From 2238dac49b27b0ada5126c703cc1a5a7f2f217d3 Mon Sep 17 00:00:00 2001
From: Ananth Ravi Kumar <ananthravikumar@berkeley.edu>
Date: Mon, 11 Apr 2016 09:56:08 -0700
Subject: [PATCH] Removed Files

---
 function3.py | 27 ---------------------------
 function4.py | 19 -------------------
 2 files changed, 46 deletions(-)
 delete mode 100644 function3.py
 delete mode 100644 function4.py

diff --git a/function3.py b/function3.py
deleted file mode 100644
index 0710598..0000000
--- a/function3.py
+++ /dev/null
@@ -1,27 +0,0 @@
-import numpy as np
-from function4 import getSkipMean
-def removePeriodicMean(signalMat, period, sliderWidth, NoDataCode):
-    """
-    :param signalMat: n - column matrix where variables represent timeseries
-    :param period: length of repeating pattern of data (i.e. seasons, years, etc).
-    :param sliderWidth: Number of periods to base the anomaly on.
-    :param NoDatCode: data value to be ignored
-    :return: matrix of values that accounts for periodic averages
-    """
-    nData, nSignals = np.shape(signalMat)   
-    newLength = nData - period * (sliderWidth - 1)
-    anomalyMat = np.nan * np.zeros(shape = (newLength, nSignals))
-    avg = np.nan * np.zeros(shape=(nData, nSignals))
-
-    for i in range(newLength):
-        for j in range(nSignals):
-            end = i + (sliderWidth*period) - 1
-            avg[i,j] = getSkipMean(signalMat[i:end:period, j], NoDataCode)
-
-        if avg[i,j] == NoDataCode or signalMat[i,j] == NoDataCode:
-            anomalyMat[i,j] = NoDataCode
-        else:
-            anomalyMat[i,j] = signalMat[i,j] - avg[i,j]
-
-    return anomalyMat
-
diff --git a/function4.py b/function4.py
deleted file mode 100644
index a41b527..0000000
--- a/function4.py
+++ /dev/null
@@ -1,19 +0,0 @@
-import numpy as np
-def getSkipMean(vector, NoDataCode):
-    """
-    :param vector: vector of values.
-    :param NoDataCode: indicates value to be ignored
-    :return: average of the values in the vector ignoring NoData values
-    """
-    N, _ = np.shape(vector)
-    sum = 0
-    nVals = 0
-    for i in range(N):
-        if vector[i] != NoDataCode:
-            sum+=vector[i]
-            nVals += 1
-    if nVals > 0:
-        avg = sum/nVals
-    else:
-        avg = NoDataCode
-    return avg
\ No newline at end of file