def create_correlation_table(plot_variable1, plot_variable2, values1, values2, seconds):
if len(values2) == len(values1):
print ''
print 'Creating new table...'
print ''
number_of_plates1 = 0
number_of_plates2 = 0
if plot_variable1[0][0] in ('pulseheights', 'integrals'):
number_of_plates1 = get_number_of_plates(values1[0])
if plot_variable2[0][0] in ('pulseheights', 'integrals'):
number_of_plates2 = get_number_of_plates(values2[0])
# declare a class
class Variable1(IsDescription):
if number_of_plates1 in range(1, 5) and number_of_plates2 in range(1, 5):
variable1 = Float64Col(shape=(number_of_plates1,))
variable2 = Float64Col(shape=[number_of_plates2,])
elif number_of_plates1 in range(1, 5) and number_of_plates2 not in range(1, 5):
variable1 = Float64Col(shape=(number_of_plates1,))
variable2 = Float64Col()
elif number_of_plates1 not in range(1, 5) and number_of_plates2 in range(1, 5):
variable1 = Float64Col()
variable2 = Float64Col(shape=(number_of_plates2,))
elif number_of_plates1 not in range(1, 5) and number_of_plates2 not in range(1, 5):
variable1 = Float64Col()
variable2 = Float64Col()
else:
print 'weird'
# create filename for correlation table from data filenames
intermediate1 = plot_variable1[0][1].replace('data_s%s_' % plot_variable1[0][2], '')
intermediate2 = intermediate1.partition('_')
start_date = intermediate2[0]
intermediate3 = intermediate2[2][1:]
end_date = intermediate3.replace('.h5', '')
filename = (('interpolated_table_%s_station%s_with_%s_station%s_%s_%s'
'_timeinterval_%d.h5') %
(plot_variable1[0][0], plot_variable1[0][2],
plot_variable2[0][0], plot_variable2[0][2],
start_date, end_date, seconds))
# make new table
with openFile(filename, 'w') as data_cor:
group_variable1 = data_cor.createGroup("/", 'correlation')
table_variable1 = data_cor.createTable(group_variable1, 'table', Variable1)
# Insert a new particle record
particle = table_variable1.row
for i in range(len(values1)):
particle['variable1'] = values1[i]
particle['variable2'] = values2[i]
particle.append()
table_variable1.flush()
print 'Done.'
return filename
else:
print 'Your variable lists are not of the same length. Interpolation is necessary.'
def plot_data(plot_variable):
MPV = False
# These variables are stored per plate, so we have 2 or 4 values
# for one event instead of just 1.
if plot_variable[0][0] in ('pulseheights', 'integrals',
'baseline', 'std_dev', "n_peaks"):
if plot_variable[0][0] in ('pulseheights', 'integrals'):
MPV = query_yes_no('Do you want to PLOT the MPV (Most probable value) of the %s?' % plot_variable[0][0])
if MPV == True:
print ''
interval = question.digit("Select the time interval (in seconds) over which the MPV values must be calculated ( e.g. for a day enter '86400' ): ")
seconds = int(interval)
variable_parts, time, number_of_plates = split_data_file_in_parts(plot_variable, seconds)
#e.g. variable_parts = [[p1, p2...pn], [p1, p2...pn], ....]
# time [t1, t2...tn] times are timestamps in the middle of every time interval
if plot_variable[0][0] == 'pulseheights':
MPV_list, number_of_plates, times = find_MPV_pulseheights(variable_parts, plot_variable, time, number_of_plates)
#times = array(time) necessary?
times_dates = [datetime.fromtimestamp(x) for x in times]
plot_variable1 = [('pulseheights', plot_variable[0][1], plot_variable[0][2], 'events')]
plot_variable2 = [('time', plot_variable[0][1], plot_variable[0][2], 'events')]
values1 = MPV_list
values2 = time
filename = create_correlation_table(plot_variable1, plot_variable2, values1, values2, seconds)
elif plot_variable[0][0] == 'integrals':
MPV_list, number_of_plates = find_MPV_integrals(variable_parts, plot_variable)
values = array(MPV_list)
for i in range(number_of_plates):
y = values[:, i]
plt.plot(times_dates, y)
plt.xlabel('time')
plt.ylabel('%s (%s)' % (plot_variable[0][0], units[plot_variable[0][0]]))
# create filename for correlation table from data filenames
intermediate1 = plot_variable[0][1].replace('data_s%s_' % str(plot_variable[0][2]), '')
intermediate2 = intermediate1.partition('_')
start_date = intermediate2[0]
intermediate1b = plot_variable[-1][1].replace('data_s%s_' % str(plot_variable[-1][2]), '')
intermediate2b = intermediate1b.partition('_')
intermediate3b = intermediate2b[2][1:]
end_date = intermediate3b.replace('.h5', '')
fname = ('MPV_%s_s%s_%s-%s_timeinterval_%d_seconds.png' %
(plot_variable[0][0], plot_variable[0][2], start_date, end_date, seconds))
plt.savefig(fname)
plt.show()
returntype = 'MPV'
else:
time_list = []
plate1 = []
plate2 = []
plate3 = []
plate4 = []
number_of_plates = 0
for i in range(len(plot_variable)):
with tables.openFile(plot_variable[i][1], 'r') as data:
tree_time = "data.root.s%s.%s.col('timestamp')" % (plot_variable[i][2], plot_variable[i][3])
time = eval(tree_time)
tree_variable = "data.root.s%s.%s.col('%s')" % (plot_variable[i][2], plot_variable[i][3], plot_variable[i][0])
variable = eval(tree_variable)
time_list.extend(time)
number_of_plates = get_number_of_plates(variable[0])
plate1.extend(list(variable[:, 0]))
plate2.extend(list(variable[:, 1]))
if number_of_plates == 4:
plate3.extend(list(variable[:, 2]))
plate4.extend(list(variable[:, 3]))
dat_sorted1 = array(sorted(zip(time_list, plate1)))
dat_sorted2 = array(sorted(zip(time_list, plate2)))
if number_of_plates == 4:
dat_sorted3 = array(sorted(zip(time_list, plate3)))
dat_sorted4 = array(sorted(zip(time_list, plate4)))
print ''
print 'Your file(s) contain(s) data from ' + str(datetime.fromtimestamp(dat_sorted1[0][0])) + ' until ' + str(datetime.fromtimestamp(dat_sorted1[-1][0]))
print ''
whole = query_yes_no('Do you want to PLOT this whole time interval')
if whole == True:
times = dat_sorted1[:, 0]
x = [datetime.fromtimestamp(i) for i in times]
y = dat_sorted1[:, 1]
plt.plot(x, y)
y = dat_sorted2[:, 1]
plt.plot(x, y)
if number_of_plates == 4:
y = dat_sorted3[:, 1]
plt.plot(x, y)
y = dat_sorted4[:, 1]
plt.plot(x, y)
values = array(zip(dat_sorted1[:, 1], dat_sorted2[:, 1],
dat_sorted3[:, 1], dat_sorted4[:, 1]))
else:
values = array(zip(dat_sorted1[:, 1], dat_sorted2[:, 1]))
plt.ylabel('%s (%s)' % (plot_variable[0][0], units[plot_variable[0][0]]))
plt.grid(True)
plt.show()
returntype = 'whole'
elif whole == False:
x_lim_low = 2
x_lim_up = 2
while True:
start = datetime.fromtimestamp(dat_sorted1[0][0])
print ''
print 'Start time: ' + str(start)
print 'Seconds in interval: ' + str(dat_sorted1[-1][0] - dat_sorted1[0][0])
print ''
print 'First you are going to enter the LOWER time limit.'
while True:
x_lim_low = question.digit('Enter the number of seconds after the start time shown above ( e.g. input "3600" means x_begin = timestamp + 3600 s ): ')
x_lim_low = int(x_lim_low)
if dat_sorted1[0][0] + x_lim_low <= dat_sorted1[-1][0]:
break
else:
print "Oops! Your lower time limit lies beyond your data set. Try again."
print ''
print 'Now you are going to enter the UPPER time limit.'
while True:
x_lim_up = question.digit('Enter the number of seconds after the start time shown above ( e.g. input "86400" means x_end = timestamp + 86400 s ): ')
x_lim_up = int(x_lim_up)
if x_lim_up > x_lim_low and dat_sorted1[0][0] + x_lim_up <= dat_sorted1[-1][0]:
break
elif x_lim_up <= x_lim_low:
print "Oops! The upper time limit less than or equal to the lower time limit. Try again."
elif dat_sorted1[0][0] + x_lim_up > dat_sorted1[-1][0]:
print "Oops! Your upper time limit lies beyond your data set. Try again."
plot_list1 = array([[t, v] for t, v in dat_sorted1 if dat_sorted1[0][0] + x_lim_low < t < dat_sorted1[0][0] + x_lim_up])
plot_list2 = array([[t, v] for t, v in dat_sorted2 if dat_sorted2[0][0] + x_lim_low < t < dat_sorted2[0][0] + x_lim_up])
if number_of_plates == 4:
plot_list3 = array([[t, v] for t, v in dat_sorted3 if dat_sorted3[0][0] + x_lim_low < t < dat_sorted3[0][0] + x_lim_up])
plot_list4 = array([[t, v] for t, v in dat_sorted4 if dat_sorted4[0][0] + x_lim_low < t < dat_sorted4[0][0] + x_lim_up])
values = array(zip(plot_list1[:, 1], plot_list2[:, 1],
plot_list3[:, 1], plot_list4[:, 1]))
else:
values = array(zip(plot_list1[:, 1], plot_list2[:, 1]))
times = plot_list1[:, 0]
x = [datetime.fromtimestamp(i) for i in times]
plt.plot(x, plot_list1[:, 1])
plt.plot(x, plot_list2[:, 1])
if number_of_plates == 4:
plt.plot(x, plot_list3[:, 1])
plt.plot(x, plot_list4[:, 1])
plt.ylabel('%s (%s)' % (plot_variable[0][0], units[plot_variable[0][0]]))
returntype = 'part'
plt.show()
again = query_yes_no('Do you want to plot again with different values for the UPPER and LOWER time?')
if again != True:
break
else:
variable_list = []
time_list = []
for i in range(len(plot_variable)):
with tables.openFile(plot_variable[i][1], 'r') as data:
tree_time = "data.root.s%s.%s.col('timestamp')" % (plot_variable[i][2], plot_variable[i][3])
time = eval(tree_time)
tree_variable = "data.root.s%s.%s.col('%s')" % (plot_variable[i][2], plot_variable[i][3], plot_variable[i][0])
variable = eval(tree_variable)
time_list.extend(time)
variable_list.extend(variable)
dat_sorted = array(sorted(zip(time_list, variable_list)))
print ''
print 'Your file(s) contain(s) data from %s until %s' % (str(datetime.fromtimestamp(dat_sorted[0][0])), str(datetime.fromtimestamp(dat_sorted[-1][0])))
print ''
whole = query_yes_no('Do you want to PLOT this whole time interval?')
if whole == True:
times = dat_sorted[:, 0]
x = [datetime.fromtimestamp(i) for i in times]
dat_sorted = array(dat_sorted)
values = dat_sorted[:, 1]
plt.plot(x, values)
plt.ylabel('%s (%s)' % (plot_variable[0][0], units[plot_variable[0][0]]))
plt.grid(True)
plt.show()
returntype = 'whole'
elif whole == False:
x_lim_low = 2
x_lim_up = 2
plot_list = []
while True:
start = datetime.fromtimestamp(dat_sorted[0][0])
print ''
print 'Start time = ' + str(start)
print 'Seconds in interval: ' + str(dat_sorted[-1][0] - dat_sorted[0][0])
print ''
print 'First you are going to enter the LOWER time limit.'
while True:
x_lim_low = question.digit('Enter the number of seconds after the start time shown above ( e.g. input "3600" means x_begin = timestamp + 3600 s ): ')
x_lim_low = int(x_lim_low)
if dat_sorted[0][0] + x_lim_low <= dat_sorted[-1][0]:
break
else:
print "Oops! Your lower time limit lies beyond your data set. Try again."
print ''
print 'Now you are going to enter the UPPER time limit.'
while True:
x_lim_up = question.digit('Enter the number of seconds after the start time shown above ( e.g. input "86400" means x_end = timestamp + 86400 s ): ')
x_lim_up = int(x_lim_up)
if x_lim_up > x_lim_low and dat_sorted[0][0] + x_lim_up <= dat_sorted[-1][0]:
break
elif x_lim_up <= x_lim_low:
print "Oops! The upper time limit less than or equal to the lower time limit. Try again."
elif dat_sorted[0][0] + x_lim_up > dat_sorted[-1][0]:
print "Oops! Your upper time limit lies beyond your data set. Try again."
plot_list = []
# e.g. dat_sorted = (timestamp, variable)
for t, v in dat_sorted:
if t > dat_sorted[0][0] + x_lim_low and t < dat_sorted[0][0] + x_lim_up:
plot_list.append([t, v])
plot_list = array(plot_list)
times = plot_list[:, 0]
values = plot_list[:, 1]
x = [datetime.fromtimestamp(i) for i in times]
plt.plot(x, values)
plt.ylabel('%s (%s)' % (plot_variable[0][0], units[plot_variable[0][0]]))
plt.grid(True)
plt.show()
returntype = 'part'
again = query_yes_no('Do you want to plot again with a different time limits?')
if again != True:
break
return values, times, returntype
def find_MPV_integrals(pulseintegral_list, plot_variable):
print ''
show_plot = query_yes_no('Do you want to see a plot of every individual fit for every plate?')
MPV_list = []
for pi in pulseintegral_list:
print 'Time interval %d of %d.' % (pulseintegral_list.index(pi) + 1, len(pulseintegral_list))
print ''
MPV_MIPs = []
number_of_plates = get_number_of_plates(pi[0])
for i in range(number_of_plates):
print ''
print 'plate %d ' % i + 1
p_plate_total = array(pi[:, i])
hist = plt.hist(p_plate_total, 750)
binsize = hist[0]
value = hist[1]
del hist
plt.clf()
binsize_sort = sorted(binsize)
photon_bin = 0
for g in range(len(binsize)):
if binsize[g] == binsize_sort[-1]:
photon_bin = g
break
for h in range(len(binsize)):
if h > photon_bin and binsize[h + 1] > binsize[h]:
lowest_bin = h
lowest_p = value[h]
break
binsize = binsize[lowest_bin:]
value = value[lowest_bin:]
binsize_sort = sorted(binsize)
MPV_bin = binsize_sort[-1]
for j in range(len(binsize)):
if binsize[j] == MPV_bin:
MPV_value = (value[j] - value[j - 1]) / 2 + value[j]
#print 'MPV = ', MPV_value
extra = [1500, 1250, 1000, 750, 500]
list = []
success = False
for k in extra:
pi_red = [pi for pi in p_plate_total if (MPV_value - k < pi < MPV_value + k)]
plo = plt.hist(pi_red, 500)
del pi_red
values = plo[0]
#print values
bins = plo[1]
del plo
bin_centers = (bins[:-1] + bins[1:]) / 2
del bins
#print bin_centers
plt.clf()
try:
popt, pcov = curve_fit(func, bin_centers, values)
del pcov
a = popt[0]
b = popt[1]
c = popt[2]
deviation = abs(MPV_value - b)
#print 'THE VALUES deviation,a,b,c,k: ', deviation,a,b,c,k
if a < 0 and deviation < 500:
success = True
#print success
list.append([deviation, a, b, c, k])
except RuntimeError:
print 'Error'
if success:
list = sorted(list)
MPV_MIPs.append(list[0][2])
print ''
afw = "Deviation = %g" % list[0][0]
print afw
ap = "a = %g" % list[0][1]
print ap
bp = "b = %g" % list[0][2]
print bp
cp = "c = %g" % list[0][3]
print cp
kp = "k = %g" % list[0][4]
print kp
print ''
if show_plot:
hist = plt.hist(p_plate_total, 750)
plt.yscale('log')
plt.axvline(list[0][2])
print 'Close plot to continue...'
print ''
plt.show()
print 'MPV value = %.2f %s' % (list[0][2], units[plot_variable[0][0]])
print ''
else:
MPV_MIPs.append(MPV_value)
print ''
print 'WARNING: Bad fit'
print ''
print ''
print 'MPV value = %.2f %s' % (MPV_value, units[plot_variable[0][0]])
print ''
if show_plot:
hist = plt.hist(p_plate_total, 750)
plt.yscale('log')
plt.axvline(MPV_value)
print ''
print 'Close plot to continue...'
plt.show()
#print MPV_MIPs
MPV_list.append(MPV_MIPs)
return MPV_list, number_of_plates
