From 3dd509d254cb4f0134b4eea763fbca4f8e6ce69f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?D=C3=A9sir=C3=A9e=20Lussier?= <9257980+dllussier@users.noreply.github.com> Date: Tue, 29 Sep 2020 15:34:22 -0400 Subject: [PATCH] Add files via upload --- examples/dypac_anat_demo.ipynb | 535 +++++++++++++++++++++++++++++++++ 1 file changed, 535 insertions(+) create mode 100644 examples/dypac_anat_demo.ipynb diff --git a/examples/dypac_anat_demo.ipynb b/examples/dypac_anat_demo.ipynb new file mode 100644 index 0000000..1c69e73 --- /dev/null +++ b/examples/dypac_anat_demo.ipynb @@ -0,0 +1,535 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import pickle\n", + "from dypac import Dypac\n", + "from niak_load_confounds import load_confounds #for fmriprep: from load_confounds import load_confounds\n", + "import numpy as np\n", + "import sklearn as sk\n", + "import scipy as sp\n", + "import matplotlib.pyplot as plt\n", + "import time\n", + "from nilearn import datasets\n", + "from nilearn import image\n", + "from nilearn.input_data import NiftiMasker\n", + "from nilearn import plotting\n", + "from nilearn.decomposition import DictLearning, CanICA\n", + "from scipy.stats import pearsonr" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here we will desigate the paths to the preprocessed anatomical vbm data and add the files to a list." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "path_base = '/home/lussier/Projects/data/adni/vbm/'\n", + "path_anat1 = 'output/002S0295_20060418_MP-RAGE/'\n", + "path_anat2 = 'output/002S0295_20090522_MP-RAGE/'\n", + "path_anat3 = 'output/002S0413_20140501_MPRAGE/'\n", + "\n", + "path_atlas = 'code/templates/'" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "anat1 = os.path.join(path_base, path_anat1, 'smwrc1acpc_002S0295_20060418_MP-RAGE_T1w_stereolin.nii.gz')\n", + "anat2 = os.path.join(path_base, path_anat2, 'smwrc1acpc_002S0295_20090522_MP-RAGE_T1w_stereolin.nii.gz')\n", + "anat3 = os.path.join(path_base, path_anat3, 'smwrc1acpc_002S0413_20140501_MPRAGE_T1w_stereolin.nii.gz')\n", + "\n", + "anat = [anat1, anat2, anat3]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will also load an atlas for probabilistic grey matter segmentation." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "mni = datasets.fetch_icbm152_2009()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we run dypac. First we specify the model, with the main relevant options. Then we fit the model on the functional data." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[MultiNiftiMasker.fit] Loading data from [/home/lussier/Projects/data/adni/vbm/output/002S0295_20060418_MP-RAGE/smwrc1acpc_002S0295_20060418_MP-RAGE_T1w_stereolin.nii.gz, /home/lussier/Projects/data/adni/vbm/output/002S0295_20090522_MP-RAGE/\n", + "[MultiNiftiMasker.fit] Computing mask\n", + "[MultiNiftiMasker.transform] Resampling mask\n", + "[Dypac] Restrict brain mask to grey matter\n", + "[MultiNiftiMasker.fit] Loading data from None\n", + "[MultiNiftiMasker.transform] Resampling mask\n", + "[Dypac] Processing batch 0\n", + "[MultiNiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(121, 145, 121, 1),\n", + "affine=array([[ -1.5, 0. , 0. , 90. ],\n", + " [ 0. , 1.5, 0. , -126. ],\n", + " [ 0. , 0. , 1.5, -72. ],\n", + " [ 0. , 0. , 0. ,\n", + "[MultiNiftiMasker.transform_single_imgs] Smoothing images\n", + "[MultiNiftiMasker.transform_single_imgs] Extracting region signals\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.6/dist-packages/dypac/dypac.py:304: UserWarning: 4 batches were requested, but only 3 datasets available. Using 4 batches instead.\n", + " self.n_batch, len(imgs), self.n_batch\n", + "/home/lussier/.local/lib/python3.6/site-packages/nilearn/signal.py:163: UserWarning: Detrending of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Detrending of 3D signal has been requested but '\n", + "/home/lussier/.local/lib/python3.6/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n", + "Replicating clusters in data #0: 0%| | 0/1 [00:00,\n", + " memory_level=1, n_batch=3, n_clusters=3, n_init=1, n_init_aggregation=1,\n", + " n_replications=1, random_state=RandomState(MT19937) at 0x7F3ABC7DC258,\n", + " smoothing_fwhm=5, subsample_size=1, threshold_sim=0.2)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model = Dypac(subsample_size=1, n_clusters=3, n_states=3, grey_matter=mni.gm,\n", + " verbose=1, n_init=1, n_init_aggregation=1, n_replications=1, detrend=True, \n", + " smoothing_fwhm=5, standardize=True, n_batch=4, threshold_sim=0.2)\n", + "model.fit(anat) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Visualize components maps, first in an interactive plot." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "num_comp = 0 # the component number\n", + "comp = model.masker_.inverse_transform(model.components_[num_comp,:].todense())\n", + "plotting.view_img(comp, threshold=0.1, vmax=1, title=\"Dwell time: {dt}\".format(dt=model.dwell_time_[num_comp]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Then in static plots." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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oKSkBEGbT4eSsC1xzzTV4+eWX6+x6Pho3Pv/8cxQXF+OZZ56xsdyR9lHHCuXjJ4AYi1gAoQ163dy5tnm1NDcXfQ6/anzyQL1cHoi+H0o6ViIRyAKC++p/cyZOik06kgYbCZTAlk+fjmm3RhFCXx7ADTeEpMQXX3zRWtlFUNcBwLK8PKTmWzlw2WcuklVVVcCukF9l9Ny54MRzqgaj5uQ1BEnPR2TUmxZt/OYoVuDmm2/GM88843jKCy+8YDvmz6uGBVavIxVwMuH07CP5yFWubzdfuhccOnQIQFgTpj+c/dJdg+cxipu/p2+bVgD+nj7qtm3bAghHlTc0NOpN2mb6cVjEHt0ZpmrjQ+TGGJgROj8llgXJkBJ37typXTyX5uYiLS0NqQhPCIITTk5AILSpk5ZvXNZ8/sJxwz6ZSrKdDGCEZ3V1tWthes9IhMvm8KtRacs6wYIlWKUf1Ufy4VZcyKu7LBFgGcqY4pkdcrYz9wFzDHN1+/bto2rOvO8E0p+zb8F9Ic26PpHUTbouyON9JBZ1TR7vw4cPPVgH2lP1vwRtzKmpqTZfNP9K4W3L4sVAMGhqp+r3//f12QDsxu4RpcMBAIERoc06LS0NeBxo2fIYgLDGSz5x5mhTobFV1TLuewKsbGpPr1pl3g9gD86kpk0FitcZPHgwHkUove3ret6ggUamSTNybtu2bdYvFE1j9t5ZpkYZDAbRrJl9gsm/j94SR+3nCFqO1J6dIDVqTij+dsGECQBC9zA+q5C/skrNBhJVN/W2226zkMfn5OQkjTy+sYIV2SorKy1/Dx8+jOeff95TG14CfZyec51AM69358OyGbA+Oeedr2H78JFYNJpN2kvU9uy9s6JqMyo/dAwYbKRRrMzPT0h788eNQ01NDSYVFSlF0ZUTygMIKp/jNdPUBXl8Y0KifMtum7M6X2qfrU3cPOU7o9O4vJrVlfP2zISlTd/lklhccMEFcbexYMECjB071tO5Tz75JFJSUmyaNCOrKYwygvrYsWOW71XmMv62IhBWKsY8PtrMveY1qOHyL4NwmfcsNemMjAxs2LABffv2tXa+UxCZ+8Km9O4GG9ue0lI88Iv+5nFiw4IFAMK+aNmPXr16YTiArw2lMFxouG7RoDdpSulegyVUQgDATjsnzR11hdTUVLMvXMRUbV+FLvqWfyMVUJe46667sGPHDvcTNagL8vjGgt69e9fZtVJSUsx5EM3zbgjgO8v+7927tz670+jhhVHMC6YZZCEzSB4SBx566CEUFRV5Pn9Unz7AAtQN54YhLGYGgU2bNoWOVVaGj+8Lm8T7KoLLFk0dbRVfo3426ga9SQPA7t277QcTEEhj1hpNIig95mCy5Tgnybq5c2Nqd8GECRhrFDyvyNKbRLfn7AByjA9RaDp1SR7fGJBQoS6GuetoNUkkEhGYZrShmsNvvvnm+Nv9iSKRFJNNmjSJOnKZc56+Zmq35KdmzWbJ8qXycEuliEqUjNrmedItyTbZByoq/L0bGOUtucGd0LRpU/Ne2E9Gfdc3GuQmzUR5craa0CwmC14J+Wp1G5CqtWpNh/GaAKMAKfgmKsekCZT8soTcKGgSHeyVmag8PAZuG3Vdksc3VDhuzJHmQgKjadUUk0DAOf4gLqg5qR7mdyQiHse+GW0+NwvAc6Hr3HTTTQDCC/Nzzz3nubs/VehIS7yirKzM9t5OnToVM2fOtJ27dWuISDvSZj5w4EAAQGFhofacROHBnJB28YzBHe6EVUZgmFORkU2bNjkX1FA4v1XcPniwVpum9vy18U89VhdokJu0j4aBuiCP9+HDhx3t2rWzH9QwdDlh+/btaNasmU07PXbsGAoKCkxGsVNPPRVAmN1L+qKpQXODBkKMXcxlpo/ayR1HZUCXfio1ayflYeDAgSYPBftGQaJVq1YAwmU0eZ1mzZqFUl+NPrHWNqGrhc17Idgv8oWfvmOHuUnXJZK+SUdDHv+wUYllmVHv04IIEr80zUh/LyecTYv2ov1EoXF4akcDleC+IhAwCE2AuaNHAwjfG18mjunWkhIMxwjv/SgPRFXtJdnk8Q0JWrO2ktc5yeDeZjBLWloaJi9aZAaseJlT1D51GmpVVZW5wAzNywO6eut/VIhiPqu1ezkfOf9GZ821net0nb17w+PSvXt3U7PmHPQ1ax8+nJH0TdorebybebHw5fkYd834mPowaMqU0H9uguMiOnv2bADhhVfNlzPRKRiVaXBrSQmG/z6KzVOBumFPMhaxWdnZUbVR9NpCjO48JuI5XkzfySaPbyjQbdAhKbxvSErv70xAOHvkSNQ+FhIEF8OF3lCZR7rC9cOV6O56S8HSYFJRkblRA2G3DIVKbYyEYmJXSV4YaOYjhO7du+Opp56yHZdaX6Zmim3evBlAWIhiiUkZwUytk+dxHZCat1PVq6NHj5oas2xfBY/xGlQ0GBEutXBqri1atMATy5ahefPmuB/2lFn2Vfq2+T3vjce3bt2Ku+++29Y/+f7pfOiZmZkAQnO1P0J7Wl0GkSV1kz7//PM9nXffffe5nkPThhN0xcO9poPwYXNz5qSJB4mOIOcEp59F5lNLxFqk3emZDRs2LKa2GjIeeeQRAGFyfR24CMlFTC5ydZ0xUJ9ITU215ffHCi7k119/PYDwuP5UNWvLBl0ewOQdId9suhGdzfHOdUun82HB1q1bUVlZaU3b0vinGxoahE96g1F4G4BNW139/60yN6ji10Nh/6OuGo1ooNNGqEF7jRb0AlZiaQGg5K3FyMjIwJAhQ7Tnsw+TJ092/N7UqocPd/z+4SuGWj6v+/ta43+VWLFvOY4dO2YfL/8FN7Fx40b7wfIABizpDwCm784rhq0ZiqVwGV/leKYDkX+kiP36gmqiH28EDhXn5ET4hQMc5p2qVd9www1x9fFkhIyedhOKyNZFYUeyaUlIRjFCaq8qMjIyzHYpZPGv9OsCYeWJGrR0R/KvLFKkW5elRq17R2X7blHe7Lu0NjDKu77SIetlkybVnYVLWGNKzsjIsPmcJfpPDMVJrzByANUcUwubmLI4zJ4925y41Jb4ULQVrVz80yPXZ+O000K/TU1NxQMGWxg0m/SyZcvMyc2IyxMnTiDfgfxkyYA/YfSGUWYfzRw/sZhLDSfixIrSP30ygHEP33//vW2DpklxwgMPoFUrqxlPLiRy3DjOTZs2VVKmYhOGvGzQkvfYExIQX6GaCEcZAmmioBb64Ib9U67OVZEFwEUfYd4z1zIShfhwRmlpqWnCP378OLBgQViwUIhYvIDEUcnm9m5cTAk+fPjwcRIiGAyGtdbyAFAewKzsbNTW1qK2thZVVVWoqqpCZWUlKisrUZEV2sSn3ZqLo0eP2v7x/EAggEAggJSUFKSkpJifeT22L8HzmjZtiqZNm5rFLwBg7ty55vEWLVqgRYsWaNKkCZo0aWK2V1tba16D/1JTU5Gamor09HSkp6cjLS0NaWlp5vcnTpzAiRMncOzYMfQbNw5d+/e39EUH3pvuHmtqalBTU2OOXXV1Naqrqy19fTAnxzzO3/GeeI9t27ZF27Ztcd9992HMffeZzyDZqFNNmvWeSZxuIoJkf/+lDwAANvxvmdb8QU0isMfqN3SafPPmzTMnF/3c1JZoUqLJyCu65d5qsOkccc7NE1i/fj1qa2vRrFkzGzF9bW0tZsyYYTIEqSjqWxz+oIm3Uf3zQ39j9yXrNDBqLk5lC08G0OVw6NAhq3uFKA9gyqBBSEtLQzOEfc20XHBc+bzkc6MmnZaWhsLx43Hw4EGsgAtblEeN9v5F/fDDDz9g9TPPYIhRsvDMoWcCMN6lbeHrj5ozJ+mm8rjb91A7WJ2HjAQH4JkX3YePkwV1bu7W1V6OBiVvLcaIP9ijnad2jUzsMW/evJiu54Sq8tDfbk/fGtXv1q9f7+m8MWNCkdkLFy703HbpP9YBsAsmOoR8n6Fn8PzzP42Sl44bNICHlg9K+LWGrByMb775Bk9MiaGgvYLCsjIAwKDbboNbSGPRpEnA9pApL6c4JNRVhaoKoiLL/ly1G67sbyJJfaIci71791o26pMJ3bt3tx4oDyD36WmoqalBq1b2tFIKYyVGwZt8zMRcI7J+2rRpNh+2pJeVflrpFpP0xTInmaDCRKWEJmOVu1u6hHiu9CHzGrx2enq6GYuzYcMG0x0p/eMymFOuW9JNKn3ONTU1GKCQRkn/ugzSJWQpzWSXs6yTTZoVg84555yY26itrTUHL9pgHkL6oKkt8SHzIWp90g6Q3NqS0k4HamjMeybUiRoPvFDh6dC1a9eTppoRfdBupTYlmYOEXCQ5R7gAyCpmbC+RJT5ra2tNKxTb5zxh/+qLnz7Z4Lt74403Aji5NGo1orsiC0CMRflmzJiBAoMuOBlYsmQJjhw5gokTJ5oFO0pKShJ+nQGTJmEeQrUDkomJEycC14c26XjM1hVZdoEkkahTTXr+/PnhD0mg29SCkvtbcU4ohdTiX09EV5g8VmQb+dGLF3vL044WZpCTsqbv3r37pNOmtRYMc0xHJrcDamRzlM8x+557onbBAKH87WPHjqHbmWciJSUFK4YPNzUgChOjs+a65jWb/ebxegDrKZ9sGrXTRtS0aVNTyKdmTLilXuoK90hiJ7dNReYcUziU7jwqTBRaVRej7pq8B2rnTm7Jtm3bmm3r8qTldWTxIjkWUqOW4PV4j5JbnO1JxSrZSOomzQRyJtgDsLzkTtKLzvxWWVlpG8RowcGVmricTLoXgP0tzsnB74yJJk04khFMQr481IT4O04ItquLaHcCgyWcruMKsSifDFHfXsaAzzRjfIbjb+QCIl98LqacM9JM2Lp161Ba1kCDRS+GTe60004z5xc1SrYvo/el+bJp06ZmQE2LFi1s0erFOTmYDU2UtlOqXqxm8ASl++3duxe9e/c2i3c05nxqp/m5xkjJjBXjx4cIn2x1DxKIlStXmkRPtw8ejKcSVKmr98iQoPy0wcmdLExS6yKY8zKA+42x27xoUfSNJlF4bRB50j58+PDxUwKDaAmm/zUzSkBKHzKFQa9CuBTGpDbL9nU5y/I8qV1SCDixYgVgRInrIAVY6RJiX198/HEAwClCANX5ogldn6WLyqvC0XvkSGwqLjZTtag4sd8UlMm8N6moyBT2vbA4RoukbNIMhrjwwgtNsg4AQHlAa/t3ixitrKzUOvK9gr+XAQcy8IBa8MKFC80ALpQHsMSgM02DfcLJoIMmTZqgrLAw9HnxYvPabFtOHOlv5/l8OXNzczF9usbkyDKU/wybdKWG5eZzUYPInDRqta+NAZ4sCco4crzlYiPL6MkYBJrO5NyUcylWVGQBrSa0sll/dPnvsv/p6emWNBzdNYAI72Ckwg6RNOskkeWoljludnwOjVmz9uHDCUnTpCW9HRBaDDYVF5vBNCandizw6iPrFMTy5csBhAPGvGLMmDFm+/NenAsgcUFAcSFJi5+FhKORspFFsznXRY4jEWtN6AUkxGkocEufquN5w3WmsXGAyyyXJ4yiQi2Ez1nWRLa5oTTjrVNIdND5fXWkPezPoUOHzCCyvLw8S5syqlsKuIFAALcYBWv+vGmT7XvZNylkuvndVZcPEParcz9gUCkQYnZU+dH7jBoFCZrB2b4tlRhIitk7KZv0hRdeqP2uqqrKkbTdDVVVVbZIWq9QKxYB9ofJCUet1Skyu6qqyhIxLYMRZFsMpFDD/QH7ZJcTkhNKBmR4ha48nI/I0M0p3YLBcdYVpk/Uc5ALHSEXIn6Wc1g1ezot1CdLFDgFcG7WjSk7oSILgEPhv0ig71mitLQUQPQKSSKQl5cXipj2CG7QDQW6EpYEfeZ1jaSs5DK3l1rEejW6W0Ek7SJ/9wxHiWXDhg3GwliKB37RP8aeOmPcuHGh/5QHMPeFOXGlMxGjDf/FihUrYm4jNzfXVgwkO8rqWF5gMX0DprSeDH9LncElYDHZyGUZViz3dP6ELaFFuC7ogosmTUJNTQ0K4Px+NgZs27YNvXr1qu9uxAwKW3SP8K90t7gJVfTz6lyCOp+2bF/3V7ZDPm5CVXBkaisFWbe0RN21oo3yJigoU3CJNYW3vpDQTVotDE5UBALYZJAqHFJ24toAACAASURBVD5wAADMguFeTH+1tbXmw+WEpXbAibjmr6u111+7dq25scmHLAubHz161BL5V5EFHJ5y2EYQD9gnHO9J+ir5mdLZkGAQRUVFtnJq0sfNPjMFQ/rN+bt169YBCE1E1e8YrbVh+fTpeDg313LvgPGMlCjfhhz1HaketNvGLOcEITVjPndZfk9nTlSZyACgf8kD5u8WKMQqI3v3tlynSZNvANhjFHSWGPbjxx9/BBCeN2S1S0lJwZEjR2z59+pCaolCj4QGWqBl27ZtAIDevXs3WI1anaNcEx4rKMApUbazenVozZMxMfHGQMQLKmhmLI/AOI2iVh8oM0iCuP5zfa9eGC7zK9eNXWvWmO/a7WopYwWJXiN9m6gPHz581CPIKw2EhTH+5eZ73b33mubYjRs3aoU1N+HcTTN209idUgydsHDhQrxnpGbNNRQJiUz1GkowoE7glYqKW064PC4FbrmJWqwPhgCaGYQlhqWbgyKYbCRkk6bUSukOgHljW0tKcMLwQdMX7cbGNXFrKFgmpE2GfWlSa5EmIqYFqP7Apk2bak07qjZs8fEYfZ85YgTw44+OXOByslIao2YtNagiQ0Ofg7Dpe/ny5TbGKJkwL/3lMkpcpjdYXl6X4LodS5eai0PKoUNYmZ+Pb7/9FgAw2QiSsHJ9Bxqs6fsOg9PaAuO+p+/KA/KsX0nrTK1IcZH3Jhc/WarPjSSCCwAXtdTUVMwZNco873RhGuRfvjMkM5FxGTKQR6aLnDhxwix2cPjwYVu/2B7nb6+5PQEAf9q+3d3S5YGDuz6wefNmk6OhoWrUPnx4RcI06d27d1s+L3qjOOZUqfqGuTGNqNduJA6dgo51i/GO/ieFhtDStGlTDFdLZzZQU6cTcrZPanT+p4aCsX37AsWh0ocl/ZfoT2yg82Hr1q0AgFtuuaWee+KMikAAi6dMCQnjwaBNyKIwft2999p+e++992L79u0A9FohodOIdZzeOgVKaqH83KZNG6xfvx5HjhzB0KHW2vbpXboAEBqzQGlpKZo1a2YhYpJ9d3NBSbjlkksFSipcvQ3Xkwlq1coa6iWuJVGKTEI2aSdqu/T0dBsNm9dIZQZFyQkkNVpp6tH523TaB49L6j2C1+VCrwodfMCnnBLyJp122mmW41IjckJlZaXNXy4nDNuV1HRygkl48UkHAgGzXRnMwSALXbH4hoIePXoAcH6Gqo/e7YWWUfkELRYyulrOPRnlLU1xMspb9kvmVctsAWlR0RUVkPMnNTXVQu0oFzDpY+c4ct4ePHgQjRmcvyeTRs0NuqFh2bJllvnCd1PFzJkzTTpQrp0NDZs3b7Zv1IBFENVu2EkQVpPik64IBIA//SkZTfuIFYrp25xUHtM+1s+fj6NHj+LhrNywCbQ80GCCyJ544gnbsYpAAMjJqYfenHy4f1E/U2jTBpY1UI16+/bt6NmzZ313wxEtWrQwhQgZIBjJCqm+b27sW141bJ1GTaFNRp1LxYgbr66cMNGhQwcb8RMhBVNem32SvPMymFPmU7tFwkurgNec8rpGXJv0TTfd5Mjws2PpUgRgJ4OXgzd5R2gRnX3XHBS8NE954M5J6RI6LckrBR4hf8+NqNWO0MTjC+Tkk+Z37Lss4SY1LBXZ2dlm4QcdeYAsm0boItXVMS4tLbXda3X1SmClEclYWWn6OikB0xfO++D9paSkYMOCBeibNdYyRrxWXW/UlHRtOffGZlFsbNDyRZTjJueoTC3h+HCTknNZ+oT5vOX3bkEuMhBIauqSEc0tDYVQrQlOpn85HrxPatJcKDnOD/5pgKUtGXWetnk85vcuDDXeQDZsap49evSoV4063pz0HTt2JKgndYOvvvoKAPDyyy8DiK7mQt++fW3HdGVmk4EtW7agpqYG9zq4GwAAnazkJ6rykuh570d3+/Dhw0eSIRnRHl+4EE1hF+p1WuCrW7cCtbVa1i2dAOCW96xTZChsVlRUALCyiZWUlKBNmzYA7FHl6kYsgyUJeQ8UPPv06eN4D0Tfvn1RVlbmOga6MdG5hqSArP5u48aN2o06WvbAWBHXJn3qqadaD5TT/BAqCSkrPNEHIRP0AWDCdSGmmpK3FpsPV5oddA9XZ6ZwC9VX+1dUVIQjR45gqlFMHYA5EXkec6Gd+iSZoaQmPX36dNtvly5damMG8qIZeYHOn19dXY27hg0DAJTOm2dq0DxP5qBTc+TndUaB+YlQKsnUIfr16wcg7Dt+6qmnHIlKjo8OaYAynkBq1oSMluf3zDuWGrXOp0zNU1dnXGdK00Xpuy0kbvNFlg7UWZ90lgVZjY0WBsYwUMNWq3SNeXw0MjIyMCYrEF7IGoBW/eSTT5pc37fddhsA4JlnnqnPLvnw4Yq4NulNmzZZPhe8NA8AEE+s0YgRI7B06dJ4uhU/jAVlAgLmPcUDuUFPnz4d7dvXTT1qiaG/GYaKBLQzbM1QLO0U/lzX/uktE0LRuyjfajk+wki9SW65eB9esHDiRKTsCAkFo9QNW0U9cX2zCFBdgUIgTaRV80LrCoUcuhekcEToFBBCx7mtg676FcH+SD5uILRGzzP6365dO8v9OfVJQgYAHz161Cx9acIpbbSTs89Z5/qLdS2S0d+OiMTRneD4jISau3WDJAnOqW3oor11dZ2llkNI2k5diL7snyw+LgMZgJA2LWntIoH3yr463WPLli1dmYEkJ7Puex3kvTqlVlRWVpr9lAEfMhhDF3Ve13AL6pBWD5kpIDVWHZMbF0lqztSkOXflc+bvaJlgu7Lusy4zgXBLL/FaZMBp7tfW1rou9lJzZ/9lXjjfCY6Ljuox1trvyQbXDAaVNdSI6ecNViz7ypR8jBihz0ElR/eaNWviuoaT71m7AZYH0K9faH47BYsmCxs3bgRgzbR48Ffh761cEom/fkybtJOEVBEIAIYpNFqEuKLDn4cPHw4gXK2kLrFkyRLz+ugUBMoTU9CcWLBgQULb84IBFiL7wQAaDglJLNgw+nHH46PKRgL4tm4748MTinNyMCprjsM3SvBNHRb72L17d53mUEshmUIkhRgpBPE4hUGd71oKVTohzCv/NYUvN8Ip4v/+7/8AAGeeeSYA58IeMtiRbceT3hcMBm2KiC4IU8LNiqBL+aXi4kVZSyTi1qRpvlk8ZQpaaCjlqB1wwskIUh0efvhhLFq0yJygkp2LiOSHczouH6aMVFWZy1TGMiftRufnpnZeU1ODVatWmdeWARe66GxdX3Xn6+41Um764EcfNWtky6pdUmOUNIXNmzc3n31dLK79+vXD+pFlAKwbdEVWiHe8trYWbdqE7/uAwRNPDY+WC68mOEKS8+tKBuqi/aU1SKaN6GgYdRq1zMPWLThOGnIgEIh6gZGbgYwU5/1JHzXHieOWkZGBwvHjkZKSgjHz4nchJQIkYOrWrVs996QRQFMnfPbs2Zg8eXJMTZJ50QlOZCF1Failw4ABA1wL9dgYGhMAP7rbhw8fPpIMafb/7rvvAISFRyoi/EvhLfuPRnnETkGsWrXK5oZwU1i8VpTiXypOprDqZHoWaUazZ88GAAwZMsRCbHXeeecBsBYwAoBvvvnG3qaCiixgVJ8+OOeccwAAmZmZAICxGGeeU1VVpfVNy3uV0Ck+UtOvrKzEgw8+aL1vpY/EMsNvT0H1448/BgBsz0qMCyXqTVp349XV1bacYF2+Micio70jSUiVlZW28muy8o+bn05CRzOna8epwozULKS5Sib760rBSf+414AP3b3ozFcq1LqpKuXnHKXQuZzIcux1PvVE50wzLSOkRYeRv3sGACBjbgaaKP1lxgEXBpoVqdFJDVVnMpM+eRkPoWMoowVFmiUJnSlNNz/cMhR036sasLqwS83ezdSn07xlFDjvm8cZBU6LhkraMWfUKPO8CYr7pyJQP9HgqampZtQ3A8t8+GgoiEuTrggEMOORR+IvMK55Iec3oLJmqkQ1Z46Tby2Eno88AsBqAmZJtIYGi5m6PIAihEqK0oTshrLCQlRUVGBsIFCn/sSKLAAz6uxyPpKIwvHjLeULwxqKIIpI4qb91FNPORdoSQBuu+02PP300+bnhUbAVZqhVdIvS/eSGpw0vbt1kh87dswmHLu5+tz8r1I4rK6uDsfkKMh7JhdAKCVxUlFR2JTbKYirrroKb7zxBgArFegVV1wBAPj+++8BAJ999pnl71VXXWWe+/rrr5ua6tzRo3EGwoIfUZFlVKUy+ikDfXVpp1591bL+tY0oSQNaRfgME53hEre5OzU1NVxJSVSl0uU5y/xpHWSRbkrtbhG+uhxTXV41LQDyIeqqdqkPwc03zHOkdSFSAr36vZsPVWq6UjN3ilj3Amo+klGKYPvJ5vbWpUHIqGnpO2X0+ddffw0gbIqS9yPHVwaH8NlL86Lue859XT6z7K/XBUW3wLgtPBI6ZjtCRp3Ld07nQ+fv5LyhRs13iZ85Xg2lAAo3RzLZbVZKJ/rwUZ+oN59075Ej61T7SiQezMnBvmefdfyuvoMbnLBs2TJbhRobVPL4IBTvD7ByZWIj3KOBNHMDIR9Q/Za295FI5A8fjmbNmlk0ahWh7A+H3NNIuaoNgDwFAE4//XTLZ7r4pOKh0vPm831TU7nLAzhxokCbGimhE+6lkCnP1wl7FNpatGiBkqlTkY+Zjtd68sknzf+TeIj0oP/6178AAHv37rW0fc011wAIW1Fa54ZSdSVVrwo1nVAnaLtB3qtattWyXmrm2SQja4Z2ZCoGfMa9evUCAGzbti0uN2BUm7SktgPgWK+5pqYGg6ZMcWzD3MQibNDrjCLhMn9Zp3W4sS+55QzriNr54pB1yryHYBAXGqlZ+coGpjPLHT9+XKsZyT7KvFk3n7OE9K9TsykpCbHARcp91IFEA2vXrrWNfXp6OlbPmoVBSqR3IohNwlVowhrN5B05aN26NZo0scclSN8xrTTMzacGx/HQmQ2lyUvm4BM0bfF6svCAnGvSiuSVSczrGDqliUxYsACZ+4APsAIAcPNdzm4apyjVgrFjLf2SsRduFgBp6eD40IcvzbtAaLNWn4vFX62YwT0JwppoZB127doFAKZvur6Qv3JlgxT0JYasDK0JK1bUc0caCeJZC/3obh8+fPhIEmS8DhUPSVfrRm4EOAdlSiHfTYuUQryugpSELgUPAN58803H3zCKmz5pqUET0u0ZkelLgbxXXd/lGLm5hrzmiDOdloqATPN0SzH2Cs+btM580rx5c5sWmJGRgfXz56NVq1bo8fDDUUVsbtiwwbF+M2DXKnXSvM6Px0H74osvAFgp7/Ly8nDGGWdYrqtGBBcVFVnz+lp2ARA5R3jJkiU2nzB9o19++SUAoKCgwPxu0aJF5oPXpRdEy+1M3yBNMMuXL8fDDz+s7bMTHnvsMZP3Wd5PshL709LSUDbKWvUmIyPDtshQM+P9cu7wheF9c8Ggb1RXj1vOcxnVzRdYznldFLfX4xK6KHBqnjnFxZbzHedhoVGN6oMPQn8vcZ6rmU4/BUxtVGrac0ePtmnKsr+EHB+OJ5+TZB9U51Pe0KG2lKBWrVphERY73kci4HWB9oqioqLwh/IAgBLH8+b0NIigIlTVZH2D0n+sS1DvGhYYVBdnGHKdIHMfMCkr9GyX5uZ6+k2sFkZfk/bhw4ePBIN+Vgku1C1btsTthhvJq3l7ydslOOWUU5Caqk/h0wXrSsUlUmrdqlWrcOTIEYxSUjKJaAMVgbCrSQddfWl5LVUQVRnHdIqKtBJIRArqXLJkCb777jvk5uaGlUvhm+ZzG5Y1HY8VFJgWAQqWtJpcd911Ee/fDXFv0irnc39DEtphFMho0qQJdq9bh/6d+kdsg4U6AoEA0tLStJV6opVAdDmfhw8fRiG1DABdunTBq6++CiCUatWxY0cAYS2MGrUaQNWlSxfb9VasWGHpY0ZGhvnAqDn/7//+LwDnhP6RI0PEBaWlpa735KZRE05WhQ0bNpgaGftnI7g3wPgAyRonfZOLjRiEmbKBKEEuZfnCTt+VB/XWZBSyTJeQ5BCSg1tq3LI9aX6UGiPHT5e3rqu2Jc2STj7d8YWF+oWbC4aqocUAci7r3qna2loMGhS6ltS0Fyoa9lzDuiQ5zNV2VMhxlj58aTmipq1quNTsk+G73b17N+644w4/b9pHg0FCNenHFy4EAMikChbr1hWNkAtZMjFkyBDbsVdffRVdunTBhRdeGHfb0URC63w59QFWHpObS6wpXD7cMbagwHmjmR99ZPJcgzd/0iR9CdGVK1dqBWAnrF692twkKdxMmjTJFBQyg9YNGwAWTJgQdd+jxazsbDRr1gxjsua5b9T1FOUtaygDoTE6PDs0jvdkZ0ctZLRu3dp8bhRaZCAehRvJZKZbY3WuQrc1WRdQGekabtApZU5aezAY1KazSoVFUunqqmTxMzVim+tDziVj7mfuA8YjNO/X/T0cXEtXo9NciAZxb9LNmze3+KLVvzq/n5upRJpidDm6bjnEcuJF8p++9tpreO211yzHqF2Sno7+4kggwxWLpX/00UcA7FV2br75Zm0bNTU1ninuJHSkBbqqRvwr84N1v5cvgtSI4oXkCid0GpmcY7QM8Pcyn1vm68p8YI6PfEF1/iRpZtRZNGS0uNfgGK/wUpWstrbWNW+bxyWTmCSW0IHjJn350qeu06gJ9pMLJmM5dGk3iUTz5s1NoSRW7Ny50/O5a/662hz3B3810PqlsTGsX7/e8bc6CxiQoAJF3Jj2xGsjc8eM20PshzP35LucGR8cK2/BXnoZgD0WScHiNxcBCM3RgZcPAgDc+uCD2FriHHcQK3yftIFonfrM/XvllVcAeJcW1WudlBC8vrFADRgbtymUCuTCe9NosPgB5QW+T/miUxCFhYUhDeitElvAVaSUrMGDB0dcrAHg3//+d3wdN0Az+cGDBzFmzBiLVg2ENOsxj+sLJyQSCyZMwDwUuJ8YJViasK5qTh88eNB0renA5y55sCPh+PHjtohjXUCivI4UIqW7x83P7PTbSP10Oj+SJq32W0fkJF1Tbtq/tEK4Cb6kIHZTIOIlfIp7k05PT9cyeOkq9ui0EWm64e+lNkRty43HWiKaYAcg7INmEEiHDh3M7y6++GIA4fSCTz75BECY8u65556L6loSuvxTHTgBpUackpKC/v37my4HufhT43TjbNZp6ES8VHikE5QTWhdNLq0kPI8aF+cQzX2cM9QISccoo43dUlzkOEnNWFfrfOF9Dj7kTkFz00v5+zq0bdvWdoru+mz36NGjWLhwoan58a/KltetWzcEg0Hs2xe2r8oYA2qs3Cx0qUKcL+3bt0dZWZn5rpu0uZ2CWGhQeo7eMMo2LnxOcp7qqn7J0o1yXCZtC8XBzO0lKmslwMwdCAQsNJcqUUcsKJ03D3DJhij7H6vGHPjfDY7nxcJ30FhhFhlBdlKvc++99wIIC2kE9wFZy8GyNlFY3RcA/jux/fI1aR8+fPhIJgzfZUZGkSlUPlZQAPyZQkqlKVxKoZOorKzEwIHCFO6ClJQUrX9WJ3TqUgQn3zQFM/fkm0LZbEO4xOrV2utT03SLa9mzZ0/oP8ZGNxkBzNyTj0AggHHXjLcIXKtXr3YlhJJ/o61fzc0aCJnAdQKiWnt71apVAICHfh0eY11wabSIe5M+duyYLZdRTgwpRcuHRq2H/lyaUnSFLCjZUEuSgyCrY6lmjHXr1uHYsWMYNmyYY9sqYcD1119vaY880OoxPnhq0nzZdIhk6l61apUZ3S6jf3X5uPyeGhTHcKIRaU/o/DDUsGX1LmlCcuNujhfU3FRig7xnctG8uVXDihSNDNhNZ1IDlEEhnGtsV76QuuvozIayfydOnEBJ/yXWRoxFp7S01MaN7aa58/7Igsf5x898/tSkd+7ciQ8++AB//etf8eGHH5pZDDrQakStntYjliDkwkuTIMeL8+jYsWN46KFQn4s6wdygaAKX80xuHjozv656F7+fsCVcqCNRUd/BYDCqACkfPpKBuDbpjVGmgWRnO5srIjnnnTB48OC4+aSXLl0acaOWuPbaay2fL7jgAgDOVKlAaPGIZiOjJBYv5ObsBt3mvXXr1piur1aqiQWOZuFGivm9w2l+qjawePHiuCM+I0Ga6wDg8ssvT9r1JFatWoWvv/4aU6dONe97IZLvqy4cPx6HDx9GXtayuOYg8fTTTyfEL83I9xNzT5jCaFpamrn+LF68WFtoh4hWiwasrkg3n7RTcO+qVavw0EMPhQ50CmIqwpH8XuouUCDzGnRoQrmW+t6sW7fO4k5yc6fqCixFgz59+pgBZVIzV12C5jiVDzYVJips8RI+xbVJ63zIhNRidIglkvLIkSOmNO+WTy2l7lgq71x44YVRTTbzoXmEzDvWRXfLiUeN6dtvv43qem6gdUTmv+qqR8WiWd96663m/50qomVkZNiCR9wsCuyvzkQl0yI4Z6lRy2hn+XsJXVBKpAWhZcuWnquc8R3TRYdTs+XcjKT5XXDBBeb5jKWQGQ0vv/yy429vuOEGAMC5554LALjooosAhHzTQHhcad3ieSqaNm1q4zyX0fnSRCitcW7vRaJTBn1NWoEIEowVnuJs6jh1riKQoHK7nYLA8xqOfOWdj8YEnhSf9Izb86Ma5EcffVT/pYYon5r3Y489FnX/CNOP4GFDlZruB6Ra1MCrps92E5GSM23aNMvnCpeJEGlSRpOm4MOKSNaAtWvXJvXaM2boC22r13Yi40k0ysrK8MMPPwAARowIYnan0PGKQACF48cn7bqzsrOxqNyuidUF1EAziePHj5uBkapQ2qpVKy35TTyorq6OWniONrgWAG688UbzflQSIP6/Xbt2APTR8nQrukHHlqYTeOWYxhplLa0Psl2ZrknXEwV/t5LMbggA0D7FFUqJE6eXmpHMUvs769NPkW68kOS49oqqV1/F/xnl3aR0fM7nn4c+i77QV+wWgSzB89Soba+gBhtveD1TubxCvkRVVVU4++yzbedVKb7HL372M63Zi8fPP/98/UUPh9v6+khHy1fUNDhRz/r0U/P50P85ZMgQy1wi1DJ+Hc8O+/urykN/919wgTavl5AmKEIXLSx/pwvycCsMr4u+v7iDw/Ns2cVknHNbhGX0Nu9L1i1XNc3zzjsvYpuR5up7770HIFy43iuokbNNatA6boTa2lqTGx8Iz8/PDQ4Cr5YFQkfKIjNM1HkV7VrUvHlzS2qbl4yNHj164IknnrAco7C8LC/PTOu5JzvbFJLXrVtnW/jlfemEZrV9ndBdWlpqWjrkfNeZjAlaclxL3Rro06eP+f/7778fgN4l6BUULt2KgsjUJ4KbpRPVqZMiI8eR7iNdfM7x48ct9RBycnLM66nXn2UE2WU2BE3ahw8fPn6KoPmfqAgEUFZYiNraWjSH1Q1TVlaGQCCA9PR0c+OhW8OrH1PdZHQm20i1l92E32g1e9XS5mZt9Ao3d6bUcKXgLAVfN8hx1BE3qc9o+fLlOHDgAHJycsxiKZN3hDZrJxKsaHg5Im7SKoWmk4R7aseOWJmf71gy7FEYptfDcDc5lQcwfvM4HDhwAEB40HlzMj96cMeOlkF85513ANi1Dl1agdRS/va3vzmSyUcCJ+All1wS1e9ULFq0yMYARuj86jI69ttvv7USuJOmcQgw45FHQmPw17/aonF1wRSpqakYPXeuJUKWgS/r589H06Z/BxA2ZdHHSC7yGbfnm9WWyIEOONOxPvLII+b/bx/wJ/NapfPmhe63vNycW7yeJGegtMq5I6t+EXzm8oXmcUZJMzqaJioZfU3NQvqKCwy3iyWyWJn3JL2ReenyOdM8/O677wKwuxdoGlTrWLuxW0Waq5dccgnGjx9vWsViDRhkgfvLLrsMQJilT51vX331lTnefQ0N9RflAUzaNlHLDqjjXtBp7myfMRq/X7cu/Ew0VcAiQd2kGPmu89v78JEMeNakA4EAhg4danI8u8FCgl/uLC3wnPnjxnntRtJQXFyMmpoajDWK3ccEeZ/1wBvMMZ2hbIDRomjSJKQ/pZBI5EcRbBfnPZfOm+d+UgOEbnMGQsQTv/jFLxJ6PTO3NAGYb6Qu3XPPPQlr0w0s4Th6dBBzFV91UQTu8biRADY8Nzj5H9u0aWNLJdtr0HzKVEBdxomENt7EwRdfXV1tCks6pjGiLmhXo8WAAQMAhIv9EG71pKUGbWNJ0+xLgNWFoJrwVVCApsBYVVWFkpIS3GMkMZ02/zRLv1iMZqH2qs6IytxNbUUFNQ+1M9Emb7NdaiUMNJDBCLoocelfcUtn0PFU1/XErKmp0fpRnM4F7NR1umhWjhU1XU5QGeVMSAYtLh58JjKSn5u2WlnMK+666y4AzguaDA6RUd3yxZMWBo6LvB8ZHa2bo7xPglYc2Z5XqkFeS/rAdaBvWBegl8xo43POOcd8Njt27Ijqt9u2bQMQngedOoV2XkaBy/l65plnOrYjzazS4iAZ8XQ+3EQFYEUT0Bnt+tGvX79ou2PDsrw8AKH3NXvWrLBypHRl8ODBZh57YwR90vGSgkioddJX5udbeOq7GSlvkaK+dZv3HOMd0OYZRCksxuWTzgwGAU1ebnFODlJSUpCdNcvx+/njxqFqpBHsE2UK1uZFi5JGEFdYWIhxXjR7I5iqItBRe4ouVaGwsDCmKMqGjHBEc7RyIjDv7oLwC5N4KuakY8Pox8MfkqypaU2thlYwqixEocj5NamoCFUrVhiBnJFdM4WFhWap0LqC5CsYY1hSkqpR1zGqqqpsLFWJ2nAYNOtVKNFFKutS2xqCRi2DJnWuIl1QrMoMpkNaWpqNGCpWZGZmWj5TQYo1yDiqTVpqGUCo3B4APDp4sKPDfupDD9lMLDU1NUBFhdkeb4IsR7ISkqxhLKVbyXim0y51E1Fqqaw1rd2sywOoKrdHK3tFgHonigAAIABJREFUMBh0nfxyLGUfOeFk3WOCE0JyWkuGLbl4SN+t1PRlHeaampoQ01MULE/MUVZN6OuMUotBYeWQvked1YRt8TPvR+WwViGfPb+XpjE5Dmp0bGFZWaixDc7Psnv37mZEM+e6zsrDz8xf/t3vfgcA+Mtf/gIglKf8/PPPO15n5MiRaNIklNLUrJmzZhmKmHdPS2K1tm7dugEAnn32We25TpBmeL7DzB6QMRXt2rXD1q1bUVFRgeHBoGlmHD13LoomTdJG7kqftdS0EyUE09/fo0cPxzbVrAWnQKl///nPjqJR+3/9Cx+UG2maMWTAfPLMMwCAW4xjgUAA7958M841sggOiL787Gc/A+BeJY+Q38cSBMZ3L94AMlpj3Pqoi1Dv0KGDmQGj9qVKeXadzj/fYgl+76WXwu2/9BIAOGbRmFAyYC66yPrEOVd5H++Vr0B6y1A/OH+cYnYIP7rbhw8fPpIE6ZZxFM6VBV67YSvnfHrWWagRbptIJC779+931dx1SkND0KSJaBUbL/js7LNDm3NNjZaal+2R+jkQCODctp84trf/8CXa65vPqpPj11pEtUk7le5iwEyLx1uY2gf91LoobR6npCXZrQip7VmkaiVAQkrVOj+SW85sfUAn/bn1ya0usdQsOUZ8Nrq6yzL6W9U0ZwkyfTNYSo03Kg8gkIWI4Dxg3yuyAMy1nsN+cPHRFQKQKSTSh87zqfnL8ZKaNNtjPXD6iFu2bGn53fqRZcB6e5qG+tyqq6tN09n+/fsBhH2xclFldDnPowWBGq2TL3vYsGFo1aoVmjZtaranY0yLFrt27YrLZ0qNmtYx/uUaIt/pdu3aYfPmzehtHK8IBFBbW6sl+dCl2XCcHONX4nBFBINBx2ArtwwY5kxLa98jM2Y4c4zrItDLw261pc9nm1kAfO7MWx9vWAFVP+qbb75pnictUTptVMZgMLI9GiQiAwYI8y24xRpJgYWfv/vuO2sGjIGKjh2xdvRo29og415k0F+TJk1wY1dnAq63P15na4fvNjNgbuo+wzEDRoeoNelBgwZhtbpYGxN/UlYAuUpCd12CPq0lS5a4nBkdCgoKMGHChJh+qyP5ZyRtsrCWRUkSGGCUt2yZ+f9EFS9QkbkPwIuJbzdRWG6UKMzcB2WhX49evXpZAieThWdo2rzlFlP4UolBkoWysjIzl7c+QFfawij56FUUjB2LQixIVJeiBhdobtKuCkGkiGND+G09tbWW6phuI3XEUlJSXAu3EIlkPEsUZB91NbClYOqFBrqystIMXKZgLF2FMv2zSZMmWPjqAlMQtCo6Ndoyv7G+R1Ft0k5J2SoYlS0lGUp5HCx2mpq0NAnJnFTpZ9JFeevMFIR8mInSOqKBWx90L5ObP53gGEvJXSbgc2xl/WCpWcdCSu8GeQ0VujrX0lcuo3wZdc6/bIcvnowCluMpo4XlODrhu+++i5gzW1kZLkH46aefAggHpVAz53Mg8xyvR7+9mjZSWVlpaqT8vcyzjzXDIhJuv/12PPXUUzH9lv3nu861QCKSuVblOpZ56zoTpY5/IFZEXSSB1b/mOQsZc0aNQk5WMQDvgu+a2bPNcXRDwriofdQ7EuqTHjFzJgBgplKQfMrixViam5vIywAAlr+7DMFgEEOjtO8nBJ2CQLkLN3c95EgnG14Xk3glx4aEFTt3Oi52sioawXt2Mq/FiptuuimmSjpDBJd7rHNSJUtJ9jMl5/0dCWwzzNmQ/DxpJ9TU1JhCZzwKQXV1tanNUUijECQDE1U4ae86TVoqC8kQ0qOFjoCI0AngUmBzQnp6uvk9x5QKCwV86UqS/ZJBpnLMZBpotIhqk3arZkVMLSmxfB42fbrtnE0GeQgQ1lpkiS81glj9rGreqsQ4YsQILF68WKtRSy1WfpYTM9IE1Tn/dRvZggUhkxsnlE7zkdfWfU+o6SuLFy+2aZi6ymSceNSkqblJn/TdI0YkzMR94403AnDmd9blx+p8aDwumb9kFLruxaIPWuaDUxOfb5BNqBv0LbfcYpq333jjjYj3+pIREcrNWle/WmqCvH++C7w/+nLLjIhyumHkfNBZXqINVtHBLSqY4H2zDjXnlxP3uAqnbIWxBQW2ghzyOcp8eukXNBFj4Q0vZuBAIID77rvPc05yscHxPCrLuWqSihURCqec7OAa58T/HxOMOTAnSpbJeDH7Lvfn7AQ/utuHDx8+EgQqGETmPgCb7SVUVTfX6llhLgmZOkghrYkhHErtTpZadVIsqqqqbNqmzhWo48WOB3feeaet6Egs8CqQyuO6/GgepwYt6ac5FnwGksBIKkQ660O8Yxj1Jj179mzrgQiBDpHQZ9Qo0wzOwaL2ICM6I0X4biouxkil3ZSUFBtHNyG1Fam16UqgRQWNhC59alLil32U0a8yT9gJ1dXV5kvOl1Ym8nPsZO45NRgZgR8TNHNCarU5N042//+goVU8ZgQLSQ1XVu+RkZeS0Ur37HQ+bF7v+PHjKHjsMYsG3bVrV7P8HH9/5ZVXAvCuUUuwPrO0qEgLyuuvv279oTG2hw+HqhJJgoRk+KQjgfP0qquuAmDvL7UfnSZN8DOfh+460oJCyOevvtOOlqAoKXx37typdXH48JFMxK1J09/z9KpVpvTXe+TICL9IPFSe1eHDhwOw13+OFfPmzUNNTQ0mT57seq7OLFxQUJCwABaC9wkoPL4LEhfFOui/jBrbSYjmJmbuyQcATNWkM9Q1ZhgbitygiTfffFP72zrzv3MzWeON47muYBMmDDBFafPmzXG1z9SipJkoE1R/2kmIZt8LlLoAUliXQjuFaLYnaxRTOJPCP7E0Nxd5xv8HDx6M9Yb7Rgaq6mhVE8nhfezYMXTt2hVXXHFFxHrnbpCKi/RV6yDLbHLPCgy3Cvhsh2MsFQU5Jm7856oLbe0j6yznJK1UZSTtKi0tzZSWvUKt8wmEb0pq0HICuvEvsw1d5CcfspS6ZWBCooIn0tLSbGxp8iXVFRSXuX+RqO2qq6u1vlYKUNLfL003kYIs4oXsm9OCRg1J94I45Syqx3WQPkyOAzU3nYXCNDdqmN2Im2++GYC3msMA8MILL1g+Mw+Vi7NbQRO+O9K/L+dVQwH7IzVpvmPchBgFr4PkoCf/u86Ckkiu859i9auRcShcf//7323Hpk2bFvNGPWzYMM8FniLBDGxuJNHvcat3T61caVvYn1m9GrcNGmR+3rVmDQCYpOWJxqbiUCpDnervBjNQ5j6FqL0+IrrLA9hYVBRz5KATbrr/fpQZkne//7w/Ye02dKgaNDfdP//5z/XSl6efftrx+CDlvdJh9NwwM0zmPuAAEDX1pIqKQMBc2KRgTTA9M2/ZMss4UoP2KjSMmhNbcE3CEGelLKeiMcThw4e1JEJSMZE5vpKMiK5BXTtyvCX5kS6nOJHETsw/puD6X//1X3G3WVtb63oPkohJQipCFOClssjfS+uGFITl2MkU4lgyM1QkLXDsmdWrw5qrOE5+Yhg1XxOG8gCWvbPUVetJKDoFtYU0koURSopbRRaAIv25sSBzH4D/Cf2/9B/r0P+XAyKeP+/FuZh4feMuiEBzIOFVIybIsJUIs/fu3bu135FIaMCAAeHSfdK/yhoZ3Gxi4U4uD6DgpXkhlqRx4wAH3n4nrMzPB2bORIcOHfDgrwaid+9QH1glKxJuGRB5nvmIEgky4ceC7OxsbXnWPKNyF//6iIy4C2wcPXrUlOak6U36PXhMmr7k751SdAB9apQq/aWkpNiuL2lD1XMBe6pXoqXKtLQ0U0KWOXdufLHyr1OfamtrtXSZhNS0KRVKOlBCpjZFQiQTvAoGUV188cWWa6igNEvJX/ZP58uTEZYyxYl9pNlfEukkCtdffz0A4MUXo6NQ4/2REMgNdSGIqvNWahOMiNWxOpFpiyCNpSzowuP79+83i0VEAp+nZIXSmbmlxp8sXH311QCcyVpmZWeH3CrBoKkBS5ebZLeS1kmOL+cxNWq+Q/J9lu/Wgw8+CCCcwqcjVZJrYLRQY2Uk2Hc+u2jN12SU1PVNptLqiF+mLF4MAJhmxEtwLNk/jiHTUznXJX2ovJ504zntf7GgTlOwnjXqgiYLK/YtT1rbM2fOxNSpU6P6TWFhoefc8qhhSMkbEhgsRpT9z3oM+q/IZu6KrJCbgRM8TBiR8O4kFQsfN8pMRshtZWDeuH79zBfw9NNPBxDyaS8btNzUVl544QUzcjtaRKO9L1+uzPUkaEoLX41/XhW9thD3ZYXG7qEIAm9FAqwPCcNJSELko3Ejqk1aSsdASApxY3zhRkUmF0omknBDStn8KzVenc+hpqbGTHxfs2aNloRfak86chMvG+zVV1+NV155xfG7Jk2a2DRhmVtH6DRlVftX/ZHcFIOFzly80nrAsaTvkH8lZSs1D6dNtyIrzA1enV8NHDpkBl5NeOABAEApHnMcCxUy6Cn7sRGYihJLf+nb00XFS3+ULF1JyNKTDFCqrq4Ob9AAUB6wFIEnZo4YAYwYgaqqKrRAeHxUDXL0hlHIyQpnGDAozIs2wg09WvN6ssANs5mh4TAvV1pUZHClDExkYZLZRuDR5Dg34jwjQrelMU9lyUvZL6kdJRscJ/4lKrKAUx49xVxLZMAi/8qASa51cg3iffM6nGPSsqCzEOkInHhcpsNGg7y8PMt6RQIeZkiwbZVoZujQoTh06JAnApjhw4djyZIlrlWmpP9eB2m14xqo06CldUMSLcn0QElrHSvqjrTahw8fPn5iWPJow0gvTCaGDRsWt3+5b9++ruckqoBSZjBY77zmwWDQszs1Kk3aycb//fffa9MqKGFQAqHUSAmLKVuyXCD9VDL9RfonZfpMVVUVFi1ahNTUVItvZJlRxUnn39X5hYlIGrUuVUZKfPJabiUqpSYsfT2sdtNMMA8ROomYGrSUFjmWjMgsMUz71duVFK0JQNAI+uOY83deif+BsITrJBFzrnjlOtblSuo0aJnaRUgteupDoTxxPl2pgUi/FCvAHbz3XmzcuBEA0L17d22UNvH8889H/L4uUREImARDzY1npPPxE3KeyhgAzo8Rd9+Nkq1bo+rPrOxs851vIfKI5fOW851rhywx6ooYo7tlzATB68t4G5kHLf/KMr6EHGe+L2yPFijdmiXfJz5fjtu///1vAGFLiBfU1NSY7arrIdftc845x9JX6av1WkmO53HtkpqtTKFVi9M4Qc4l9l3uN4T0OfPZqPuP+ldXDjRa/CRoQZnMbvHjJQjJMlOqnNwSyS53GTfMRa4B+RoNlI3agH7FkaX2GY88AsSR0nbvvfd6CliK5+UlF7w0W44ZMybqtmjiXjxlSlIXhBF3323+nwtg8aZN5rFHBw/WmrF9RIf+EycmJA+Y65AuwEutpx0vevfuDSB+4hsJmskl1q1bhwGNIKMgqneSGrCK48eP27Q4WTBckobwL/2h1KhlXpksNyh9BLIsIf/qIpJl2Uadb9vNf+wF0oogJX+d79SLD001lciIQ5nbx+syHoB/Oea8Lq0XktlIkp0QMq/TaW7owGs5SftSM3Yr9C4hNXzGUahS9YkTJ8wC7E7IyMiwzREZF8HxldKzpL/s0iWUn8zC9QQXpFjhxsUcK6hR8R2SJDoyjkRqdlLLkEV0JPe0ihYtWtjeZV1RHM4HrhnsN6/P5+BGCpNo1NbWWlLiOE+kRi3zn6UmLeNy5Fok6X45rny/ZQAnfb5S06d2+q9//QsA8PHHHwOwW7R69OgBIPw+cf4x95k+cTXrgH1iNodcf/mMpHWL7wb7wOMcs/PPPx9AOHhTFgWS+0bbtm2Ra1iIpotiT02aNLEVcJJrjhxrriX8q9s/ONbp6ekYvu4RLBnwJ8SCuATnikAAEJRrDQULFy7EoUOHMDQvz/Q/qNppwiqqJBCSvk5FRSCAzYsWabmNfXhDRRaAXs7fTRowwLVmeix45ZVXHF0fsaCoKJQUr9uUFy5cCCC0sEya5J67PnHiRGDChKQyzUUCA8uSWdO9sWYe+PABeNykb7vtNgBhKY0ozslBG9ilaikdUhKRkbH8y0L21KzlC0sfBP0tMgdQRlRyI0tNTcXK/HwMVri9i4uLkZKSguzsbNNXLf1oOj9xNJDauMydk3mJQ4cONU0yw4cPt6WllBUWAlVVNumSf/ls5PWkdCn9OfRBU4Pm2MnIfEJHbxoN4xnzpSmdA+EFtHqLNWLS7VnIuSZ90DJ6tn/Xrig1iDXuufpqbDEi8ycPHIgU6DUdjivnGs+j71BG23K8MzMzcffdd5v9jjU9CwhtwG6lHqPN8Wd7UlOWFglp3XKrACR9lNRSpLaiowvVPXf5nNV3HQjPb14nJoEoDhKQ2tpao958qI2+Y8di3dy5Nl+xmyVCWmiktimfF9sdNGVKqCM3hfu0YcMGWzEhvg8ffvghAOCf//ynpX1Zr5prN393wQUXAADOPPNMAGFNWl27+Y7wmRDy3SY3wGeffWY5zrnDZ7zViGno1auXpf0zzjjD0j7XNu4nvIfDhw8jPz8fjyrBfHSBVgQCZulQjpUsXyuL8ci5Lq2LfCbxCsA/CZ+0Dx8+fNQHMvcBiI7XJmaMmTcv/KFTEOvWras3C0lDBuM2aHUCQgoc6ztWBAJm4GyyEQwGXV1Vnjbp1NRUPPnkk7bjNA3KfDFKGpS61Lqcyx/SmJkNqdULscFTK1cCCGuPvB79jPRP8TgjddOGDUOeoT0jO9tiXl6yZIkpZVJiisfPx3tnm5JZiGOmmuDvNug+K0aMMIvcUzprZkiy0qpA8LxIjD8AbBSS03flAbBbESSDka5aj4w36Ft0XyReEAssEeHG8x+XFcCs7GxHNjL1OlLjo6Qv81BlRZvMzExMeOABVFdX4ywA9xkMYW2NOcM5Le9PxhhI3zk1aWrwfD6U5mmNiodjXWWW05VblXnCbpDvLsFx4zslfbw6iwb7JzVmqSnqSnTqovSlViOZxzj+Mi5FdQ9VZCXP5K2rRkVIy4LOxy6fo9Sspa+fcPK9p6ena4sTffTRRwBChEtOIHOe9IF36NABAHDZZZcBCK9HTu4KHauZtML9/Oc/BxB+dxizIuMfCFLMmpH/xrvGd1eWr5Vj6IVl8NixY+bc4b3L+AKdi0bWDo+3AmJMvzY3UlVy84BIG3RxcTFatWqFgdI8ZWwqpf9YFx6UEydw++DBAIAnuOl6RN7QoaHNfeJEzFP6z81Nla6SDXWDrggEUDh+fNiEEmOb5KA+cuSIs4+7UxBr165FVVUVhmQ9jNxueQCA8ZvHxXjFxKB///4AgNJ9wJSsEG1fXUmzdY0uXbrg4osv9lxOdf78+TELjGPGjMH111+PCy+8MKbf+wihzkqRxon6zv9tTBgzZozjep8ZDMIUXSQvvoFRZXVXzsnTJq3TaqhVUJqVZREl/3Ik1NTURDwvNTXVVmqSffvyyy8BhHP82A8ppTICOVJOb0ZGhtl+NBHXErw2pSnp23XSdI4dO2b2nWMuJXD2pX379gDsGjXPl/EDKjIyMmwBaDouYSn18j6klMoxjSZ1Zu/eveb/+/TpY/v+yJEjNt+6lOw5TtJ3Kn1pHC/OAQpDkimL0jy/p3QufW4yh19Gv0tpm5+/NYrK0P/mBU7c7Cprk3p9zqv9+/eb14kUbCjHl+0xipf5srooa8mypNOadGxM8nypScpx5fzj+yAje+V8iJftyStkVoUKFp9ZsW+57TnqfPM6M7X0YQcCAXQ1BFzVSrBp0yakpqbaYmOopf7jH/+IeD/knv/jH/8IIKxBX3HFFQDCcUQ6i4AKnYDDe2aU9uWXXw4AeOeddwCE5/Ibb7zh+HumarEvv/rVrwDY87H5jnKtVC2m48ePN9fUYqOaogVKfIGK4n6LzP8/unOqpV35DBsFd/fC+7yXaSotLRUPtTRpkZ/Tpk0DAEt90+HDhzs/LIRJ6tdG4CBnUIIMllChari0SuS7maljwIYNGyKTpygTcN7dBZi4dULC+xA1OgWRuS/Up0lZsZf3eqRnT/eTTnJwvkYCo8UjQQ12U61hQ1c/HFvH6hAzhbXCj/T20djgaZOWkjjNkKcY0qPkjfUMJXqySZMmNolDRpBSOzp06BBK580LaT3ffGNKQtQeJQuW9Oewv/Rd5+bmWvLnpLZIrYJS6J133ok5DnVvr732WlMaZNSjzF+WG/T8cSEzc9C4N15LWiGkNs/26POkxkcNg5uxruqWU47yvLsLAAAz9+Sb9y6jc3k/UnOT/YoW1NgGDRqE1atD84KbNWBnBLOY9QxBQz3nT9u3Y2C3bqYGKzUvgr5Wlk+VFdE452T0PDU2ji/nEn2j0vLB4zrLig4zZ84EYNdQpObCOc/nwbn//fffx1zpq0+fPqZ16uuvvw4dVN7ZZQjznZOoRFbnkrV7CemDlfcntRBdVoGsQCTzu2NCDFHdXlIjT5w4oa3g53af0od/s8GVD1jfBbLdSe2V85mWnKeeesq1vwDws5/9DACQlRV60FxvvJj/3SL15dwgMxmf4bvvvuupj5988gkA4KKLLnLsI+eCTK+UltLs7GwAwGKjShYArblbxYiZM7F61ixbtLeu7rUKL+PoR3f78OHDRx3j3tGjTW2+6LXo42BeUjfjzZsbjc+8MWCcoTiFBOkcU+CWxFSmgDkruXEAnjbpl19+2fJZ+pEIKbE0b94cdw4dCnRVTnKQUktLS9GyZUstpza1nK+++gpAKCJxzJgxtrw0/qXWI/1a0r9L6beiosLSHwZ0MbCM36u+bDJIdezYEUDYd8O+Ss1MV1VGah7M+dNxffMeZF1kaqLU4HU55/xs+rL5PBSJcWrXR1H6j3UA7D5FmSsopdGFjz8eseyjDuSw7tGjB+688060b98eK1aE50pmpPfAgYZ0VJ8+aIWw20FWbZLxFDKSU/rcCOmrl3nCbE8ykslYgUjuECBM/SotIITUoJnvTkuMmkdfW1uLv/71rxg0aJDZf77TkfKIzznnHPM+GPdxzTXXAAjNn127wq6J1AWhd1HyHut86ZIxjdDlS+s4p+X48/o5GpdVtPC6+bHyWadOnbTnHD161NGqcfDgQZtWKX3UHDe+t7QQyY1D95fPgTEXbiBdJv28tDhFU+fea466nBsMcpRrjWTtI5599lkA4TVYRnnLjBW+25wrslqVzqoh+6v7qxv7WBGTJv2I4cP1Uss4cx+05iOSd3ghwR87dmz4Q3kAwGjX30QD+oaTFR0p6egAYM6oUWjhcG48GDkyHHXISG8dNm3aFA7YEgEStxgv6fNGkXivSOT4DRkyxFaoIRgMYpPC93wyQpcWkwxwIendu3fU49qtWzfs2hV63sWbQu1MUcqp1ifoRhofx1hGq53GyiSXd1t4bZi5Jz+mNnycvIjL3C0rz8jcUje/kBsFIyWQL774wvE7mSOq82vJfDupNTnVyQbCuYReclv5QtOH+fnnn1vuwQk1NTU2H67MrZOagtQgGJVMK4OKqqoqm2YirQ9uoKYuubwJmc8ZL5zy8SW8bCbUVKm5UoPgs5Q1Yhn1zfHknJa1z3WatIxj0OUF6zR0FSrBgYwBIGS8hqyhy/iJQCCAQCCAlJQUNG/eXFt1a/PmzbZxPXjwIC699FIA4Qjc999/37E/BH3vUpOW81xqHYRuY3SrVCc1z2TSjEaL3KenGWvlj+aaOXf0aCyEPWhvaldR2lKj4KxZswaAvioYIdcLt8pQTEW95JJLAITnv5sGLdcjIPyu0RIpK3W55Rkzf5rrtU6TJqqrq83A3XXr1tm+l/nTcn9Q5+SDvxroeA3GYOxas8Y2t90+x4qk+6QrspxNlWVlZTH7USqyACQ4TW1Unz44duwYngRw//33A7DTjcYDS4UXU2MdkbD2CdUiMHBgaKJFKqhOYoBevXpZTN9m9Gt5wrsYNwKBQNzl33zYEQgEcOONNwIAzjvvvKh+a1pQjOCbhoIFEyZgbEGB+dk1qjuGoDEfPpKJuDZpmRvrVSoGnOnQdFqjzAUGrFKYjplGx4tLyNxafmaOKa8rtWQgrKl17twZQFhqpG+QbcoIcxUnTpyw5YfqGIikBCutFk5jpF5HV+HFzV9CKVgXkUl/jleGq7qC9CfJijuE9AFyPKkRSB+q9LlyPGX9a+nnohZBjT5S7qRan1fXT1npR/rC+TyOHTtmVk3zItFT07766qsBhOcvNWpqNx988IHj76UlSPfu6ea3TvjS+aYJaTFqSDh+/LhNq0pJScG4TSEXXmEfd7ehhFvktO495/W5bjF25Ze//CWAcDS3zArRVR/jPOP7MlUhIOIcicRXv2TJEhtbnNR4yW5GP7mTlgxY1+cBAwaY7j6dFUC+U9EgIyNDO7aSJa/O6kkHAgH06tULW7duDUvNRvmvSFiZn48mRhAMTSeRNpSIMDTQuaMT64+WUIOYkgJTWk9cLVYboixeX1paCoAv3WIlSM4bkct01upetqzOF8pu3brhyJEj2AJgYLduAIDz6rQHicG8efMavYWgsLDQtOYsnDixnntjRUQtWnlXEjl/vXAPjNs0Vr9ROxT7mD9/vuk2aUiYOnWqSFkycurLOzr/oFPQNK/TfP+TQJTWmqg0aZpGCUpTOqmZCw4jVUkeQvYnajeEzG9OTU01c9dUSJ5anUYuo7opHMhcVyeeX/V7QpW4JG+slPBlpRQnn21VVZX5e1l1ib+XkY/S58YxPPvsswEAmxeFmHCyFX/Ad999Z/pcpR+f90yOZkrGM24PBbCQLlSy98go87omh+jevTuAcH8lBzUle/aTmiY1PakZc7wls5h8fv2VjWftnDk2xiudr5TWGUZJn3XWWZbz5mkodqWGr4scZT8Y3c/+vvfee0hJScEPP/xgVh/zgleM6mBE166hFA1akCLlBVOIn1sesOSuF+fkuOZH6zZIneaos+INzw/N38ySZBHBAAAgAElEQVR9AO7SdjWEJG3QgL0al9R0Y/Gdt27d2jbf3HzSsuIUFSbmJjM+yK1OuWTqc/Nxe8XBgwe1EeR8J3/9618DCM/tMhHUKvvi9k4Scr/wwjB56NAh7TPUcQPEioYTXeHDhw8fjRiBQAA333xzTL+dvivPLHbT2DB58mQHLdoDlPNZmSoa0I3Df40JN910k2eBMC6fNLUVWRlI8gGPGjUKgJUbda5SY5W/oz/XsVh9eQDFr4eiIU87zdm3TM1X1r6VEbeM5ub1vv32W+xQ+GHpQ5H816pkJLVz6ZuUvkunCPGKigrzfEqR/Mx7khq45KHlZ/6O9xSq+BMa/wkTwhOYQWTSp3zixImwP6k8gAlbxhvXt1oEpJT5ww8/YO66dcA9tttLCu42mK3o29VJ+rI6FvstqznJGuU6q0tKSgqyZ80yr5O5D3gwK8fWv6WGC4iaxmeffYblTz6J08V5DxiMUWSuk1K35EondHEbMp+eGlOLFi0SEum8Z88ex+MRfcmdgpag0dnKVzSJs4ZvtJD3VFtbaz6fzH0AbndpoJM3DT5aqHz0arsyCltqW9E8I+a+A+6ZNFJzp+Ys55ebz59gf7k2emXO8wInXnK1T7Ti/OY3v/HUns4aQMjIdO4LP/74I3B55LYrKiq0FQGl1cspFkSXZeGEqDdpNbK2pKQEI0Z4j1CuCARMU9ikSZMcObBtG7QhbZW8tRhAfKHskZCpmIVYpi0ZuPrqq01T4q5du/Dww8nhP14wYQLGZoWiWlV6zb59g47R3qokXJEFYLz3a6m58HXlj+amce211yb9WqMUClg1D9wpayHP4fd33nkn4JBa1r9/fzPVpbHD6blH0m44jrMBrQZGU3lxTo7lGVjaUd0sagiJB79fQwwyK3x5Pu43ytRa7k2JMRkxYgSWRVn9L1mIZf2y8Kc7+Ny94iGjBDGryXnhoa8vDJg0CYjRJRh3CtaBAwdM7UTy7coKLxKUmKg16li5AKs0Iv1hUiuSFWn4MpKVi1oOryerrOgia9U+uEUMSilQsrYRlN5kXq9kwpLMQ9T8pKZNjTGSX6WystLG8S3B72U+sIxaJxdwXUHeF31rPE7JnnNBRo5K9iCdrz2RcMr95jujmy+yTrfur4zOl+8c86Td0K9fPwBh3yQZ8/jOPPfcc65tJAuJysGvD8haxFKrkn7N1NRULMvLCz2/PSJvWtnQWAOAG5Sb/5NzQBdJrWN7lP5a2W+1X7lPT7NkeVx5ZciaM2pVyAVw7rnnAgBOnWTUG3gxNNfatGkD7Fth08p1GQBcK8nuxtzo/HxvRDC6ynG0Qubm/v/tnXtwVfW1x78nkEQxKeq0p1jrTLHT0TvKrTXxjneGuRW08pRQXgLDS2lUjEDAEF4SgiCvSAxBCCQxL0KAklRERFQKyDjXkZf1jjOV6R1sqGM1F2s1hJKEcO4fe699fmft/Tvvk3MS1mfmzMlJ9tn7t3d+e/9+67fW+q6VwJkVjt9dO3++8b1vvrGtnnLdfvVZHUnMTrdqd5csXYq1Skf7nalO9Oqrr1pRfgB8ZtZL9i22pDJjSXfOqgOlm0SL9QsWGB1lL5BnBu+5T7vwpKH0h4Zzu/CUWZdbveZlhYVAhAn43cWBAwesILKZw4cjgrIKUWPcuHFBibL0dtR7ym9fd7KilFz9jSjSu1NCsMAS0XIWhECENUirg0z9gl0AgLk1z9lyRfmsPiUlBS++tQr9+/fHlEzv0rcalZeXl4fLl41ZomENddlm0mQB0yyVjktWAI8SJGuVvse/7zkNuJQoVPIXUEQrj4hW4drVdEz6rKvFTZDKE+mF02yMfIqUakEWNVk4NPvjebwErxJUVlgIAHCfdGO8eaxrO6/5LHHvKi5GW1sb+vSxW3S8jvOlS5e8ZQsz7DnvsaKjowMHDx70+V1aWpqtj/BcS54RQCsB3MdL0Pb8ezpGjhwJQO+75VBf5fmsukpwXHGLwy0idUXFXy58VpbhvKU8Wep3FO1PPn2qMNTc3AwAePPNNwOdomP7ONrBO0JRkUQZkKmf8fuIZ55Qe3meOdUqnrtmjaM1lp2djYqKiqAn/Lp8cl4Xnqsy0jt9j6xXAHj1wy345ptvoFuE4lk09JlXjuMZLLp4C3qn1bKBAwcCAMrLy71GB5zjFtTv82f3ygApxUsbl+DGG73Xhr/r6gNYK79hugSlCpYgCEKCU7p8OfC6MYlbpa/hETMofZZD9RdixShWE/1tU89BR3l5ecjlYAFgAdPeIL/51oICZQIUnGaEytN03QKlAfoh8kHanB1crZxjzRC4Wg3NkNSauk3btgFm8EN7ezvWrFlj+b90usQ8N5RXSeG5rbzyC72TFUp+YtWKVuFWkaqcw9vAozqDQQ3CI61lstx4lPG/WL1pXhtbp0zG84c7Ojqwu6TE8OtcvYraT2sAAJe3XcYNCKzFTefd3b5ogireqJSYqxGLZsywWSrcr8Vz4um60vWimACesUC0KLNgNYjs0KFDALxKXTqd4QkTJgDw3gu8r/L4B25N6P7P3JIiC/idd94xAtcY1Je5X45cS9SvaCWCfP/BVlEKlkCqhIEYbYrXOPWLRIDuV+pX3JKlfsYtaB6roK5GclJSUmzWp66f8OtNz05qJ9cdCDYegPqHunLIn//8HPnKK1/dcvKzX7161aYUxrUPAt0b/J7yV8cgNTXV2k5X45ueIfRsoc/B5FsHQ0SDtDrIlJWVIT8/sLpOIuExl490g3R30tDQgKlTp8a7GUGzrakJaOzeiG4di2fNirgcnD/KV6+2pfW1t7djHumkK9Htx48ftwZqITLUfjV27FgA3klDMEVv4oX6XNxY60K+mW4XLdQsGcCbzrdnz56o7F9nNavHLzeDtAIVSYqUvaWlPoP6Y2Yc0yGNNGioPMksdcAUFlq/PuLCGIASoR+B+yaqy91knfCZEs/l5RZyoAo3NCOh/fC8NLphaRZI2/PKQDRbDPeBTjVjAW/4f7A+SMrtO3nypHabzs5Oy+dMcH1xOjc6d+7PoZmszgrh1XB4bh/tj/uRAlUMiyd9+vSxPbx5H+MWNPUJpxroKnQdeFUnf7EGAwcO1FrSpLbHYwYIPsvXWdB8e/5OKzM66F6k/ydFxpI+MinUkYVEVk6g8qexYv/+/XE5bqS4TwOX1l2yNLL5/crvP24lcsW5lJQUHKiogFNBUKd6CDxrgOcG033Al3uJFocJ+PoFC5DGngvUn1SrlKv90Soh9SlaXeDZPWS9c8s4LS0NdUVFRsxRRwfGPm3IKh+urfXZTmdJU3t0tR62bdsGwPs/4pky1C5uedN+uUokz0IK15iJeJB2uVwYP348GhsbUTpzCwBgWVN4AgXdyWsHD2LIpYfMT8fj1g7KyT5y5Aj2LWkEAMzaEt2ZdyzobhnQRKQoL8+40XcBxfBmLVRXV6O6ujruKwyCIPR8omJJNzU1GT+YJv2/6o1ZGc0WuZWjsx50Wqjc8uU61/R9bjHT71Xrk/yXT2VlwWNaG6NGjQLgnfkEo3FMOXWBIAuaZprDhg1zPKeZM2eittZob81cF2ZsNvJW6doRNCvl1Y+4IpjOj0K/J58l17DmPjP6n5Ev8vPPPzca0o0R3YHo6urS6vFSn6C2kgVMfYgsaG7h0PXh9aK5ZUt9ZuEuo88XK0E9WVlZeOONNwB4fcAUrc/jK3RWgM4yIvj3eRYAZ8iQIT6fT5w44fNZV2FICA3Vimtqclmqi3Sf8ZrG3BfN33nksxNdXV22FRp+X/Bnolr/mXCynl8wVw779u0LXLliHYeeC041DOga0L1G9xB/ftM9yn3S6nkB3r5N53DAzBEnL30ghTGCngHqube4XOgqLfX5Pl/doGchV9TkmTA+z9golD6V6G5BEIQYQoOKbkk5LBS9iZqaGptITygsW7bMvl8Ywh3WgBkglbSnQlLVsYgG2jyjFMDmiPcTtUFaDZZ4ZVoJntz6hM1a4FYa9xHw2SOPyNXVXua/J98G9+9VHDjg1VA2LRwAVqF78pGQtaFTCQsFml3RvmkW6SR2UVdXh6ysLOzf70HdfEWiE0CeqQhFajt81kbXiEcUckua+2i5xUxw3+2XX34JwKs8FU8rWu1rgLFywqNnCe4XopUHbkE75RcDdm1jvkLB4yJU+cakpCQ8+OCDAAC32w3Aa3Hwvhmokk6gKG/ajlaRdGIqdD5OFpQQW5z6qc5C5v9v6l9O8TTqfnWxDjp/rL/4HMqZB+zWJz1jub9WfS5w3XLdc5orQPJnGO/ztArBV7/4qgG/Zwk6Hl9tonuHW9C6qlY6tUl/FeLCITaWdIYHVTlGw2kZMJ68UXAAAOA6EOeGBMnYsWOxf7/RIUl3++XMndZAHS/IZ55o/OEPfwDgjXKNJ8++Ngfb4pDHKiQm6oSyKqcaBW84y02GCk3ed5dEbqnx/VqypNcRr65YgeiVCjGJUgnUmC93X7p0SZv3xmcqfPZHszNe3Ypb2PydoBlTIEhhjHJYaVZKqTS8tm4okOVE74Fy595QLHzOtWvXrHPUKRhx3XJuceuU0HiOOc0GKR+6sbERcChOlki0trZa15nnifPIUp5vyiMzed4y74sEv77qLFqtF66L6g5UX5nQaXXT/qj9f//73x2/T9B5RNKnhTDJ8ODSLqMkI48Q1vlTeb+g/x8pCLqY9cezE3i8j86PqtKvXz+bdjwXCCGrk56x/DiA3lqnzBK6V8g65/EiXAObjxM6tUB+j+lqw/NVM66zrqtcposLoPasHU/FYNY6bhcqUR2knQbb8qcrML9uXjQPExTbzeU+N5P87ClQdaejR70WdT0MCdZ5tcFXHosqUQiCiBZOfW3766/j+WnT4tUkQRCEqBMTS9rHZ3jGZTrQgSe3GjmYgapk8RkStw65VUh+0++//x5VpvKQOwyhElI8I59HNKwNGkwaG0NbKiZ/OGlCHzrksYI6XtiyBavNgiS6nD16577qQFWyaHuKXt+8Zw/cHo+VH5soEd2E2tfcHg92mtdo0oaJAOxqdLxP6foawX34XIGJz87V1RvStx43bpylJ0/t4PvR6RTz4/CoXfpMFvTXX38NfwSTuSBEF3VCWVxcDMAbrBUoT15XlUrVh567Zg0AQ/iD4P1dV0/BaVk7OTk5oG+bV9XSxcQA3r7O9cC5BgTFidDqE1eu1MU2kXSo22OU4dX5oglVAbNglKHX3ZIJvGyWCKV26eJFdPEE1kpulJa5reNFvAdBEAQhJLxLotHj8Xndv2KZSNTX14e0fUFBAVoyvf79RCVmPmmf5UjTuqnK8eZgujK9Qh7ke+DRejq4rizNfN5+++2IRDaiEc3NCUfTW0WtEEYzNPdpF/6vyKhSxPMu6Z2rrvFcQ643q15DwCuZit3RnRXGAp++Zl6j3y92YfjyYZYlQP4uHgXLZ908k4BXuCG45c0r4KikpaVZ/xedZRLIN80taPoeVav661//CsAQxRF6BhcvXrSsR74yovMl83f+rOR/55Y3X410qvLm8XgsK5Yfh+sG8NoAaswGt9ZpW75KQJYz+dO5ehnPvCB0Fi7BV2AJrj1B0LOB2qlbheT75c+KaBPzwDGeLkMDtjEIGA+UlkxgtimUHw415sDiM0BbSw6JObBERIYHexZ5z2tm6YywdlO6d699UrMaNt9zog7OHF6/2MwWswRkBCGe+DwLMzwAnvK7fbCUFRbiRz/6ESbk5ERlfz2FSXON2BxLx7yhIY6tMSBpUSB6z82EETPhNYJDYXsU25Fo3HbbbQG3aW5utunjEtxCVim1/aZ30tnZafmKqR4yzZZ53jKvuKarrENwX5/TjZmammrbD/f5cYtHZ1GTFUIWNJ1PT9W2vp4pf9pQzJpXO9fKOuArJTpLmn5P9ztZh0MmTwYAnNi3D4DeMicr9aabbkJ1dbWl2e4+DfT97742BUKeD81jN5z6P/2Ozo1WDXSa2vweIbiOfXJyMmYvW2YNzjt37vQ5J53vmnja1PzmkCXN6yTw1UZdre1YVQbslkGaWzgc92kXdHHDTv4Cv0vaCRSBHE2mTp2KBnWmqJynFd92xs/MbXWAA0Q52CHe0DkMGTIER48etaQOZ40YEc9mCYIghES3W9K6AUCXH0piHkHRywYaANhtao2rP2vr7IY4QfG9Rr3jenGOHTsGl8tlqcgdXf22NfEbP3iwLW+aLBOKxuZxEjpdefqflO7dC7CSgampqVqLiFvQPL+bxw5QBgJF30e7vrMQW5ziJ17IdKF0+XIAdoU7QhfLoFbROlxbi+GmoE+gqmlcn9oiw4PHM42/vVNXZ8teIJ8zvZO1yVcAVLhGAfcJB6obzvOX+/Xr52Ooccucx29oxwJm1FD7eMwTVx+k9nP1NVL5i/bYI9HdgiAIccQdYJDqDqhym8qwGeHFusSSZcOWY/7gXEPVsqoKVVVVYe9LXaU9+NprEbWrpqYm4GQjXBLGJ61dEg9gHV4P1iAn1NWI3rKqEAkUue+TN//BB7btqFoV+ap1+aRcAUqN7Bw5ciRSU1OtmXVaWlpAPxtBxyEL+dNPPwXgX4lO6PlQzARfYeFKeKovGdBbsLyuvK4fB5L/5BY09Uvq72qtZx3cj87fufY2z7jQtZHnUXNlS90958Tly5dtFcl0Nb/peHRNfDJwYkDCDNIqMqiEh1w3QegZ8KyXJa+8AgDY8sIL8WoSACMIa7oakMWkluOOabRVVFQ4po+Fyt7S0oifm3v37rV+jsUzOCEHaUGIF++99x4AINusn6uzQLgvWc0P7erqsqqVAYYPjVsPPDqW77+lpQWAWNC9GdWXSkvebQsNbW+eW0yfyZrjUd1kJR6urTW+Zw6u1C/p+5QFwrW5VVWv+vp6m74C90VT28mip3ZwPQF13zyTgecdc60HbhEnJSWhsrISycnJSElJ0Q6IvA1c5W/jxo0AgLaCAuDiRVvNbm5Rc789XevcdaYgzdq1MTWQZJAWBBMS1Pyx362c2fL73wMApj/6aMQCNoIgCIQM0oJgYgXwuFy2fFAelc0rsRG8ChFgRIXqlMV43jRFin711VdROCOhp0H571Q1jaxKXuWKLGmyRskvyrMQurq68Jyp8w8A5eXlAGDLy+YrO5yZ+fmo37TJspx5VSyur62i0wvn36Fz0fmEdVWoqO08E0I97927d9vuWar5QPA60vwc6fdtbW2Yu2ZNtwX8SXS3IAhCHFGXSkmYI1Y89VT4KmfTnn8eTy5dGsXWBIaKZ4TKc889Z6RY0SvKqAN0rGOBxJIWBBPLSj4NTNpgWLRksXDLl2b9bW1tKN61C0+OGgUAOGhGdKv07dvX5ovWVbsi1SKqoCVcf9TX11uqWNz3TFYd+YbVqmvq9pTf75S33NHRYX2ftiMrkfdLpzoKN998s21FiOsF8J8Bu39dF9XNv8ctaL4drT5R5LlTlou6UsBXJ8gC5/rm3PKmc6R4ke5CBmlB4GR48Oo+40FQOGdOUF+hEqmCEA7qwGPUNdiBZyqc5SuDRV3u9ff7PUx8xwm3x2Op9o1T7onGrVsjaKGeseYkxe3xADU1oe+AWc+PTp8OAHgrgrxqAFi/fr31c3dl08ggLQh++Oc//wnAG8XKK97Q3/2RlJSkvaFpfzSb/+KLLyJrsNDzMdOM/nfxI7jnnnsAeC1ksoCp/5Elzau6zczPB/5zblDHmTx5sjVQ037I6lUjm2mJt0XpyxNyclC+erVjPXb6mSxcHr1N/nUecc6tfx4PQhYtnTv5ljs7O/HCiBV+T9nj8ViWO11T7o/nFj6tmm2YtBHAenQ3MkgLggOWz2nqVO02RXV13u0jKJEqCIKgIy6D9IABA7Bjxw5kZmbiJz/5CX72s59Z1XwAYOLEicjNzcV9992HkydPWrrLgqASqB+Fiyo00dDQYC2d6YrDu0/DrzKeuj+uokTWwZdffgkAaGpqirj9Qs9F7StHjhzB8OHDAQB33303AHulJvKXkuVLVmpQk0ZaEs7wWFYpj2R2ivpWg6ZazEwI3h7A29e5lc+3JUuajjkmO9sxMIur+9H3yQLPf3hxwFNW/dVc/5yOQ9eA2vm8mVeNDfGpDRGXQfratWs4fPgw1q1bhw8//ND293/84x8oKSnB3XffjaFDh8ahhUJPIFA/EoSeiOqfPmwWRc/NzY3dAc+4APjXrqao8ytXrlhCP4A5YBcWRqUZY8z9qgN0TU2NY/CbyoL/Wuj37y2ZwKHq6oBpZjq6M5LbiYCDdF5eHh588EFMmDDB+t3mzZvh8XjC7jgtLS0oKyvTarL+8Y9/BADMnj07rP0Licedd96JU6dO4ZFHHsHHH3+M2267DZ988gkmTpyI999/P6x9BupHkeBUrcjt0WwThL68LmKVqllFYwVA6L189tlnAIBf/OIXAOx+XF2982Ahvy7tl0d9c+1wlfT0dMtqVpX36Lu33norAOCHP/whAHseNFmuTiQlJdksaPrs73tO8HuQ50ProsbjTcBBur6+HoWFhejfvz++++479OnTB5MnT8aIESOwdetWTNX47C5cuIBf/vKXUW+w0DM5f/48Fi9ejPr6emRmZqK6uhq1tbV4//33E7ofRTJz3rRpU0wmEML1gTq5O3z4sLX0HQvmDzYMroqz5QG3rampwaxZs6zPzz+UBwAoOroxau2pra0NeO/N+Y9ng9rXIVbdKxhyXnwRQPytaCCIQfqrr77CiRMnMHHiRFRWVmL48OG4ePEizp49i7NnzyInJ6c72plwnDt3Lt5N6HFUVlbisccew0cffQSPx4MxY8YAAHJycq6bfkRLd+RP+/zzzwHENi9a+mrPxWnpe+jQobjrrrsAGDnLgD1yetPxl63BMxR01dkIsn6prOUTTzxh/W3R0Hysf2+d9jtksTpZ44B3QNy5cyeSkpJstazpc0pKCp55IHBqJMWQeKqc1f2oPTQRogyLtWvXAqtWWfuJd+GioBTHamtrMW3aNADAtGnTQlLFGTx4MFpbW9Ha2mqV3esNFBcXo7i4ON7N6HFUVFRg0KBB2LJli01S0x+9tR91B9JXBaHnElTg2P79+1FWVoZ77rkHo0ePRn5+PgCgrKzMGrw5zc3NuPfee/HBBx9YEYnC9c1NN92EkpISVFZWorCwEE1NTfj22297fD9y8jnroO1Im7u+vj5m7RJ6D2ofO3r0qBWZnb39dwCAH//YKAujWp1kSYaSHkjWJe2HcoTJiuW1lTmqBc7vCQrcIt8yvZP/m87J5fI1AsllRNsFe6+9WVlJjfJpm7o68cSSJQD0GRrxtqKBIC3p9vZ2NDY2oqGhASdPnsTf/vY3AMCcOXOQnp7u+Lr33nv97jM1NdVniYZ+BowlwdTUVEtOkX4WejabN2/G6dOnkZ2djbfeegvbt28HELt+JAi9CZfL5R00MoyAxopnKlHxTCXW/PalqBzjiX8PTSv7tdd8o8KXDVuOZcOWh3zccJbm/RGMb33xI0vgpjKhGb6+Z59rHWeCHvlqa2uRnZ3t44OIBJpFAV6fGV2U6dOno0aRgrty5Qpqamqidmyh+xkzZgyGDx+OQYMGAQAWLlyIP/3pT5g6daqRixwm/vpRd/Lss0YQy7Zt27Bp0yYkJSX5KI3RO+WjSjS3EG3Onz+PAQMGAEBEq04ej8emh81VungVLU5HR4fN4lX17tXP3CrnmgK8Frt6z+tob2+35Xrzalk9BReAoNYO7rjjDnz22WcYMGCArcSXIFzvzDH1jH/+858DsD9YaJCmh97Zs2cBAK87FOQQhED4DIAhVnmq/LgCN9xwA6b923T/GyrW5bp1RkAYH6Sz73euqlX45kr86le/Mpp35gwA4Ac/+AEA+yCdnp6OxY8sCekcdGz+oMRWElMdpKfk5nqX/zOc0yITjaAsaZfLhYULF2LPnj0yQAuCA2QNcOuBaxpTlSsZnIVIUAeUUAfsa9euobOzE9X/U4Xk5GT9YH3GZQ1kS5USlUVFRdrBmWhra7Mpi3HLmXzMNPBHypq3VwNotVxeasW62cuWAbD750ePHo23Erw4TsBBul+/fvj666/R3Nwc0zw9QRAEQRB8CXq5WxAEQUhcIlkCjzZPlz9lGXXHjh0DANx+++0AfLW6J5j6CNEoUNOSCby8aJFlmVOE+trxLHc7wzdvOtGRQVoQBKGX4fF44j5Qf3pmBwCg3NQ1uP3226Pme3Yif+8iAN7l8xezVts3yvD0mMGZkLwmQRAEIWZQNDX5pGMFWc4U99FbkEFaEAQhjjz00EMoKCjA/fffj2+//RYDBw60bTNv3jzk5ubC7XbjwoULyMrKwl/+8hftPm0CO3GwqpMzzB9OARXPVMb8eEteeUW/bN7DlrhVghIzEQRBEGJDW1sbqqqqsGjRIse/z549G7Nnz8aoUaOQlpaG0aNHB2Ut+ohyZHj81jyPJbG2oAl/A3QiiZOEigzSgiAIETBp0iRLV761tRVXrlyxgqWC4dSpU6ivr8f58+dtf3O5XFi5ciUWLFiAP//5zwAM0RIqcZrI9MM59IMUd4kUCRwTBEGIEunp6fjoo49QUlKCW265BUuW6AOlbrnlFp/PDz/8MCorK32Wu++44w5cuHAB8+fPR15eHq5evYq6ujqsWrUqaA1rle5cAndl+n6ePn066urqfH8Zqzb0wAAxHeKTFgRBiAIulwsNDQ04fvw4yssN7egNGzZEtM+f/vSnAIBHH30UgwYNws0334x3330XX3zxBSorQ/fzRiKCEtJxMp1/P2PGDOucbrzxRqxY4Qn/+H4LYvSOARqQ5W5BEISo8NJLLyE9PR3z5s2L2j4pMnrjxo347rvv0NzcjB07dmDkyJFRO4aQ2IglLQiCECGPP/44pkyZggceeMBKBVq6dCmWmXKUTgRTBOPcuXNob2/3sXrDWeZ2QmtVE1G2rnfuNEpQjhgxAgDgdrsxaxiVfhAAAAE2SURBVNYsUx70GZT9bnvgnbBqVdcD4pMWBEGIgPvuuw/vvvsufvOb3+CTTz4J+fsulwspKSkYMmQItm/fjrvuusvS1waMCoS33norpkyZgv79++PIkSMoKipCVVVVtE/FB9vAHWDQ1i1xc9RBGvBqeFPRDtL2Ju1vqhdBEe379u0L7kC9CI+85CUveckrvNfKlSs9nZ2dntbWVut16NChoL//61//2sM5duyY9ff09HTP7t27Pd9//73nwoULnhWGIzfmLxun4fcV7/9Db32JJS0IgiAICYoEjgmCIAhCgiKDtCAIgiAkKDJIC4IgCEKCIoO0IAiCICQoMkgLgiAIQoIig7QgCIIgJCgySAuCIAhCgiKDtCAIgiAkKDJIC4IgCEKCIoO0IAiCICQoMkgLgiAIQoLy/+1iA+oSJx3JAAAAAElFTkSuQmCC\n", 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#interate through the components and plot them\n", + "num_comp = 0\n", + "while num_comp < 3:\n", + " comp = model.masker_.inverse_transform(model.components_[num_comp,:].todense())\n", + " plotting.plot_stat_map(comp, threshold=0.2, vmax=1, colorbar=False, black_bg=True, title=\"Dwell time: {dt}\".format(dt=model.dwell_time_[num_comp]))\n", + " plotting.show()\n", + " num_comp += 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It is possible to generate a R2 map, which quantifies the quality of this embedding. It computes the fraction of the variance of the anatamical vbm file captured by the parcels. A score of 1 means perfect approximation. The score can be negative, in which case the parcellation approximation performs worst than the average of the signal. " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[MultiNiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(121, 145, 121, 1),\n", + "affine=array([[ -1.5, 0. , 0. , 90. ],\n", + " [ 0. , 1.5, 0. , -126. ],\n", + " [ 0. , 0. , 1.5, -72. ],\n", + " [ 0. , 0. , 0. ,\n", + "[MultiNiftiMasker.transform_single_imgs] Smoothing images\n", + "[MultiNiftiMasker.transform_single_imgs] Extracting region signals\n", + "[MultiNiftiMasker.transform_single_imgs] Cleaning extracted signals\n", + "[MultiNiftiMasker.transform_single_imgs] Loading data from Nifti1Image(\n", + "shape=(121, 145, 121, 1),\n", + "affine=array([[ -1.5, 0. , 0. , 90. ],\n", + " [ 0. , 1.5, 0. , -126. ],\n", + " [ 0. , 0. , 1.5, -72. ],\n", + " [ 0. , 0. , 0. ,\n", + "[MultiNiftiMasker.transform_single_imgs] Smoothing images\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/lussier/.local/lib/python3.6/site-packages/nilearn/signal.py:163: UserWarning: Detrending of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Detrending of 3D signal has been requested but '\n", + "/home/lussier/.local/lib/python3.6/site-packages/nilearn/signal.py:61: UserWarning: Standardization of 3D signal has been requested but would lead to zero values. Skipping.\n", + " warnings.warn('Standardization of 3D signal has been requested but '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[MultiNiftiMasker.transform_single_imgs] Extracting region signals\n", + "[MultiNiftiMasker.transform_single_imgs] Cleaning extracted signals\n" + ] + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "num_s = 0 # the subject number\n", + "img = model.load_img(anat[num_s])\n", + "\n", + "score = model.score(img)\n", + "plotting.view_img(score, vmax=1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can save the R2 maps as nifti files for further processing or use with Nistats/Nilearn. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.9" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}