - " 'p_value': 0.5309317895058829,\n", - " 'anomaly_score': 1.8834811170953998},\n", - " 'total_anomaly_score': 7.65648713834635},\n", - " 362: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 363: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 364: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 365: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 366: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 367: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 368: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 369: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 370: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 371: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 372: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 373: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 374: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 375: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12819491764815183,\n", - " 'loc': 0,\n", - " 'scale': 3.6509211613916137,\n", - " 'p_value': 0.008438462188099297,\n", - " 'anomaly_score': 118.50500455050836},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 118.50500455050836},\n", - " 376: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 377: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 378: {'xandr': {'c': -0.13097458502798853,\n", - " 'loc': 0,\n", - " 'scale': 2.44904047321159,\n", - " 'p_value': 0.10272565830800587,\n", - " 'anomaly_score': 9.734666260318972},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 9.734666260318972},\n", - " 379: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 380: {'xandr': {'c': -0.131338325487662,\n", - " 'loc': 0,\n", - " 'scale': 2.4511886567285623,\n", - " 'p_value': 0.18773955672416873,\n", - " 'anomaly_score': 5.326527970177446},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 5.326527970177446},\n", - " 381: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 382: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 383: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 384: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 385: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 386: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 387: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 388: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 389: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 390: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15274680134424376,\n", - " 'loc': 0,\n", - " 'scale': 6.106197405631094,\n", - " 'p_value': 0.4506959280370531,\n", - " 'anomaly_score': 2.218790847202389},\n", - " 'total_anomaly_score': 2.218790847202389},\n", - " 391: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 392: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 393: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 394: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 395: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 396: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 397: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 398: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 399: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 400: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 401: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 402: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 403: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15280687739834664,\n", - " 'loc': 0,\n", - " 'scale': 6.106063216053914,\n", - " 'p_value': 0.15072163980020542,\n", - " 'anomaly_score': 6.634747348327596},\n", - " 'total_anomaly_score': 6.634747348327596},\n", - " 404: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 405: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 406: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 407: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 408: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 409: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 410: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 411: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 412: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 413: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 414: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 415: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 416: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 417: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 418: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1531885122646223,\n", - " 'loc': 0,\n", - " 'scale': 6.110545302882727,\n", - " 'p_value': 0.2597360183766395,\n", - " 'anomaly_score': 3.8500628686388585},\n", - " 'total_anomaly_score': 3.8500628686388585},\n", - " 419: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 420: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 421: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 422: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1278562157738628,\n", - " 'loc': 0,\n", - " 'scale': 3.655290830491465,\n", - " 'p_value': 0.6052709670843869,\n", - " 'anomaly_score': 1.652152596740329},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.652152596740329},\n", - " 423: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 424: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 425: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 426: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 427: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1534465785059624,\n", - " 'loc': 0,\n", - " 'scale': 6.113017829885326,\n", - " 'p_value': 0.4881942341832458,\n", - " 'anomaly_score': 2.048365035840726},\n", - " 'total_anomaly_score': 2.048365035840726},\n", - " 428: {'xandr': {'c': -0.13165168596522342,\n", - " 'loc': 0,\n", - " 'scale': 2.4525905015317813,\n", - " 'p_value': 0.0028898766507449423,\n", - " 'anomaly_score': 346.03553052765193},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 346.03553052765193},\n", - " 429: {'xandr': {'c': -0.13010342609203834,\n", - " 'loc': 0,\n", - " 'scale': 2.4535563826083227,\n", - " 'p_value': 0.6640327653765199,\n", - " 'anomaly_score': 1.505949784620914},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15345647640023904,\n", - " 'loc': 0,\n", - " 'scale': 6.112368418779203,\n", - " 'p_value': 0.13533325243806524,\n", - " 'anomaly_score': 7.389166978438254},\n", - " 'total_anomaly_score': 8.895116763059168},\n", - " 430: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 431: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 432: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 433: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 434: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15386060221650538,\n", - " 'loc': 0,\n", - " 'scale': 6.117217515433548,\n", - " 'p_value': 0.34146944487036457,\n", - " 'anomaly_score': 2.9285197109792356},\n", - " 'total_anomaly_score': 2.9285197109792356},\n", - " 435: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 436: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 437: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 438: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 439: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 440: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 441: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 442: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 443: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 444: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15402775705636412,\n", - " 'loc': 0,\n", - " 'scale': 6.118432797997585,\n", - " 'p_value': 0.010571202960174823,\n", - " 'anomaly_score': 94.5966134381609},\n", - " 'total_anomaly_score': 94.5966134381609},\n", - " 445: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 446: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 447: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 448: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12778671710395545,\n", - " 'loc': 0,\n", - " 'scale': 3.6543309959838317,\n", - " 'p_value': 0.6247738992020193,\n", - " 'anomaly_score': 1.6005790275125629},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.6005790275125629},\n", - " 449: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 450: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 451: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 452: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 453: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 454: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 455: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 456: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 457: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 458: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 459: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 460: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 461: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 462: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 463: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 464: {'xandr': {'c': -0.12998565199067963,\n", - " 'loc': 0,\n", - " 'scale': 2.4527011064940685,\n", - " 'p_value': 0.38009125462539334,\n", - " 'anomaly_score': 2.6309471418530013},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.6309471418530013},\n", - " 465: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 466: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12771499202145228,\n", - " 'loc': 0,\n", - " 'scale': 3.6532784514514303,\n", - " 'p_value': 0.005560486569885134,\n", - " 'anomaly_score': 179.84037681448038},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 179.84037681448038},\n", - " 467: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 468: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 469: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 470: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 471: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 472: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 473: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 474: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 475: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 476: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 477: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 478: {'xandr': {'c': -0.1300931337495862,\n", - " 'loc': 0,\n", - " 'scale': 2.452918107558835,\n", - " 'p_value': 0.36000158156319134,\n", - " 'anomaly_score': 2.7777655744117036},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.7777655744117036},\n", - " 479: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 480: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1270809814603206,\n", - " 'loc': 0,\n", - " 'scale': 3.6571889681256637,\n", - " 'p_value': 0.9324431948088518,\n", - " 'anomaly_score': 1.0724513896044865},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.0724513896044865},\n", - " 481: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 482: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 483: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 484: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 485: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 486: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12684817036549878,\n", - " 'loc': 0,\n", - " 'scale': 3.654911840889901,\n", - " 'p_value': 0.5950173266398125,\n", - " 'anomaly_score': 1.6806233284788687},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.6806233284788687},\n", - " 487: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 488: {'xandr': {'c': -0.13024708071933289,\n", - " 'loc': 0,\n", - " 'scale': 2.4532985057097254,\n", - " 'p_value': 0.2680458814509267,\n", - " 'anomaly_score': 3.7307045890316277},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.7307045890316277},\n", - " 489: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 490: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 491: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 492: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 493: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 494: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15366493598952713,\n", - " 'loc': 0,\n", - " 'scale': 6.124721166128449,\n", - " 'p_value': 0.8233900129606126,\n", - " 'anomaly_score': 1.214491291197912},\n", - " 'total_anomaly_score': 1.214491291197912},\n", - " 495: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1534140099414202,\n", - " 'loc': 0,\n", - " 'scale': 6.121207509138831,\n", - " 'p_value': 0.17028279678036543,\n", - " 'anomaly_score': 5.872583836462485},\n", - " 'total_anomaly_score': 5.872583836462485},\n", - " 496: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 497: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 498: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 499: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 500: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 501: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1267914124356338,\n", - " 'loc': 0,\n", - " 'scale': 3.6539597256939884,\n", - " 'p_value': 0.07101466824974074,\n", - " 'anomaly_score': 14.081597853604713},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 14.081597853604713},\n", - " 502: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 503: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 504: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 505: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 506: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 507: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 508: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 509: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1537805682026105,\n", - " 'loc': 0,\n", - " 'scale': 6.125347282101335,\n", - " 'p_value': 0.3691589187016205,\n", - " 'anomaly_score': 2.7088604645314516},\n", - " 'total_anomaly_score': 2.7088604645314516},\n", - " 510: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1539119365610424,\n", - " 'loc': 0,\n", - " 'scale': 6.126142911990785,\n", - " 'p_value': 0.7317361928002672,\n", - " 'anomaly_score': 1.3666127353535966},\n", - " 'total_anomaly_score': 1.3666127353535966},\n", - " 511: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 512: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 513: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 514: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 515: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 516: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 517: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15373277952312736,\n", - " 'loc': 0,\n", - " 'scale': 6.123372780274661,\n", - " 'p_value': 0.32601139980018706,\n", - " 'anomaly_score': 3.067377400339073},\n", - " 'total_anomaly_score': 3.067377400339073},\n", - " 518: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 519: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 520: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 521: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 522: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 523: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 524: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 525: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 526: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 527: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 528: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 529: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 530: {'xandr': {'c': -0.1304590467771443,\n", - " 'loc': 0,\n", - " 'scale': 2.4541793215467576,\n", - " 'p_value': 0.2623004209405475,\n", - " 'anomaly_score': 3.8124223987679304},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.8124223987679304},\n", - " 531: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 532: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 533: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 534: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 535: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 536: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 537: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 538: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 539: {'xandr': {'c': -0.13069633061486172,\n", - " 'loc': 0,\n", - " 'scale': 2.455043883051114,\n", - " 'p_value': 0.607727476100181,\n", - " 'anomaly_score': 1.6454743932544442},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.6454743932544442},\n", - " 540: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 541: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 542: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 543: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 544: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 545: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 546: {'xandr': {'c': -0.13061906473549784,\n", - " 'loc': 0,\n", - " 'scale': 2.454375268784613,\n", - " 'p_value': 0.8438274752751813,\n", - " 'anomaly_score': 1.185076368453029},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.185076368453029},\n", - " 547: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 548: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 549: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 550: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 551: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 552: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 553: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 554: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 555: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 556: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 557: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 558: {'xandr': {'c': -0.13037382419519727,\n", - " 'loc': 0,\n", - " 'scale': 2.4529505574496917,\n", - " 'p_value': 0.2873423250030013,\n", - " 'anomaly_score': 3.480169515540584},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.480169515540584},\n", - " 559: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15390781342090615,\n", - " 'loc': 0,\n", - " 'scale': 6.124754881482607,\n", - " 'p_value': 0.3332483839365471,\n", - " 'anomaly_score': 3.0007647394635444},\n", - " 'total_anomaly_score': 3.0007647394635444},\n", - " 560: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 561: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 562: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 563: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 564: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 565: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 566: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 567: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 568: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 569: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 570: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 571: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12708250823224423,\n", - " 'loc': 0,\n", - " 'scale': 3.6575389057420495,\n", - " 'p_value': 0.1747462292498064,\n", - " 'anomaly_score': 5.722584139829775},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 5.722584139829775},\n", - " 572: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 573: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 574: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 575: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 576: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 577: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 578: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 579: {'xandr': {'c': -0.13057643732827023,\n", - " 'loc': 0,\n", - " 'scale': 2.4536911008991114,\n", - " 'p_value': 0.5731335864239253,\n", - " 'anomaly_score': 1.7447939253386167},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.7447939253386167},\n", - " 580: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 581: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 582: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 583: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 584: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15409018040617886,\n", - " 'loc': 0,\n", - " 'scale': 6.126103078659257,\n", - " 'p_value': 0.26528881253908754,\n", - " 'anomaly_score': 3.7694767089081846},\n", - " 'total_anomaly_score': 3.7694767089081846},\n", - " 585: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 586: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 587: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 588: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 589: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 590: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 591: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 592: {'xandr': {'c': -0.13051981171900937,\n", - " 'loc': 0,\n", - " 'scale': 2.4531289884722938,\n", - " 'p_value': 0.521083488446376,\n", - " 'anomaly_score': 1.9190782708957563},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.9190782708957563},\n", - " 593: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 594: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 595: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 596: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 597: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 598: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 599: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 600: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 601: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 602: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 603: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 604: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 605: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 606: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 607: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 608: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 609: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 610: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 611: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 612: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 613: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 614: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 615: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 616: {'xandr': {'c': -0.13053711032347368,\n", - " 'loc': 0,\n", - " 'scale': 2.4528101823004107,\n", - " 'p_value': 0.5688815876188901,\n", - " 'anomaly_score': 1.7578350605186548},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.7578350605186548},\n", - " 617: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 618: {'xandr': {'c': -0.13049037190311025,\n", - " 'loc': 0,\n", - " 'scale': 2.452310729329019,\n", - " 'p_value': 0.007848013051861643,\n", - " 'anomaly_score': 127.4207870695103},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 127.4207870695103},\n", - " 619: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 620: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 621: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 622: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 623: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 624: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 625: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 626: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 627: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 628: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 629: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12734501889038946,\n", - " 'loc': 0,\n", - " 'scale': 3.659611365498087,\n", - " 'p_value': 0.14270341557558663,\n", - " 'anomaly_score': 7.0075407513306756},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 7.0075407513306756},\n", - " 630: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 631: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 632: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1276252052296069,\n", - " 'loc': 0,\n", - " 'scale': 3.662031561753581,\n", - " 'p_value': 0.015444052078480017,\n", - " 'anomaly_score': 64.74984640808195},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 64.74984640808195},\n", - " 633: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15433789201589226,\n", - " 'loc': 0,\n", - " 'scale': 6.128375818442765,\n", - " 'p_value': 0.2783640629708039,\n", - " 'anomaly_score': 3.592417747203541},\n", - " 'total_anomaly_score': 3.592417747203541},\n", - " 634: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 635: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 636: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 637: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 638: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 639: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 640: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 641: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 642: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 643: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 644: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 645: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 646: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 647: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 648: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 649: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 650: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 651: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 652: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 653: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 654: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 655: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 656: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 657: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 658: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 659: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 660: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 661: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 662: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1545635392244461,\n", - " 'loc': 0,\n", - " 'scale': 6.130418753162877,\n", - " 'p_value': 0.9984670691433717,\n", - " 'anomaly_score': 1.001535284341369},\n", - " 'total_anomaly_score': 1.001535284341369},\n", - " 663: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 664: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 665: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 666: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 667: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 668: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 669: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 670: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 671: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 672: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 673: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 674: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 675: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 676: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 677: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 678: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 679: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 680: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 681: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 682: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 683: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 684: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 685: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 686: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 687: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 688: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 689: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 690: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15420183894426742,\n", - " 'loc': 0,\n", - " 'scale': 6.1258349536575,\n", - " 'p_value': 0.6246990423222337,\n", - " 'anomaly_score': 1.6007708228311603},\n", - " 'total_anomaly_score': 1.6007708228311603},\n", - " 691: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 692: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 693: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 694: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1541125003614811,\n", - " 'loc': 0,\n", - " 'scale': 6.124000975459261,\n", - " 'p_value': 0.7485558560990463,\n", - " 'anomaly_score': 1.3359056533353517},\n", - " 'total_anomaly_score': 1.3359056533353517},\n", - " 695: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 696: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 697: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 698: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 699: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 700: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 701: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 702: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 703: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 704: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 705: {'xandr': {'c': -0.12989594558758466,\n", - " 'loc': 0,\n", - " 'scale': 2.454574799490383,\n", - " 'p_value': 0.7401360057932588,\n", - " 'anomaly_score': 1.3511030299468079},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.3511030299468079},\n", - " 706: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 707: {'xandr': {'c': -0.12974504108657994,\n", - " 'loc': 0,\n", - " 'scale': 2.45351344535304,\n", - " 'p_value': 0.39595771411234393,\n", - " 'anomaly_score': 2.525522206940191},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.525522206940191},\n", - " 708: {'xandr': {'c': -0.1298580816854441,\n", - " 'loc': 0,\n", - " 'scale': 2.453733206447355,\n", - " 'p_value': 0.8450111577351154,\n", - " 'anomaly_score': 1.1834163263362125},\n", - " 'gam': {'c': -0.12757057210594247,\n", - " 'loc': 0,\n", - " 'scale': 3.666472274492349,\n", - " 'p_value': 0.8174078460793679,\n", - " 'anomaly_score': 1.2233794975132928},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.4067958238495053},\n", - " 709: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 710: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 711: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 712: {'xandr': {'c': -0.12961613615974055,\n", - " 'loc': 0,\n", - " 'scale': 2.4523541511807463,\n", - " 'p_value': 0.30313146456710105,\n", - " 'anomaly_score': 3.2988987185084526},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.2988987185084526},\n", - " 713: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 714: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 715: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 716: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 717: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 718: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 719: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15391626169003647,\n", - " 'loc': 0,\n", - " 'scale': 6.121148409351369,\n", - " 'p_value': 0.6645468298434517,\n", - " 'anomaly_score': 1.5047848474961072},\n", - " 'total_anomaly_score': 1.5047848474961072},\n", - " 720: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1273889724135031,\n", - " 'loc': 0,\n", - " 'scale': 3.664600221753989,\n", - " 'p_value': 0.83984338554469,\n", - " 'anomaly_score': 1.1906981911293362},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.1906981911293362},\n", - " 721: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15378008133683285,\n", - " 'loc': 0,\n", - " 'scale': 6.118868230343635,\n", - " 'p_value': 0.33223688287358477,\n", - " 'anomaly_score': 3.009900620758284},\n", - " 'total_anomaly_score': 3.009900620758284},\n", - " 722: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12718845035652726,\n", - " 'loc': 0,\n", - " 'scale': 3.662668124147629,\n", - " 'p_value': 0.2355545676698449,\n", - " 'anomaly_score': 4.245300823041597},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 4.245300823041597},\n", - " 723: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 724: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 725: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 726: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 727: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 728: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 729: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 730: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 731: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1274017530927177,\n", - " 'loc': 0,\n", - " 'scale': 3.664094669236447,\n", - " 'p_value': 0.2775738527358901,\n", - " 'anomaly_score': 3.6026448101777593},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.6026448101777593},\n", - " 732: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 733: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 734: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 735: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 736: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 737: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 738: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 739: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 740: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15395696546051646,\n", - " 'loc': 0,\n", - " 'scale': 6.120229243646298,\n", - " 'p_value': 0.9949248988570313,\n", - " 'anomaly_score': 1.0051009891789813},\n", - " 'total_anomaly_score': 1.0051009891789813},\n", - " 741: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 742: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15359169535609923,\n", - " 'loc': 0,\n", - " 'scale': 6.115604814323539,\n", - " 'p_value': 0.0034050166862848626,\n", - " 'anomaly_score': 293.68431703372283},\n", - " 'total_anomaly_score': 293.68431703372283},\n", - " 743: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12758332546546314,\n", - " 'loc': 0,\n", - " 'scale': 3.6651760735475536,\n", - " 'p_value': 0.02555193819168817,\n", - " 'anomaly_score': 39.13597444147277},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 39.13597444147277},\n", - " 744: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 745: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 746: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 747: {'xandr': {'c': -0.1297914234523527,\n", - " 'loc': 0,\n", - " 'scale': 2.4529781424278703,\n", - " 'p_value': 0.2953414612532828,\n", - " 'anomaly_score': 3.3859113304190194},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.3859113304190194},\n", - " 748: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 749: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 750: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 751: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15209430947160046,\n", - " 'loc': 0,\n", - " 'scale': 6.117544353674063,\n", - " 'p_value': 0.7022629153920644,\n", - " 'anomaly_score': 1.4239681151918904},\n", - " 'total_anomaly_score': 1.4239681151918904},\n", - " 752: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 753: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 754: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 755: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 756: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 757: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 758: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 759: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 760: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 761: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 762: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 763: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12770883249984266,\n", - " 'loc': 0,\n", - " 'scale': 3.669619229709562,\n", - " 'p_value': 0.5040780844113419,\n", - " 'anomaly_score': 1.983819632166297},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.983819632166297},\n", - " 764: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 765: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 766: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 767: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 768: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 769: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 770: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 771: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 772: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 773: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 774: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 775: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 776: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 777: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 778: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 779: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 780: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 781: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 782: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 783: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 784: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 785: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 786: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12770152426136702,\n", - " 'loc': 0,\n", - " 'scale': 3.6691081919680983,\n", - " 'p_value': 0.5174424186745508,\n", - " 'anomaly_score': 1.932582184818824},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.932582184818824},\n", - " 787: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 788: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12769453261872965,\n", - " 'loc': 0,\n", - " 'scale': 3.668574494621729,\n", - " 'p_value': 0.015599455499959749,\n", - " 'anomaly_score': 64.10480160686251},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 64.10480160686251},\n", - " 789: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 790: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 791: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 792: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 793: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 794: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 795: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 796: {'xandr': {'c': -0.12999741691188582,\n", - " 'loc': 0,\n", - " 'scale': 2.453704034723514,\n", - " 'p_value': 0.898305061487569,\n", - " 'anomaly_score': 1.1132075759920879},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.1132075759920879},\n", - " 797: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 798: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 799: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 800: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12764955713646112,\n", - " 'loc': 0,\n", - " 'scale': 3.673109088763599,\n", - " 'p_value': 0.6822251999279018,\n", - " 'anomaly_score': 1.4657916478395712},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.4657916478395712},\n", - " 801: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 802: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 803: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 804: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 805: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 806: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 807: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 808: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 809: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 810: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 811: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 812: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 813: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 814: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 815: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 816: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 817: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12753871942614192,\n", - " 'loc': 0,\n", - " 'scale': 3.671789907192652,\n", - " 'p_value': 0.06537401620366085,\n", - " 'anomaly_score': 15.29659730380771},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 15.29659730380771},\n", - " 818: {'xandr': {'c': -0.12971663624095814,\n", - " 'loc': 0,\n", - " 'scale': 2.4520782372092484,\n", - " 'p_value': 0.711159612126881,\n", - " 'anomaly_score': 1.4061540938879777},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.4061540938879777},\n", - " 819: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 820: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 821: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 822: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 823: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 824: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 825: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 826: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 827: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 828: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 829: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 830: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 831: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 832: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 833: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 834: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 835: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 836: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 837: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 838: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 839: {'xandr': {'c': -0.12959457101432678,\n", - " 'loc': 0,\n", - " 'scale': 2.4511690405417568,\n", - " 'p_value': 0.35444612250439145,\n", - " 'anomaly_score': 2.821303257415689},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.821303257415689},\n", - " 840: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 841: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 842: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 843: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 844: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 845: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 846: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 847: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 848: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 849: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 850: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 851: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 852: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 853: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 854: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 855: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 856: {'xandr': {'c': -0.12972470320619972,\n", - " 'loc': 0,\n", - " 'scale': 2.4515405902391647,\n", - " 'p_value': 0.7608452483488162,\n", - " 'anomaly_score': 1.3143277192966594},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.3143277192966594},\n", - " 857: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 858: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 859: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15193172563003027,\n", - " 'loc': 0,\n", - " 'scale': 6.114996022654367,\n", - " 'p_value': 0.24127203501741332,\n", - " 'anomaly_score': 4.144699156401723},\n", - " 'total_anomaly_score': 4.144699156401723},\n", - " 860: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 861: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1278371408367373,\n", - " 'loc': 0,\n", - " 'scale': 3.675449794850559,\n", - " 'p_value': 0.43322501518327455,\n", - " 'anomaly_score': 2.3082692941379506},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.3082692941379506},\n", - " 862: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 863: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 864: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15220626352065258,\n", - " 'loc': 0,\n", - " 'scale': 6.117690131977027,\n", - " 'p_value': 0.3580041615594176,\n", - " 'anomaly_score': 2.793263619182904},\n", - " 'total_anomaly_score': 2.793263619182904},\n", - " 865: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12788866774970054,\n", - " 'loc': 0,\n", - " 'scale': 3.675382400225037,\n", - " 'p_value': 0.6371151327523616,\n", - " 'anomaly_score': 1.5695750243444413},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.5695750243444413},\n", - " 866: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 867: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 868: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 869: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15235641182444387,\n", - " 'loc': 0,\n", - " 'scale': 6.118668349025265,\n", - " 'p_value': 0.7714996826036726,\n", - " 'anomaly_score': 1.2961768132232796},\n", - " 'total_anomaly_score': 1.2961768132232796},\n", - " 870: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 871: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 872: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 873: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 874: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 875: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 876: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 877: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 878: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 879: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 880: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 881: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 882: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 883: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 884: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 885: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 886: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 887: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 888: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 889: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 890: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 891: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 892: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 893: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 894: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 895: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 896: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 897: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 898: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12781341371909716,\n", - " 'loc': 0,\n", - " 'scale': 3.674282533526557,\n", - " 'p_value': 0.1951423295428373,\n", - " 'anomaly_score': 5.124464806496438},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 5.124464806496438},\n", - " 899: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 900: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 901: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1280507640119365,\n", - " 'loc': 0,\n", - " 'scale': 3.676072756050779,\n", - " 'p_value': 0.32662482571419055,\n", - " 'anomaly_score': 3.0616166355800494},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 3.0616166355800494},\n", - " 902: {'xandr': {'c': -0.12951854715246358,\n", - " 'loc': 0,\n", - " 'scale': 2.4503196528702267,\n", - " 'p_value': 0.8456945123740816,\n", - " 'anomaly_score': 1.182460079104384},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.182460079104384},\n", - " 903: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 904: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 905: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 906: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 907: {'xandr': {'c': -0.12930562625306347,\n", - " 'loc': 0,\n", - " 'scale': 2.4489933803985116,\n", - " 'p_value': 0.4920110450764275,\n", - " 'anomaly_score': 2.0324746974829866},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 2.0324746974829866},\n", - " 908: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 909: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 910: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 911: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 912: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 913: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 914: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 915: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 916: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1281764350079723,\n", - " 'loc': 0,\n", - " 'scale': 3.676714457410127,\n", - " 'p_value': 0.7785756491885726,\n", - " 'anomaly_score': 1.2843967070408568},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.2843967070408568},\n", - " 917: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 918: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 919: {'xandr': {'c': -0.12930094024594058,\n", - " 'loc': 0,\n", - " 'scale': 2.4486967060327753,\n", - " 'p_value': 0.558256817095396,\n", - " 'anomaly_score': 1.7912902617168007},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.7912902617168007},\n", - " 920: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 921: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 922: {'xandr': {'c': -0.12927630619253283,\n", - " 'loc': 0,\n", - " 'scale': 2.4482010373908567,\n", - " 'p_value': 0.5953273005537192,\n", - " 'anomaly_score': 1.6797482646434847},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.6797482646434847},\n", - " 923: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1521476501478778,\n", - " 'loc': 0,\n", - " 'scale': 6.115671364072039,\n", - " 'p_value': 0.718286450094726,\n", - " 'anomaly_score': 1.3922022333403647},\n", - " 'total_anomaly_score': 1.3922022333403647},\n", - " 924: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 925: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 926: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 927: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 928: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 929: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 930: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 931: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 932: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15196679516315031,\n", - " 'loc': 0,\n", - " 'scale': 6.112954702378762,\n", - " 'p_value': 0.77450598946897,\n", - " 'anomaly_score': 1.2911455993847603},\n", - " 'total_anomaly_score': 1.2911455993847603},\n", - " 933: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 934: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 935: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 936: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 937: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 938: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15175863817404453,\n", - " 'loc': 0,\n", - " 'scale': 6.109944644871934,\n", - " 'p_value': 0.6847958473807833,\n", - " 'anomaly_score': 1.4602892290086367},\n", - " 'total_anomaly_score': 1.4602892290086367},\n", - " 939: {'xandr': {'c': -0.1292109807238307,\n", - " 'loc': 0,\n", - " 'scale': 2.447632502383772,\n", - " 'p_value': 0.5753241543781886,\n", - " 'anomaly_score': 1.7381505580637437},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.7381505580637437},\n", - " 940: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 941: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 942: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15161388646436896,\n", - " 'loc': 0,\n", - " 'scale': 6.107564461275597,\n", - " 'p_value': 0.8984357798111635,\n", - " 'anomaly_score': 1.1130456093480423},\n", - " 'total_anomaly_score': 1.1130456093480423},\n", - " 943: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 944: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 945: {'xandr': {'c': -0.129168463568738,\n", - " 'loc': 0,\n", - " 'scale': 2.4470355691112577,\n", - " 'p_value': 8.275081663809919e-05,\n", - " 'anomaly_score': 12084.472886513984},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15130547329609062,\n", - " 'loc': 0,\n", - " 'scale': 6.103547342582807,\n", - " 'p_value': 0.09120020604971042,\n", - " 'anomaly_score': 10.964887507545003},\n", - " 'total_anomaly_score': 12095.43777402153},\n", - " 946: {'xandr': {'c': -0.12078117383969411,\n", - " 'loc': 0,\n", - " 'scale': 2.434563124351655,\n", - " 'p_value': 0.5555595409094028,\n", - " 'anomaly_score': 1.799987087546164},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.799987087546164},\n", - " 947: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 948: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 949: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 950: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12802429632984458,\n", - " 'loc': 0,\n", - " 'scale': 3.6750845026705283,\n", - " 'p_value': 0.6829826998489353,\n", - " 'anomaly_score': 1.4641659301490122},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 1.4641659301490122},\n", - " 951: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 952: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.1279068039141646,\n", - " 'loc': 0,\n", - " 'scale': 3.673709570948139,\n", - " 'p_value': 0.029154783558183003,\n", - " 'anomaly_score': 34.2996886944587},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 34.2996886944587},\n", - " 953: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 954: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 955: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 956: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 957: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 958: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 959: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 960: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 961: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 962: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 963: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 964: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 965: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 966: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 967: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 968: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 969: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 970: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 971: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 972: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 973: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 974: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 975: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.15173249743487585,\n", - " 'loc': 0,\n", - " 'scale': 6.109470904932783,\n", - " 'p_value': 0.21183037385989595,\n", - " 'anomaly_score': 4.720758320812847},\n", - " 'total_anomaly_score': 4.720758320812847},\n", - " 976: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 977: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 978: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 979: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 980: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 981: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 982: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 983: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 984: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 985: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 986: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 987: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 988: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 989: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 990: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 991: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 992: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': -0.1520370853298867,\n", - " 'loc': 0,\n", - " 'scale': 6.112617457775087,\n", - " 'p_value': 0.7337478632869693,\n", - " 'anomaly_score': 1.3628659789485469},\n", - " 'total_anomaly_score': 1.3628659789485469},\n", - " 993: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 994: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12807793682090884,\n", - " 'loc': 0,\n", - " 'scale': 3.678054117218267,\n", - " 'p_value': 0.04834679912591417,\n", - " 'anomaly_score': 20.68389258605528},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 20.68389258605528},\n", - " 995: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 996: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 997: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " 998: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': -0.12834092557904497,\n", - " 'loc': 0,\n", - " 'scale': 3.6820544202032135,\n", - " 'p_value': 0.034284575585031334,\n", - " 'anomaly_score': 29.16763538518472},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 29.16763538518472},\n", - " 999: {'xandr': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'gam': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'adobe': {'c': 0.0,\n", - " 'loc': 0.0,\n", - " 'scale': 0.0,\n", - " 'p_value': 0.0,\n", - " 'anomaly_score': 0.0},\n", - " 'total_anomaly_score': 0.0},\n", - " ...}" + "{'xandr': {'c': 0.0,\n", + " 'loc': 0.0,\n", + " 'scale': 0.0,\n", + " 'p_value': 0.0,\n", + " 'anomaly_score': 0.0},\n", + " 'gam': {'c': 0.0,\n", + " 'loc': 0.0,\n", + " 'scale': 0.0,\n", + " 'p_value': 0.0,\n", + " 'anomaly_score': 0.0},\n", + " 'adobe': {'c': 0.0,\n", + " 'loc': 0.0,\n", + " 'scale': 0.0,\n", + " 'p_value': 0.0,\n", + " 'anomaly_score': 0.0},\n", + " 'total_anomaly_score': 0.0}" ] }, - "execution_count": 33, + "execution_count": 72, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pot_detector.params" + "pot_detector.params[0]" ] }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 73, "metadata": {}, "outputs": [ { @@ -34978,7 +2852,7 @@ "Name: detected data, Length: 6570, dtype: bool" ] }, - "execution_count": 34, + "execution_count": 73, "metadata": {}, "output_type": "execute_result" } @@ -34990,7 +2864,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 74, "metadata": {}, "outputs": [ { @@ -35010,7 +2884,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 75, "metadata": {}, "outputs": [ { @@ -35572,7 +3446,7 @@ "2023-12-02 21:37:00 23.861065 " ] }, - "execution_count": 36, + "execution_count": 75, "metadata": {}, "output_type": "execute_result" } @@ -35583,7 +3457,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 76, "metadata": {}, "outputs": [ { @@ -35663,7 +3537,7 @@ "2 6.168533 " ] }, - "execution_count": 37, + "execution_count": 76, "metadata": {}, "output_type": "execute_result" } @@ -35675,7 +3549,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 77, "metadata": {}, "outputs": [ { @@ -35695,7 +3569,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 78, "metadata": {}, "outputs": [ { diff --git a/pyproject.toml b/pyproject.toml index b601df0..9682730 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -6,7 +6,7 @@ build-backend = "setuptools.build_meta" name = "anomalytics" description = "The ultimate anomaly detection library." readme = "README.md" -version = "0.1.9" +version = "0.2.0" license = {file = "LICENSE"} requires-python = ">=3.10" authors = [ diff --git a/src/anomalytics/__init__.py b/src/anomalytics/__init__.py index 66b0e1d..fa28556 100644 --- a/src/anomalytics/__init__.py +++ b/src/anomalytics/__init__.py @@ -1,4 +1,4 @@ -__version__ = "0.1.9" +__version__ = "0.2.0" __all__ = [ "get_anomaly", diff --git a/tests/test_version.py b/tests/test_version.py index ea0b98a..6e4bf09 100644 --- a/tests/test_version.py +++ b/tests/test_version.py @@ -2,4 +2,4 @@ def test_pkg_version(): - assert __version__ == "0.1.9" + assert __version__ == "0.2.0"