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()