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Changed the code to take as inputs only the range corrected signal, the rest of the raw file variables and the specific constants #1

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Changed the code to take as inputs only the range corrected signal, the rest of the raw file variables and the specific constants #1

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92 changes: 7 additions & 85 deletions gluing_v05_pollynet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -114,11 +114,11 @@ def calculate_norm_factors_raman(repeats, averaged_signals_array, channel_gluing

return bin_low_list, bin_high_list, mean_norm_factor_list, corrcoef_list, snr_nf_value_list, corr_coef, snr_nf, snr_ff

def process_gluing_2nd_step_raman(time, mean_norm_factor_list, bin_low_list, bin_high_list, average_interval, first_bin, raw_signals, depol_cal_angle, depol_cal_angle_value, range_corr_arr, channel_gluing_indexes, glued_signal):
def process_gluing_2nd_step_raman(time, mean_norm_factor_list, bin_low_list, bin_high_list, average_interval, depol_cal_angle, depol_cal_angle_value, range_corr_arr, channel_gluing_indexes, glued_signal):
t = 0
k = 0
while t < time:
if np.nanmean(raw_signals[t, first_bin:first_bin + 3, channel_gluing_indexes[1]]) == 0: ### mean betwen 0:3 first heights to ensure that the raman channels was closed and not one specific height because statistical that could be zero
if np.nanmean(range_corr_arr[t, 0:3, channel_gluing_indexes[1]]) == 0: ### mean betwen 0:3 first heights to ensure that the raman channels was closed and not one specific height because statistical that could be zero
t += 1
continue
else:
Expand All @@ -132,7 +132,7 @@ def process_gluing_2nd_step_raman(time, mean_norm_factor_list, bin_low_list, bin

print(limit)
for i in range(t, limit):
if np.nanmean(raw_signals[i, first_bin:first_bin + 3, channel_gluing_indexes[1]]) == 0:
if np.nanmean(range_corr_arr[i, 0:3, channel_gluing_indexes[1]]) == 0:
continue
if int(depol_cal_angle[i]) != depol_cal_angle_value:
continue
Expand Down Expand Up @@ -190,15 +190,7 @@ def find_indexes_of_channels_to_glue(array1, array2, array3):

depol_cal_angle_value = 0

dead_time = 4 # The dead time of the photomultiplier tube. [ns]

first_bin = 251

idx_min = first_bin // 10
idx_max = first_bin * 9 // 10


bin_length = 2.997E+8 * 50E-9 / 2


##### =============================================================================
Expand All @@ -220,13 +212,7 @@ def find_indexes_of_channels_to_glue(array1, array2, array3):
continue
channels = len(d.dimensions['channel'])
height = len(d.dimensions['height'])
location = getattr(d, 'location')
daytime = file

institution = file[-15:-12]

raw_signals = d.variables["raw_signal"][:, :, :]
measurement_shots = d.variables["measurement_shots"][:, :]
depol_cal_angle = d.variables["depol_cal_angle"][:]
if_center = d.variables["if_center"][:]
polstate = d.variables["polstate"][:]
Expand Down Expand Up @@ -256,79 +242,15 @@ def find_indexes_of_channels_to_glue(array1, array2, array3):
4:"532", 5:"532s", 6:"607", 7:"1064",
8:"532NF", 9:"607NF", 10:"355NF", 11:"387NF", 12:"532sNF", 13:"1058", 14:"1064s"}

zenith_angle = d.variables["zenithangle"] # Set the zenith angle of the laser beam. [degrees]



#####################convert bins to altitude####################

distance = np.arange(0, bin_length * (height - first_bin), bin_length) # Create distance vector that corresponds to each vertical bin.
altitude = distance * np.cos(np.deg2rad(zenith_angle)) # Convert the distance to altitude.
altitude_array = np.tile(altitude, (channels,1)).T




###############DEADTIME_CORRECTION NONPARALYZABLE##############


deadtime_corr_arr = np.zeros(raw_signals.shape)

for i in range (time):
for j in range (channels):
raw_signal = raw_signals[i,:,j]
measurement_shot = measurement_shots[i, j]
deadtime_corr_arr[i,:,j] = nes_fun._deadtime_correction_from_verlauf(raw_signal, dead_time, measurement_shot)
print('end deadtime correction')



##################BACKGROUND_CORRECTION##################


background_mean_array = np.zeros((time,channels))

bg_corr_arr = np.zeros(raw_signals.shape)

for i in range (time):
for j in range (channels):
raw_signal = deadtime_corr_arr[i, :, j]
bg_corr_arr[i, :, j], background_mean = nes_fun._background_correction(raw_signal, idx_min, idx_max)
background_mean_array[i][j] = background_mean
print('end background correction')

#bg_corr_arr = ma.masked_where(bg_corr_arr<0, bg_corr_arr, copy=True)
##################FIRST_BIN_CORRECTION##################

#bg_corr_arr=bg_corr_arr.astype("float64")
#bg_corr_arr[bg_corr_arr<0] = np.nan

first_bin_corr_arr = bg_corr_arr[:,first_bin:,:] ## + 1 gia na mhn exw apeirismo sta 0 m




##################RANGE_CORRECTION##################
range_corr_arr = np.zeros(first_bin_corr_arr.shape)

for i in range (time):
raw_signal = first_bin_corr_arr[i, :, :]
range_corr_arr[i, :, :] = nes_fun._range_correction(raw_signal, altitude_array)
print('end range correction')

#range_corr_arr = ma.masked_where(range_corr_arr<0, range_corr_arr, copy=True)
#range_corr_arr = range_corr_arr.astype('float64')
#range_corr_arr[range_corr_arr.mask] = np.nan

range_corr_arr_initial = np.copy(range_corr_arr)



################## AVERAGING ####################


repeats = time // average_interval
averaged_signals_array = np.zeros((repeats, (height-first_bin), channels))
averaged_signals_array = np.zeros((repeats, len(range_corr_arr[1]), channels))


t = 0
Expand All @@ -343,7 +265,7 @@ def find_indexes_of_channels_to_glue(array1, array2, array3):
if (int(depol_cal_angle[z])!=depol_cal_angle_value):
continue
if '%s'%ch=="387" or '%s'%ch=='407' or '%s'%ch=="607" or '%s'%ch=="607NF" or '%s'%ch=="387NF" or '%s'%ch=="1058":
if np.nanmean(raw_signals[z, first_bin:first_bin+3, channels_dictionary['%s'%ch]])==0:
if np.nanmean(range_corr_arr[z, 0:3, channels_dictionary['%s'%ch]])==0:
continue
z_list.append(z)
averaged_signals_array[t,:,channels_dictionary['%s'%ch]] = np.nanmean(range_corr_arr[z_list, :, channels_dictionary['%s'%ch]], axis=0)
Expand All @@ -355,7 +277,7 @@ def find_indexes_of_channels_to_glue(array1, array2, array3):
if (int(depol_cal_angle[z])!=depol_cal_angle_value):
continue
if '%s'%ch=="387" or '%s'%ch=='407' or '%s'%ch=="607" or '%s'%ch=="607NF" or '%s'%ch=="387NF" or '%s'%ch=="1058":
if np.nanmean(raw_signals[z, first_bin:first_bin+3, channels_dictionary['%s'%ch]])==0:
if np.nanmean(range_corr_arr[z, 0:3, channels_dictionary['%s'%ch]])==0:
continue
z_list.append(z)
averaged_signals_array[t,:,channels_dictionary['%s'%ch]] = np.nanmean(range_corr_arr[z_list, :, channels_dictionary['%s'%ch]], axis=0)
Expand Down Expand Up @@ -415,7 +337,7 @@ def find_indexes_of_channels_to_glue(array1, array2, array3):
# snr_ff = f"snr_ff_{if_center[ch[0]]}"

process_gluing_2nd_step_raman(
time, mean_norm_factor_list, bin_low_list, bin_high_list, average_interval, first_bin, raw_signals, depol_cal_angle, depol_cal_angle_value, range_corr_arr, ch, glued_signal)
time, mean_norm_factor_list, bin_low_list, bin_high_list, average_interval, depol_cal_angle, depol_cal_angle_value, range_corr_arr, ch, glued_signal)

else:

Expand Down