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SignalProcessing/linearity_adder.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+@author: imp
+"""
+
+file = './data.npz'
+
+import numpy as np
+import matplotlib.pyplot as plt
+import pwelch_solv as ps
+
+# load Data
+loaded = np.load(file)
+# sort Data
+sinuses = loaded['sinuses']
+noises = loaded['noises']
+signal = loaded['signal']
+weightedSignal = loaded['weightedSignal']
+
+
+T = 10                          # 10 seconds sampling time
+N_samples = len(sinuses[0])     # Nr of samples
+fs = N_samples/T                # sample frequency
+Ts = 1/fs                       # sample Period time
+
+t = np.linspace(0, T,N_samples) # create time vector
+
+# small snippet of data
+idx =  np.linspace(0, (0.1/Ts),int(0.1/Ts)+1,dtype=int)
+
+# Signal difference between ideal and weighted
+delta = signal - weightedSignal
+
+#prepare for pwelch solver
+x = delta - np.mean(delta)
+hwin = np.hanning(len(x))
+N_overl = len(hwin)/2;
+
+S = ps.func_pwelch(x, hwin, N_overl, fs)
+
+plt.figure()
+plt.semilogx(S['vfp'], S['LS'])
+plt.xlabel('f in Hz')
+plt.ylabel('LS in V')
+plt.title('LS of delta')
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