# ============================================================================== # # mainwindow.py - AcouSed # # Copyright (C) 2024 INRAE # # # # This program is free software: you can redistribute it and/or modify # # it under the terms of the GNU General Public License as published by # # the Free Software Foundation, either version 3 of the License, or # # (at your option) any later version. # # # # This program is distributed in the hope that it will be useful, # # but WITHOUT ANY WARRANTY; without even the implied warranty of # # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # # GNU General Public License for more details. # # # # You should have received a copy of the GNU General Public License # # along with this program. If not, see . # # by Brahim MOUDJED # # ============================================================================== # # -*- coding: utf-8 -*- import os import logging from cProfile import label from PyQt5.QtWidgets import ( QWidget, QHBoxLayout, QVBoxLayout, QPushButton, QGroupBox, QLabel, QSpinBox, QComboBox, QLineEdit, QSlider, QGridLayout, QMessageBox, QScrollArea, QFileDialog, QSpacerItem, QSizePolicy ) from PyQt5.QtGui import QIcon from PyQt5.QtCore import ( Qt, QCoreApplication, QEvent, pyqtSignal, QPropertyAnimation, QSize ) import numpy as np from copy import deepcopy from astropy.convolution import convolve import matplotlib.pyplot as plt from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolBar from matplotlib.colors import LogNorm, BoundaryNorm from os import path from View.show_popup_combobox import ComboBoxShowPopUpWindow from View.plot_noise_window import PlotNoiseWindow import Translation.constant_string as cs from Model.acoustic_data_loader import AcousticDataLoader import settings as stg from tools import trace _translate = QCoreApplication.translate logger = logging.getLogger("acoused") class SignalProcessingTab(QWidget): ''' This class generates the Signal Processing Tab ''' FillCombobox = pyqtSignal() def __init__(self, widget_tab): super().__init__() self._setup_icons() ### --- General layout of widgets --- # |-----------------| |------------| |-----------------| # | Data to be | | Plot SNR | | Pre-processing | # | pre-processed | |------------| | options | # |-----------------| |-----------------| # |------------------------------------------------------------------------| # |-----------------------| |-----------------------| |------------------| # | Plot pre-processed | | Plot pre-processed | | Pre-processed | # | data 2D field | | data profile | | data list | # |-----------------------| |-----------------------| |------------------| # |------------------------------------------------------------------------| self.verticalLayoutMain = QVBoxLayout(widget_tab) self.horizontalLayout_Top = QHBoxLayout() self.verticalLayoutMain.addLayout(self.horizontalLayout_Top, 5) self.horizontalLayout_Bottom = QHBoxLayout() self.verticalLayoutMain.addLayout(self.horizontalLayout_Bottom, 5) # -------------------------------------------------------------------------------------------------------------- ### --- Layout of groupbox in the top layout box self.groupbox_study_data = QGroupBox() self.horizontalLayout_Top.addWidget(self.groupbox_study_data, 3) self.groupbox_plot_SNR = QGroupBox() self.horizontalLayout_Top.addWidget(self.groupbox_plot_SNR, 5) self.groupbox_pre_processing_option = QGroupBox() self.horizontalLayout_Top.addWidget(self.groupbox_pre_processing_option, 2) # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ # +++ --- Download data to be processed + Download noise file + compute noise data from profile tail + --- +++ # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ self.groupbox_study_data.setTitle("Study data") ### --- Groupbox download data to be processed --- self.verticalLayout_groupbox_study_data = QVBoxLayout(self.groupbox_study_data) self.horizontalLayout_groupbox_data_to_be_processed_Pushbutton_plot_clear_noise = QHBoxLayout() self.verticalLayout_groupbox_study_data.addLayout(self.horizontalLayout_groupbox_data_to_be_processed_Pushbutton_plot_clear_noise) self.groupbox_data_to_be_processed = QGroupBox() self.gridLayout_groupbox_data_to_be_processed = QGridLayout(self.groupbox_data_to_be_processed) self.groupbox_data_to_be_processed.setTitle("Data to be processed") self.combobox_acoustic_data_choice = QComboBox() self.combobox_acoustic_data_choice.setMinimumWidth(200) self.gridLayout_groupbox_data_to_be_processed.addWidget(self.combobox_acoustic_data_choice, 0, 0, 1, 1, Qt.AlignCenter) self.pushbutton_update = QPushButton() self.pushbutton_update.setIcon(self.icon_update) self.gridLayout_groupbox_data_to_be_processed.addWidget(self.pushbutton_update, 0, 1, 1, 1, Qt.AlignCenter) self.horizontalLayout_groupbox_data_to_be_processed_Pushbutton_plot_clear_noise.addWidget( self.groupbox_data_to_be_processed) self.pushbutton_plot_noise_data = QPushButton() self.pushbutton_plot_noise_data.setText("Plot noise field") self.horizontalLayout_groupbox_data_to_be_processed_Pushbutton_plot_clear_noise.addWidget( self.pushbutton_plot_noise_data) self.pushbutton_clear_noise_data = QPushButton() self.pushbutton_clear_noise_data.setIcon(self.icon_clear) self.horizontalLayout_groupbox_data_to_be_processed_Pushbutton_plot_clear_noise.addWidget( self.pushbutton_clear_noise_data) ### --- Groupbox download noise file --- self.groupbox_download_noise_file = QGroupBox() self.groupbox_download_noise_file.setTitle("Noise file") self.groupbox_download_noise_file.setCheckable(True) self.groupbox_download_noise_file.setChecked(True) self.gridLayout_groupbox_noise_file = QGridLayout(self.groupbox_download_noise_file) self.verticalLayout_groupbox_study_data.addWidget(self.groupbox_download_noise_file) self.pushbutton_noise_file = QPushButton() self.pushbutton_noise_file.setIcon(self.icon_folder) self.gridLayout_groupbox_noise_file.addWidget(self.pushbutton_noise_file, 0, 0, 1, 1, Qt.AlignCenter) self.lineEdit_noise_file = QLineEdit() self.gridLayout_groupbox_noise_file.addWidget(self.lineEdit_noise_file, 0, 1, 1, 2, Qt.AlignLeft) ### --- Groupbox compute noise from profile tail --- self.groupbox_compute_noise_from_profile_tail = QGroupBox() self.groupbox_compute_noise_from_profile_tail.setTitle("Profile tail") self.groupbox_compute_noise_from_profile_tail.setCheckable(True) self.groupbox_compute_noise_from_profile_tail.setChecked(False) self.verticalLayout_groupbox_study_data.addWidget(self.groupbox_compute_noise_from_profile_tail) self.horizontalLayout_groupbox_compute_noise_from_profile_tail = QHBoxLayout(self.groupbox_compute_noise_from_profile_tail) self.groupbox_plot_profile_tail = QGroupBox() self.horizontalLayout_groupbox_compute_noise_from_profile_tail.addWidget(self.groupbox_plot_profile_tail) self.verticalLayout_groupbox_plot_profile_tail = QVBoxLayout(self.groupbox_plot_profile_tail) self.canvas_profile_tail = FigureCanvas() self.verticalLayout_groupbox_plot_profile_tail.addWidget(self.canvas_profile_tail) self.horizontalLayout_groupbox_compute_noise_from_profile_tail.addWidget(self.groupbox_plot_profile_tail) self.groupbox_option_profile_tail = QGroupBox() self.horizontalLayout_groupbox_compute_noise_from_profile_tail.addWidget(self.groupbox_option_profile_tail) self.gridLayout_groupbox_option_profile_tail = QGridLayout(self.groupbox_option_profile_tail) self.combobox_freq_noise_from_profile_tail = QComboBox() self.gridLayout_groupbox_option_profile_tail.addWidget(self.combobox_freq_noise_from_profile_tail, 0, 0, 1, 2, Qt.AlignCenter) self.lineEdit_val1 = QLineEdit() self.lineEdit_val1.setText("0.00") self.gridLayout_groupbox_option_profile_tail.addWidget(self.lineEdit_val1, 1, 0, 1, 1, Qt.AlignCenter) self.lineEdit_val2 = QLineEdit() self.lineEdit_val2.setText("0.00") self.gridLayout_groupbox_option_profile_tail.addWidget(self.lineEdit_val2, 1, 1, 1, 1, Qt.AlignCenter) self.pushbutton_plot_profile_tail = QPushButton() self.pushbutton_plot_profile_tail.setIcon(self.icon_apply) self.gridLayout_groupbox_option_profile_tail.addWidget(self.pushbutton_plot_profile_tail, 1, 2, 1, 1, Qt.AlignCenter) self.lineEdit_profile_tail_value = QLineEdit() self.lineEdit_profile_tail_value.setText("0.0000") self.gridLayout_groupbox_option_profile_tail.addWidget(self.lineEdit_profile_tail_value, 2, 0, 1, 1, Qt.AlignCenter) self.label_Volts = QLabel() self.label_Volts.setText("Volts") self.gridLayout_groupbox_option_profile_tail.addWidget(self.label_Volts, 2, 1, 1, 1, Qt.AlignLeft) self.pushbutton_apply_noise_from_profile_tail = QPushButton() self.pushbutton_apply_noise_from_profile_tail.setIcon(self.icon_apply) self.gridLayout_groupbox_option_profile_tail.addWidget(self.pushbutton_apply_noise_from_profile_tail, 2, 2, 1, 1, Qt.AlignCenter) # ++++++++++++++++++++++++ # +++ --- Plot SNR --- +++ # ++++++++++++++++++++++++ self.groupbox_plot_SNR.setTitle("Plot SNR") self.verticalLayout_groupbox_plot_SNR = QVBoxLayout(self.groupbox_plot_SNR) self.canvas_SNR = FigureCanvas() self.toolbar_SNR = NavigationToolBar(self.canvas_SNR, self) self.verticalLayout_groupbox_plot_SNR.addWidget(self.toolbar_SNR) self.scroll_SNR = QScrollArea() self.scroll_SNR.setWidget(self.canvas_SNR) self.scroll_SNR.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOn) self.scroll_SNR.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOn) self.scroll_SNR.setAlignment(Qt.AlignCenter) self.verticalLayout_groupbox_plot_SNR.addWidget(self.scroll_SNR) # +++++++++++++++++++++++++++++++++++++ # +++ --- Pre-processing option --- +++ # +++++++++++++++++++++++++++++++++++++ self.groupbox_pre_processing_option.setTitle("Pre-processing options") self.verticalLayout_groupbox_pre_processing_option = QVBoxLayout(self.groupbox_pre_processing_option) ### --- Groupbox SNR criterion --- self.groupbox_SNR_criterion = QGroupBox() self.groupbox_SNR_criterion.setTitle("SNR filter") self.gridLayout_SNR_criterion = QGridLayout(self.groupbox_SNR_criterion) self.label_SNR_criterion = QLabel("SNR < ") self.gridLayout_SNR_criterion.addWidget(self.label_SNR_criterion, 0, 0, 1, 1, Qt.AlignCenter) self.lineEdit_SNR_criterion = QLineEdit() self.lineEdit_SNR_criterion.setMaximumWidth(60) self.gridLayout_SNR_criterion.addWidget(self.lineEdit_SNR_criterion, 0, 1, 1, 1, Qt.AlignCenter) self.pushbutton_Apply_SNR_filter = QPushButton() self.pushbutton_Apply_SNR_filter.setIcon(self.icon_apply) self.gridLayout_SNR_criterion.addWidget(self.pushbutton_Apply_SNR_filter, 0, 2, 1, 1, Qt.AlignCenter) self.verticalLayout_groupbox_pre_processing_option.addWidget(self.groupbox_SNR_criterion) # --- Rayleigh criterion groupbox --- self.groupbox_Rayleigh_criterion = QGroupBox() self.groupbox_Rayleigh_criterion.setTitle("Despiking the signal") self.groupbox_Rayleigh_criterion.setDisabled(True) self.gridLayout_Rayleigh_criterion = QGridLayout(self.groupbox_Rayleigh_criterion) self.label_Rayleigh_criterion = QLabel() self.label_Rayleigh_criterion.setText("/² <=") self.gridLayout_Rayleigh_criterion.addWidget(self.label_Rayleigh_criterion, 0, 0, 1, 1) self.spinbox_Rayleigh_criterion = QSpinBox() self.spinbox_Rayleigh_criterion.setRange(0, 9999) self.spinbox_Rayleigh_criterion.setValue(10) self.gridLayout_Rayleigh_criterion.addWidget(self.spinbox_Rayleigh_criterion, 0, 1, 1, 1) self.label_4pi = QLabel() self.label_4pi.setText("% x 4/pi") self.gridLayout_Rayleigh_criterion.addWidget(self.label_4pi, 0, 2, 1, 1) self.pushbutton_despiking_signal = QPushButton() self.pushbutton_despiking_signal.setText("Despiking the signal") self.gridLayout_Rayleigh_criterion.addWidget(self.pushbutton_despiking_signal, 0, 3, 1, 1) self.verticalLayout_groupbox_pre_processing_option.addWidget(self.groupbox_Rayleigh_criterion) # --- Average signal groupbox --- self.groupbox_window_size = QGroupBox() self.groupbox_window_size.setTitle("Horizontal averaging") self.gridLayout_groupbox_window_size = QGridLayout(self.groupbox_window_size) self.label_signal_averaging_horizontal = QLabel() self.label_signal_averaging_horizontal.setText("Horizontal +/- ") self.gridLayout_groupbox_window_size.addWidget(self.label_signal_averaging_horizontal, 0, 0, 1, 1, Qt.AlignCenter) self.lineEdit_horizontal_average = QLineEdit() self.lineEdit_horizontal_average.setText("0.00") self.lineEdit_horizontal_average.setMaximumWidth(60) self.gridLayout_groupbox_window_size.addWidget(self.lineEdit_horizontal_average, 0, 1, 1, 1, Qt.AlignCenter) self.label_cells_horizontal = QLabel() self.label_cells_horizontal.setText("cells = +/- ? sec") self.gridLayout_groupbox_window_size.addWidget(self.label_cells_horizontal, 0, 2, 1, 1, Qt.AlignCenter) self.pushbutton_average = QPushButton() self.pushbutton_average.setIcon(self.icon_apply) self.gridLayout_groupbox_window_size.addWidget(self.pushbutton_average, 0, 3, 1, 1, Qt.AlignCenter) self.verticalLayout_groupbox_pre_processing_option.addWidget(self.groupbox_window_size) # # ++++++++++++++++++++++++++++++++++++++++++++++ # # +++ --- Plot BS data filtered with SNR --- +++ # # ++++++++++++++++++++++++++++++++++++++++++++++ # -------------------------------------------------------------------------------------------------------------- ### --- Layout of groupbox in the bottom layout box self.groupbox_plot_pre_processed_data_2D_field = QGroupBox() self.horizontalLayout_Bottom.addWidget(self.groupbox_plot_pre_processed_data_2D_field, 5) self.groupbox_plot_pre_processed_data_profile = QGroupBox() self.horizontalLayout_Bottom.addWidget(self.groupbox_plot_pre_processed_data_profile, 3) self.groupbox_list_pre_processed_data = QGroupBox() self.horizontalLayout_Bottom.addWidget(self.groupbox_list_pre_processed_data, 2) # ++++++++++++++++++++++++++++++++++++++++++++++++ # +++ --- Plot pre-processed data 2D field --- +++ # ++++++++++++++++++++++++++++++++++++++++++++++++ self.groupbox_plot_pre_processed_data_2D_field.setTitle("Display pre-processed data 2D fields") self.verticalLayout_groupbox_plot_pre_processed_data_2D_field = QVBoxLayout( self.groupbox_plot_pre_processed_data_2D_field) self.canvas_BS = FigureCanvas() self.toolbar_BS = NavigationToolBar(self.canvas_BS, self) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.addWidget(self.toolbar_BS) self.scroll_BS = QScrollArea() self.scroll_BS.setWidget(self.canvas_BS) self.scroll_BS.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff) self.scroll_BS.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOn) self.scroll_BS.setAlignment(Qt.AlignCenter) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.addWidget(self.scroll_BS) # +++++++++++++++++++++++++++++++++++++++++++++++ # +++ --- Plot pre-processed data profile --- +++ # +++++++++++++++++++++++++++++++++++++++++++++++ self.groupbox_plot_pre_processed_data_profile.setTitle("Display pre-processed data profile") self.verticalLayout_groupbox_plot_pre_processed_data_2D_profile = QVBoxLayout( self.groupbox_plot_pre_processed_data_profile) self.horizontalLayout_profile_frequency = QHBoxLayout() self.verticalLayout_groupbox_plot_pre_processed_data_2D_profile.addLayout( self.horizontalLayout_profile_frequency) self.spacerItem_frequency_profile = QSpacerItem(50, 10, QSizePolicy.Expanding, QSizePolicy.Minimum) self.horizontalLayout_profile_frequency.addSpacerItem(self.spacerItem_frequency_profile) self.combobox_frequency_profile = QComboBox() self.horizontalLayout_profile_frequency.addWidget(self.combobox_frequency_profile) self.groupbox_plot_profile = QGroupBox() self.verticalLayout_groupbox_plot_profile = QVBoxLayout(self.groupbox_plot_profile) self.canvas_profile = FigureCanvas() self.toolbar_profile = NavigationToolBar(self.canvas_profile, self) self.verticalLayout_groupbox_plot_profile.addWidget(self.toolbar_profile) self.verticalLayout_groupbox_plot_profile.addWidget(self.canvas_profile) self.verticalLayout_groupbox_plot_pre_processed_data_2D_profile.addWidget(self.groupbox_plot_profile) # --- Slider for moving the profile --- self.horizontalLayout_slider = QHBoxLayout() self.verticalLayout_groupbox_plot_pre_processed_data_2D_profile.addLayout(self.horizontalLayout_slider) self.pushbutton_slider_left_to_begin = QPushButton() self.pushbutton_slider_left_to_begin.setIcon(self.icon_triangle_left_to_begin) self.horizontalLayout_slider.addWidget(self.pushbutton_slider_left_to_begin) self.pushbutton_slider_left = QPushButton() self.pushbutton_slider_left.setIcon(self.icon_triangle_left) self.horizontalLayout_slider.addWidget(self.pushbutton_slider_left) self.lineEdit_slider = QLineEdit() self.lineEdit_slider.setText("1") self.lineEdit_slider.setFixedWidth(50) self.horizontalLayout_slider.addWidget(self.lineEdit_slider) self.pushbutton_slider_right = QPushButton() self.pushbutton_slider_right.setIcon(self.icon_triangle_right) self.horizontalLayout_slider.addWidget(self.pushbutton_slider_right) self.pushbutton_slider_right_to_end = QPushButton() self.pushbutton_slider_right_to_end.setIcon(self.icon_triangle_right_to_end) self.horizontalLayout_slider.addWidget(self.pushbutton_slider_right_to_end) self.slider = QSlider() self.horizontalLayout_slider.addWidget(self.slider, 9) self.slider.setOrientation(Qt.Horizontal) self.slider.setCursor(Qt.OpenHandCursor) self.slider.setMinimum(1) self.slider.setMaximum(10) self.slider.setTickInterval(1) self.slider.setValue(1) # ++++++++++++++++++++++++++++++++++++++++++ # +++ --- List of pre-processed data --- +++ # ++++++++++++++++++++++++++++++++++++++++++ self.groupbox_list_pre_processed_data.setTitle("List pre-processed data: user label") self.verticalLayout_groupbox_list_pre_processed_data = QVBoxLayout(self.groupbox_list_pre_processed_data) # Create a scroll area self.scrollArea_list_preprocessed_data = QScrollArea() self.verticalLayout_groupbox_list_pre_processed_data.addWidget(self.scrollArea_list_preprocessed_data) # Set scrollbar policies self.scrollArea_list_preprocessed_data.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff) self.scrollArea_list_preprocessed_data.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOn) self.scroll_BS.setAlignment(Qt.AlignLeft) # Create a widget to be scrolled self.widget_scrollArea_list_preprocessed_data = QWidget() self.verticalLayout_scrollArea_list_pre_processed_data = QVBoxLayout() self.widget_scrollArea_list_preprocessed_data.setLayout(self.verticalLayout_scrollArea_list_pre_processed_data) # Add content to the widget (labels in this example) for i in range(20): exec("self.lineEdit_list_pre_processed_data_" + str(i) + "= QLineEdit()") eval("self.verticalLayout_scrollArea_list_pre_processed_data.addWidget(" "self.lineEdit_list_pre_processed_data_" + str(i) + ")") eval("self.lineEdit_list_pre_processed_data_" + str(i) + ".setDisabled(True)") # Set the widget as the scroll area's widget self.scrollArea_list_preprocessed_data.setWidget(self.widget_scrollArea_list_preprocessed_data) self.scrollArea_list_preprocessed_data.setWidgetResizable(True) # -------------------------------------------------------------------------------------------------------------- # -------------------------------------------------------------------------------------------------------------- # +++++++++ CONNECT SIGNAL OF WIDGET TO SLOT FUNCTION +++++++++ # -------------------------------------------------------------------------------------------------------------- # -------------------------------------------------------------------------------------------------------------- self.pushbutton_update.clicked.connect(self.update_SignalPreprocessingTab) # self.pushbutton_update.clicked.connect(self.compute_average_profile_tail) # self.pushbutton_update.clicked.connect(self.plot_averaged_profile_tail) self.combobox_acoustic_data_choice.currentIndexChanged.connect(self.combobox_acoustic_data_choice_change_index) self.groupbox_download_noise_file.toggled.connect(self.groupbox_download_noise_file_toggle) self.groupbox_compute_noise_from_profile_tail.toggled.connect(self.groupbox_option_profile_tail_toggle) self.pushbutton_noise_file.clicked.connect(self.open_dialog_box) self.pushbutton_plot_noise_data.clicked.connect(self.open_plot_noise_window) self.pushbutton_clear_noise_data.clicked.connect(self.clear_noise_data) self.pushbutton_plot_profile_tail.clicked.connect(self.compute_average_profile_tail) self.pushbutton_plot_profile_tail.clicked.connect(self.replot) self.pushbutton_apply_noise_from_profile_tail.clicked.connect(self.compute_noise_from_profile_tail_value) self.pushbutton_apply_noise_from_profile_tail.clicked.connect(self.replot) self.combobox_freq_noise_from_profile_tail.currentIndexChanged.connect(self.compute_average_profile_tail) self.combobox_freq_noise_from_profile_tail.currentIndexChanged.connect(self.plot_averaged_profile_tail) self.pushbutton_Apply_SNR_filter.clicked.connect(self.remove_point_with_snr_filter) self.pushbutton_Apply_SNR_filter.clicked.connect(self.replot) self.lineEdit_horizontal_average.returnPressed.connect(self.update_label_cells_sec) self.pushbutton_average.clicked.connect(self.compute_averaged_BS_data) self.pushbutton_slider_left_to_begin.clicked.connect(self.slide_profile_number_to_begin) self.pushbutton_slider_left.clicked.connect(self.slide_profile_number_to_left) self.lineEdit_slider.returnPressed.connect(self.profile_number_on_lineEdit) self.pushbutton_slider_right.clicked.connect(self.slide_profile_number_to_right) self.pushbutton_slider_right_to_end.clicked.connect(self.slide_profile_number_to_end) self.slider.valueChanged.connect(self.update_lineEdit_by_moving_slider) self.slider.valueChanged.connect(self.update_plot_pre_processed_profile) def _setup_icons(self): def path_icon(icon): return os.path.join( "icons", icon ) self.icon_folder = QIcon(path_icon("folder.png")) self.icon_triangle_left = QIcon(path_icon("triangle_left.png")) self.icon_triangle_right = QIcon(path_icon("triangle_right.png")) self.icon_triangle_left_to_begin = QIcon( path_icon("triangle_left_to_begin.png") ) self.icon_triangle_right_to_end = QIcon( path_icon("triangle_right_to_end.png") ) self.icon_update = QIcon(path_icon("update.png")) self.icon_clear = QIcon(path_icon("clear.png")) self.icon_apply = QIcon(path_icon("circle_green_arrow_right.png")) # -------------------------------------------------------------------------------------------------------------- # -------------------------------------------------------------------------------------------------------------- # +++++++++ FUNCTION +++++++++ # -------------------------------------------------------------------------------------------------------------- # -------------------------------------------------------------------------------------------------------------- def update_SignalPreprocessingTab(self): """ The tab is updated in two cases : - the user remove a file (in the list widget) in the first tab (Acoustic data), so that the combobox of data to be processed is updated, - the user change the limits of one or all the records in the first tab (Acoustic data) """ if len(stg.filename_BS_raw_data) == 0: msgBox = QMessageBox() msgBox.setWindowTitle("Compute noise from profile tail error") msgBox.setIcon(QMessageBox.Warning) msgBox.setText("Download acoustic data in previous tab before updating data") msgBox.setStandardButtons(QMessageBox.Ok) msgBox.exec() else: data_id = self.combobox_acoustic_data_choice.currentIndex() self.combobox_acoustic_data_choice.blockSignals(True) self.combobox_freq_noise_from_profile_tail.blockSignals(True) logger.debug("Update the Signal preprocessing tab...") self.combobox_acoustic_data_choice.clear() self.combobox_acoustic_data_choice.addItems(stg.filename_BS_raw_data) if stg.noise_method[data_id] == 0: self.groupbox_download_noise_file.setChecked(True) self.groupbox_compute_noise_from_profile_tail.setChecked(False) self.groupbox_download_noise_file_toggle() elif stg.noise_method[data_id] == 1: self.groupbox_download_noise_file.setChecked(False) self.groupbox_compute_noise_from_profile_tail.setChecked(True) self.groupbox_option_profile_tail_toggle() self.combobox_freq_noise_from_profile_tail.clear() self.combobox_freq_noise_from_profile_tail.addItems( stg.freq_text[data_id] ) self.recompute() self.replot() logger.debug("Update the Signal preprocessing tab... Done") self.combobox_freq_noise_from_profile_tail.blockSignals(False) self.combobox_acoustic_data_choice.blockSignals(False) @trace def recompute(self, *args): data_id = self.combobox_acoustic_data_choice.currentIndex() self.compute_average_profile_tail() if stg.noise_method[data_id] == 0: if stg.filename_BS_noise_data[data_id] != "": self.load_noise_data_and_compute_SNR() elif stg.noise_method[data_id] == 1: self.compute_noise_from_profile_tail_value() self.compute_averaged_BS_data() @trace def replot(self, *args): self.plot_averaged_profile_tail() self.plot_transect_with_SNR_data() self.plot_pre_processed_BS_signal() self.plot_pre_processed_profile() def activate_list_of_pre_processed_data(self): for i in range(self.combobox_acoustic_data_choice.count()): eval("self.lineEdit_list_pre_processed_data_" + str(i) + ".setDisabled(True)") eval("self.lineEdit_list_pre_processed_data_" + str( self.combobox_acoustic_data_choice.currentIndex()) + ".setEnabled(True)") eval("self.lineEdit_list_pre_processed_data_" + str( self.combobox_acoustic_data_choice.currentIndex()) + ".returnPressed.connect(self.rename_preprocessed_data)") eval("self.lineEdit_list_pre_processed_data_" + str(self.combobox_acoustic_data_choice.currentIndex()) + ".setText(stg.filename_BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()])") def rename_preprocessed_data(self): exec("stg.data_preprocessed[self.combobox_acoustic_data_choice.currentIndex()] = " "self.lineEdit_list_pre_processed_data_" + str(self.combobox_acoustic_data_choice.currentIndex()) + ".text()") # ------------------------------------------------------ def groupbox_download_noise_file_toggle(self): if self.groupbox_download_noise_file.isChecked() == True: self.groupbox_compute_noise_from_profile_tail.setChecked(False) elif self.groupbox_download_noise_file.isChecked() == False: self.groupbox_compute_noise_from_profile_tail.setChecked(True) def groupbox_download_noise_file_size_change(self): duration = 500 self.animation_groupbox_download_noise_file = QPropertyAnimation(self.groupbox_download_noise_file, b"size") self.animation_groupbox_download_noise_file.setDuration(duration) self.animation_groupbox_download_noise_file.setStartValue(QSize(self.groupbox_download_noise_file.width(), self.groupbox_download_noise_file.height())) if self.groupbox_download_noise_file.isChecked(): self.animation_groupbox_download_noise_file.setEndValue( QSize(self.groupbox_download_noise_file.width(), self.groupbox_download_noise_file.sizeHint().height())) else: self.animation_groupbox_download_noise_file.setEndValue(QSize(self.groupbox_download_noise_file.width(), 25)) self.animation_groupbox_download_noise_file.start() def groupbox_option_profile_tail_toggle(self): if self.groupbox_compute_noise_from_profile_tail.isChecked() == True: self.groupbox_download_noise_file.setChecked(False) elif self.groupbox_compute_noise_from_profile_tail.isChecked() == False: self.groupbox_download_noise_file.setChecked(True) def groupbox_option_profile_tail_size_change(self): duration = 500 self.animation_groupbox_option_profile_tail = QPropertyAnimation(self.groupbox_option_profile_tail, b"size") self.animation_groupbox_option_profile_tail.setDuration(duration) self.animation_groupbox_option_profile_tail.setStartValue(QSize(self.groupbox_option_profile_tail.width(), self.groupbox_option_profile_tail.height())) if self.groupbox_option_profile_tail.isChecked(): self.animation_groupbox_option_profile_tail.setEndValue( QSize(self.groupbox_option_profile_tail.width(), self.groupbox_option_profile_tail.sizeHint().height())) else: self.animation_groupbox_option_profile_tail.setEndValue(QSize(self.groupbox_option_profile_tail.width(), 25)) self.animation_groupbox_option_profile_tail.start() # ------------------------------------------------------ @trace def compute_average_profile_tail(self, *args): data_id = self.combobox_acoustic_data_choice.currentIndex() freq_noise_id = self.combobox_freq_noise_from_profile_tail.currentIndex() if ((float(self.lineEdit_val1.text()) == 0) and (float(self.lineEdit_val2.text()) == 0)): if stg.time_cross_section[data_id].shape != (0,): self.lineEdit_val1.setText(str( '%.3f' % np.nanmin( stg.time_cross_section[data_id][ freq_noise_id ] ) )) self.lineEdit_val2.setText(str( '%.3f' % np.nanmax( stg.time_cross_section[data_id][ freq_noise_id ] ) )) elif stg.time[data_id].shape != (0,): self.lineEdit_val1.setText(str( '%.3f' % np.nanmin(stg.time[data_id][ freq_noise_id]))) self.lineEdit_val2.setText(str( '%.3f' % np.nanmax(stg.time[data_id][ freq_noise_id]))) # --- Find index of line edit value --- if stg.time_cross_section[data_id].shape != (0,): time_data = stg.time_cross_section elif stg.time[data_id].shape != (0,): time_data = stg.time val1 = np.where( np.abs( time_data[data_id][freq_noise_id] - float(self.lineEdit_val1.text().replace(",", ".")) ) == np.nanmin( np.abs( time_data[data_id][freq_noise_id] - float(self.lineEdit_val1.text().replace(",", ".")) ) ) )[0][0] val2 = np.where( np.abs( time_data[data_id][freq_noise_id] - float(self.lineEdit_val2.text().replace(",", ".")) ) == np.nanmin( np.abs( time_data[data_id][freq_noise_id] - float(self.lineEdit_val2.text().replace(",", ".")) ) ) )[0][0] stg.BS_mean[data_id] = ( np.nanmean( stg.BS_raw_data[data_id][:, :, val1:val2], axis=2 ) ) @trace def plot_averaged_profile_tail(self, *args): # --- Plot averaged signal --- if len(stg.filename_BS_raw_data) == 0: msgBox = QMessageBox() msgBox.setWindowTitle("Compute noise from profile tail error") msgBox.setIcon(QMessageBox.Warning) msgBox.setText("Download acoustic data in previous tab before computing noise from profile tail") msgBox.setStandardButtons(QMessageBox.Ok) msgBox.exec() elif self.combobox_acoustic_data_choice.count() == 0: msgBox = QMessageBox() msgBox.setWindowTitle("Compute noise from profile tail error") msgBox.setIcon(QMessageBox.Warning) msgBox.setText("Refresh acoustic data before computing noise from profile tail") msgBox.setStandardButtons(QMessageBox.Ok) msgBox.exec() else: if stg.BS_mean[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): self.verticalLayout_groupbox_plot_profile_tail.removeWidget(self.canvas_profile_tail) self.fig_profile_tail, self.axis_profile_tail = plt.subplots(nrows=1, ncols=1, layout='constrained') self.canvas_profile_tail = FigureCanvas(self.fig_profile_tail) self.verticalLayout_groupbox_plot_profile_tail.addWidget(self.canvas_profile_tail) self.axis_profile_tail.plot( -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq_noise_from_profile_tail.currentIndex()], stg.BS_mean[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq_noise_from_profile_tail.currentIndex()], color="blue", linewidth=1) self.axis_profile_tail.plot( -stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ self.combobox_freq_noise_from_profile_tail.currentIndex()], float(self.lineEdit_profile_tail_value.text().replace(",", ".")) * np.ones(stg.depth[self.combobox_acoustic_data_choice.currentIndex()][ self.combobox_freq_noise_from_profile_tail.currentIndex()].shape[0]), linestyle='dashed', linewidth=2, color='red') self.axis_profile_tail.set_yscale('log') self.axis_profile_tail.tick_params(axis='both', labelsize=8) self.axis_profile_tail.text(.98, .03, "Depth (m)", fontsize=8, fontweight='bold', fontname="DejaVu Sans", c="black", alpha=0.9, horizontalalignment='right', verticalalignment='bottom', rotation='horizontal', transform=self.axis_profile_tail.transAxes) self.axis_profile_tail.text(.1, .45, "BS signal (v)", fontsize=8, fontweight='bold', fontname="DejaVu Sans", c="black", alpha=0.9, horizontalalignment='right', verticalalignment='bottom', rotation='vertical', transform=self.axis_profile_tail.transAxes) self.axis_profile_tail.text(.98, .85, stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()][ self.combobox_freq_noise_from_profile_tail.currentIndex()], fontsize=10, fontweight='bold', fontname="DejaVu Sans", c="black", alpha=0.5, horizontalalignment='right', verticalalignment='bottom', transform=self.axis_profile_tail.transAxes) self.fig_profile_tail.canvas.draw_idle() # ------------------------------------------------------ def combobox_acoustic_data_choice_change_index(self): self.combobox_frequency_profile.blockSignals(True) self.compute_average_profile_tail() self.lineEdit_SNR_criterion.setText(str(stg.SNR_filter_value[self.combobox_acoustic_data_choice.currentIndex()])) self.lineEdit_horizontal_average.setText(str(stg.Nb_cells_to_average_BS_signal[self.combobox_acoustic_data_choice.currentIndex()])) self.combobox_frequency_profile.clear() self.combobox_frequency_profile.addItems( [f for f in stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()]]) self.replot() if self.combobox_acoustic_data_choice.count() > 0: for i in range(self.combobox_acoustic_data_choice.count()): eval("self.lineEdit_list_pre_processed_data_" + str(i) + ".setDisabled(True)") # eval("self.lineEdit_list_pre_processed_data_" + str( self.combobox_acoustic_data_choice.currentIndex()) + ".setEnabled(True)") self.combobox_frequency_profile.blockSignals(False) def clear_noise_data(self): if len(stg.filename_BS_raw_data) == 0: pass else: stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.SNR_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.SNR_cross_section[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.SNR_stream_bed[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.time_noise[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.SNR_filter_value[self.combobox_acoustic_data_choice.currentIndex()] = 0 stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) print("stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()]", stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()]) if stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 0: self.lineEdit_noise_file.clear() elif stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 1: self.lineEdit_val1.clear() self.lineEdit_val1.setText("0.00") self.lineEdit_val2.clear() self.lineEdit_val2.setText("0.00") self.lineEdit_profile_tail_value.clear() self.lineEdit_profile_tail_value.setText("0.0000") self.verticalLayout_groupbox_plot_profile_tail.removeWidget(self.canvas_profile_tail) self.canvas_profile_tail = FigureCanvas() self.verticalLayout_groupbox_plot_profile_tail.addWidget(self.canvas_profile_tail) self.lineEdit_SNR_criterion.setText("0.00") self.lineEdit_horizontal_average.setText("0.00") # --- Clear SNR plot --- self.verticalLayout_groupbox_plot_SNR.removeWidget(self.toolbar_SNR) self.verticalLayout_groupbox_plot_SNR.removeWidget(self.scroll_SNR) self.canvas_SNR = FigureCanvas() self.toolbar_SNR = NavigationToolBar(self.canvas_SNR, self) self.scroll_SNR.setWidget(self.canvas_SNR) self.verticalLayout_groupbox_plot_SNR.addWidget(self.toolbar_SNR) self.verticalLayout_groupbox_plot_SNR.addWidget(self.scroll_SNR) # --- Clear BS plot --- self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.removeWidget(self.toolbar_BS) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.removeWidget(self.scroll_BS) self.canvas_BS = FigureCanvas() self.toolbar_BS = NavigationToolBar(self.canvas_BS, self) self.scroll_BS.setWidget(self.canvas_BS) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.addWidget(self.toolbar_BS) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field.addWidget(self.scroll_BS) self.combobox_frequency_profile.clear() self.verticalLayout_groupbox_plot_profile.removeWidget(self.toolbar_profile) self.verticalLayout_groupbox_plot_profile.removeWidget(self.canvas_profile) self.canvas_profile = FigureCanvas() self.toolbar_profile = NavigationToolBar(self.canvas_profile, self) self.verticalLayout_groupbox_plot_profile.addWidget(self.toolbar_profile) self.verticalLayout_groupbox_plot_profile.addWidget(self.canvas_profile) self.slider.setValue(1) self.slider.setMaximum(10) self.slider.setValue(0) self.slider.setMaximum(10) def open_dialog_box(self): if self.combobox_acoustic_data_choice.count() > 0: filename = QFileDialog.getOpenFileNames(self, "AQUAscat Noise file", [stg.path_BS_raw_data[-1] if self.combobox_acoustic_data_choice.count() > 0 else ""][0], "Aquascat file (*.aqa)", options=QFileDialog.DontUseNativeDialog) if filename[0]: dir_name = path.dirname(filename[0][0]) name = path.basename(filename[0][0]) stg.path_BS_noise_data[self.combobox_acoustic_data_choice.currentIndex()] = dir_name stg.filename_BS_noise_data[self.combobox_acoustic_data_choice.currentIndex()] = name try: self.load_noise_data_and_compute_SNR() except ValueError as e: msgBox = QMessageBox() msgBox.setWindowTitle("Download Error") msgBox.setIcon(QMessageBox.Warning) msgBox.setText("Please select a file") msgBox.setStandardButtons(QMessageBox.Ok) msgBox.exec() else: self.lineEdit_noise_file.setText(stg.filename_BS_noise_data[self.combobox_acoustic_data_choice.currentIndex()]) self.lineEdit_noise_file.setToolTip(stg.path_BS_noise_data[self.combobox_acoustic_data_choice.currentIndex()]) self.plot_transect_with_SNR_data() self.combobox_frequency_profile.clear() self.combobox_frequency_profile.addItems([f for f in stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()]]) self.combobox_frequency_profile.currentIndexChanged.connect(self.plot_pre_processed_BS_signal) self.combobox_frequency_profile.currentIndexChanged.connect(self.update_plot_pre_processed_profile) if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): self.slider.setMaximum(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[1]) else: self.slider.setMaximum(stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape[1]) self.plot_pre_processed_BS_signal() self.plot_pre_processed_profile() stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] = 0 self.activate_list_of_pre_processed_data() else: msgBox = QMessageBox() msgBox.setWindowTitle("Download Error") msgBox.setIcon(QMessageBox.Warning) msgBox.setText("Please upload acoustic data") msgBox.setStandardButtons(QMessageBox.Ok) msgBox.exec() def load_noise_data_and_compute_SNR(self): stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] = 0 noise_data = AcousticDataLoader(stg.path_BS_noise_data[self.combobox_acoustic_data_choice.currentIndex()] + "/" + stg.filename_BS_noise_data[self.combobox_acoustic_data_choice.currentIndex()]) stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = noise_data._BS_raw_data stg.time_noise[self.combobox_acoustic_data_choice.currentIndex()] = noise_data._time stg.depth_noise[self.combobox_acoustic_data_choice.currentIndex()] = noise_data._r if stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): noise = np.zeros(stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape) for f, _ in enumerate(noise_data._freq): noise[f, :, :] = np.mean( stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, :, :], axis=(0, 1)) stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] = noise stg.SNR_stream_bed[self.combobox_acoustic_data_choice.currentIndex()] = ( np.divide((stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()] - stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()]) ** 2, stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] ** 2)) elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): noise = np.zeros(stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape) for f, _ in enumerate(noise_data._freq): noise[f, :, :] = np.mean( stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, :, :], axis=(0, 1)) stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] = noise stg.SNR_cross_section[self.combobox_acoustic_data_choice.currentIndex()] = ( np.divide((stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()] - stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()]) ** 2, stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] ** 2)) # stg.SNR_reshape = np.reshape(stg.SNR_cross_section, (stg.r.shape[1] * stg.t.shape[1], stg.freq.shape[0]), order="F") else: noise = np.zeros(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape) for f, _ in enumerate(noise_data._freq): noise[f, :, :] = np.mean( stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, :, :], axis=(0, 1)) stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] = noise stg.SNR_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = ( np.divide((stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()] - stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()]) ** 2, stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] ** 2)) def open_plot_noise_window(self): pnw = PlotNoiseWindow() pnw.exec() @trace def compute_noise_from_profile_tail_value(self, *args): stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] = 1 stg.noise_value[self.combobox_acoustic_data_choice.currentIndex()] = ( float(self.lineEdit_profile_tail_value.text().replace(",", "."))) if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): stg.time_noise[self.combobox_acoustic_data_choice.currentIndex()] = ( stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]) else: stg.time_noise[self.combobox_acoustic_data_choice.currentIndex()] = ( stg.time[self.combobox_acoustic_data_choice.currentIndex()]) if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): stg.depth_noise[self.combobox_acoustic_data_choice.currentIndex()] = ( stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]) else: stg.depth_noise[self.combobox_acoustic_data_choice.currentIndex()] = ( stg.depth[self.combobox_acoustic_data_choice.currentIndex()]) # --- Compute noise from value and compute SNR --- if stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = np.array([]) stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = ( np.full(stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape, float(self.lineEdit_profile_tail_value.text().replace(",", ".")))) stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] = ( stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()][:, :, :stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape[2]]) stg.SNR_stream_bed[self.combobox_acoustic_data_choice.currentIndex()] = ( np.divide((stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()] - stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()]) ** 2, stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] ** 2)) elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = ( np.full(stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape, float(self.lineEdit_profile_tail_value.text().replace(",", ".")))) stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] = ( stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()][:, :, :stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[2]]) stg.SNR_cross_section[self.combobox_acoustic_data_choice.currentIndex()] = ( np.divide((stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()] - stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()]) ** 2, stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] ** 2)) # else: stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = ( np.full(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape, float(self.lineEdit_profile_tail_value.text().replace(",", ".")))) stg.BS_noise_averaged_data[self.combobox_acoustic_data_choice.currentIndex()] = ( stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()]) stg.SNR_raw_data[self.combobox_acoustic_data_choice.currentIndex()] = ( np.divide((stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()] - stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()]) ** 2, stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()] ** 2)) self.combobox_frequency_profile.clear() self.combobox_frequency_profile.addItems( [f for f in stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()]]) # --- Trigger graphic widgets --- if stg.SNR_filter_value[self.combobox_acoustic_data_choice.currentIndex()] == 0: self.lineEdit_SNR_criterion.setText("0.00") else: self.lineEdit_SNR_criterion.setText(str(stg.SNR_filter_value[self.combobox_acoustic_data_choice.currentIndex()])) if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): self.slider.setMaximum(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[1]) else: self.slider.setMaximum(stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape[1]) # self.activate_list_of_pre_processed_data() @trace def plot_noise(self, *args): self.horizontalLayout_groupbox_plot_noise_data.removeWidget(self.canvas_noise) self.fig_noise, self.axis_noise = plt.subplots(nrows=1, ncols=1, layout="constrained") self.canvas_noise = FigureCanvas(self.fig_noise) self.horizontalLayout_groupbox_plot_noise_data.addWidget(self.canvas_noise) val_min = np.nanmin(stg.BS_noise_raw_data[self.combobox_freq_noise.currentIndex(), :, :]) val_max = np.nanmax(stg.BS_noise_raw_data[self.combobox_freq_noise.currentIndex(), :, :]) if val_min == val_max: pcm = self.axis_noise.pcolormesh(stg.time_snr[0, :], -stg.depth[self.combobox_freq_noise.currentIndex(), :], stg.BS_noise_raw_data[self.combobox_freq_noise.currentIndex(), :, :], cmap='viridis') else: if val_min == 0: val_min = 1e-5 pcm = self.axis_noise.pcolormesh(stg.time_snr[0, :], -stg.r[self.combobox_freq_noise.currentIndex(), :], stg.BS_noise_raw_data[self.combobox_freq_noise.currentIndex(), :, :], cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max)) self.axis_noise.tick_params(axis='both', which='minor', labelsize=10) @trace def plot_transect_with_SNR_data(self, *args): # --- Condition if table is not filled --- # if not self.lineEdit_noise_file.text(): if len(stg.BS_noise_raw_data) == 0: msgBox = QMessageBox() msgBox.setWindowTitle("Plot transect Error") msgBox.setIcon(QMessageBox.Warning) msgBox.setText("Load data before plot transect 2D field") msgBox.setStandardButtons(QMessageBox.Ok) msgBox.exec() # elif self.canvas_SNR == None: else: if ((self.combobox_acoustic_data_choice.currentIndex() != -1) and (stg.BS_noise_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,))): self.verticalLayout_groupbox_plot_SNR.removeWidget(self.toolbar_SNR) self.verticalLayout_groupbox_plot_SNR.removeWidget(self.scroll_SNR) self.fig_SNR, self.axis_SNR = plt.subplots(nrows=stg.freq[self.combobox_acoustic_data_choice.currentIndex()].shape[0], ncols=1, sharex=True, sharey=False, layout='constrained') self.canvas_SNR = FigureCanvas(self.fig_SNR) self.toolbar_SNR = NavigationToolBar(self.canvas_SNR, self) self.scroll_SNR.setWidget(self.canvas_SNR) self.verticalLayout_groupbox_plot_SNR.addWidget(self.toolbar_SNR) self.verticalLayout_groupbox_plot_SNR.addWidget(self.scroll_SNR) for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]): if stg.SNR_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): x, y = np.meshgrid( stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :], stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :]) elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): x, y = np.meshgrid( stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :], stg.depth[self.combobox_acoustic_data_choice.currentIndex()][f, :]) else: if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): x, y = np.meshgrid( stg.time[self.combobox_acoustic_data_choice.currentIndex()][f, :], stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :]) elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): x, y = np.meshgrid( stg.time[self.combobox_acoustic_data_choice.currentIndex()][f, :], stg.depth[self.combobox_acoustic_data_choice.currentIndex()][f, :]) val_min = np.nanmin(stg.SNR_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][f, :, :]) val_max = np.nanmax(stg.SNR_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][f, :, :]) if val_min == val_max: levels = np.array([00.1, 1, 2, 10, 100, 1000, 1e6]) bounds = [00.1, 1, 2, 10, 100, 1000, val_max * 1.2] norm = BoundaryNorm(boundaries=bounds, ncolors=300) else: if val_min == 0: val_min = 1e-5 if val_max > 1000: levels = np.array([00.1, 1, 2, 10, 100, 1000, 1e6]) bounds = [00.1, 1, 2, 10, 100, 1000, val_max * 1.2] norm = BoundaryNorm(boundaries=bounds, ncolors=300) else: levels = np.array([00.1, 1, 2, 10, 100, 1000, val_max * 1000 + 1]) bounds = [00.1, 1, 2, 10, 100, 1000, val_max * 1000 + 1] norm = BoundaryNorm(boundaries=bounds, ncolors=300) cf = (self.axis_SNR[f].contourf(x, -y, stg.SNR_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][f, :, :], levels, cmap='gist_rainbow', norm=norm)) elif stg.SNR_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): x, y = np.meshgrid( stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :], stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :]) elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): x, y = np.meshgrid( stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :], stg.depth[self.combobox_acoustic_data_choice.currentIndex()][f, :]) else: if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): x, y = np.meshgrid( stg.time[self.combobox_acoustic_data_choice.currentIndex()][f, :], stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :]) elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): x, y = np.meshgrid( stg.time[self.combobox_acoustic_data_choice.currentIndex()][f, :], stg.depth[self.combobox_acoustic_data_choice.currentIndex()][f, :]) val_min = np.nanmin(stg.SNR_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :, :]) val_max = np.nanmax(stg.SNR_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, :, :]) if val_min == val_max: levels = np.array([00.1, 1, 2, 10, 100, 1000, 1e6]) bounds = [00.1, 1, 2, 10, 100, 1000, val_max * 1.2] norm = BoundaryNorm(boundaries=bounds, ncolors=300) else: if val_min == 0: val_min = 1e-5 if val_max > 1000: levels = np.array([00.1, 1, 2, 10, 100, 1000, 1e6]) bounds = [00.1, 1, 2, 10, 100, 1000, val_max * 1.2] norm = BoundaryNorm(boundaries=bounds, ncolors=300) else: levels = np.array([00.1, 1, 2, 10, 100, 1000, val_max * 1000 + 1]) bounds = [00.1, 1, 2, 10, 100, 1000, val_max * 1000 + 1] norm = BoundaryNorm(boundaries=bounds, ncolors=300) cf = (self.axis_SNR[f].contourf(x, -y, stg.SNR_cross_section[ self.combobox_acoustic_data_choice.currentIndex()][f, :, :], levels, cmap='gist_rainbow', norm=norm)) else: x, y = np.meshgrid(stg.time[self.combobox_acoustic_data_choice.currentIndex()][0, :], stg.depth[self.combobox_acoustic_data_choice.currentIndex()][0, :]) val_min = np.nanmin(stg.SNR_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, :, :]) val_max = np.nanmax(stg.SNR_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, :, :]) if val_min == val_max: levels = np.array([00.1, 1, 2, 10, 100, 1000, 1e6]) bounds = [00.1, 1, 2, 10, 100, 1000, val_max * 1.2] norm = BoundaryNorm(boundaries=bounds, ncolors=300) else: if val_min == 0: val_min = 1e-5 if val_max > 1000: levels = np.array([00.1, 1, 2, 10, 100, 1000, 1e6]) bounds = [00.1, 1, 2, 10, 100, 1000, val_max * 1.2] norm = BoundaryNorm(boundaries=bounds, ncolors=300) else: levels = np.array([00.1, 1, 2, 10, 100, 1000, val_max*1000 + 1]) bounds = [00.1, 1, 2, 10, 100, 1000, val_max * 1000 + 1] norm = BoundaryNorm(boundaries=bounds, ncolors=300) cf = (self.axis_SNR[f].contourf(x, -y, stg.SNR_raw_data[ self.combobox_acoustic_data_choice.currentIndex()][f, :, :], levels, cmap='gist_rainbow', norm=norm)) self.axis_SNR[f].text(1, .70, stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()][f], fontsize=14, fontweight='bold', fontname="DejaVu Sans", c="black", alpha=0.5, horizontalalignment='right', verticalalignment='bottom', transform=self.axis_SNR[f].transAxes) self.fig_SNR.supxlabel('Time (sec)', fontsize=10) self.fig_SNR.supylabel('Depth (m)', fontsize=10) cbar = self.fig_SNR.colorbar(cf, ax=self.axis_SNR[:], shrink=1, location='right') cbar.set_label(label='Signal to Noise Ratio', rotation=270, labelpad=10) cbar.set_ticklabels(['0', '1', '2', '10', '100', r'10$^3$', r'10$^6$']) self.fig_SNR.canvas.draw_idle() else: self.verticalLayout_groupbox_plot_SNR.removeWidget(self.toolbar_SNR) self.verticalLayout_groupbox_plot_SNR.removeWidget(self.scroll_SNR) self.canvas_SNR = FigureCanvas() self.toolbar_SNR = NavigationToolBar(self.canvas_SNR, self) self.scroll_SNR.setWidget(self.canvas_SNR) self.verticalLayout_groupbox_plot_SNR.addWidget(self.toolbar_SNR) self.verticalLayout_groupbox_plot_SNR.addWidget(self.scroll_SNR) def remove_point_with_snr_filter(self): if len(stg.filename_BS_raw_data) == 0: msgBox = QMessageBox() msgBox.setWindowTitle("Compute noise from profile tail error") msgBox.setIcon(QMessageBox.Warning) msgBox.setText("Download acoustic data in previous tab before applying SNR filter") msgBox.setStandardButtons(QMessageBox.Ok) msgBox.exec() elif len(stg.BS_noise_raw_data) == 0: msgBox = QMessageBox() msgBox.setWindowTitle("SNR filter Error") msgBox.setIcon(QMessageBox.Warning) msgBox.setText("Define noise data (file or profile tail) before using SNR filter") msgBox.setStandardButtons(QMessageBox.Ok) msgBox.exec() else: data_id = self.combobox_acoustic_data_choice.currentIndex() stg.SNR_filter_value[data_id] = ( float(self.lineEdit_SNR_criterion.text().replace(",", "."))) if stg.BS_stream_bed[data_id].shape != (0,): stg.BS_stream_bed_pre_process_SNR = deepcopy(stg.BS_stream_bed) for f, _ in enumerate(stg.freq[data_id]): stg.BS_stream_bed_pre_process_SNR[data_id][ f, np.where(stg.SNR_stream_bed[data_id][f, :, :] < float(self.lineEdit_SNR_criterion.text().replace(",", ".")))[0], np.where(stg.SNR_stream_bed[data_id][f, :, :] < float(self.lineEdit_SNR_criterion.text().replace(",", ".")))[1]] \ = np.nan elif stg.BS_cross_section[data_id].shape != (0,): stg.BS_cross_section_pre_process_SNR = deepcopy(stg.BS_cross_section) for f, _ in enumerate(stg.freq[data_id]): stg.BS_cross_section_pre_process_SNR[data_id][ f, np.where(stg.SNR_cross_section[data_id][f, :, :] < float(self.lineEdit_SNR_criterion.text().replace(",", ".")))[0], np.where(stg.SNR_cross_section[data_id][f, :, :] < float(self.lineEdit_SNR_criterion.text().replace(",", ".")))[1]] \ = np.nan else: stg.BS_raw_data_pre_process_SNR = deepcopy(stg.BS_raw_data) for f, _ in enumerate(stg.freq[data_id]): stg.BS_raw_data_pre_process_SNR[data_id][ f, np.where(stg.SNR_raw_data[data_id][f, :, :] < float(self.lineEdit_SNR_criterion.text().replace(",", ".")))[0], np.where(stg.SNR_raw_data[data_id][f, :, :] < float(self.lineEdit_SNR_criterion.text().replace(",", ".")))[1]] \ = np.nan self.compute_averaged_BS_data() @trace def plot_pre_processed_BS_signal(self, *args): data_id = self.combobox_acoustic_data_choice.currentIndex() self.lineEdit_horizontal_average.setText( str(stg.Nb_cells_to_average_BS_signal[data_id]) ) if ((data_id != -1) and (stg.BS_noise_raw_data[data_id].shape != (0,))): self.verticalLayout_groupbox_plot_pre_processed_data_2D_field\ .removeWidget(self.toolbar_BS) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field\ .removeWidget(self.scroll_BS) self.fig_BS, self.axis_BS = plt.subplots( nrows=stg.freq[data_id].shape[0], ncols=1, sharex=True, sharey=False, layout="constrained" ) self.canvas_BS = FigureCanvas(self.fig_BS) self.toolbar_BS = NavigationToolBar(self.canvas_BS, self) self.scroll_BS.setWidget(self.canvas_BS) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field\ .addWidget(self.toolbar_BS) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field\ .addWidget(self.scroll_BS) if stg.time_cross_section[data_id].shape != (0,): logger.info("time_cross_section") if stg.depth_cross_section[data_id].shape != (0,): x_time = stg.time_cross_section[data_id] y_depth = stg.depth_cross_section[data_id] elif stg.depth[data_id].shape != (0,): x_time = stg.time_cross_section[data_id] y_depth = stg.depth[data_id] else: logger.info("time") if stg.depth_cross_section[data_id].shape != (0,): x_time = stg.time[data_id] y_depth = stg.depth_cross_section[data_id] elif stg.depth[data_id].shape != (0,): x_time = stg.time[data_id] y_depth = stg.depth[data_id] for f, _ in enumerate(stg.freq[data_id]): bed = False if stg.BS_stream_bed_pre_process_average[data_id].shape != (0,): BS_data = stg.BS_stream_bed_pre_process_average bed = True elif stg.BS_cross_section_pre_process_average[data_id].shape != (0,): BS_data = stg.BS_cross_section_pre_process_average elif stg.BS_raw_data_pre_process_average[data_id].shape != (0,): BS_data = stg.BS_raw_data_pre_process_average elif stg.BS_stream_bed_pre_process_SNR[data_id].shape != (0,): BS_data = stg.BS_stream_bed_pre_process_SNR bed = True elif stg.BS_cross_section_pre_process_SNR[data_id].shape != (0,): BS_data = stg.BS_cross_section_pre_process_SNR elif stg.BS_raw_data_pre_process_SNR[data_id].shape != (0,): BS_data = stg.BS_raw_data_pre_process_SNR elif stg.BS_stream_bed[data_id].shape != (0,): BS_data = stg.BS_stream_bed bed = True elif stg.BS_cross_section[data_id].shape != (0,): BS_data = stg.BS_cross_section elif stg.BS_raw_data[data_id].shape != (0,): BS_data = stg.BS_raw_data val_min = np.nanmin( BS_data[data_id][f, :, :] ) val_max = np.nanmax( BS_data[data_id][f, :, :] ) if val_min == 0: val_min = 1e-5 pcm = self.axis_BS[f].pcolormesh( x_time[f, :], -y_depth[f, :], BS_data[data_id][f, :, :], cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max) ) if bed: self.axis_BS[f].plot( x_time[f, :], -stg.depth_bottom[data_id], color='black', linewidth=1, linestyle="solid" ) 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 ) # --- Display red line on acoustic recording for profile position --- freq_id = self.combobox_frequency_profile.currentIndex() self.red_line_return, = self.axis_BS[freq_id].plot( x_time[freq_id, self.slider.value() - 1] * np.ones(y_depth.shape[1]), -y_depth[freq_id, :], linestyle="solid", linewidth=2, color="red" ) self.fig_BS.supxlabel('Time (sec)', fontsize=10) self.fig_BS.supylabel('Depth (m)', fontsize=10) cbar = self.fig_BS.colorbar(pcm, ax=self.axis_BS[:], shrink=1, location='right') cbar.set_label(label='Acoustic backscatter signal (V)', rotation=270, labelpad=10) self.fig_BS.canvas.draw_idle() else: self.verticalLayout_groupbox_plot_pre_processed_data_2D_field\ .removeWidget(self.toolbar_BS) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field\ .removeWidget(self.scroll_BS) self.canvas_BS = FigureCanvas() self.toolbar_BS = NavigationToolBar(self.canvas_BS, self) self.scroll_BS.setWidget(self.canvas_BS) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field\ .addWidget(self.toolbar_BS) self.verticalLayout_groupbox_plot_pre_processed_data_2D_field\ .addWidget(self.scroll_BS) def update_label_cells_sec(self): print("Je change la valeur du moyennage") print(stg.nb_profiles_per_sec) print(stg.nb_profiles_per_sec[self.combobox_acoustic_data_choice.currentIndex()][0]) print(self.combobox_acoustic_data_choice.currentIndex()) self.label_cells_horizontal.clear() self.label_cells_horizontal.setText( "cells = +/- " + str((float(self.lineEdit_horizontal_average.text().replace(",", ".")) // 2) * (1 / stg.nb_profiles_per_sec[self.combobox_acoustic_data_choice.currentIndex()][0])) + " sec") @trace def compute_averaged_BS_data(self, *args): if len(stg.filename_BS_raw_data) == 0: msgBox = QMessageBox() msgBox.setWindowTitle("Compute noise from profile tail error") msgBox.setIcon(QMessageBox.Warning) msgBox.setText("Download acoustic data in previous tab before applying SNR filter") msgBox.setStandardButtons(QMessageBox.Ok) msgBox.exec() elif len(stg.BS_noise_raw_data) == 0: msgBox = QMessageBox() msgBox.setWindowTitle("SNR filter Error") msgBox.setIcon(QMessageBox.Warning) msgBox.setText("Define noise data (file or profile tail) before using SNR filter") msgBox.setStandardButtons(QMessageBox.Ok) msgBox.exec() else: data_id = self.combobox_acoustic_data_choice.currentIndex() kernel_avg = np.ones(2 * int(float(self.lineEdit_horizontal_average.text().replace(",", "."))) + 1) print(kernel_avg) stg.Nb_cells_to_average_BS_signal[data_id] = ( float(self.lineEdit_horizontal_average.text().replace(",", "."))) if stg.time_cross_section[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): x_time = stg.time_cross_section[data_id] y_depth = stg.depth_cross_section[data_id] elif stg.depth[data_id].shape != (0,): x_time = stg.time_cross_section[data_id] y_depth = stg.depth[data_id] else: if stg.depth_cross_section[data_id].shape != (0,): x_time = stg.time[data_id] y_depth = stg.depth_cross_section[data_id] elif stg.depth[data_id].shape != (0,): x_time = stg.time[data_id] y_depth = stg.depth[data_id] if stg.BS_stream_bed_pre_process_SNR[data_id].shape != (0,): stg.BS_stream_bed_pre_process_average[data_id] = (deepcopy( stg.BS_stream_bed_pre_process_SNR[data_id])) for f, _ in enumerate(stg.freq[data_id]): for i in range(y_depth.shape[1]): stg.BS_stream_bed_pre_process_average[data_id][f, i, :] = ( convolve(stg.BS_stream_bed_pre_process_SNR[data_id][f, i, :], kernel_avg)) elif stg.BS_cross_section_pre_process_SNR[data_id].shape != (0,): stg.BS_cross_section_pre_process_average[data_id] = (deepcopy( stg.BS_cross_section_pre_process_SNR[data_id])) for f, _ in enumerate(stg.freq[data_id]): for i in range(y_depth.shape[1]): stg.BS_cross_section_pre_process_average[data_id][f, i, :] = ( convolve(stg.BS_cross_section_pre_process_SNR[data_id][f, i, :], kernel_avg)) elif stg.BS_raw_data_pre_process_SNR[data_id].shape != (0,): stg.BS_raw_data_pre_process_average[data_id] = (deepcopy( stg.BS_raw_data_pre_process_SNR[data_id])) for f, _ in enumerate(stg.freq[data_id]): for i in range(y_depth.shape[1]): stg.BS_raw_data_pre_process_average[data_id][f, i, :] = ( convolve(stg.BS_raw_data_pre_process_SNR[data_id][f, i, :], kernel_avg)) elif stg.BS_stream_bed[data_id].shape != (0,): stg.BS_stream_bed_pre_process_average[data_id] = (deepcopy( stg.BS_stream_bed[data_id])) for f, _ in enumerate(stg.freq[data_id]): for i in range(y_depth.shape[1]): stg.BS_stream_bed_pre_process_average[data_id][f, i, :] = ( convolve(stg.BS_stream_bed[data_id][f, i, :], kernel_avg)) elif stg.BS_cross_section[data_id].shape != (0,): stg.BS_cross_section_pre_process_average[data_id] = (deepcopy( stg.BS_cross_section[data_id])) for f, _ in enumerate(stg.freq[data_id]): for i in range(y_depth.shape[1]): stg.BS_cross_section_pre_process_average[data_id][f, i, :] = ( convolve(stg.BS_cross_section[data_id][f, i, :], kernel_avg)) elif stg.BS_raw_data[data_id].shape != (0,): stg.BS_raw_data_pre_process_average[data_id] = (deepcopy( stg.BS_raw_data[data_id])) for f, _ in enumerate(stg.freq[data_id]): for i in range(y_depth.shape[1]): stg.BS_raw_data_pre_process_average[data_id][f, i, :] = ( convolve(stg.BS_raw_data[data_id][f, i, :], kernel_avg)) @trace def plot_pre_processed_profile(self, *args): data_id = self.combobox_acoustic_data_choice.currentIndex() if ((data_id != -1) and (stg.BS_noise_raw_data[data_id].shape != (0,))): self.verticalLayout_groupbox_plot_profile.removeWidget(self.toolbar_profile) self.verticalLayout_groupbox_plot_profile.removeWidget(self.canvas_profile) self.figure_profile, self.axis_profile = plt.subplots(nrows=1, ncols=1, layout="constrained") self.canvas_profile = FigureCanvas(self.figure_profile) self.toolbar_profile = NavigationToolBar(self.canvas_profile, self) self.verticalLayout_groupbox_plot_profile.addWidget(self.toolbar_profile) self.verticalLayout_groupbox_plot_profile.addWidget(self.canvas_profile) # --- PLot profile --- if stg.BS_stream_bed_pre_process_average[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_cross_section_pre_process_average[self.combobox_frequency_profile.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_raw_data_pre_process_average[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_stream_bed_pre_process_SNR[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_cross_section_pre_process_SNR[self.combobox_frequency_profile.currentIndex()].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_raw_data_pre_process_SNR[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_stream_bed[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_cross_section[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_raw_data[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) self.axis_profile.text( .95, .05, stg.freq_text[data_id][ self.combobox_frequency_profile.currentIndex()], fontsize=10, fontweight='bold', fontname="DejaVu Sans", fontstyle="normal", c="black", alpha=0.2, horizontalalignment='right', verticalalignment='bottom', transform=self.axis_profile.transAxes) self.axis_profile.set_xlabel("Acoustic Backscatter Signal (V)") self.axis_profile.set_ylabel("Depth (m)") self.figure_profile.canvas.draw_idle() else: self.combobox_frequency_profile.clear() self.verticalLayout_groupbox_plot_profile.removeWidget(self.toolbar_profile) self.verticalLayout_groupbox_plot_profile.removeWidget(self.canvas_profile) self.canvas_profile = FigureCanvas() self.toolbar_profile = NavigationToolBar(self.canvas_profile, self) self.verticalLayout_groupbox_plot_profile.addWidget(self.toolbar_profile) self.verticalLayout_groupbox_plot_profile.addWidget(self.canvas_profile) self.slider.setValue(1) self.slider.setMaximum(10) def update_plot_pre_processed_profile(self): data_id = self.combobox_acoustic_data_choice.currentIndex() if ((data_id != -1) and (stg.BS_noise_raw_data[data_id].shape != (0,))): self.axis_profile.cla() # --- PLot profile --- if stg.BS_stream_bed_pre_process_average[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_cross_section_pre_process_average[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_raw_data_pre_process_average[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data_pre_process_average[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_stream_bed_pre_process_SNR[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_cross_section_pre_process_SNR[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_raw_data_pre_process_SNR[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data_pre_process_SNR[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_stream_bed[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_stream_bed[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_cross_section[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.BS_raw_data[data_id].shape != (0,): if stg.depth_cross_section[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) elif stg.depth[data_id].shape != (0,): self.axis_profile.plot( stg.BS_raw_data[data_id][ self.combobox_frequency_profile.currentIndex(), :, self.slider.value() - 1], -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :], linestyle='solid', color='k', linewidth=1) self.axis_profile.text( .95, .05, stg.freq_text[data_id][ self.combobox_frequency_profile.currentIndex()], fontsize=10, fontweight='bold', fontname="DejaVu Sans", fontstyle="normal", c="black", alpha=0.2, horizontalalignment='right', verticalalignment='bottom', transform=self.axis_profile.transAxes) self.axis_profile.set_xlabel("Acoustic Backscatter Signal (V)") self.axis_profile.set_ylabel("Depth (m)") self.figure_profile.canvas.draw_idle() # --- Update red line position on transect --- if stg.depth_cross_section[data_id].shape != (0,): if stg.time_cross_section[data_id].shape != (0,): self.red_line_return.set_data( stg.time_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), self.slider.value()-1] * np.ones(stg.depth_cross_section[data_id].shape[1]), -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :]) elif stg.time[data_id].shape != (0,): self.red_line_return.set_data( stg.time[data_id][ self.combobox_frequency_profile.currentIndex(), self.slider.value() - 1] * np.ones(stg.depth_cross_section[data_id].shape[1]), -stg.depth_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), :]) elif stg.depth[data_id].shape != (0,): if stg.time_cross_section[data_id].shape != (0,): self.red_line_return.set_data( stg.time_cross_section[data_id][ self.combobox_frequency_profile.currentIndex(), self.slider.value() - 1] * np.ones(stg.depth[data_id].shape[1]), -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :]) elif stg.time[data_id].shape != (0,): self.red_line_return.set_data( stg.time[data_id][ self.combobox_frequency_profile.currentIndex(), self.slider.value() - 1] * np.ones(stg.depth[data_id].shape[1]), -stg.depth[data_id][ self.combobox_frequency_profile.currentIndex(), :]) self.fig_BS.canvas.draw_idle() # ------------------------------------- Connect Push Button Load Data + Slider ------------------------------------- def slide_profile_number_to_begin(self): self.slider.setValue(int(self.slider.minimum())) self.update_lineEdit_by_moving_slider() def slide_profile_number_to_right(self): self.slider.setValue(int(self.slider.value()) + 1) self.update_lineEdit_by_moving_slider() def slide_profile_number_to_left(self): self.slider.setValue(int(self.slider.value()) - 1) self.update_lineEdit_by_moving_slider() def slide_profile_number_to_end(self): self.slider.setValue(int(self.slider.maximum())) self.update_lineEdit_by_moving_slider() def profile_number_on_lineEdit(self): if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): self.slider.setValue( int(np.where( np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_frequency_profile.currentIndex()] - float(self.lineEdit_slider.text().replace(",", "."))) == np.nanmin( np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_frequency_profile.currentIndex()] - float(self.lineEdit_slider.text().replace(",", ".")))))[0][0])) else: self.slider.setValue( int(np.where( np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_frequency_profile.currentIndex()] - float(self.lineEdit_slider.text().replace(",", "."))) == np.nanmin( np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_frequency_profile.currentIndex()] - float(self.lineEdit_slider.text().replace(",", ".")))))[0][0])) def update_lineEdit_by_moving_slider(self): if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,): self.lineEdit_slider.setText( str(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][ self.combobox_frequency_profile.currentIndex(), self.slider.value()-1])) else: self.lineEdit_slider.setText( str(stg.time[self.combobox_acoustic_data_choice.currentIndex()][ self.combobox_frequency_profile.currentIndex(), self.slider.value()-1]))