def determine(datadate, numhead):
Nloops = len(
os.listdir('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_50centered'))
writename10 = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_histograms/10_jitter.txt'
writename20 = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_histograms/20_jitter.txt'
writename80 = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_histograms/80_jitter.txt'
writename90 = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_histograms/90_jitter.txt'
if not os.path.exists('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_histograms/histogram_images'):
os.makedirs('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_histograms/histogram_images')
#peak amplitude acquisition
for i in range(Nloops):
print(i)
filename = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_50centered/D1--waveforms--%05d.txt' % i
(t, y, _) = rw(filename, numhead)
y_norm = y / min(y)
check10 = y_norm <= .1 #determining where 10% and 90% are located
check90 = y_norm >= .9
index10 = np.asarray([k for k, x in enumerate(check10) if x])
index90 = np.asarray([k for k, x in enumerate(check90) if x])
index_90 = int(index90[0] + 0.5) #turning 90% rising point into int
index10_removed = index10[np.where(
index10 < index_90)] #removing all 10% points after 90% index
index_10 = int(index10_removed[len(index10_removed) - 1] +
0.5) #turning last 10% index before 90% index into int
check20 = y_norm <= .2 #determining where 20% and 80% rising are located
check80 = y_norm >= .8
index20 = np.asarray([k for k, x in enumerate(check20) if x])
index80 = np.asarray([k for k, x in enumerate(check80) if x])
index_80 = int(index80[0] + 0.5) #turning 80% rising point into int
index20_removed = index20[np.where(
index20 < index_80)] #removing all 20% points after 80% index
index_20 = int(index20_removed[len(index20_removed) - 1] +
0.5) #turning last 20% index before 90% index into int
#gathering times at rising 10,20,80,90% points
t10 = str(t[index_10])
t20 = str(t[index_20])
t80 = str(t[index_80])
t90 = str(t[index_90])
#writing values to respective histogram files
wh(t10, writename10)
wh(t20, writename20)
wh(t80, writename80)
wh(t90, writename90)
#create histograms from saved files
(histo_mean10, histo_std10) = gh(writename10)
(histo_mean20, histo_std20) = gh(writename20)
(histo_mean80, histo_std80) = gh(writename80)
(histo_mean90, histo_std90) = gh(writename90)
rh(writename10, "Seconds", "Histogram of 10% Jitter", "10_Jitter",
datadate, histo_mean10, histo_std10)
rh(writename20, "Seconds", "Histogram of 20% Jitter", "20_Jitter",
datadate, histo_mean20, histo_std20)
rh(writename80, "Seconds", "Histogram of 80% Jitter", "80_Jitter",
datadate, histo_mean80, histo_std80)
rh(writename90, "Seconds", "Histogram of 90% Jitter", "90_Jitter",
datadate, histo_mean90, histo_std90)
def determine(datadate, numhead):
Nloops = len(
os.listdir(
'G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_50centered')) #determining size of directory
writename = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_histograms/20_80_rise_time.txt' #setting file name to write to
if not os.path.exists('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_histograms/histogram_images'
): #creating write directory if nonexistant
os.makedirs('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_histograms/histogram_images')
#determine rise times
for i in range(Nloops):
print(i)
filename = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_50centered/D1--waveforms--%05d.txt' % i #setting file name to read from
(t, y, _) = rw(filename, numhead) #taking in waveform values
y_norm = y / min(y) #normalizing voltage values
check20 = y_norm <= .2 #determining where 20% and 80% rising are located
check80 = y_norm >= .8
index20 = np.asarray([k for k, x in enumerate(check20) if x])
index80 = np.asarray([k for k, x in enumerate(check80) if x])
index_80 = int(index80[0] + 0.5)
index20_removed = index20[np.where(
index20 < index_80)] #removing all values after 80% rise index
index_20 = int(index20_removed[len(index20_removed) - 1] +
0.5) #turning last 20% rise index into int
rise_time = str(t[index_80] -
t[index_20]) #rise time is time at 80% - time at 10%
wh(rise_time, writename) #writing value to histogram txt file
#create histogram from saved file
(histo_mean, histo_std) = gh(writename)
rh(writename, "Seconds", "Histogram of 20-80 Rise Times", "20_80_Rise",
datadate, histo_mean, histo_std)
def determine(datadate, numhead):
Nloops = len(
os.listdir('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_50centered'))
writename = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_histograms/charge.txt'
if not os.path.exists('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_histograms/histogram_images'):
os.makedirs('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_histograms/histogram_images')
#determining charge
for i in range(Nloops):
print(i)
area = 0
filename = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_50centered/D1--waveforms--%05d.txt' % i
(t, y, _) = rw(filename, numhead)
#determining area under curve
for i in range(len(y) - 1):
area += ((t[i + 1] - t[i]) * y[i])
charge = str(
-1 * area / 50
) #area under curve/resistance gives charge, made positive for graphical reasons
wh(charge, writename)
#create histogram from saved file
(histo_mean, histo_std) = gh(writename)
rh(writename, "Coulombs", "Histogram of Charges", "Charge", datadate,
histo_mean, histo_std)
def determine(datadate, numhead):
Nloops = len(
os.listdir(
'G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_50centered')) #determining size of directory
writename = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_histograms/10_90_fall_time.txt' #setting file name to write to
if not os.path.exists('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_histograms/histogram_images'
): #creating write directory if nonexistant
os.makedirs('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_histograms/histogram_images')
#determine fall times
for i in range(Nloops):
print(i)
filename = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_50centered/D1--waveforms--%05d.txt' % i #setting file name to read from
(t, y, _) = rw(filename, numhead) #taking in waveform values
y_norm = y / min(y) #normalizing voltage values
check10 = y_norm <= .1 #determining where 10% and 90% falling are located
check90 = y_norm >= .9
index10 = np.asarray([k for k, x in enumerate(check10) if x])
index90 = np.asarray([k for k, x in enumerate(check90) if x])
index_90 = int(index90[len(index90) - 1] + 0.5)
index10_removed = index10[np.where(
index10 > index_90)] #removing all values before 90% fall index
index_10 = int(index10_removed[0] +
0.5) #turning first 10% fall index into int
fall_time = str(t[index_10] -
t[index_90]) #fall time is time at 10% - time at 90%
wh(fall_time, writename) #writing value to histogram txt file
#create histogram from saved file
(histo_mean, histo_std) = gh(writename)
rh(writename, "Seconds", "Histogram of 10-90 Fall Times", "10_90_Fall",
datadate, histo_mean, histo_std)
def determine(datadate,numhead,directory):
Nloops = len(os.listdir('G:/data/watchman/'+datadate+'_watchman_spe/d2/d2_'+directory))
if directory == 'raw':
Nloops -= 1
writename = 'G:/data/watchman/'+datadate+'_watchman_spe/d2/d2_histograms/10_90_rise_time_'+directory+'.txt'
if not os.path.exists('G:/data/watchman/'+datadate+'_watchman_spe/d2/d2_histograms/histogram_images/'):
os.makedirs('G:/data/watchman/'+datadate+'_watchman_spe/d2/d2_histograms/histogram_images/')
#determine rise times
for i in range(Nloops):
print(i)
filename = 'G:/data/watchman/'+datadate+'_watchman_spe/d2/d2_'+directory+'/D2--waveforms--%05d.txt' % i
(t,y,_) = rw(filename,numhead)
y_norm = y/min(y)
check10 = y_norm <= .1 #determining where 10% and 90% are located
check90 = y_norm >= .9
index10 = np.asarray([k for k, x in enumerate(check10) if x])
index90 = np.asarray([k for k, x in enumerate(check90) if x])
index_90 = int(index90[0] + 0.5)
index10_removed = index10[np.where(index10 < index_90)] #removing all values after 90% rise index
index_10 = int(index10_removed[len(index10_removed)-1] + 0.5) #turning last 10% rise index into int
rise_time = str(t[index_90] - t[index_10]) #rise time is time at 90% - time at 10%
wh(rise_time,writename) #writing value to histogram txt file
#create histogram from saved file
(histo_mean,histo_std) = gh(writename)
rh(writename,"Seconds","Histogram of 10-90 Rise Times","10_90_Rise_"+directory,datadate,histo_mean,histo_std)
def determine(datadate,numhead):
Nloops = len(os.listdir('G:/data/watchman/'+datadate+'_watchman_spe/d2/d2_raw')) - 1
writename = 'G:/data/watchman/'+datadate+'_watchman_spe/d2/d2_histograms/raw_peak_amplitude.txt'
if not os.path.exists('G:/data/watchman/'+datadate+'_watchman_spe/d2/d2_histograms/histogram_images'):
os.makedirs('G:/data/watchman/'+datadate+'_watchman_spe/d2/d2_histograms/histogram_images')
#peak amplitude acquisition
for i in range(Nloops):
print(i)
filename = 'G:/data/watchman/'+datadate+'_watchman_spe/d2/d2_raw/D2--waveforms--%05d.txt' % i
(_,y,_) = rw(filename,numhead)
index_min = np.where(y == min(y)) #determining index of peak
value = str((-1*y[index_min])[0]) #flipping peak to positive
wh(value,writename) #writing value to histogram txt file
#create histogram from saved file
(histo_mean,histo_std) = gh(writename)
rh(writename,"Volts","Histogram of Peak Amplitudes","Peak_Amplitude",datadate,histo_mean,histo_std)
def determine(datadate, numhead):
Nloops = len(
os.listdir('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_50centered'))
writename = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_histograms/FWHM.txt'
if not os.path.exists('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_histograms/histogram_images'):
os.makedirs('G:/data/watchman/' + datadate +
'_watchman_spe/d1/d1_histograms/histogram_images')
#determine rise times
for i in range(Nloops):
print(i)
filename = 'G:/data/watchman/' + datadate + '_watchman_spe/d1/d1_50centered/D1--waveforms--%05d.txt' % i
(t, y, _) = rw(filename, numhead)
y_norm = y / min(y)
check = y_norm <= .5 #determining where values under 50% are
check_peak = y_norm == 1 #determining where peak is
index_peak = np.asarray([k for k, x in enumerate(check_peak) if x])
peak_index = int(index_peak[0] + 0.5) #turning peak index into int
index = np.asarray([k for k, x in enumerate(check) if x])
index_low = index[np.where(
index < peak_index)] #removing all values after peak
index_high = index[np.where(
index > peak_index)] #removing all values before peak
index_first = int(index_low[len(index_low) - 1] +
0.5) #turning last 50% point before peak into int
index_last = int(index_high[0] +
0.5) #turning first 50% point after peak into int
FWHM = str(
t[index_last] -
t[index_first]) #FWHM is time at falling 50% - time at rising 50%
wh(FWHM, writename) #writing to histogram txt file
#create histogram from saved file
(histo_mean, histo_std) = gh(writename)
rh(writename, "Seconds", "Histogram of Full Width Half Maximums", "FWHM",
datadate, histo_mean, histo_std)