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#!/usr/bin/env python
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#-*- coding: utf-8 -*-
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"""Simple python library to compute transfert functions
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"""
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import time
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import sys
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import os
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import matplotlib.pyplot as plt
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import numpy as np
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from scipy import fftpack
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__author__ = "Alexis Jeandet"
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__copyright__ = "Copyright 2015, Laboratory of Plasma Physics"
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__credits__ = []
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__license__ = "GPLv2"
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__version__ = "1.0.0"
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__maintainer__ = "Alexis Jeandet"
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__email__ = "alexis.jeandet@member.fsf.org"
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__status__ = "Development"
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def __parseFFT(FFTi,FFTo,signalFreq,samplingFreq):
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index=signalFreq*len(FFTi)/samplingFreq
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powI=np.abs(FFTi[index-4:index+4])
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i=np.argmax(powI)+index-4
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mod=np.abs(FFTo[i])/np.abs(FFTi[i])
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arg=np.angle(FFTo[i])-np.angle(FFTi[i])
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if arg<-np.pi:
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arg = (np.pi*2)+arg
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if arg>np.pi:
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arg = (-np.pi*2)+arg
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return [signalFreq,mod,arg]
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def __step(device,freq,offset=0.0,maxAmp=5.0,lastAmp=1.0):
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device.analog_out_gen(freq, shape='Sine', channel=0, amplitude=lastAmp, offset=offset)
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samplesCount=8192
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if freq > 500000:
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FS=freq*samplesCount/500.0
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elif freq > 100000:
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FS=freq*samplesCount/50.0
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else:
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FS=freq*samplesCount/10.0
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res=device.analog_in_read(ch1=True,ch2=True,frequency=FS,samplesCount=samplesCount,ch1range=5.0,ch2range=5.0)
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FFTi=fftpack.fft(res[0][0])
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FFTo=fftpack.fft(res[0][1])
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return __parseFFT(FFTi,FFTo,freq,res[1])
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def computeTF(device,startFreq=1.0,stopFreq=100.0,offset=0.0,maxAmp=5.0,nstep=100):
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freq=np.zeros(nstep)
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f=[]
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mod=[]
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arg=[]
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for i in range(int(nstep)) :
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freq[i]=startFreq*np.power(10,((np.log10(stopFreq/startFreq))*i/(nstep-1)))
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lastAmp=0.1
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for i in range(len(freq)):
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step=__step(device,freq[i],offset=offset,maxAmp=maxAmp,lastAmp=lastAmp)
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f.append(step[0])
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mod.append(step[1])
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arg.append(step[2])
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return [f,mod,arg]
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if __name__ == '__main__':
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print("")
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