Init

plot.py

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+import matplotlib.pyplot as plt
+import matplotlib
+import pandas as pd
+import numpy as np
+from scipy.signal import savgol_filter
+import scipy.signal as signal
+import sys
+df = pd.read_csv(sys.argv[1],delimiter="\t")
+target = sys.argv[2]
+time_size = 5
+window = time_size * 30 + 1
+
+def reject_outliers(data,indicies, m = 2.):
+    d = np.abs(data - np.median(data))
+    mdev = np.median(d)
+    s = d/mdev if mdev else 0.
+    return (data[s<m],indicies[s<m])
+
+xhat = savgol_filter(df[target].array.to_numpy(),window,3)
+indexs = np.arange(len(xhat))
+xhat,xs = reject_outliers(xhat,indexs,m=1.5)
+indicies = signal.argrelextrema(xhat, np.less,order=int(window/2))[0]
+
+plt.plot(df[target])
+plt.plot(xs,xhat,color="green")
+plt.plot(xs[indicies],xhat[indicies],marker="o", ls="", ms=3 )
+
+value1 = np.median(xhat)
+print(np.median(xhat))
+# value2 = np.percentile(xhat, 75)
+plt.plot([0,len(df[target])],[value1,value1],color="purple")
+#plt.plot([0,len(xhat)],[value2,value2])
+plt.show()