parouby
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acoused
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Merge branch 'dev-parouby' into dev

dev-parouby
Pierre-Antoine 2025-03-26 15:33:17 +01:00
parent 5a75697de7 714be64915
commit 883d43adb4
10 changed files with 341 additions and 257 deletions
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17
Model/create_table_for_save_as.py
View File

@ -99,6 +99,7 @@ class CreateTableForSaveAs:
ID INTEGER PRIMARY KEY AUTOINCREMENT, ID INTEGER PRIMARY KEY AUTOINCREMENT,
acoustic_data INTEGER, acoustic_data INTEGER,
temperature FLOAT, temperature FLOAT,
distance_to_free_surface FLOAT,
tmin_index FLOAT, tmin_value FLOAT, tmin_index FLOAT, tmin_value FLOAT,
tmax_index FLOAT, tmax_value FLOAT, tmax_index FLOAT, tmax_value FLOAT,
rmin_index FLOAT, rmin_value FLOAT, rmin_index FLOAT, rmin_value FLOAT,
@ -312,11 +313,9 @@ class CreateTableForSaveAs:
VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""", """,
( (
stg.acoustic_data[i], #stg.date[i], stg.hour[i], stg.acoustic_data[i],
str(stg.date[i].year) + str('-') stg.date[i].isoformat(),
+ str(stg.date[i].month) + str('-') stg.hour[i].isoformat(),
+ str(stg.date[i].day),
str(stg.hour[i].hour) + str(':') + str(stg.hour[i].minute),
stg.freq[i][j], stg.freq[i][j],
stg.water_attenuation[i][j], stg.water_attenuation[i][j],
stg.kt_read[j], stg.kt_corrected[j], stg.kt_read[j], stg.kt_corrected[j],
@ -410,16 +409,17 @@ class CreateTableForSaveAs:
cur.execute( cur.execute(
""" """
INSERT into Settings( INSERT into Settings(
acoustic_data, temperature, acoustic_data, temperature, distance_to_free_surface,
tmin_index, tmin_value, tmax_index, tmax_value, tmin_index, tmin_value, tmax_index, tmax_value,
rmin_index, rmin_value, rmax_index, rmax_value, rmin_index, rmin_value, rmax_index, rmax_value,
freq_bottom_detection_index, freq_bottom_detection_value, freq_bottom_detection_index, freq_bottom_detection_value,
SNR_filter_value, Nb_cells_to_average_BS_signal SNR_filter_value, Nb_cells_to_average_BS_signal
) )
VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""", """,
( (
stg.acoustic_data[i], stg.temperature, stg.acoustic_data[i], stg.temperature,
stg.distance_from_ABS_to_free_surface[i],
stg.tmin[i][0], stg.tmin[i][1], stg.tmin[i][0], stg.tmin[i][1],
stg.tmax[i][0], stg.tmax[i][1], stg.tmax[i][0], stg.tmax[i][1],
stg.rmin[i][0], stg.rmin[i][1], stg.rmin[i][0], stg.rmin[i][1],
@ -543,7 +543,8 @@ class CreateTableForSaveAs:
np.array(stg.X_exponent).tobytes(), np.array(stg.X_exponent).tobytes(),
np.array(stg.alpha_s).tobytes(), np.array(stg.alpha_s).tobytes(),
np.array(stg.zeta).tobytes(), np.array(stg.zeta).tobytes(),
stg.FCB.tobytes(), stg.depth_real.tobytes(), np.array(stg.FCB).tobytes(),
np.array(stg.depth_real).tobytes(),
np.array(stg.lin_reg).tobytes() np.array(stg.lin_reg).tobytes()
) )
) )

132
Model/read_table_for_open.py
View File

@ -26,6 +26,8 @@ import sqlite3
import logging import logging
import numpy as np import numpy as np
from datetime import date, time
from PyQt5.QtWidgets import QFileDialog, QApplication, QWidget, QTabWidget from PyQt5.QtWidgets import QFileDialog, QApplication, QWidget, QTabWidget
import settings as stg import settings as stg
@ -33,6 +35,7 @@ from settings import BS_raw_data, acoustic_data
from View.acoustic_data_tab import AcousticDataTab from View.acoustic_data_tab import AcousticDataTab
from tools import trace
logger = logging.getLogger("acoused") logger = logging.getLogger("acoused")
@ -81,6 +84,7 @@ class ReadTableForOpen:
self.read_table_settings() self.read_table_settings()
self.read_table_sediment_file() self.read_table_sediment_file()
self.read_table_table_sediment_data() self.read_table_table_sediment_data()
self.read_table_table_calibration()
logger.debug(f"Reading '{stg.filename_open}' done") logger.debug(f"Reading '{stg.filename_open}' done")
@ -113,6 +117,7 @@ class ReadTableForOpen:
stg.filename_BS_raw_data.append( stg.filename_BS_raw_data.append(
str(data[1]) + '.aqa' str(data[1]) + '.aqa'
) )
stg.path_BS_raw_data.append("")
stg.ABS_name.append(data[2]) stg.ABS_name.append(data[2])
stg.path_BS_noise_data.append(data[3]) stg.path_BS_noise_data.append(data[3])
stg.filename_BS_noise_data.append(data[4]) stg.filename_BS_noise_data.append(data[4])
@ -134,7 +139,7 @@ class ReadTableForOpen:
stg.hour = [0]*len(stg.acoustic_data) stg.hour = [0]*len(stg.acoustic_data)
for i in range(len(stg.acoustic_data)): for i in range(len(stg.acoustic_data)):
query1 = f''' query = f'''
SELECT SELECT
acoustic_data, Date, Hour, frequency, acoustic_data, Date, Hour, frequency,
sound_attenuation, kt_read, kt_corrected, NbProfiles, sound_attenuation, kt_read, kt_corrected, NbProfiles,
@ -144,38 +149,38 @@ class ReadTableForOpen:
FROM Measure FROM Measure
WHERE (acoustic_data = {i}) WHERE (acoustic_data = {i})
''' '''
data1 = self.execute(query1) data = self.execute(query)
logger.debug(f"data1 for {i}: {data1}") logger.debug(f"data for {i}: {data}")
stg.date[i] = data1[0][1] stg.date[i] = date.fromisoformat(data[0][1])
stg.hour[i] = data1[0][2] stg.hour[i] = time.fromisoformat(data[0][2])
stg.freq.append( stg.freq.append(
np.array([x[3] for x in data1]) np.array([x[3] for x in data])
) )
stg.freq_text.append( stg.freq_text.append(
[str(x[3]*1e-6) + 'MHz' for x in data1] [str(x[3]*1e-6) + 'MHz' for x in data]
) )
stg.water_attenuation.append( stg.water_attenuation.append(
[x[4] for x in data1] [x[4] for x in data]
) )
stg.kt_read = [x[5] for x in data1] stg.kt_read = [x[5] for x in data]
stg.kt_corrected = [x[6] for x in data1] stg.kt_corrected = [x[6] for x in data]
stg.nb_profiles.append([x[7] for x in data1]) stg.nb_profiles.append([x[7] for x in data])
stg.nb_profiles_per_sec.append([x[8] for x in data1]) stg.nb_profiles_per_sec.append([x[8] for x in data])
stg.nb_cells.append([x[9] for x in data1]) stg.nb_cells.append([x[9] for x in data])
stg.cell_size.append([x[10] for x in data1]) stg.cell_size.append([x[10] for x in data])
stg.pulse_length.append([x[11] for x in data1]) stg.pulse_length.append([x[11] for x in data])
stg.nb_pings_per_sec.append( stg.nb_pings_per_sec.append(
[x[12] for x in data1] [x[12] for x in data]
) )
stg.nb_pings_averaged_per_profile.append( stg.nb_pings_averaged_per_profile.append(
[x[13] for x in data1] [x[13] for x in data]
) )
stg.gain_rx.append([x[14] for x in data1]) stg.gain_rx.append([x[14] for x in data])
stg.gain_tx.append([x[15] for x in data1]) stg.gain_tx.append([x[15] for x in data])
logger.debug("measure:") logger.debug("measure:")
logger.debug(f"- stg.acoustic_data: {stg.acoustic_data}") logger.debug(f"- stg.acoustic_data: {stg.acoustic_data}")
@ -477,7 +482,7 @@ class ReadTableForOpen:
for s in range(len(stg.acoustic_data)): for s in range(len(stg.acoustic_data)):
query3 = f''' query3 = f'''
SELECT SELECT
acoustic_data, temperature, acoustic_data, temperature, distance_to_free_surface,
tmin_index, tmin_value, tmax_index, tmax_value, tmin_index, tmin_value, tmax_index, tmax_value,
rmin_index, rmin_value, rmax_index, rmax_value, rmin_index, rmin_value, rmax_index, rmax_value,
freq_bottom_detection_index, freq_bottom_detection_value, freq_bottom_detection_index, freq_bottom_detection_value,
@ -490,13 +495,14 @@ class ReadTableForOpen:
x = data[0] x = data[0]
stg.temperature = [x[1]][0] stg.temperature = [x[1]][0]
stg.tmin.append((x[2], x[3])) stg.distance_from_ABS_to_free_surface.append(x[2])
stg.tmax.append((x[4], x[5])) stg.tmin.append((x[3], x[4]))
stg.rmin.append((x[6], x[7])) stg.tmax.append((x[5], x[6]))
stg.rmax.append((x[8], x[9])) stg.rmin.append((x[7], x[8]))
stg.freq_bottom_detection.append((x[10], x[11])) stg.rmax.append((x[9], x[10]))
stg.SNR_filter_value.append(x[12]) stg.freq_bottom_detection.append((x[11], x[12]))
stg.Nb_cells_to_average_BS_signal.append(x[13]) stg.SNR_filter_value.append(x[13])
stg.Nb_cells_to_average_BS_signal.append(x[14])
logger.debug(f"stg.temperature: {stg.temperature}") logger.debug(f"stg.temperature: {stg.temperature}")
logger.debug(f"stg.tmin: {stg.tmin}") logger.debug(f"stg.tmin: {stg.tmin}")
@ -536,6 +542,7 @@ class ReadTableForOpen:
+ list(stg.radius_grain_sand) + list(stg.radius_grain_sand)
) )
@trace
def read_table_table_sediment_data(self): def read_table_table_sediment_data(self):
np_f64_parse = lambda d: np.frombuffer(d, dtype=np.float64) np_f64_parse = lambda d: np.frombuffer(d, dtype=np.float64)
@ -558,32 +565,32 @@ class ReadTableForOpen:
stg.frac_vol_sand = [] stg.frac_vol_sand = []
stg.frac_vol_sand_cumul = [] stg.frac_vol_sand_cumul = []
for f in range(len(data)): for d in data:
stg.sample_fine.append((data[f][0], data[f][1])) stg.sample_fine.append((d[0], d[1]))
stg.distance_from_bank_fine.append(data[f][2]) stg.distance_from_bank_fine.append(d[2])
stg.depth_fine.append(data[f][3]) stg.depth_fine.append(d[3])
stg.time_fine.append(data[f][4]) stg.time_fine.append(d[4])
stg.Ctot_fine.append(data[f][5]) stg.Ctot_fine.append(d[5])
stg.Ctot_fine_per_cent.append(data[f][6]) stg.Ctot_fine_per_cent.append(d[6])
stg.D50_fine.append(data[f][7]) stg.D50_fine.append(d[7])
stg.frac_vol_fine.append( stg.frac_vol_fine.append(
np_f64_parse(data[f][8]) np_f64_parse(d[8])
) )
stg.frac_vol_fine_cumul.append( stg.frac_vol_fine_cumul.append(
np_f64_parse(data[f][9]) np_f64_parse(d[9])
) )
stg.sample_sand.append((data[f][10], data[f][11])) stg.sample_sand.append((d[10], d[11]))
stg.distance_from_bank_sand.append(data[f][12]) stg.distance_from_bank_sand.append(d[12])
stg.depth_sand.append(data[f][13]) stg.depth_sand.append(d[13])
stg.time_sand.append(data[f][14]) stg.time_sand.append(d[14])
stg.Ctot_sand.append(data[f][15]) stg.Ctot_sand.append(d[15])
stg.Ctot_sand_per_cent.append(data[f][16]) stg.Ctot_sand_per_cent.append(d[16])
stg.D50_sand.append(data[f][17]) stg.D50_sand.append(d[17])
stg.frac_vol_sand.append( stg.frac_vol_sand.append(
np_f64_parse(data[f][18]) np_f64_parse(d[18])
) )
stg.frac_vol_sand_cumul.append( stg.frac_vol_sand_cumul.append(
np_f64_parse(data[f][19]) np_f64_parse(d[19])
) )
stg.frac_vol_fine = np.array(stg.frac_vol_fine) stg.frac_vol_fine = np.array(stg.frac_vol_fine)
@ -592,3 +599,36 @@ class ReadTableForOpen:
stg.frac_vol_sand_cumul = np.array(stg.frac_vol_sand_cumul) stg.frac_vol_sand_cumul = np.array(stg.frac_vol_sand_cumul)
logger.debug(f"fine: {stg.Ctot_fine}, sand: {stg.sample_sand}") logger.debug(f"fine: {stg.Ctot_fine}, sand: {stg.sample_sand}")
@trace
def read_table_table_calibration(self):
np_f64_parse = lambda d: np.frombuffer(d, dtype=np.float64)
query = f'''
SELECT
path_calibration_file,
filename_calibration_file,
range_lin_interp,
M_profile_fine,
ks, sv,
X_exponent,
alpha_s, zeta, FCB,
depth_real, lin_reg
FROM Calibration
'''
data = self.execute(query)
it = iter(data[0])
stg.path_calibration_file = next(it)
stg.filename_calibration_file = next(it)
stg.range_lin_interp = np_f64_parse(next(it))
stg.M_profile_fine = np_f64_parse(next(it))
stg.ks = np_f64_parse(next(it))
stg.sv = np_f64_parse(next(it))
stg.X_exponent = np_f64_parse(next(it))
stg.alpha_s = np_f64_parse(next(it))
stg.zeta = np_f64_parse(next(it))
stg.FCB = np_f64_parse(next(it))
stg.depth_real = np_f64_parse(next(it))
stg.lin_reg = np_f64_parse(next(it))

96
Model/update_table_for_save.py
View File

@ -147,15 +147,8 @@ class UpdateTableForSave:
) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''', ) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
( (
stg.acoustic_data[i], stg.acoustic_data[i],
( stg.date[i].isoformat(),
str(stg.date[i].year) + str('-') + stg.hour[i].isoformat(),
str(stg.date[i].month) + str('-') +
str(stg.date[i].day)
),
(
str(stg.hour[i].hour) + str(':') +
str(stg.hour[i].minute)
),
stg.freq[i][j], stg.freq[i][j],
stg.water_attenuation[i][j], stg.water_attenuation[i][j],
stg.kt_read[j], stg.kt_read[j],
@ -214,21 +207,29 @@ class UpdateTableForSave:
BS_mean) BS_mean)
VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''', VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
(stg.acoustic_data[i], stg.time[i].tobytes(), stg.depth[i].tobytes(), stg.BS_raw_data[i].tobytes(), (stg.acoustic_data[i], stg.time[i].tobytes(), stg.depth[i].tobytes(), stg.BS_raw_data[i].tobytes(),
stg.time_reshape[i].tobytes(), stg.depth_reshape[i].tobytes(), stg.BS_raw_data_reshape[i].tobytes(), stg.time_reshape[i].tobytes(),
stg.time_cross_section[i].tobytes(), stg.depth_cross_section[i].tobytes(), stg.BS_cross_section[i].tobytes(), stg.depth_reshape[i].tobytes(),
stg.BS_stream_bed[i].tobytes(), stg.BS_raw_data_reshape[i].tobytes(),
stg.depth_bottom[i].tobytes(), stg.val_bottom[i].tobytes(), np.array(stg.ind_bottom[i]).tobytes(), stg.time_cross_section[i].tobytes(),
stg.time_noise[i].tobytes(), stg.depth_noise[i].tobytes(), stg.depth_cross_section[i].tobytes(),
stg.BS_noise_raw_data[i].tobytes(), stg.BS_cross_section[i].tobytes(),
stg.SNR_raw_data[i].tobytes(), stg.SNR_cross_section[i].tobytes(), np.array(stg.BS_stream_bed[i]).tobytes(),
stg.SNR_stream_bed[i].tobytes(), np.array(stg.depth_bottom[i]).tobytes(),
stg.BS_raw_data_pre_process_SNR[i].tobytes(), np.array(stg.val_bottom[i]).tobytes(),
stg.BS_raw_data_pre_process_average[i].tobytes(), np.array(stg.ind_bottom[i]).tobytes(),
stg.BS_cross_section_pre_process_SNR[i].tobytes(), np.array(stg.time_noise[i]).tobytes(),
stg.BS_cross_section_pre_process_average[i].tobytes(), np.array(stg.depth_noise[i]).tobytes(),
stg.BS_stream_bed_pre_process_SNR[i].tobytes(), np.array(stg.BS_noise_raw_data[i]).tobytes(),
stg.BS_stream_bed_pre_process_average[i].tobytes(), np.array(stg.SNR_raw_data[i]).tobytes(),
stg.BS_mean[i].tobytes() np.array(stg.SNR_cross_section[i]).tobytes(),
np.array(stg.SNR_stream_bed[i]).tobytes(),
np.array(stg.BS_raw_data_pre_process_SNR[i]).tobytes(),
np.array(stg.BS_raw_data_pre_process_average[i]).tobytes(),
np.array(stg.BS_cross_section_pre_process_SNR[i]).tobytes(),
np.array(stg.BS_cross_section_pre_process_average[i]).tobytes(),
np.array(stg.BS_stream_bed_pre_process_SNR[i]).tobytes(),
np.array(stg.BS_stream_bed_pre_process_average[i]).tobytes(),
np.array(stg.BS_mean[i]).tobytes()
) )
) )
@ -245,28 +246,47 @@ class UpdateTableForSave:
cur.execute(''' DROP TABLE Settings''') cur.execute(''' DROP TABLE Settings''')
cur.execute('''CREATE TABLE Settings(ID INTEGER PRIMARY KEY AUTOINCREMENT, cur.execute('''
CREATE TABLE Settings(
ID INTEGER PRIMARY KEY AUTOINCREMENT,
acoustic_data INTEGER, acoustic_data INTEGER,
temperature FLOAT, temperature FLOAT,
tmin_index FLOAT, tmin_value FLOAT, tmax_index FLOAT, tmax_value FLOAT, distance_to_free_surface FLOAT,
rmin_index FLOAT, rmin_value FLOAT, rmax_index FLOAT, rmax_value FLOAT, tmin_index FLOAT, tmin_value FLOAT,
freq_bottom_detection_index FLOAT, freq_bottom_detection_value STRING, tmax_index FLOAT, tmax_value FLOAT,
SNR_filter_value FLOAT, Nb_cells_to_average_BS_signal FLOAT rmin_index FLOAT, rmin_value FLOAT,
)''' rmax_index FLOAT, rmax_value FLOAT,
freq_bottom_detection_index FLOAT,
freq_bottom_detection_value STRING,
SNR_filter_value FLOAT,
Nb_cells_to_average_BS_signal FLOAT
)
'''
) )
for i in stg.acoustic_data: for i in stg.acoustic_data:
cur.execute('''INSERT into Settings(acoustic_data, temperature, cur.execute('''
INSERT into Settings(
acoustic_data, temperature,
distance_to_free_surface,
tmin_index, tmin_value, tmax_index, tmax_value, tmin_index, tmin_value, tmax_index, tmax_value,
rmin_index, rmin_value, rmax_index, rmax_value, rmin_index, rmin_value, rmax_index, rmax_value,
freq_bottom_detection_index, freq_bottom_detection_value, freq_bottom_detection_index, freq_bottom_detection_value,
SNR_filter_value, Nb_cells_to_average_BS_signal) SNR_filter_value, Nb_cells_to_average_BS_signal
VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''', ) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
(stg.acoustic_data[i], stg.temperature, ''',
stg.tmin[i][0], stg.tmin[i][1], stg.tmax[i][0], stg.tmax[i][1], (
stg.rmin[i][0], stg.rmin[i][1], stg.rmax[i][0], stg.rmax[i][1], stg.acoustic_data[i], stg.temperature,
stg.freq_bottom_detection[i][0], stg.freq_bottom_detection[i][1], stg.distance_from_ABS_to_free_surface[i],
stg.SNR_filter_value[i], stg.Nb_cells_to_average_BS_signal[i]) stg.tmin[i][0], stg.tmin[i][1],
stg.tmax[i][0], stg.tmax[i][1],
stg.rmin[i][0], stg.rmin[i][1],
stg.rmax[i][0], stg.rmax[i][1],
stg.freq_bottom_detection[i][0],
stg.freq_bottom_detection[i][1],
stg.SNR_filter_value[i],
stg.Nb_cells_to_average_BS_signal[i]
)
) )
cnx.commit() cnx.commit()

20
View/acoustic_data_tab.py
View File

@ -59,6 +59,7 @@ from Model.acoustic_data_loader import AcousticDataLoader
from Model.acoustic_data_loader_UBSediFlow import AcousticDataLoaderUBSediFlow from Model.acoustic_data_loader_UBSediFlow import AcousticDataLoaderUBSediFlow
from Model.calibration_constant_kt import CalibrationConstantKt from Model.calibration_constant_kt import CalibrationConstantKt
from tools import trace
locale.setlocale(locale.LC_ALL, '') locale.setlocale(locale.LC_ALL, '')
@ -733,6 +734,7 @@ class AcousticDataTab(QWidget):
# -------------------- Functions for Acoustic dataTab -------------------- # -------------------- Functions for Acoustic dataTab --------------------
@trace
def full_update(self): def full_update(self):
logger.debug(f"{__name__}: Update") logger.debug(f"{__name__}: Update")
self.blockSignals(True) self.blockSignals(True)
@ -842,7 +844,6 @@ class AcousticDataTab(QWidget):
self.groupbox_measurement_information_UBSediFlow() self.groupbox_measurement_information_UBSediFlow()
def groupbox_measurement_information_no_ABS(self): def groupbox_measurement_information_no_ABS(self):
self.label_ABS_name.hide() self.label_ABS_name.hide()
self.combobox_ABS_name.hide() self.combobox_ABS_name.hide()
@ -1190,15 +1191,22 @@ class AcousticDataTab(QWidget):
self.lineEdit_distance_from_ABS_to_free_surface.setText("0.00") self.lineEdit_distance_from_ABS_to_free_surface.setText("0.00")
else: else:
stg.distance_from_ABS_to_free_surface[self.fileListWidget\ stg.distance_from_ABS_to_free_surface[
.currentRow()] = ( self.fileListWidget.currentRow()
] = (
float( float(
self.lineEdit_distance_from_ABS_to_free_surface\ self.lineEdit_distance_from_ABS_to_free_surface\
.text().replace(",", ".") .text().replace(",", ".")
) )
) )
self.lineEdit_distance_from_ABS_to_free_surface.setText( self.lineEdit_distance_from_ABS_to_free_surface.setText(
str("%4s" % stg.distance_from_ABS_to_free_surface[self.fileListWidget.currentRow()])) str(
"%4s" % stg.distance_from_ABS_to_free_surface[
self.fileListWidget.currentRow()
]
)
)
def refresh_distance_from_ABS_to_free_surface(self): def refresh_distance_from_ABS_to_free_surface(self):
self.pushbutton_distance_from_ABS_to_free_surface.blockSignals(True) self.pushbutton_distance_from_ABS_to_free_surface.blockSignals(True)
@ -1777,6 +1785,10 @@ class AcousticDataTab(QWidget):
.currentIndexChanged\ .currentIndexChanged\
.connect(self.combobox_frequency_information_update) .connect(self.combobox_frequency_information_update)
self.lineEdit_distance_from_ABS_to_free_surface.setText(
str(stg.distance_from_ABS_to_free_surface[file_id])
)
logger.debug(f"Set temperature = {stg.temperature}") logger.debug(f"Set temperature = {stg.temperature}")
self.lineEdit_temperature.setText(str(stg.temperature)) self.lineEdit_temperature.setText(str(stg.temperature))

2
View/acoustic_inversion_tab.py
View File

@ -48,6 +48,7 @@ from View.checkable_combobox import CheckableComboBox
import settings as stg import settings as stg
from Model.acoustic_inversion_method_high_concentration import AcousticInversionMethodHighConcentration from Model.acoustic_inversion_method_high_concentration import AcousticInversionMethodHighConcentration
from tools import trace
_translate = QCoreApplication.translate _translate = QCoreApplication.translate
@ -371,6 +372,7 @@ class AcousticInversionTab(QWidget):
# ------------------------------------ Functions for Acoustic Inversion Tab ---------------------------------------- # ------------------------------------ Functions for Acoustic Inversion Tab ----------------------------------------
# ================================================================================================================== # ==================================================================================================================
@trace
def full_update(self): def full_update(self):
logger.debug(f"{__name__}: Update") logger.debug(f"{__name__}: Update")
self.blockSignals(True) self.blockSignals(True)

4
View/note_tab.py
View File

@ -10,6 +10,8 @@ from PyQt5.QtCore import Qt
import settings as stg import settings as stg
from tools import trace
logger = logging.getLogger("acoused") logger = logging.getLogger("acoused")
class NoteTab(QWidget): class NoteTab(QWidget):
@ -136,7 +138,7 @@ class NoteTab(QWidget):
## ---------- Functions ---------- ## ---------- Functions ----------
## ------------------------------- ## -------------------------------
@trace
def full_update(self): def full_update(self):
logger.debug(f"{__name__}: Update") logger.debug(f"{__name__}: Update")
self.blockSignals(True) self.blockSignals(True)

5
View/sample_data_tab.py
View File

@ -49,6 +49,8 @@ import Translation.constant_string as cs
import settings as stg import settings as stg
from tools import trace
_translate = QCoreApplication.translate _translate = QCoreApplication.translate
logger = logging.getLogger("acoused") logger = logging.getLogger("acoused")
@ -278,6 +280,7 @@ class SampleDataTab(QWidget):
self.groupbox_plot_PSD.setTitle(_translate("CONSTANT_STRING", cs.DISTRIBUTION_PLOT)) self.groupbox_plot_PSD.setTitle(_translate("CONSTANT_STRING", cs.DISTRIBUTION_PLOT))
@trace
def full_update(self): def full_update(self):
logger.debug(f"{__name__}: Update") logger.debug(f"{__name__}: Update")
self.blockSignals(True) self.blockSignals(True)
@ -475,6 +478,7 @@ class SampleDataTab(QWidget):
self.item_checkbox_fine.setCheckState(Qt.Checked) self.item_checkbox_fine.setCheckState(Qt.Checked)
self.tableWidget_fine.setItem(i, 1, self.item_checkbox_fine) self.tableWidget_fine.setItem(i, 1, self.item_checkbox_fine)
self.item_checkbox_fine.setText("F" + str(i + 1)) self.item_checkbox_fine.setText("F" + str(i + 1))
if len(stg.sample_fine) <= i:
stg.sample_fine.append(("F" + str(i + 1), i)) stg.sample_fine.append(("F" + str(i + 1), i))
# --- Fill table with data --- # --- Fill table with data ---
@ -570,6 +574,7 @@ class SampleDataTab(QWidget):
self.item_checkbox_sand.setCheckState(Qt.Checked) self.item_checkbox_sand.setCheckState(Qt.Checked)
self.tableWidget_sand.setItem(i, 1, self.item_checkbox_sand) self.tableWidget_sand.setItem(i, 1, self.item_checkbox_sand)
self.item_checkbox_sand.setText("S" + str(i + 1)) self.item_checkbox_sand.setText("S" + str(i + 1))
if len(stg.sample_sand) <= i:
stg.sample_sand.append(("S" + str(i + 1), i)) stg.sample_sand.append(("S" + str(i + 1), i))
# --- Fill table with data --- # --- Fill table with data ---

304
View/sediment_calibration_tab.py
View File

@ -48,6 +48,8 @@ import settings as stg
from View.checkable_combobox import CheckableComboBox from View.checkable_combobox import CheckableComboBox
from Model.acoustic_inversion_method_high_concentration import AcousticInversionMethodHighConcentration from Model.acoustic_inversion_method_high_concentration import AcousticInversionMethodHighConcentration
from tools import trace
logger = logging.getLogger("acoused") logger = logging.getLogger("acoused")
class SedimentCalibrationTab(QWidget): class SedimentCalibrationTab(QWidget):
@ -857,6 +859,7 @@ class SedimentCalibrationTab(QWidget):
# ----------------------------------- Functions for Signal processing Tab -------------------------------------- # ----------------------------------- Functions for Signal processing Tab --------------------------------------
# ============================================================================================================== # ==============================================================================================================
@trace
def full_update(self): def full_update(self):
logger.debug(f"{__name__}: Update") logger.debug(f"{__name__}: Update")
self.blockSignals(True) self.blockSignals(True)
@ -873,7 +876,7 @@ class SedimentCalibrationTab(QWidget):
return return
self.update_acoustic_data() self.update_acoustic_data()
# self.compute_depth_2D() self.compute_depth_2D()
def update_acoustic_data(self): def update_acoustic_data(self):
self.combobox_acoustic_data_choice.clear() self.combobox_acoustic_data_choice.clear()
@ -931,11 +934,13 @@ class SedimentCalibrationTab(QWidget):
self.compute_FCB() self.compute_FCB()
def plot_acoustic_recording(self): def plot_acoustic_recording(self):
data_id = self.combobox_acoustic_data_choice.currentIndex()
# --- Record frequencies for calibration --- # --- Record frequencies for calibration ---
stg.frequencies_for_calibration.clear() stg.frequencies_for_calibration.clear()
stg.frequencies_for_calibration.append( stg.frequencies_for_calibration.append(
( (
stg.freq[self.combobox_acoustic_data_choice.currentIndex()][ stg.freq[data_id][
self.combobox_freq1.currentIndex() self.combobox_freq1.currentIndex()
], ],
self.combobox_freq1.currentIndex() self.combobox_freq1.currentIndex()
@ -943,7 +948,7 @@ class SedimentCalibrationTab(QWidget):
) )
stg.frequencies_for_calibration.append( stg.frequencies_for_calibration.append(
( (
stg.freq[self.combobox_acoustic_data_choice.currentIndex()][ stg.freq[data_id][
self.combobox_freq2.currentIndex() self.combobox_freq2.currentIndex()
], ],
self.combobox_freq2.currentIndex() self.combobox_freq2.currentIndex()
@ -952,7 +957,7 @@ class SedimentCalibrationTab(QWidget):
stg.frequency_for_inversion = tuple() stg.frequency_for_inversion = tuple()
stg.frequency_for_inversion = ( stg.frequency_for_inversion = (
stg.freq[self.combobox_acoustic_data_choice.currentIndex()][ stg.freq[data_id][
self.combobox_freq2.currentIndex() self.combobox_freq2.currentIndex()
], ],
self.combobox_freq2.currentIndex() self.combobox_freq2.currentIndex()
@ -970,18 +975,18 @@ class SedimentCalibrationTab(QWidget):
self.verticalLayout_groupbox_data_plot.addWidget(self.canvas_BS) self.verticalLayout_groupbox_data_plot.addWidget(self.canvas_BS)
if stg.BS_stream_bed_pre_process_average[ if stg.BS_stream_bed_pre_process_average[
self.combobox_acoustic_data_choice.currentIndex() data_id
].shape != (0,): ].shape != (0,):
val_min = np.nanmin( val_min = np.nanmin(
stg.BS_stream_bed_pre_process_average[ stg.BS_stream_bed_pre_process_average[
self.combobox_acoustic_data_choice.currentIndex() data_id
][ ][
self.combobox_freq2.currentIndex(), :, : self.combobox_freq2.currentIndex(), :, :
] ]
) )
val_max = np.nanmax( val_max = np.nanmax(
stg.BS_stream_bed_pre_process_average[ stg.BS_stream_bed_pre_process_average[
self.combobox_acoustic_data_choice.currentIndex() data_id
][ ][
self.combobox_freq2.currentIndex(), :, : self.combobox_freq2.currentIndex(), :, :
] ]
@ -989,346 +994,346 @@ class SedimentCalibrationTab(QWidget):
if val_min == 0: if val_min == 0:
val_min = 1e-5 val_min = 1e-5
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.time_cross_section[data_id].shape != (0,):
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_stream_bed_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_stream_bed_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_stream_bed_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_stream_bed_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
elif stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): elif stg.BS_stream_bed_pre_process_SNR[data_id].shape != (0,):
val_min = np.nanmin( val_min = np.nanmin(
stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_stream_bed_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
val_max = np.nanmax( val_max = np.nanmax(
stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_stream_bed_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
if val_min == 0: if val_min == 0:
val_min = 1e-5 val_min = 1e-5
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.time_cross_section[data_id].shape != (0,):
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_stream_bed_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_stream_bed_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_stream_bed_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_stream_bed_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
elif stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): elif stg.BS_stream_bed[data_id].shape != (0,):
val_min = np.nanmin( val_min = np.nanmin(
stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
:, :]) :, :])
val_max = np.nanmax( val_max = np.nanmax(
stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
:, :]) :, :])
if val_min == 0: if val_min == 0:
val_min = 1e-5 val_min = 1e-5
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.time_cross_section[data_id].shape != (0,):
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
:, :], :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
:, :], :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
:, :], :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), stg.BS_stream_bed[data_id][self.combobox_freq2.currentIndex(),
:, :], :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
elif stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): elif stg.BS_cross_section_pre_process_average[data_id].shape != (0,):
val_min = np.nanmin( val_min = np.nanmin(
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
val_max = np.nanmax( val_max = np.nanmax(
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
if val_min == 0: if val_min == 0:
val_min = 1e-5 val_min = 1e-5
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.time_cross_section[data_id].shape != (0,):
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): elif stg.BS_cross_section_pre_process_SNR[data_id].shape != (0,):
val_min = np.nanmin( val_min = np.nanmin(
stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
val_max = np.nanmax( val_max = np.nanmax(
stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
if val_min == 0: if val_min == 0:
val_min = 1e-5 val_min = 1e-5
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.time_cross_section[data_id].shape != (0,):
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0): if stg.depth_cross_section[data_id].shape != (0):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0): if stg.depth_cross_section[data_id].shape != (0):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): elif stg.BS_cross_section[data_id].shape != (0,):
val_min = np.nanmin( val_min = np.nanmin(
stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
val_max = np.nanmax( val_max = np.nanmax(
stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
if val_min == 0: if val_min == 0:
val_min = 1e-5 val_min = 1e-5
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.time_cross_section[data_id].shape != (0,):
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
else: else:
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_cross_section[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
elif stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): elif stg.BS_raw_data_pre_process_average[data_id].shape != (0,):
val_min = np.nanmin(stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ val_min = np.nanmin(stg.BS_raw_data_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
val_max = np.nanmax(stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ val_max = np.nanmax(stg.BS_raw_data_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
if val_min == 0: if val_min == 0:
val_min = 1e-5 val_min = 1e-5
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :], stg.time[data_id][self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :], -stg.depth[data_id][self.combobox_freq2.currentIndex(), :],
stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_raw_data_pre_process_average[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): elif stg.BS_raw_data_pre_process_SNR[data_id].shape != (0,):
val_min = np.nanmin(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ val_min = np.nanmin(stg.BS_raw_data_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
val_max = np.nanmax(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ val_max = np.nanmax(stg.BS_raw_data_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
if val_min == 0: if val_min == 0:
val_min = 1e-5 val_min = 1e-5
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :], stg.time[data_id][self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :], -stg.depth[data_id][self.combobox_freq2.currentIndex(), :],
stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_raw_data_pre_process_SNR[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
elif stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): elif stg.BS_raw_data[data_id].shape != (0,):
val_min = np.nanmin(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][ val_min = np.nanmin(stg.BS_raw_data[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
val_max = np.nanmax(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][ val_max = np.nanmax(stg.BS_raw_data[data_id][
self.combobox_freq2.currentIndex(), :, :]) self.combobox_freq2.currentIndex(), :, :])
if val_min == 0: if val_min == 0:
val_min = 1e-5 val_min = 1e-5
self.axis_BS.pcolormesh( self.axis_BS.pcolormesh(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :], stg.time[data_id][self.combobox_freq2.currentIndex(), :],
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex(), :], -stg.depth[data_id][self.combobox_freq2.currentIndex(), :],
stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][ stg.BS_raw_data[data_id][
self.combobox_freq2.currentIndex(), :, :], self.combobox_freq2.currentIndex(), :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
@ -1367,16 +1372,16 @@ class SedimentCalibrationTab(QWidget):
# --- Plot vertical red line for position of FCB profile --- # --- Plot vertical red line for position of FCB profile ---
if stg.sand_sample_target_indice: if stg.sand_sample_target_indice:
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,):
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.time_cross_section[data_id].shape != (0,):
self.red_line_plot_return, = ( self.red_line_plot_return, = (
self.axis_BS.plot( self.axis_BS.plot(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] * self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] *
np.ones(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[1]), np.ones(stg.depth_cross_section[data_id].shape[1]),
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
color='red', linestyle="solid", linewidth=2)) color='red', linestyle="solid", linewidth=2))
@ -1384,23 +1389,23 @@ class SedimentCalibrationTab(QWidget):
self.red_line_plot_return, = ( self.red_line_plot_return, = (
self.axis_BS.plot( self.axis_BS.plot(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] * self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] *
np.ones(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[1]), np.ones(stg.depth_cross_section[data_id].shape[1]),
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth_cross_section[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
color='red', linestyle="solid", linewidth=2)) color='red', linestyle="solid", linewidth=2))
else: else:
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.time_cross_section[data_id].shape != (0,):
self.red_line_plot_return, = ( self.red_line_plot_return, = (
self.axis_BS.plot( self.axis_BS.plot(
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ stg.time_cross_section[data_id][
self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] * self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] *
np.ones(stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape[1]), np.ones(stg.depth[data_id].shape[1]),
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
color='red', linestyle="solid", linewidth=2)) color='red', linestyle="solid", linewidth=2))
@ -1408,10 +1413,10 @@ class SedimentCalibrationTab(QWidget):
self.red_line_plot_return, = ( self.red_line_plot_return, = (
self.axis_BS.plot( self.axis_BS.plot(
stg.time[self.combobox_acoustic_data_choice.currentIndex()][ stg.time[data_id][
self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] * self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[0][1]] *
np.ones(stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape[1]), np.ones(stg.depth[data_id].shape[1]),
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ -stg.depth[data_id][
self.combobox_freq2.currentIndex(), :], self.combobox_freq2.currentIndex(), :],
color='red', linestyle="solid", linewidth=2)) color='red', linestyle="solid", linewidth=2))
@ -1941,13 +1946,12 @@ class SedimentCalibrationTab(QWidget):
def compute_depth_2D(self): def compute_depth_2D(self):
if self.combobox_acoustic_data_choice.count() > 0: if self.combobox_acoustic_data_choice.count() > 0:
for k in range(self.combobox_acoustic_data_choice.count()): for k in range(self.combobox_acoustic_data_choice.count()):
while len(stg.depth_2D) <= k:
stg.depth_2D.append(np.array([]))
if stg.depth_cross_section[k].shape != (0,): if stg.depth_cross_section[k].shape != (0,):
if stg.time_cross_section[k].shape != (0,): if stg.time_cross_section[k].shape != (0,):
stg.depth_2D[k] = ( stg.depth_2D[k] = (
np.zeros((stg.freq[k].shape[0], np.zeros((stg.freq[k].shape[0],
stg.depth_cross_section[k].shape[1], stg.depth_cross_section[k].shape[1],
@ -1961,7 +1965,6 @@ class SedimentCalibrationTab(QWidget):
axis=1)) axis=1))
elif stg.time[k].shape != (0,): elif stg.time[k].shape != (0,):
stg.depth_2D[k] = ( stg.depth_2D[k] = (
np.zeros((stg.freq[k].shape[0], np.zeros((stg.freq[k].shape[0],
stg.depth_cross_section[k].shape[1], stg.depth_cross_section[k].shape[1],
@ -1976,9 +1979,7 @@ class SedimentCalibrationTab(QWidget):
axis=1)) axis=1))
elif stg.depth[k].shape != (0,): elif stg.depth[k].shape != (0,):
if stg.time_cross_section[k].shape != (0,): if stg.time_cross_section[k].shape != (0,):
stg.depth_2D[k] = ( stg.depth_2D[k] = (
np.zeros((stg.freq[k].shape[0], np.zeros((stg.freq[k].shape[0],
stg.depth[k].shape[1], stg.depth[k].shape[1],
@ -1993,7 +1994,6 @@ class SedimentCalibrationTab(QWidget):
axis=1)) axis=1))
elif stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): elif stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
stg.depth_2D[k] = ( stg.depth_2D[k] = (
np.zeros((stg.freq[k].shape[0], np.zeros((stg.freq[k].shape[0],
stg.depth[k].shape[1], stg.depth[k].shape[1],

1
View/signal_processing_tab.py
View File

@ -511,6 +511,7 @@ class SignalProcessingTab(QWidget):
self.icon_clear = QIcon(path_icon("clear.png")) self.icon_clear = QIcon(path_icon("clear.png"))
self.icon_apply = QIcon(path_icon("circle_green_arrow_right.png")) self.icon_apply = QIcon(path_icon("circle_green_arrow_right.png"))
@trace
def full_update(self): def full_update(self):
logger.debug(f"{__name__}: Update") logger.debug(f"{__name__}: Update")
self.blockSignals(True) self.blockSignals(True)

3
tools.py
View File

@ -35,9 +35,10 @@ def trace(func):
f"{head} Return {func.__module__}." + f"{head} Return {func.__module__}." +
f"{func.__qualname__}: {value}" f"{func.__qualname__}: {value}"
) )
dt = t1-t
logger.debug( logger.debug(
f"{head}[TIME] {func.__module__}." + f"{head}[TIME] {func.__module__}." +
f"{func.__qualname__}: {t1-t} sec" f"{func.__qualname__}: {dt:f} sec"
) )
return value return value