timestart = time.time()
F = fp.loadfile_frequency('frequency.txt')
files = glob.glob('*.txt')
files.sort(key=os.path.getmtime)
files.remove('frequency.txt')
bar = Bar('Processing', max=len(files) * 100)
iteration = 0
with open('data.csv', 'a') as data_file:
data_file.write(
'Timestamp,Delay1[m],Delay1_amplitude[dB],Delay2[m],Delay2_amplitude[dB]\n'
)
for filename in files:
#print 'File %i out of %i being processed...' % (iteration+1,len(files))
timestamps_temp, temp_sdata = fp.loadfile_multisweep(filename)
heights1 = []
heights2 = []
loop_timestart = time.time()
for n, i in enumerate(temp_sdata):
delay1, delay2, height1, height2 = td.transform(
F, i, verbose=0, overs=oversampling_factor)
heights1.append(height1)
heights2.append(height2)
#sys.stdout.write('.')
#sys.stdout.flush()
bar.next()
with open('data.csv', 'a') as data_file:
data_file.write(
'%f,%3.10f,%2.2f,%3.10f,%2.2f\n' %
(timestamps_temp[n], delay1, height1, delay2, height2))
import sys
import library.timedomain as td
import library.fileprocessing as fp
import matplotlib
if __name__ == '__main__':
if len(sys.argv) == 3:
filename1 = sys.argv[1]
filename2 = sys.argv[2]
else:
print "USAGE: python Filequality <Phasedata_file> <frequency file>"
sys.exit()
F = fp.loadfile_frequency(filename2)
timestamp, X = fp.loadfile_multisweep(filename1)
td.plotresponse(F, X[0])
A, B, C, D = td.transform(F, X[0], verbose=3)
print "Peak 1 level %0.2fdB, Peak 2 level %0.2f" % (C, D)
matplotlib.pyplot.show()
starttime = time.time()
files = glob.glob(directory + '/*.txt')
files.sort(key=os.path.getmtime)
files.remove(directory + '/frequency.txt')
#array storing delta length changes and time_stamps for files in directory
delta_length = np.empty(0)
delta_length2 = np.empty(0)
timestamps = np.empty(0)
pulse_peak1 = np.empty(0)
pulse_peak2 = np.empty(0)
#Determine peakindex with one run of transform code
temptime, S = fp.loadfile_multisweep(files[0])
temp1, temp2, temp3, temp4, peak1, peak2 = td.transform(F,
S[0],
verbose=0,
overs=oversampling)
#Enumerate through each files and solve for the reference delay and store into delta_length
#Only taking the first sweep in the file
for n, fname in enumerate(files[::file_skipping_factor]):
timest, S = fp.loadfile_multisweep(fname)
Xpeak, Xpeak2, pulse_height1, pulse_height2, temp1, temp2 = td.transform(
F,
S[0],
verbose=0,
overs=oversampling,
peak1_index=peak1,
files = glob.glob(directory+'/*.txt')
files.sort(key=os.path.getmtime)
files.remove(directory+'/frequency.txt')
#array storing delta length changes and time_stamps for files in directory
delta_length = np.empty(0)
delta_length2 = np.empty(0)
timestamps = np.empty(0)
pulse_peak1 = np.empty(0)
pulse_peak2 = np.empty(0)
#Enumerate through each files and solve for the reference delay and store into delta_length
#Only taking the first sweep in the file
for n,fname in enumerate(files[::file_skipping_factor]):
timest,S = fp.loadfile_multisweep(fname)
Xpeak,Xpeak2,pulse_height1,pulse_height2 = td.transform(F,S[0],verbose=0,overs=oversampling)
if n==0:
Xfirstpeak=Xpeak
Xfirstpeak2=Xpeak2
delta_length = np.append(delta_length,(Xpeak-Xfirstpeak)*1000)
delta_length2 = np.append(delta_length2,(Xpeak2-Xfirstpeak2)*1000)
timestamps = np.append(timestamps,timest[0])
print 'peak at %8.3f m and %8.3f m, Delta1 = %+6.10f ps, Delta2 = %+6.10f ps SWEEP FILE %4.0f/%4.0f' % (Xpeak,Xpeak2,(Xpeak-Xfirstpeak)/c*1e12,(Xpeak2-Xfirstpeak2)/c*1e12,n,len(files))
pulse_peak1 = np.append(pulse_peak1,pulse_height1)
pulse_peak2 = np.append(pulse_peak2,pulse_height2)
print 'Sampling rate = %3.1f seconds\n' % (timestamps[2] - timestamps[1])
plt.plot(timestamps,0.5*(delta_length/1000/c)*1e12,'b',timestamps,0.5*(delta_length2/c)*1e12,'r')
import sys, os, glob, time import numpy as np #import matplotlib.pyplot as plt import library.timedomain as td import library.fileprocessing as fp if __name__ == '__main__': if len(sys.argv) == 3: #directory = sys.argv[1] filename = sys.argv[1] filename2 = sys.argv[2] time_stamps,sdata = fp.loadfile_multisweep(filename) F = fp.loadfile_frequency(filename2) #F = f[::10] td.transform(F,sdata[0],verbose=1,overs=50) starttime = time.time() #files = glob.glob(directory+'/*.txt') #files.sort(key=os.path.getctime) #files.remove(directory+'/frequency.txt') #array storing delta length changes and time_stamps for files in directory #delta_length = np.empty(0) #timestamps = np.empty(0) #Enumerate through each files and solve for the reference delay and store into delta_length #Only taking the first sweep in the file #for n,fname in enumerate(files[::10]):