def demo3(myfile):
"""plot fastframe record on continuous time scale.
not very practical for high frame counts or large delays between triggers"""
volts, tstart, tscale, tfrac, tdatefrac, tdate = tekwfm.read_wfm(myfile)
# create time vector
samples, frames = volts.shape
tstop = samples * tscale + tstart
t = np.linspace(tstart, tstop, num=samples, endpoint=False)
# fractional trigger
times = np.zeros(volts.shape)
for frame, subsample in enumerate(tfrac):
toff = subsample * tscale
times[:,frame] = t + toff
# scale trigger times to first frame
ref_frame = 0
tdate -= tdate[ref_frame]
tdatefrac -= tdatefrac[ref_frame]
# the following operation reduces resolution
# this may not be suitable for high frame counts
# or acquisitions with large delays between triggers
tdateall = tdate + tdatefrac
times += tdateall # shift sample times
# plot
plt.figure(3)
plt.plot(times, volts)
plt.xlabel('time (s)')
plt.ylabel('volts (V)')
plt.title('all frames, continuous time')
plt.show()
def demo2(myfile):
"""plot frame 0 vs all frames on a two plot figure with locked time axes"""
volts, tstart, tscale, tfrac, tdatefrac, tdate = tekwfm.read_wfm(myfile)
# print trigger time stamps
print('local trigger times for: {}'.format(myfile))
for frame, utcseconds in enumerate(tdate):
print('frame: {:02d}, trigger: {}'.format(frame, time.ctime(utcseconds)))
# create time vector
samples, frames = volts.shape
tstop = samples * tscale + tstart
t = np.linspace(tstart, tstop, num=samples, endpoint=False)
# fractional trigger
times = np.zeros(volts.shape)
for frame, subsample in enumerate(tfrac):
toff = subsample * tscale
times[:,frame] = t + toff
# plot: fastframe
plt.figure(2)
ax1 = plt.subplot(2, 1, 1)
ax1.axvline(linewidth=1, color='r') # trigger annotation
ax1.plot(times[:,0], volts[:,0])
plt.ylabel('volts (V)')
plt.title('only frame 1')
ax2 = plt.subplot(2, 1, 2, sharex=ax1)
ax2.axvline(linewidth=1, color='r') # trigger annotation
ax2.plot(times, volts)
plt.xlabel('time (s)')
plt.ylabel('volts (V)')
plt.title('all frames')
plt.show()
def ReadFile(File, FileName, FilePeaks, Print_Introduction_bool, dleddt,
distance, height):
File = File.rstrip('\n')
print("\nReading File:\n" + ntpath.split(File)[1])
# Read File
volts, tstart, tscale, tfrac, tdatefrac, tdate = tekwfm.read_wfm(File)
# Create time vector
samples, frames = volts.shape
tstop = samples * tscale + tstart
t = np.linspace(tstart, tstop, num=samples, endpoint=False)
times = np.zeros(volts.shape)
for frame, subsample in enumerate(tfrac):
toff = subsample * tscale
times[:, frame] = t + toff
# Conversions
k_times = 1e9
k_volts = 1e3
times *= k_times # times in ns
volts *= k_volts # volts in mV
# Invert:
volts *= -1
# DLED
times_dled, volts_dled = DLED(times, volts, dleddt)
# Print Introduction
if Print_Introduction_bool:
FilePeaks.write("Peaks from file:\n")
FilePeaks.write(FileName + "\n")
FilePeaks.write("Sampling = " + str(1 / (tscale * k_times)) +
" GHz (Time Resolution = " +
str(tscale * k_times * 1e3) + " ps)\n")
FilePeaks.write(
"Peaks found with find_peaks(volts_dled[:,i], height=0)\n")
FilePeaks.write("NO trace smoothing\n")
FilePeaks.write("TimeWindow = [" + str(tstart * k_times) + " , " +
str(tstop * k_times) + "] ns, Dt = " +
str((tstop - tstart) * k_times) + " ns\n")
FilePeaks.write("DLED related: dleddt = " + str(dleddt) + " indices\n")
FilePeaks.write("END_INTRODUCTION\n")
# Find Peaks
for i in range(frame + 1):
# for i in range(3):
indices, _ = find_peaks(volts_dled[:, i],
height=height,
distance=distance)
for j in range(len(indices)):
FilePeaks.write(
str(times_dled[indices[j], i]) + "\t" +
str(volts_dled[indices[j], i]) + "\n")
FilePeaks.write("N\n")
def demo4(myfile):
"""plot bar chart of time between frames"""
volts, tstart, tscale, tfrac, tdatefrac, tdate = tekwfm.read_wfm(myfile)
samples, frames = volts.shape
x = np.arange(1, frames)
iseconds = np.diff(tdate)
fseconds = np.diff(tdatefrac)
# the following operation reduces resolution
# this may not be suitable for high frame counts
# or acquisitions with large delays between triggers
fseconds += iseconds
# bar plot
plt.figure(4)
plt.bar(x, fseconds)
#plt.xticks(x)
plt.xlabel('diff(frame)')
plt.ylabel('time (s)')
plt.title('time between frames')
plt.show()
def demo1(myfile):
"""print date of trigger and plot scaled wfm 'myfile'"""
volts, tstart, tscale, tfrac, tdatefrac, tdate = tekwfm.read_wfm(myfile)
# print trigger time stamp
print('local trigger time for: {}'.format(myfile))
print('trigger: {}'.format(time.ctime(tdate)))
# create time vector
toff = tfrac * tscale
samples, frames = volts.shape
tstop = samples * tscale + tstart
t = np.linspace(tstart+toff, tstop+toff, num=samples, endpoint=False)
# plot
plt.figure(1)
plt.axvline(linewidth=1, color='r') # trigger annotation
plt.plot(t, volts)
plt.xlabel('time (s)')
plt.ylabel('volts (V)')
plt.title('single waveform')
plt.show()
prerun_name = path + '/'
for i in range(len(file_split) - 2):
prerun_name += file_split[i] + '_'
return len(ch_set), len(run_set), prerun_name
max(run_num)
numbChannels, numbFiles, fname = openfiles(path)
if numbChannels != 4:
raise Exception("Problem with the number of channels")
for fnum in range(1, numbFiles + 1):
print("I'm reading: %s%i_CH1.wfm" % (fname, fnum))
volts_ch1, tstart_ch1, tscale_ch1, tfrac_ch1, tdatefrac_ch1, tdate_ch1 = tekwfm.read_wfm(
"%s%i_CH1.wfm" % (fname, fnum))
volts_ch2, tstart_ch2, tscale_ch2, tfrac_ch2, tdatefrac_ch2, tdate_ch2 = tekwfm.read_wfm(
"%s%i_CH2.wfm" % (fname, fnum))
volts_ch3, tstart_ch3, tscale_ch3, tfrac_ch3, tdatefrac_ch3, tdate_ch3 = tekwfm.read_wfm(
"%s%i_CH3.wfm" % (fname, fnum))
volts_ch4, tstart_ch4, tscale_ch4, tfrac_ch4, tdatefrac_ch4, tdate_ch4 = tekwfm.read_wfm(
"%s%i_CH4.wfm" % (fname, fnum))
if tfrac_ch1.all() != tfrac_ch2.all() and tfrac_ch1.all() != tfrac_ch3.all(
) and tfrac_ch1.all() != tfrac_ch4.all():
raise Exception("times don't match between channels!")
if tscale_ch1 != tscale_ch2 and tscale_ch1 != tscale_ch3 and tscale_ch1 != tscale_ch4:
raise Exception("time scales don't match between channels!")
for evt_local in range(len(tfrac_ch1)):
i_evt[0] = evt_local + len(tfrac_ch1) * (fnum - 1)