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plot_signals.py
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plot_signals.py
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'''
Author : Siddharth Nayak
email:[email protected]
'''
import matplotlib.pyplot as plt
import numpy as np
from sklearn.preprocessing import scale
from scipy.interpolate import interp1d
import sys
'''
This module plots the signals for the dynamic data
'''
ALL_AXES=True
filename = '/Users/siddharthnayak/Downloads/dynamic data/n_sample_0_65.txt'
sample_size_fit = 50
data_raw=[]
for i in open(filename):
data_raw.append(list(float(x) for x in i.split()))
data = np.array(data_raw).astype(float)
f, axarr = plt.subplots(3)
axarr[0].set_title("Raw Data")
if ALL_AXES:
axarr[0].plot(data)
else:
axarr[0].plot(data[:,1])
#print data
data_norm = scale(data)
axarr[1].set_title("Y Normalized Data")
if ALL_AXES:
axarr[1].plot(data_norm)
else:
axarr[1].plot(data_norm[:,1])
acx = data_norm[:,10]
acy = data_norm[:,11]
acz = data_norm[:,12]
gx = data_norm[:,13]
gy = data_norm[:,14]
gz = data_norm[:,15]
x = np.linspace(0, data.shape[0], data.shape[0])
f_acx = interp1d(x, acx)
f_acy = interp1d(x, acy)
f_acz = interp1d(x, acz)
f_gx = interp1d(x, gx)
f_gy = interp1d(x, gy)
f_gz = interp1d(x, gz)
xnew = np.linspace(0, data.shape[0], sample_size_fit)
acx_stretch = f_acx(xnew)
acy_stretch = f_acy(xnew)
acz_stretch = f_acz(xnew)
gx_stretch = f_gx(xnew)
gy_stretch = f_gy(xnew)
gz_stretch = f_gz(xnew)
axarr[2].set_title("X Normalized to 50 samples")
axarr[2].plot(acx_stretch)
if ALL_AXES:
axarr[2].plot(acy_stretch)
axarr[2].plot(acz_stretch)
'''
axarr[2].plot(gx_stretch)
axarr[2].plot(gy_stretch)
axarr[2].plot(gz_stretch)'''
plt.show()
# print data
# print data_norm