parouby
/
acoused
mirror of https://forgemia.inra.fr/theophile.terraz/acoused
1
0
Fork 0
Code Issues Packages Projects Releases Activity

Commit with minor modifications

dev-brahim
brahim 2023-09-27 11:46:58 +02:00
parent cd33f9d85c
commit e0b76447e6
4 changed files with 65 additions and 24 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

7
View/acoustic_data_tab.py
View File

@ -28,7 +28,7 @@ import Translation.constant_string as cs
from Model.TableModel import TableModel
from Model.AquascatDataLoader import RawAquascatData
from Model.acoustic_data_loader import AcousticDataLoader
from View.window_noise_level_averaged_profile import WindowNoiseLevelTailAveragedProfile
# from View.window_noise_level_averaged_profile import WindowNoiseLevelTailAveragedProfile
from View.sample_data_tab import SampleDataTab
@ -717,6 +717,7 @@ class AcousticDataTab(QWidget):
try:
stg.path_BS_noise_data = dir_name
stg.filename_BS_noise_data = name
self.load_noise_data_and_compute_SNR()
except ValueError as e:
msgBox = QMessageBox()
msgBox.setWindowTitle("Download Error")
@ -725,7 +726,6 @@ class AcousticDataTab(QWidget):
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox.exec()
else:
self.load_noise_data_and_compute_SNR()
self.lineEdit_noise_file.setText(stg.filename_BS_noise_data)
self.lineEdit_noise_file.setToolTip(stg.path_BS_noise_data)
self.label_date_groupbox_noise_file.setText(
@ -922,10 +922,13 @@ class AcousticDataTab(QWidget):
# --- Backscatter acoustic signal is recorded for next tab ---
stg.BS_data = stg.BS_raw_data[:, :, np.where(np.round(stg.time, 2) == self.spinbox_tmin.value())[0][0]:
np.where(np.round(stg.time, 2) == self.spinbox_tmax.value())[0][0]]
print("stg.time shape ", stg.time.shape)
stg.t = stg.time[np.where(np.round(stg.time, 2) == self.spinbox_tmin.value())[0][0]:
np.where(np.round(stg.time, 2) == self.spinbox_tmax.value())[0][0]]
print("stg.t shape ", stg.t.shape)
stg.r_2D = stg.r_2D[:, np.where(np.round(stg.time, 2) == self.spinbox_tmin.value())[0][0]:
np.where(np.round(stg.time, 2) == self.spinbox_tmax.value())[0][0]]
print("stg.r shape ", stg.r_2D.shape)
for f in range(stg.freq.shape[0]):
self.axis_BS[f].cla()

2
View/acoustic_inversion_tab.py
View File

@ -333,6 +333,8 @@ class AcousticInversionTab(QWidget):
int(stg.frequencies_to_compute_VBI[1, 0])], :],
stg.r_2D, stg.kt_corrected_3D))
else:
print("stg.r_2D.shape ", stg.r_2D.shape)
print("stg.kt_corrected_3D.shape ", stg.kt_corrected_3D.shape)
stg.J_cross_section = (
self.inv_hc.j_cross_section(
stg.BS_data_section_SNR_filter[:, [int(stg.frequencies_to_compute_VBI[0, 0]),

54
View/sample_data_tab.py
View File

@ -16,6 +16,7 @@ from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as Navigatio
from copy import deepcopy
from os import path
import csv
from Model.granulo_loader import GranuloLoader
@ -525,15 +526,24 @@ class SampleDataTab(QWidget):
# --- Function to export data of table ---
def export_table(self):
if self.tableWidget_sample.columnCount() > 10:
print("Export table")
else:
msgBox = QMessageBox()
msgBox.setWindowTitle("Export table Error")
msgBox.setIcon(QMessageBox.Warning)
msgBox.setText("Fill table before export table")
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox.exec()
pass
# if self.tableWidget_sample.columnCount() > 10:
# name = QFileDialog.getSaveFileName(self, 'Save File')
# with open(fichiercsv, 'w', newline='') as csvfile:
# csvwriter = csv.writer(csvfile, delimiter=';', quoting=csv.QUOTE_MINIMAL)
# for row in range(0, self.tableWidget_sample.rowCount()):
# ligne = []
# for col in range(0, self.tableWidget_sample.columnCount()):
# valeurcase = self.tableWidget_sample.item(row, col).text().strip()
# ligne.append(valeurcase)
# csvwriter.writerow(ligne)
# else:
# msgBox = QMessageBox()
# msgBox.setWindowTitle("Export table Error")
# msgBox.setIcon(QMessageBox.Warning)
# msgBox.setText("Fill table before export table")
# msgBox.setStandardButtons(QMessageBox.Ok)
# msgBox.exec()
# ------------------------------------------------------------------------------------------------------------------
# --- Functions to plot samples positions on transect ---
@ -701,7 +711,7 @@ class SampleDataTab(QWidget):
self.axis_plot_sample_position_on_transect.set_yticks([])
self.figure_plot_sample_position_on_transect.canvas.draw_idle()
else: #self.canvas_plot_sample_position_on_transect != None:
elif stg.BS_data_section.size == 0:
val_min = np.nanmin(stg.BS_data[:, stg.freq_bottom_detection, :])
val_max = np.nanmax(stg.BS_data[:, stg.freq_bottom_detection, :])
@ -725,6 +735,30 @@ class SampleDataTab(QWidget):
self.axis_plot_sample_position_on_transect.set_yticks([])
self.figure_plot_sample_position_on_transect.canvas.draw_idle()
else:
val_min = np.nanmin(stg.BS_data_section[:, stg.freq_bottom_detection, :])
val_max = np.nanmax(stg.BS_data_section[:, stg.freq_bottom_detection, :])
if val_min == 0:
val_min = 1e-5
self.axis_plot_sample_position_on_transect.pcolormesh(
stg.t, -stg.r, stg.BS_data_section[:, self.combobox_frequencies.currentIndex(), :],
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
if stg.r_bottom.size != 0:
self.axis_plot_sample_position_on_transect.plot(
stg.t, -stg.r_bottom, color='black', linewidth=1, linestyle="solid")
self.axis_plot_sample_position_on_transect.scatter(stg.sample_time[position_list],
stg.sample_depth[position_list],
linestyle='None', marker="o", s=14, c=color_list)
self.axis_plot_sample_position_on_transect.set_xticks([])
self.axis_plot_sample_position_on_transect.set_yticks([])
self.figure_plot_sample_position_on_transect.canvas.draw_idle()
# ------------------------------------------------------------------------------------------------------------------
# --- Functions to plot total concentration ---

26
View/signal_processing_tab.py
View File

@ -1198,23 +1198,25 @@ class SignalProcessingTab(QWidget):
def update_plot_FCB(self):
for f in range(stg.freq.shape[0]):
if stg.FCB.size != 0:
self.axis_FCB_profile[f].cla()
for f in range(stg.freq.shape[0]):
self.axis_FCB_profile[f].plot(stg.r, stg.FCB[:, f, self.slider.value()], linestyle="solid", linewidth=1, color="k")
self.axis_FCB_profile[f].cla()
# self.axis_FCB_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
self.axis_FCB_profile[f].plot(stg.r, stg.FCB[:, f, self.slider.value()], linestyle="solid", linewidth=1, color="k")
self.axis_FCB_profile[f].text(.95, .05, stg.freq_text[f],
fontsize=10, fontweight='bold', fontname="Ubuntu",
fontstyle="normal", c="black", alpha=0.2,
horizontalalignment='right', verticalalignment='bottom',
transform=self.axis_FCB_profile[f].transAxes)
# self.axis_FCB_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
self.figure_FCB_profile.supylabel("FCB")
self.figure_FCB_profile.supxlabel("Depth (m)")
self.figure_FCB_profile.canvas.draw_idle()
self.axis_FCB_profile[f].text(.95, .05, stg.freq_text[f],
fontsize=10, fontweight='bold', fontname="Ubuntu",
fontstyle="normal", c="black", alpha=0.2,
horizontalalignment='right', verticalalignment='bottom',
transform=self.axis_FCB_profile[f].transAxes)
self.figure_FCB_profile.supylabel("FCB")
self.figure_FCB_profile.supxlabel("Depth (m)")
self.figure_FCB_profile.canvas.draw_idle()