Acoustic data: Add bottom detection setting to SQL and refactoring.

dev
Pierre-Antoine 2025-04-17 17:54:18 +02:00
parent 7bf93bb6d8
commit 24f270a2a4
4 changed files with 286 additions and 343 deletions

View File

@ -106,7 +106,11 @@ class CreateTableForSaveAs:
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
depth_bottom_detection_min FLOAT,
depth_bottom_detection_max FLOAT,
depth_bottom_detection_inverval FLOAT,
SNR_filter_value FLOAT,
Nb_cells_to_average_BS_signal FLOAT
)
"""
@ -435,9 +439,12 @@ class CreateTableForSaveAs:
tmin_index, tmin_value, tmax_index, tmax_value,
rmin_index, rmin_value, rmax_index, rmax_value,
freq_bottom_detection_index, freq_bottom_detection_value,
depth_bottom_detection_min,
depth_bottom_detection_max,
depth_bottom_detection_inverval,
SNR_filter_value, Nb_cells_to_average_BS_signal
)
VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""",
(
stg.acoustic_data[i], stg.temperature,
@ -448,6 +455,9 @@ class CreateTableForSaveAs:
stg.rmax[i][0], stg.rmax[i][1],
stg.freq_bottom_detection[i][0],
stg.freq_bottom_detection[i][1],
stg.depth_bottom_detection_min,
stg.depth_bottom_detection_max,
stg.depth_bottom_detection_interval,
stg.SNR_filter_value[i],
stg.Nb_cells_to_average_BS_signal[i]
)

View File

@ -497,23 +497,30 @@ class ReadTableForOpen:
tmin_index, tmin_value, tmax_index, tmax_value,
rmin_index, rmin_value, rmax_index, rmax_value,
freq_bottom_detection_index, freq_bottom_detection_value,
depth_bottom_detection_min,
depth_bottom_detection_max,
depth_bottom_detection_inverval,
SNR_filter_value, Nb_cells_to_average_BS_signal
FROM Settings
WHERE (acoustic_data = {s})
'''
data = self.execute(query3)
x = data[0]
it = iter(data[0])
stg.temperature = [x[1]][0]
stg.distance_from_ABS_to_free_surface.append(x[2])
stg.tmin.append((x[3], x[4]))
stg.tmax.append((x[5], x[6]))
stg.rmin.append((x[7], x[8]))
stg.rmax.append((x[9], x[10]))
stg.freq_bottom_detection.append((x[11], x[12]))
stg.SNR_filter_value.append(x[13])
stg.Nb_cells_to_average_BS_signal.append(x[14])
acoustic_data = next(it)
stg.temperature = [next(it)][0]
stg.distance_from_ABS_to_free_surface.append(next(it))
stg.tmin.append((next(it), next(it)))
stg.tmax.append((next(it), next(it)))
stg.rmin.append((next(it), next(it)))
stg.rmax.append((next(it), next(it)))
stg.freq_bottom_detection.append((next(it), next(it)))
stg.depth_bottom_detection_min = next(it)
stg.depth_bottom_detection_max = next(it)
stg.depth_bottom_detection_interval = next(it)
stg.SNR_filter_value.append(next(it))
stg.Nb_cells_to_average_BS_signal.append(next(it))
logger.debug(f"stg.temperature: {stg.temperature}")
logger.debug(f"stg.tmin: {stg.tmin}")

View File

@ -750,7 +750,10 @@ class AcousticDataTab(QWidget):
self.fill_table()
self.plot_backscattered_acoustic_signal_recording()
self.plot_profile()
self.update_frequency_combobox()
self.update_bottom_detection_settings()
self.water_attenuation()
self.compute_tmin_tmax()
self.compute_rmin_rmax()
@ -2445,7 +2448,6 @@ class AcousticDataTab(QWidget):
self.fig_BS.canvas.draw_idle()
def update_plot_backscattered_acoustic_signal_recording(self):
# --- Condition if table is filled but transect is not plotted
# --- => Error message if spin box values of tmin or tmax is change
if self.canvas_BS == None:
@ -2455,112 +2457,81 @@ class AcousticDataTab(QWidget):
msgBox.setText("Plot transect before change x-axis value")
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox.exec()
return
else:
data_id = self.fileListWidget.currentRow()
if self.fileListWidget.currentRow() != -1:
if len(self.axis_BS.tolist()) != stg.freq[self.fileListWidget.currentRow()].shape[0]:
self.fig_BS, self.axis_BS = plt.subplots(nrows=stg.freq[self.fileListWidget.currentRow()].shape[0],
if data_id == -1:
return
if len(self.axis_BS.tolist()) != stg.freq[data_id].shape[0]:
self.fig_BS, self.axis_BS = plt.subplots(
nrows=stg.freq[data_id].shape[0],
ncols=1,
sharex=False, sharey=False, layout="constrained")
sharex=False, sharey=False,
layout="constrained"
)
for f, _ in enumerate(stg.freq[self.fileListWidget.currentRow()]):
for f, _ in enumerate(stg.freq[data_id]):
self.axis_BS[f].cla()
if stg.BS_cross_section[self.fileListWidget.currentRow()].shape != (0,):
val_min = np.nanmin(stg.BS_cross_section[self.fileListWidget.currentRow()][f, :, :])
val_max = np.nanmax(stg.BS_cross_section[self.fileListWidget.currentRow()][f, :, :])
if val_min == 0:
val_min = 1e-5
if self.combobox_ABS_system_choice.currentIndex() == 1:
pcm = self.axis_BS[f].pcolormesh(
stg.time_cross_section[self.fileListWidget.currentRow()][f, :],
-stg.depth_cross_section[self.fileListWidget.currentRow()][f, :],
stg.BS_cross_section[self.fileListWidget.currentRow()][f, :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
elif self.combobox_ABS_system_choice.currentIndex() == 2:
pcm = self.axis_BS[f].pcolormesh(
stg.time_cross_section[self.fileListWidget.currentRow()][f, :],
-stg.depth_cross_section[self.fileListWidget.currentRow()][f, :],
np.log(stg.BS_cross_section[self.fileListWidget.currentRow()][f, :,
:]),
cmap='Blues')
# --- Plot red solid line on transect to visualize position of plotted profile ---
slider_value = \
[self.slider.value() - 1 if self.slider.value() - 1 <=
stg.time_cross_section[self.fileListWidget.currentRow()].shape[
1] - 1
else np.max(stg.time_cross_section[self.fileListWidget.currentRow()].shape[1] - 1)][0]
self.axis_BS[self.combobox_frequency_profile.currentIndex()].plot(
stg.time_cross_section[self.fileListWidget.currentRow()][
0, # self.combobox_frequency_profile.currentIndex(),
slider_value] * np.ones(
stg.depth_cross_section[self.fileListWidget.currentRow()].shape[1]),
-stg.depth_cross_section[self.fileListWidget.currentRow()][
self.combobox_frequency_profile.currentIndex(), :],
color='red', linestyle="solid", linewidth=2)
# --- Plot river bottom line ---
if stg.depth_bottom[self.fileListWidget.currentRow()].shape != (0,):
self.axis_BS[f].plot(stg.time_cross_section[self.fileListWidget.currentRow()][
self.combobox_frequency_bathymetry.currentIndex(), :],
-stg.depth_bottom[self.fileListWidget.currentRow()],
color='black', linewidth=1, linestyle="solid")
if stg.BS_cross_section[data_id].shape != (0,):
BS_data = stg.BS_cross_section
time_data = stg.time_cross_section
depth_data = stg.depth_cross_section
else:
BS_data = stg.BS_raw_data
time_data = stg.time
depth_data = stg.depth
val_min = np.nanmin(BS_data[data_id][f, :, :])
val_max = np.nanmax(BS_data[data_id][f, :, :])
val_min = np.nanmin(stg.BS_raw_data[self.fileListWidget.currentRow()][f, :, :])
val_max = np.nanmax(stg.BS_raw_data[self.fileListWidget.currentRow()][f, :, :])
if val_min == 0:
val_min = 1e-5
if self.combobox_ABS_system_choice.currentIndex() == 1:
pcm = self.axis_BS[f].pcolormesh(stg.time[self.fileListWidget.currentRow()][f, :],
-stg.depth[self.fileListWidget.currentRow()][f,
:],
stg.BS_raw_data[self.fileListWidget.currentRow()][f, :,
:],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
pcm = self.axis_BS[f].pcolormesh(
time_data[data_id][f, :],
-depth_data[data_id][f, :],
BS_data[data_id][f, :, :],
cmap='viridis',
norm=LogNorm(vmin=val_min, vmax=val_max)
)
elif self.combobox_ABS_system_choice.currentIndex() == 2:
pcm = self.axis_BS[f].pcolormesh(stg.time[self.fileListWidget.currentRow()][f, :],
-stg.depth[self.fileListWidget.currentRow()][f,
:],
np.log(
stg.BS_raw_data[self.fileListWidget.currentRow()][f,
:, :]),
cmap='Blues')
pcm = self.axis_BS[f].pcolormesh(
time_data[data_id][f, :],
-depth_data[data_id][f, :],
np.log(BS_data[data_id][f, :, :]),
cmap='Blues'
)
# --- Plot red solid line on transect to visualize position of plotted profile ---
slider_value = \
[self.slider.value() - 1 if self.slider.value() - 1 <=
stg.time[self.fileListWidget.currentRow()].shape[
1] - 1
else np.max(stg.time[self.fileListWidget.currentRow()].shape[1] - 1)][0]
slider_value = [
self.slider.value() - 1
if self.slider.value() - 1 <= time_data[data_id].shape[1] - 1
else np.max(time_data[data_id].shape[1] - 1)
][0]
self.axis_BS[self.combobox_frequency_profile.currentIndex()].plot(
stg.time[self.fileListWidget.currentRow()][0, slider_value] *
np.ones(stg.depth[self.fileListWidget.currentRow()].shape[1]),
-stg.depth[self.fileListWidget.currentRow()][
self.combobox_frequency_profile.currentIndex(), :],
color='red', linestyle="solid", linewidth=2)
freq_id = self.combobox_frequency_profile.currentIndex()
self.axis_BS[freq_id].plot(
time_data[data_id][0, slider_value] * np.ones(
depth_data[data_id].shape[1]
),
-depth_data[data_id][freq_id, :],
color='red', linestyle="solid", linewidth=2
)
# --- Plot river bottom line ---
if stg.depth_bottom[self.fileListWidget.currentRow()].shape != (0,):
self.axis_BS[f].plot(stg.time[self.fileListWidget.currentRow()][
self.combobox_frequency_bathymetry.currentIndex(), :],
-stg.depth_bottom[self.fileListWidget.currentRow()],
color='black', linewidth=1, linestyle="solid")
self.axis_BS[f].text(1, .70, stg.freq_text[self.fileListWidget.currentRow()][f],
fontsize=14, fontweight='bold', fontname="DejaVu Sans", c="black", alpha=0.5,
horizontalalignment='right', verticalalignment='bottom',
transform=self.axis_BS[f].transAxes)
if stg.depth_bottom[data_id].shape != (0,):
self.axis_BS[f].plot(
time_data[data_id][
self.combobox_frequency_bathymetry.currentIndex(), :
],
-stg.depth_bottom[data_id],
color='black', linewidth=1, linestyle="solid"
)
self.fig_BS.supxlabel('Time (sec)', fontsize=10)
self.fig_BS.supylabel('Depth (m)', fontsize=10)
@ -2782,7 +2753,33 @@ class AcousticDataTab(QWidget):
str(stg.time[self.fileListWidget.currentRow()][self.combobox_frequency_profile.currentIndex(), self.slider.value()-1]))
def update_bottom_detection_settings(self):
self.lineEdit_depth_min_bathy.setText(
str(stg.depth_bottom_detection_min)
)
self.lineEdit_depth_max_bathy.setText(
str(stg.depth_bottom_detection_max)
)
self.lineEdit_next_cell_bathy.setText(
str(stg.depth_bottom_detection_interval)
)
def save_bottom_detection_settings(self):
stg.depth_bottom_detection_min = float(
self.lineEdit_depth_min_bathy.text()
)
stg.depth_bottom_detection_max = float(
self.lineEdit_depth_max_bathy.text()
)
stg.depth_bottom_detection_interval = float(
self.lineEdit_next_cell_bathy.text()
)
def detect_bottom(self):
self.save_bottom_detection_settings()
if self.fileListWidget.count() == 0:
msgBox = QMessageBox()
msgBox.setWindowTitle("Detect bottom Error")
@ -2790,7 +2787,7 @@ class AcousticDataTab(QWidget):
msgBox.setText("Load data before compute bathymety algorithm")
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox.exec()
return
elif self.canvas_BS == None:
msgBox = QMessageBox()
msgBox.setWindowTitle("Detect bottom Error")
@ -2798,65 +2795,104 @@ class AcousticDataTab(QWidget):
msgBox.setText("Plot transect before compute bathymety algorithm")
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox.exec()
return
elif self.lineEdit_next_cell_bathy.text() == "0.00":
return
pass
self.detect_bottom_compute()
else:
def detect_bottom_compute(self):
data_id = self.fileListWidget.currentRow()
freq_id = self.combobox_frequency_bathymetry.currentIndex()
freq_text = self.combobox_frequency_bathymetry.currentText()
if stg.BS_cross_section[self.fileListWidget.currentRow()].shape != (0,):
if stg.BS_cross_section[data_id].shape != (0,):
BS_data = stg.BS_cross_section
time_data = stg.time_cross_section
depth_data = stg.depth_cross_section
elif stg.BS_raw_data[data_id].shape != (0,):
BS_data = stg.BS_raw_data
time_data = stg.time
depth_data = stg.depth
stg.freq_bottom_detection[self.fileListWidget.currentRow()] = \
(self.combobox_frequency_bathymetry.currentIndex(), self.combobox_frequency_bathymetry.currentText())
stg.freq_bottom_detection[data_id] = (freq_id, freq_text)
rmin = float("".join(findall("[.0-9]", self.lineEdit_depth_max_bathy.text())))
rmax = float("".join(findall("[.0-9]", self.lineEdit_depth_min_bathy.text())))
rmin = float(
"".join(findall(
"[.0-9]",
self.lineEdit_depth_max_bathy.text()
))
)
rmax = float(
"".join(findall(
"[.0-9]", self.lineEdit_depth_min_bathy.text()
))
)
r_bottom = np.zeros(stg.time_cross_section[self.fileListWidget.currentRow()].shape[1])
val_bottom = np.zeros(stg.time_cross_section[self.fileListWidget.currentRow()].shape[1])
r_bottom = np.zeros(time_data[data_id].shape[1])
val_bottom = np.zeros(time_data[data_id].shape[1])
r_bottom_ind = []
BS_smooth = deepcopy(stg.BS_cross_section[self.fileListWidget.currentRow()][self.combobox_frequency_bathymetry.currentIndex(), :, :])
BS_smooth = deepcopy(BS_data[data_id][freq_id, :, :])
for k in range(stg.time_cross_section[self.fileListWidget.currentRow()].shape[1]):
for k in range(time_data[data_id].shape[1]):
BS_smooth[:, k] = savgol_filter(BS_smooth[:, k], 10, 2)
# ----------- Detecting the bottom -------------
for d in range(stg.time_cross_section[self.fileListWidget.currentRow()].shape[1]):
ind_min = np.where(stg.depth_cross_section[self.fileListWidget.currentRow()][int(self.combobox_frequency_bathymetry.currentIndex()), :] >= rmin)[0][0]
ind_max = np.where(stg.depth_cross_section[self.fileListWidget.currentRow()][int(self.combobox_frequency_bathymetry.currentIndex()), :] <= rmax)[0][-1]
for d in range(time_data[data_id].shape[1]):
ind_min = np.where(
depth_data[data_id][freq_id, :]
>= rmin
)[0][0]
ind_max = np.where(
depth_data[data_id][freq_id, :]
<= rmax
)[0][-1]
# Getting the peak
try:
val_bottom[d] = np.nanmax(BS_smooth[ind_min:ind_max, d])
except ValueError as e:
msgBox = QMessageBox()
msgBox.setWindowTitle("Detect bottom Error")
msgBox.setIcon(QMessageBox.Warning)
msgBox.setText(f"1/ {e} : maximum value of section bottom is not found. \n "
f"Please change parameter of algorithm")
msgBox.setText(
f"1/ {e} : maximum value of section bottom is not found. \n "
f"Please change parameter of algorithm"
)
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox_return = msgBox.exec()
if msgBox_return == msgBox.Ok:
break
else:
ind_bottom = np.where((BS_smooth[ind_min:ind_max, d]) == val_bottom[d])[0][0]
ind_bottom = np.where(
(BS_smooth[ind_min:ind_max, d])
== val_bottom[d]
)[0][0]
np.append(stg.ind_bottom, ind_bottom)
r_bottom[d] = stg.depth_cross_section[self.fileListWidget.currentRow()][self.combobox_frequency_bathymetry.currentIndex(), ind_bottom + ind_min]
r_bottom[d] = depth_data[data_id][
freq_id, ind_bottom + ind_min
]
r_bottom_ind.append(ind_bottom + ind_min)
# Updating the range where we will look for the peak (in the next cell)
rmin = r_bottom[d] - float("".join(findall("[.0-9]", self.lineEdit_next_cell_bathy.text())))
rmax = r_bottom[d] + float("".join(findall("[.0-9]", self.lineEdit_next_cell_bathy.text())))
BS_section_bottom = np.zeros((stg.depth_cross_section[self.fileListWidget.currentRow()].shape[1],
stg.time_cross_section[self.fileListWidget.currentRow()].shape[1]))
# Updating the range where we will look for the peak (in the next cell)
rmin = r_bottom[d] - float(
"".join(findall(
"[.0-9]", self.lineEdit_next_cell_bathy.text()
))
)
rmax = r_bottom[d] + float(
"".join(findall(
"[.0-9]", self.lineEdit_next_cell_bathy.text()
))
)
BS_section_bottom = np.zeros((
depth_data[data_id].shape[1],
time_data[data_id].shape[1]
))
for i in range(BS_section_bottom.shape[0]):
try:
@ -2865,191 +2901,81 @@ class AcousticDataTab(QWidget):
msgBox = QMessageBox()
msgBox.setWindowTitle("Detect bottom Error")
msgBox.setIcon(QMessageBox.Warning)
msgBox.setText(f"2/ {e} : maximum value of section bottom is not found. \n "
f"Please change parameter of algorithm")
msgBox.setText(
f"2/ {e} : maximum value of section bottom is not found. \n "
f"Please change parameter of algorithm"
)
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox_return = msgBox.exec()
if msgBox_return == msgBox.Ok:
break
if BS_section_bottom.sum() > 2:
stg.depth_bottom[data_id] = r_bottom
stg.val_bottom[data_id] = val_bottom
stg.ind_bottom[data_id] = r_bottom_ind
stg.depth_bottom[self.fileListWidget.currentRow()] = r_bottom
stg.val_bottom[self.fileListWidget.currentRow()] = val_bottom
stg.ind_bottom[self.fileListWidget.currentRow()] = r_bottom_ind
BS_stream_bed_copy = deepcopy(stg.BS_cross_section[self.fileListWidget.currentRow()])
for f, _ in enumerate(stg.freq[self.fileListWidget.currentRow()]):
for k, _ in enumerate(stg.depth_bottom[self.fileListWidget.currentRow()]):
BS_stream_bed_copy = deepcopy(BS_data[data_id])
for f, _ in enumerate(stg.freq[data_id]):
for k, _ in enumerate(stg.depth_bottom[data_id]):
BS_stream_bed_copy[
f, np.where(stg.depth_cross_section[self.fileListWidget.currentRow()][self.combobox_frequency_bathymetry.currentIndex(), :]
>= stg.depth_bottom[self.fileListWidget.currentRow()][k])[
0], k] = np.nan
f, np.where(
depth_data[data_id][freq_id, :]
>= stg.depth_bottom[data_id][k]
)[0], k
] = np.nan
stg.BS_stream_bed[self.fileListWidget.currentRow()] = BS_stream_bed_copy
stg.BS_stream_bed[data_id] = BS_stream_bed_copy
# --- Plot transect BS with bathymetry ---
for f, _ in enumerate(stg.freq[self.fileListWidget.currentRow()]):
self.axis_BS[f].cla()
val_min = np.min(stg.BS_raw_data[self.fileListWidget.currentRow()][f, :, :])
val_max = np.max(stg.BS_raw_data[self.fileListWidget.currentRow()][f, :, :])
if val_min == 0:
val_min = 1e-5
if self.combobox_ABS_system_choice.currentIndex() == 1:
pcm = self.axis_BS[f].pcolormesh(stg.time_cross_section[self.fileListWidget.currentRow()][f, :],
-stg.depth_cross_section[self.fileListWidget.currentRow()][f, :],
stg.BS_cross_section[self.fileListWidget.currentRow()][f, :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
elif self.combobox_ABS_system_choice.currentIndex() == 2:
pcm = self.axis_BS[f].pcolormesh(stg.time_cross_section[self.fileListWidget.currentRow()][f, :],
-stg.depth_cross_section[self.fileListWidget.currentRow()][f, :],
np.log(stg.BS_cross_section[self.fileListWidget.currentRow()][f, :, :]),
cmap='Blues')
self.axis_BS[f].plot(stg.time_cross_section[self.fileListWidget.currentRow()][self.combobox_frequency_bathymetry.currentIndex(), :],
-stg.depth_bottom[self.fileListWidget.currentRow()],
color='black', linewidth=1, linestyle="solid")
self.axis_BS[f].text(1, .70, stg.freq_text[self.fileListWidget.currentRow()][f],
fontsize=14, fontweight='bold', fontname="DejaVu Sans", c="black", alpha=0.5,
horizontalalignment='right', verticalalignment='bottom',
transform=self.axis_BS[f].transAxes)
self.detect_bottom_compute_plot_BS_with_bathymetry(
BS_data, time_data, depth_data
)
# --- Update plot profile ---
self.update_plot_profile()
self.fig_BS.canvas.draw_idle()
elif stg.BS_raw_data[self.fileListWidget.currentRow()].shape != (0,):
def detect_bottom_compute_plot_BS_with_bathymetry(
self, BS_data, time_data, depth_data
):
data_id = self.fileListWidget.currentRow()
freq_id = self.combobox_frequency_bathymetry.currentIndex()
stg.freq_bottom_detection[self.fileListWidget.currentRow()] = (
self.combobox_frequency_bathymetry.currentIndex(), self.combobox_frequency_bathymetry.currentText())
# Selecting the range in which we look for the bottom reflection
rmin = float("".join(findall("[.0-9]", self.lineEdit_depth_max_bathy.text())))
rmax = float("".join(findall("[.0-9]", self.lineEdit_depth_min_bathy.text())))
# empty result arrays
r_bottom = np.zeros(stg.time[self.fileListWidget.currentRow()].shape[1])
val_bottom = np.zeros(stg.time[self.fileListWidget.currentRow()].shape[1])
r_bottom_ind = []
BS_smooth = deepcopy(stg.BS_raw_data[self.fileListWidget.currentRow()][
self.combobox_frequency_bathymetry.currentIndex(), :, :])
for k in range(stg.time[self.fileListWidget.currentRow()].shape[1]):
BS_smooth[:, k] = savgol_filter(BS_smooth[:, k], 10, 2)
# ----------- Detecting the bottom -------------
for d in range(stg.time[self.fileListWidget.currentRow()].shape[1]):
# Index of the range where we look for the peak
ind_min = np.where(stg.depth[self.fileListWidget.currentRow()][
int(self.combobox_frequency_bathymetry.currentIndex()), :] >= rmin)[0][0]
ind_max = np.where(stg.depth[self.fileListWidget.currentRow()][
int(self.combobox_frequency_bathymetry.currentIndex()), :] <= rmax)[0][-1]
# Getting the peak
try:
val_bottom[d] = np.nanmax(BS_smooth[ind_min:ind_max, d])
except ValueError as e:
msgBox = QMessageBox()
msgBox.setWindowTitle("Detect bottom Error")
msgBox.setIcon(QMessageBox.Warning)
msgBox.setText(f"1/ {e} : maximum value of section bottom is not found. \n "
f"Please change parameter of algorithm")
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox_return = msgBox.exec()
if msgBox_return == msgBox.Ok:
break # msgBox.close()
else:
# Getting the range cell of the peak
ind_bottom = np.where((BS_smooth[ind_min:ind_max, d]) == val_bottom[d])[0][0]
np.append(stg.ind_bottom, ind_bottom)
r_bottom[d] = stg.depth[self.fileListWidget.currentRow()][
self.combobox_frequency_bathymetry.currentIndex(), ind_bottom + ind_min]
r_bottom_ind.append(ind_bottom + ind_min)
# Updating the range where we will look for the peak (in the next cell)
rmin = r_bottom[d] - float("".join(findall("[.0-9]", self.lineEdit_next_cell_bathy.text())))
rmax = r_bottom[d] + float("".join(findall("[.0-9]", self.lineEdit_next_cell_bathy.text())))
BS_section_bottom = np.zeros((stg.depth[self.fileListWidget.currentRow()].shape[1],
stg.time[self.fileListWidget.currentRow()].shape[1]))
for i in range(BS_section_bottom.shape[0]):
try:
BS_section_bottom[r_bottom_ind[i]][i] = 1
except IndexError as e:
msgBox = QMessageBox()
msgBox.setWindowTitle("Detect bottom Error")
msgBox.setIcon(QMessageBox.Warning)
msgBox.setText(f"2/ {e} : maximum value of section bottom is not found. \n "
f"Please change parameter of algorithm")
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox_return = msgBox.exec()
if msgBox_return == msgBox.Ok:
break # msgBox.close()
if BS_section_bottom.sum() > 2:
# --- Record r_bottom for other tabs ---
stg.depth_bottom[self.fileListWidget.currentRow()] = r_bottom
stg.val_bottom[self.fileListWidget.currentRow()] = val_bottom
stg.ind_bottom[self.fileListWidget.currentRow()] = r_bottom_ind
BS_stream_bed_copy = deepcopy(stg.BS_raw_data[self.fileListWidget.currentRow()])
for f, _ in enumerate(stg.freq[self.fileListWidget.currentRow()]):
for k, _ in enumerate(stg.depth_bottom[self.fileListWidget.currentRow()]):
BS_stream_bed_copy[
f, np.where(stg.depth[self.fileListWidget.currentRow()][
self.combobox_frequency_bathymetry.currentIndex(), :]
>= stg.depth_bottom[self.fileListWidget.currentRow()][k])[
0], k] = np.nan
stg.BS_stream_bed[self.fileListWidget.currentRow()] = BS_stream_bed_copy
# --- Plot transect BS with bathymetry ---
for f, _ in enumerate(stg.freq[self.fileListWidget.currentRow()]):
for f, _ in enumerate(stg.freq[data_id]):
self.axis_BS[f].cla()
val_min = np.min(stg.BS_raw_data[self.fileListWidget.currentRow()][f, :, :])
val_max = np.max(stg.BS_raw_data[self.fileListWidget.currentRow()][f, :, :])
val_min = np.min(stg.BS_raw_data[data_id][f, :, :])
val_max = np.max(stg.BS_raw_data[data_id][f, :, :])
if val_min == 0:
val_min = 1e-5
if self.combobox_ABS_system_choice.currentIndex() == 1:
pcm = self.axis_BS[f].pcolormesh(
stg.time[self.fileListWidget.currentRow()][f, :],
-stg.depth[self.fileListWidget.currentRow()][f, :],
stg.BS_raw_data[self.fileListWidget.currentRow()][f, :, :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
time_data[data_id][f, :],
-depth_data[data_id][f, :],
BS_data[data_id][f, :, :],
cmap='viridis',
norm=LogNorm(vmin=val_min, vmax=val_max)
)
elif self.combobox_ABS_system_choice.currentIndex() == 2:
pcm = self.axis_BS[f].pcolormesh(
stg.time[self.fileListWidget.currentRow()][f, :],
-stg.depth[self.fileListWidget.currentRow()][f, :],
np.log(stg.BS_raw_data[self.fileListWidget.currentRow()][f, :, :]),
cmap='Blues')
time_data[data_id][f, :],
-depth_data[data_id][f, :],
np.log(BS_data[data_id][f, :, :]),
cmap='Blues'
)
self.axis_BS[f].plot(stg.time[self.fileListWidget.currentRow()][
self.combobox_frequency_bathymetry.currentIndex(), :],
-stg.depth_bottom[self.fileListWidget.currentRow()],
color='black', linewidth=1, linestyle="solid")
self.axis_BS[f].plot(
time_data[data_id][freq_id, :],
-stg.depth_bottom[data_id],
color='black', linewidth=1, linestyle="solid"
)
self.axis_BS[f].text(1, .70, stg.freq_text[self.fileListWidget.currentRow()][f],
fontsize=14, fontweight='bold', fontname="DejaVu Sans", c="black",
alpha=0.5,
horizontalalignment='right', verticalalignment='bottom',
transform=self.axis_BS[f].transAxes)
# --- Update plot profile ---
self.update_plot_profile()
self.fig_BS.canvas.draw_idle()
self.axis_BS[f].text(
1, .70, stg.freq_text[data_id][f],
fontsize=14, fontweight='bold',
fontname="DejaVu Sans", c="black", alpha=0.5,
horizontalalignment='right',
verticalalignment='bottom',
transform=self.axis_BS[f].transAxes
)

View File

@ -105,11 +105,11 @@ BS_stream_bed = [] # BS data (raw or cross_section) with detected b
depth_bottom = [] # Depth value of th bottom : 1D array # List of arrays
val_bottom = [] # Level of the BS signal on the bottom : 1D array # List of arrays
ind_bottom = [] # Index of bottom in depth array : list of int # List of lists
freq_bottom_detection = [] # Frequency use to detect the bottom : (index, string) # List of tuple
# depth_bottom_detection_min = [] # Min value to detect bottom on the first vertical # List of float
# depth_bottom_detection_max = [] # Max value to detect bottom on the first vertical # List of float
# depth_bottom_detection_1st_int_area = [] # interval for searching area # List of float
freq_bottom_detection = [] # Frequency use to detect the bottom : (index, string) # List of tuple
depth_bottom_detection_min = [] # Min value to detect bottom on the first vertical # List of float
depth_bottom_detection_max = [] # Max value to detect bottom on the first vertical # List of float
depth_bottom_detection_interval = [] # interval for searching area # List of float
# ----------------------------------------------------------------------------------------------------------------------
# =========================================================