Averaged transect is computed before applying SNR filter + Computing water attenuation is added + transect is plotted without outliers below the section bottom
brahim
parent
ff019e5117
commit
45aa5ae2f5
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@ -17,7 +17,7 @@ from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as Navigatio
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import Translation.constant_string as cs
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from checkable_combobox import CheckableComboBox
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from View.checkable_combobox import CheckableComboBox
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import settings as stg
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@ -7,6 +7,7 @@ from PyQt5.QtCore import Qt, QCoreApplication
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import numpy as np
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from copy import deepcopy
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from scipy.ndimage import convolve1d
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import matplotlib.pyplot as plt
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from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
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@ -82,12 +83,13 @@ class SignalProcessingTab(QWidget):
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self.pushbutton_load_data = QPushButton()
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self.horizontalLayout_pushbutton_load_data_plot_bottom_line.addWidget(self.pushbutton_load_data)
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self.pushbutton_load_data.clicked.connect(self.compute_BS_data_section)
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self.pushbutton_load_data.clicked.connect(self.plot_profile_position_on_transect)
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self.pushbutton_load_data.clicked.connect(self.plot_profile)
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self.combobox_frequency = QComboBox()
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self.horizontalLayout_pushbutton_load_data_plot_bottom_line.addWidget(self.combobox_frequency)
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self.combobox_frequency.currentTextChanged.connect(self.update_plot_profile_position_on_transect)
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# self.combobox_frequency.currentTextChanged.connect(self.update_plot_profile_position_on_transect)
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# +++++++++++++++++++++++++++++++++++++++++++++++++
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# +++ --- GroupBox Display Profile Position --- +++
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@ -149,42 +151,35 @@ class SignalProcessingTab(QWidget):
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self.verticalLayout_groupbox_post_processing = QVBoxLayout(self.groupbox_post_processing)
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self.groupbox_acoustic_profile = QGroupBox()
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self.verticalLayout_groupbox_post_processing.addWidget(self.groupbox_acoustic_profile)
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self.groupbox_rayleigh_criterion = QGroupBox()
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self.verticalLayout_groupbox_post_processing.addWidget(self.groupbox_rayleigh_criterion)
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self.groupbox_window_size = QGroupBox()
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self.verticalLayout_groupbox_post_processing.addWidget(self.groupbox_window_size)
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self.groupbox_rayleigh_criterion = QGroupBox()
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self.verticalLayout_groupbox_post_processing.addWidget(self.groupbox_rayleigh_criterion)
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self.groupbox_acoustic_profile = QGroupBox()
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self.verticalLayout_groupbox_post_processing.addWidget(self.groupbox_acoustic_profile)
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# --- Groupbox acoustic profile ---
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# --- Groupbox Rayleigh criterion ---
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self.gridLayout_groupbox_acoustic_profile = QGridLayout(self.groupbox_acoustic_profile)
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self.gridLayout_rayleigh_criterion = QGridLayout(self.groupbox_rayleigh_criterion)
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# self.checkbox_SNR_criterion = QCheckBox()
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self.label_SNR_criterion = QLabel()
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self.gridLayout_groupbox_acoustic_profile.addWidget(self.label_SNR_criterion, 0, 0, 1, 1)
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self.spinbox_SNR_criterion = QSpinBox()
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self.spinbox_SNR_criterion.setRange(0, 9999)
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self.spinbox_SNR_criterion.setValue(0)
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# self.spinbox_SNR_criterion.setDisabled(True)
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self.gridLayout_groupbox_acoustic_profile.addWidget(self.spinbox_SNR_criterion, 0, 1, 1, 1)
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self.label_Rayleigh_criterion = QLabel()
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self.label_Rayleigh_criterion.setText("<V²>/<V>² <=")
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self.gridLayout_rayleigh_criterion.addWidget(self.label_Rayleigh_criterion, 0, 0, 1, 1)
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# self.checkbox_SNR_criterion.clicked.connect(self.enable_disable_spinbox_snr_value)
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self.spinbox_SNR_criterion.valueChanged.connect(self.remove_point_with_snr_filter)
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self.spinbox_rayleigh_criterion = QSpinBox()
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self.spinbox_rayleigh_criterion.setRange(0, 9999)
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self.spinbox_rayleigh_criterion.setValue(10)
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self.gridLayout_rayleigh_criterion.addWidget(self.spinbox_rayleigh_criterion, 0, 1, 1, 1)
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self.pushbutton_snr_filter = QPushButton()
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self.pushbutton_snr_filter.setText("Apply SNR")
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# self.pushbutton_snr_filter.setDisabled(True)
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self.gridLayout_groupbox_acoustic_profile.addWidget(self.pushbutton_snr_filter, 0, 2, 1, 1)
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self.label_4pi = QLabel()
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self.label_4pi.setText("% x 4/pi")
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self.gridLayout_rayleigh_criterion.addWidget(self.label_4pi, 0, 2, 1, 1)
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# self.spinbox_SNR_criterion.valueChanged.connect(self.update_plot_profiles)
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# self.spinbox_SNR_criterion.valueChanged.connect(self.update_plot_profile_position_on_transect)
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self.pushbutton_snr_filter.clicked.connect(self.update_plot_profile)
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# self.pushbutton_snr_filter.clicked.connect(self.remove_point_with_snr_filter)
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# self.pushbutton_snr_filter.clicked.connect(self.update_plot_profile_position_on_transect)
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self.pushbutton_despiking_signal = QPushButton()
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self.pushbutton_despiking_signal.setText("Despiking the signal")
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self.gridLayout_rayleigh_criterion.addWidget(self.pushbutton_despiking_signal, 0, 3, 1, 1)
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# --- Groupbox Window size ---
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@ -207,56 +202,30 @@ class SignalProcessingTab(QWidget):
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# self.pushbutton_snr_filter.setDisabled(True)
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self.horizontalLayout_groupbox_window_size.addWidget(self.pushbutton_average)
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self.pushbutton_average.clicked.connect(self.update_plot_profile_position_on_transect)
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self.pushbutton_average.clicked.connect(self.plot_averaged_profile)
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# --- Groupbox Rayleigh criterion ---
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# --- Groupbox acoustic profile ---
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# # self.groupbox_rayleigh_criterion.setTitle("Rayleigh criterion")
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# # self.groupbox_despiking_signal = QGroupBox()
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# # self.groupbox_despiking_signal.setTitle("Despiking the signal")
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# # self.verticalLayout_despiking_signal = QVBoxLayout(self.groupbox_despiking_signal)
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# # self.horizontalLayout_despiking_signal_label = QHBoxLayout()
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#
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# # self.gridLayout_rayleigh_criterion = QGridLayout(self.groupbox_rayleigh_criterion)
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# self.horizontalLayout_rayleigh_criterion = QHBoxLayout(self.groupbox_rayleigh_criterion)
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#
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# self.label_Rayleigh_criterion = QLabel()
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# self.label_Rayleigh_criterion.setText("<V²>/<V>² <=")
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# # self.horizontalLayout_despiking_signal_label.addWidget(self.label_Rayleigh_criterion)
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# # self.gridLayout_rayleigh_criterion.addWidget(self.label_Rayleigh_criterion, 0, 0, 1, 1)
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# self.horizontalLayout_rayleigh_criterion.addWidget(self.label_Rayleigh_criterion)
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# # self.lineEdit_despiking_signal_label = QLineEdit()
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# # self.lineEdit_despiking_signal_label.setText("10")
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# self.spinbox_rayleigh_criterion = QSpinBox()
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# self.spinbox_rayleigh_criterion.setRange(0, 9999)
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# self.spinbox_rayleigh_criterion.setValue(10)
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# # self.horizontalLayout_despiking_signal_label.addWidget(self.lineEdit_despiking_signal_label)
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# # self.gridLayout_rayleigh_criterion.addWidget(self.lineEdit_despiking_signal_label, 0, 1, 1, 1)
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# self.horizontalLayout_rayleigh_criterion.addWidget(self.spinbox_rayleigh_criterion)
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# self.label_4pi = QLabel()
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# self.label_4pi.setText("% x 4/pi")
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# # self.horizontalLayout_despiking_signal_label.addWidget(self.label_4pi)
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# # self.gridLayout_rayleigh_criterion.addWidget(self.label_4pi, 0, 2, 1, 1)
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# self.horizontalLayout_rayleigh_criterion.addWidget(self.label_4pi)
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# # self.verticalLayout_despiking_signal.addLayout(self.horizontalLayout_despiking_signal_label)
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# # self.pushbutton_despiking_signal = QPushButton()
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# # self.pushbutton_despiking_signal.setText("Despiking the signal")
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# # self.verticalLayout_despiking_signal.addWidget(self.pushbutton_despiking_signal)
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# self.checkbox_despiked_acoustic_signal = QCheckBox()
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# # self.checkbox_despiked_acoustic_signal.setText("Despiking")
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# self.checkbox_despiked_acoustic_signal.setToolTip("Enable for further computation")
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# # self.gridLayout_rayleigh_criterion.addWidget(self.checkbox_rayleigh_criterion_enable, 0, 3, 1, 1)
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# self.horizontalLayout_rayleigh_criterion.addWidget(self.checkbox_despiked_acoustic_signal)
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# # self.horizontalLayout_averaged_profile_despiking_signal.addWidget(self.groupbox_rayleigh_criterion)
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#
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# # self.verticalLayout_groupbox_averageprofile_despikingsignal.addWidget(self.groupbox_despiking_signal)
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self.gridLayout_groupbox_acoustic_profile = QGridLayout(self.groupbox_acoustic_profile)
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# # self.horizontalLayoutMid_signalProcessing.addWidget(self.groupbox_post_processing, 3)
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# self.verticalLayout_left_SignalProcessingTab.addWidget(self.groupbox_post_processing)
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#
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# # self.horizontalLayoutBottom_signalProcessing = QHBoxLayout()
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# # self.verticalLayout_signalProcessingTab.addLayout(self.horizontalLayoutBottom_signalProcessing, 3)
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#
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# self.checkbox_SNR_criterion = QCheckBox()
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self.label_SNR_criterion = QLabel()
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self.gridLayout_groupbox_acoustic_profile.addWidget(self.label_SNR_criterion, 0, 0, 1, 1)
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self.spinbox_SNR_criterion = QSpinBox()
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self.spinbox_SNR_criterion.setRange(0, 9999)
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self.spinbox_SNR_criterion.setValue(0)
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# self.spinbox_SNR_criterion.setDisabled(True)
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self.gridLayout_groupbox_acoustic_profile.addWidget(self.spinbox_SNR_criterion, 0, 1, 1, 1)
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self.spinbox_SNR_criterion.valueChanged.connect(self.remove_point_with_snr_filter)
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self.pushbutton_snr_filter = QPushButton()
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self.pushbutton_snr_filter.setText("Apply SNR")
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self.gridLayout_groupbox_acoustic_profile.addWidget(self.pushbutton_snr_filter, 0, 2, 1, 1)
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self.pushbutton_snr_filter.clicked.connect(self.update_plot_profile)
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self.pushbutton_snr_filter.clicked.connect(self.update_plot_profile_position_on_transect)
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# ++++++++++++++++++++++++++++++++++++
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# +++ --- GroupBox FCB options --- +++
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@ -264,103 +233,79 @@ class SignalProcessingTab(QWidget):
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self.verticalLayout_groupbox_FCBoption = QVBoxLayout(self.groupbox_FCBoption)
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# --- Groupbox water attenuation ---
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self.groupbox_water_attenuation = QGroupBox()
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self.verticalLayout_groupbox_FCBoption.addWidget(self.groupbox_water_attenuation)
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# self.verticalLayout_groupbox_water_attenuation = QVBoxLayout(self.groupbox_water_attenuation)
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# self.horizontalLayout_waterAttenuationModel_temperature = QHBoxLayout()
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# self.verticalLayout_groupbox_water_attenuation.addLayout(
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# self.horizontalLayout_waterAttenuationModel_temperature)
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#
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# self.combobox_water_attenuation_model = QComboBox()
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# self.combobox_water_attenuation_model.addItem("François & Garrison 1982")
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# self.combobox_water_attenuation_model.addItem("Other model")
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# self.horizontalLayout_waterAttenuationModel_temperature.addWidget(self.combobox_water_attenuation_model)
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#
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# self.label_temperature_water_attenation = QLabel()
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# # self.label_temperature_water_attenation.setText("Temperature:")
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# self.horizontalLayout_waterAttenuationModel_temperature.addWidget(self.label_temperature_water_attenation)
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#
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# # self.lineEdit_temperature_water_attenuation = QLineEdit()
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# self.spinbox_temperature_water_attenuation = QSpinBox()
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# self.horizontalLayout_waterAttenuationModel_temperature.addWidget(self.spinbox_temperature_water_attenuation)
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#
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# self.label_degre_celsius = QLabel()
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# self.label_degre_celsius.setText("°C")
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# self.horizontalLayout_waterAttenuationModel_temperature.addWidget(self.label_degre_celsius)
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#
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# self.horizontalLayout_comboboxFrequencies_WaterAttenuationValue = QHBoxLayout()
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# self.verticalLayout_groupbox_water_attenuation.addLayout(
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# self.horizontalLayout_comboboxFrequencies_WaterAttenuationValue)
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#
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# self.combobox_water_attenuation = QComboBox()
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# self.combobox_water_attenuation.addItem('0.3 MHz')
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# self.combobox_water_attenuation.addItem('0.5 MHz')
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# self.combobox_water_attenuation.addItem('1 MHz')
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# self.combobox_water_attenuation.addItem('5 MHz')
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# # self.combobox_water_attenuation.currentIndexChanged.connect(self.alpha_value_changed)
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#
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# self.horizontalLayout_comboboxFrequencies_WaterAttenuationValue.addWidget(self.combobox_water_attenuation)
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#
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# self.label_water_attenuation = QLabel()
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# self.label_water_attenuation.setText("\u03B1w = 0.02 dB/m")
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# self.label_water_attenuation.setFont(QFont("Ubuntu", 14, QFont.Normal))
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# self.horizontalLayout_comboboxFrequencies_WaterAttenuationValue.addWidget(self.label_water_attenuation)
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# --- Groupbox fit regression line ---
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self.groupbox_fit_regression_line = QGroupBox()
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self.verticalLayout_groupbox_FCBoption.addWidget(self.groupbox_fit_regression_line)
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# self.verticalLayout_groupbox_fit_regression = QVBoxLayout(self.groupbox_fit_regression_line)
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#
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# self.label_alphaS_expression = QLabel()
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# # self.label_alphaS_expression.setText("For homogeneous suspension: dFCB/dr = -2\u03B1<sub>s<\sub>")
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# self.verticalLayout_groupbox_fit_regression.addWidget(self.label_alphaS_expression)
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#
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# self.horizontalLayout_alphaS_computation = QHBoxLayout()
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# self.verticalLayout_groupbox_fit_regression.addLayout(self.horizontalLayout_alphaS_computation)
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#
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# self.combobox_frequency_compute_alphaS = QComboBox()
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# self.combobox_frequency_compute_alphaS.addItem("0.3 MHz")
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# self.combobox_frequency_compute_alphaS.addItem("0.5 MHz")
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# self.combobox_frequency_compute_alphaS.addItem("1 MHz")
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# self.combobox_frequency_compute_alphaS.addItem("5 MHz")
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# self.combobox_frequency_compute_alphaS.addItem("All frequencies")
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# self.horizontalLayout_alphaS_computation.addWidget(self.combobox_frequency_compute_alphaS)
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#
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# self.label_alphaS_computation_from = QLabel()
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# # self.label_alphaS_computation_from.setText("From")
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# self.horizontalLayout_alphaS_computation.addWidget(self.label_alphaS_computation_from)
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#
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# # self.lineEdit_alphaS_computation_from = QLineEdit()
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# self.spinbox_alphaS_computation_from = QDoubleSpinBox()
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# self.spinbox_alphaS_computation_from.setRange(0, 9999)
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# self.horizontalLayout_alphaS_computation.addWidget(self.spinbox_alphaS_computation_from)
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#
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# self.label_alphaS_computation_to = QLabel()
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# # self.label_alphaS_computation_to.setText("to")
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# self.horizontalLayout_alphaS_computation.addWidget(self.label_alphaS_computation_to)
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#
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# # self.lineEdit_alphaS_computation_to = QLineEdit()
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# self.spinbox_alphaS_computation_to = QDoubleSpinBox()
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# self.horizontalLayout_alphaS_computation.addWidget(self.spinbox_alphaS_computation_to)
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#
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# self.horizontalLayout_fitButton_alphaWvalue = QHBoxLayout()
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# self.verticalLayout_groupbox_fit_regression.addLayout(self.horizontalLayout_fitButton_alphaWvalue)
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#
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# self.pushbutton_fit_regression_line = QPushButton()
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# self.pushbutton_fit_regression_line.setText("Fit && Compute \u03B1s")
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# self.horizontalLayout_fitButton_alphaWvalue.addWidget(self.pushbutton_fit_regression_line)
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#
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# self.label_alphaS = QLabel()
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# self.label_alphaS.setText("\u03B1s = " + "0.0" + "dB/m")
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# self.label_alphaS.setFont(QFont("Ubuntu", 14, QFont.Normal))
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# self.horizontalLayout_fitButton_alphaWvalue.addWidget(self.label_alphaS)
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# --- Groupbox water attenuation ---
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# # self.verticalLayout_groupbox_fit_regression
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self.gridLayout_groupbox_water_attenuation = QGridLayout(self.groupbox_water_attenuation)
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self.combobox_water_attenuation_model = QComboBox()
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self.combobox_water_attenuation_model.addItem("François & Garrison 1982")
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self.combobox_water_attenuation_model.addItem("Other model")
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self.gridLayout_groupbox_water_attenuation.addWidget(self.combobox_water_attenuation_model, 0, 0, 1, 1)
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self.label_temperature_water_attenation = QLabel()
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self.gridLayout_groupbox_water_attenuation.addWidget(self.label_temperature_water_attenation, 0, 1, 1, 1)
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self.spinbox_temperature_water_attenuation = QSpinBox()
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self.gridLayout_groupbox_water_attenuation.addWidget(self.spinbox_temperature_water_attenuation, 0, 2, 1, 1)
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self.label_degre_celsius = QLabel()
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self.label_degre_celsius.setText("°C")
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self.gridLayout_groupbox_water_attenuation.addWidget(self.label_degre_celsius, 0, 3, 1, 1)
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self.combobox_freq_for_water_attenuation = QComboBox()
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# self.combobox_water_attenuation.currentIndexChanged.connect(self.alpha_value_changed)
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self.gridLayout_groupbox_water_attenuation.addWidget(self.combobox_freq_for_water_attenuation, 1, 0, 1, 1)
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self.pushbutton_water_attenuation = QPushButton()
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self.pushbutton_water_attenuation.setText("Compute \u03B1w")
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self.gridLayout_groupbox_water_attenuation.addWidget(self.pushbutton_water_attenuation, 1, 1, 1, 1)
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self.pushbutton_water_attenuation.clicked.connect(self.compute_water_attenuation)
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self.label_water_attenuation = QLabel()
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self.label_water_attenuation.setText("\u03B1w = 0.00 dB/m")
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self.label_water_attenuation.setFont(QFont("Ubuntu", 14, QFont.Normal))
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self.gridLayout_groupbox_water_attenuation.addWidget(self.label_water_attenuation, 1, 2, 1, 1)
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# --- Groupbox fit regression line ---
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self.gridLayout_groupbox_fit_regression = QGridLayout(self.groupbox_fit_regression_line)
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self.label_alphaS_expression = QLabel()
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# self.label_alphaS_expression.setText("For homogeneous suspension: dFCB/dr = -2\u03B1<sub>s<\sub>")
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self.gridLayout_groupbox_fit_regression.addWidget(self.label_alphaS_expression, 0, 0, 1, 5)
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self.combobox_frequency_compute_alphaS = QComboBox()
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self.gridLayout_groupbox_fit_regression.addWidget(self.combobox_frequency_compute_alphaS, 1, 0, 1, 1)
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self.label_alphaS_computation_from = QLabel()
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self.gridLayout_groupbox_fit_regression.addWidget(self.label_alphaS_computation_from, 1, 1, 1, 1)
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self.spinbox_alphaS_computation_from = QDoubleSpinBox()
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self.spinbox_alphaS_computation_from.setRange(0, 9999)
|
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self.gridLayout_groupbox_fit_regression.addWidget(self.spinbox_alphaS_computation_from, 1, 2, 1, 1)
|
||||
|
||||
self.label_alphaS_computation_to = QLabel()
|
||||
self.gridLayout_groupbox_fit_regression.addWidget(self.label_alphaS_computation_to, 1, 3, 1, 1)
|
||||
|
||||
self.spinbox_alphaS_computation_to = QDoubleSpinBox()
|
||||
self.gridLayout_groupbox_fit_regression.addWidget(self.spinbox_alphaS_computation_to, 1, 4, 1, 1)
|
||||
|
||||
self.pushbutton_fit_regression_line = QPushButton()
|
||||
self.pushbutton_fit_regression_line.setText("Fit && Compute \u03B1s")
|
||||
self.gridLayout_groupbox_fit_regression.addWidget(self.pushbutton_fit_regression_line, 2, 0, 1, 1)
|
||||
|
||||
self.label_alphaS = QLabel()
|
||||
self.label_alphaS.setText("\u03B1s = " + "0.0" + "dB/m")
|
||||
self.label_alphaS.setFont(QFont("Ubuntu", 14, QFont.Normal))
|
||||
self.gridLayout_groupbox_fit_regression.addWidget(self.label_alphaS, 2, 3, 1, 2)
|
||||
|
||||
# self.verticalLayout_groupbox_fit_regression
|
||||
|
||||
# --------------------------------------------------------------------------------------------------------------
|
||||
### --- Layout of groupbox in the Right vertical layout box
|
||||
|
|
@ -582,7 +527,7 @@ class SignalProcessingTab(QWidget):
|
|||
self.retranslate_signal_processing_tab()
|
||||
|
||||
# # -------------------- Functions for Signal processing Tab --------------------
|
||||
#
|
||||
|
||||
def retranslate_signal_processing_tab(self):
|
||||
self.pushbutton_load_data.setText(_translate("CONSTANT_STRING", cs.LOAD_DATA_FROM_ACOUSTIC_DATA_TAB))
|
||||
|
||||
|
|
@ -595,29 +540,31 @@ class SignalProcessingTab(QWidget):
|
|||
self.groupbox_acoustic_profile.setTitle(_translate("CONSTANT_STRING", cs.ACOUSTIC_PROFILE))
|
||||
# self.checkbox_substract_noise.setText(_translate("CONSTANT_STRING", cs.SUBTRACT_THE_NOISE))
|
||||
self.label_SNR_criterion.setText(_translate("CONSTANT_STRING", cs.SNR_CRITERION))
|
||||
#
|
||||
|
||||
self.groupbox_window_size.setTitle(_translate("CONSTANT_STRING", cs.WINDOW_SIZE))
|
||||
# self.label_averageH.setText(_translate("CONSTANT_STRING", cs.HORIZONTAL) + ": +/-")
|
||||
self.label_cells.setText(_translate("CONSTANT_STRING", cs.CELLS) + " = +/- ? sec")
|
||||
|
||||
self.groupbox_rayleigh_criterion.setTitle(_translate("CONSTANT_STRING", cs.RAYLEIGH_CRITERION))
|
||||
# self.checkbox_despiked_acoustic_signal.setText(_translate("CONSTANT_STRING", cs.DESPIKING))
|
||||
#
|
||||
|
||||
self.groupbox_FCBoption.setTitle(_translate("CONSTANT_STRING", cs.FCB_OPTIONS))
|
||||
#
|
||||
|
||||
self.groupbox_water_attenuation.setTitle(_translate("CONSTANT_STRING", cs.COMPUTING_WATER_ATTENUATION))
|
||||
# self.label_temperature_water_attenation.setText(_translate("CONSTANT_STRING", cs.TEMPERATURE) + ":")
|
||||
#
|
||||
self.label_temperature_water_attenation.setText(_translate("CONSTANT_STRING", cs.TEMPERATURE) + ":")
|
||||
|
||||
self.groupbox_fit_regression_line.setTitle(_translate("CONSTANT_STRING", cs.FIT_REGRESSION_LINE))
|
||||
# self.label_alphaS_expression.setText(
|
||||
# _translate("CONSTANT_STRING", cs.FOR_HOMOGENEOUS_SUSPENSION) + ": dFCB/dr = -2\u03B1<sub>s<\sub>")
|
||||
# self.label_alphaS_computation_from.setText(_translate("CONSTANT_STRING", cs.FROM))
|
||||
# self.label_alphaS_computation_to.setText(_translate("CONSTANT_STRING", cs.TO))
|
||||
#
|
||||
self.label_alphaS_expression.setText(
|
||||
_translate("CONSTANT_STRING", cs.FOR_HOMOGENEOUS_SUSPENSION) + ": dFCB/dr = -2\u03B1<sub>s<\sub>")
|
||||
self.label_alphaS_computation_from.setText(_translate("CONSTANT_STRING", cs.FROM))
|
||||
self.label_alphaS_computation_to.setText(_translate("CONSTANT_STRING", cs.TO))
|
||||
|
||||
self.groupbox_plot_profile.setTitle(_translate("CONSTANT_STRING", cs.PROFILE))
|
||||
self.groupbox_plot_averaged_profile.setTitle(_translate("CONSTANT_STRING", cs.AVERAGED_PROFILE))
|
||||
self.groupbox_FCB_profile.setTitle(_translate("CONSTANT_STRING", cs.FCB_PROFILE))
|
||||
|
||||
# ------------------------------------- Connect Push Button Load Data + Slider -------------------------------------
|
||||
|
||||
def slide_profile_number_to_right(self):
|
||||
self.slider.setValue(int(self.slider.value()) + 1)
|
||||
self.lineEdit_slider.setText(str(self.slider.value()))
|
||||
|
|
@ -632,48 +579,120 @@ class SignalProcessingTab(QWidget):
|
|||
def update_lineEdit_by_moving_slider(self):
|
||||
self.lineEdit_slider.setText(str(self.slider.value()))
|
||||
|
||||
# def enable_disable_spinbox_snr_value(self):
|
||||
# if self.checkbox_SNR_criterion.isChecked():
|
||||
# self.spinbox_SNR_criterion.setEnabled(True)
|
||||
# self.pushbutton_snr_filter.setEnabled(True)
|
||||
# else:
|
||||
# self.spinbox_SNR_criterion.setDisabled(True)
|
||||
# self.pushbutton_snr_filter.setDisabled(True)
|
||||
|
||||
def compute_BS_data_section(self):
|
||||
|
||||
if stg.r_bottom.size == 0:
|
||||
stg.BS_data_section = deepcopy(stg.BS_data)
|
||||
elif stg.r_bottom.size != 0:
|
||||
stg.BS_data_section = deepcopy(stg.BS_data)
|
||||
for f in range(stg.freq.shape[0]):
|
||||
for k in range(stg.r_bottom.shape[0]):
|
||||
# print(k, np.where(stg.r >= stg.r_bottom[k])[0])
|
||||
stg.BS_data_section[np.where(stg.r >= stg.r_bottom[k])[0], f, k] = np.nan
|
||||
|
||||
# ----------------------------------------- Connect Groupbox average data -----------------------------------------
|
||||
|
||||
def compute_averaged_profile(self):
|
||||
filter_convolve = np.ones(self.spinbox_average.value())
|
||||
|
||||
stg.BS_data_section_averaged = np.zeros((stg.r.shape[0], stg.freq.shape[0], stg.t.shape[0]))
|
||||
for f in range(stg.freq.shape[0]):
|
||||
for i in range(stg.r.shape[0]):
|
||||
stg.BS_data_section_averaged[i, f, :] \
|
||||
= convolve1d(stg.BS_data_section[i, f, :], weights=filter_convolve) / filter_convolve.shape[0]
|
||||
|
||||
self.label_cells.clear()
|
||||
self.label_cells.setText("cells = +/- " + str((self.spinbox_average.value() // 2)*(1/stg.nb_profiles_per_sec)) + " sec")
|
||||
|
||||
# ---------------------------------------- Connect Groupbox filter with SNR ----------------------------------------
|
||||
|
||||
def remove_point_with_snr_filter(self):
|
||||
if stg.BS_data_section_averaged.size == 0:
|
||||
stg.BS_data_section_SNR_filter = deepcopy(stg.BS_data_section)
|
||||
stg.SNR_data_average = np.divide(
|
||||
(stg.BS_data_section_SNR_filter - stg.Noise_data[:, :, :stg.t.shape[0]])**2,
|
||||
stg.Noise_data[:, :, :stg.t.shape[0]]**2)
|
||||
|
||||
stg.BS_data_filter_snr = deepcopy(stg.BS_data)
|
||||
print("Before : ", np.sum(np.isnan(stg.BS_data_filter_snr[:, 0, :])))
|
||||
for f in range(stg.freq.shape[0]):
|
||||
stg.BS_data_filter_snr[np.where(stg.SNR_data[:, 0, :] < self.spinbox_SNR_criterion.value())[0],
|
||||
f,
|
||||
np.where(stg.SNR_data[:, 0, :] < self.spinbox_SNR_criterion.value())[1]] \
|
||||
= np.nan
|
||||
print("After : ", np.sum(np.isnan(stg.BS_data_filter_snr[:, 0, :])))
|
||||
for f in range(stg.freq.shape[0]):
|
||||
stg.BS_data_section_SNR_filter[np.where(stg.SNR_data_average[:, 0, :] < self.spinbox_SNR_criterion.value())[0],
|
||||
f,
|
||||
np.where(stg.SNR_data_average[:, 0, :] < self.spinbox_SNR_criterion.value())[1]] \
|
||||
= np.nan
|
||||
|
||||
elif stg.BS_data_section_averaged.size != 0:
|
||||
stg.BS_data_section_SNR_filter = deepcopy(stg.BS_data_section_averaged)
|
||||
stg.SNR_data_average = np.divide(
|
||||
(stg.BS_data_section_SNR_filter - stg.Noise_data[:, :, :stg.t.shape[0]]) ** 2,
|
||||
stg.Noise_data[:, :, :stg.t.shape[0]] ** 2)
|
||||
|
||||
for f in range(stg.freq.shape[0]):
|
||||
stg.BS_data_section_SNR_filter[
|
||||
np.where(stg.SNR_data_average[:, 0, :] < self.spinbox_SNR_criterion.value())[0],
|
||||
f,
|
||||
np.where(stg.SNR_data_average[:, 0, :] < self.spinbox_SNR_criterion.value())[1]] \
|
||||
= np.nan
|
||||
|
||||
def compute_water_attenuation(self):
|
||||
if self.combobox_water_attenuation_model.currentIndex() == 0:
|
||||
self.Francois_and_Garrison_1982()
|
||||
|
||||
else:
|
||||
pass
|
||||
|
||||
print(f"{stg.water_attenuation:.2f}")
|
||||
self.label_water_attenuation.clear()
|
||||
self.label_water_attenuation.setText("\u03B1w = " + f"{stg.water_attenuation:.4f}" + " dB/m")
|
||||
|
||||
def Francois_and_Garrison_1982(self):
|
||||
if self.spinbox_temperature_water_attenuation.value() > 20:
|
||||
stg.water_attenuation = ((3.964 * 1e-4 - 1.146 * 1e-5 * self.spinbox_temperature_water_attenuation.value() +
|
||||
1.45 * 1e-7 * self.spinbox_temperature_water_attenuation.value() ** 2 -
|
||||
6.5 * 1e-10 * self.spinbox_temperature_water_attenuation.value() ** 3) * 1e-3 *
|
||||
(np.log(10) / 20) *
|
||||
(stg.freq[self.combobox_freq_for_water_attenuation.currentIndex()] * 1e-3) ** 2)
|
||||
else:
|
||||
stg.water_attenuation = ((4.937 * 1e-4 - 2.59 * 1e-5 * self.spinbox_temperature_water_attenuation.value() +
|
||||
9.11 * 1e-7 * self.spinbox_temperature_water_attenuation.value() ** 2 -
|
||||
1.5 * 1e-8 * self.spinbox_temperature_water_attenuation.value() ** 3) * 1e-3 *
|
||||
(np.log(10) / 20) *
|
||||
(stg.freq[self.combobox_freq_for_water_attenuation.currentIndex()] * 1e-3) ** 2)
|
||||
|
||||
# ---------------------------------------- PLOT PROFILE POSITION ON TRANSECT ---------------------------------------
|
||||
|
||||
def plot_profile_position_on_transect(self):
|
||||
|
||||
# --- Choose frequency (Combo box) to plot transect with profile position ---
|
||||
self.combobox_frequency.addItems(stg.freq_text)
|
||||
self.combobox_frequency.currentTextChanged.connect(self.update_plot_profile_position_on_transect)
|
||||
|
||||
# --- Choose frequency (Combo box) to compute water attenuation ---
|
||||
self.combobox_freq_for_water_attenuation.addItems(stg.freq_text)
|
||||
|
||||
# --- Choose frequency (Combo box) to compute sediment attenuation ---
|
||||
self.combobox_frequency_compute_alphaS.addItems(stg.freq_text)
|
||||
|
||||
# --- Fix maximum value of slider + Edit Label Profile number ---
|
||||
self.slider.setMaximum(stg.t.shape[0])
|
||||
self.label_profile_number.clear()
|
||||
self.label_profile_number.setText("Profile " + str(self.slider.value()) + " / " + str(self.slider.maximum()))
|
||||
self.label_profile_number.setText(
|
||||
"Profile " + str(self.slider.value()) + " / " + str(self.slider.maximum()))
|
||||
|
||||
# --- Create Matplotlib canvas (with figure and axis) to plot transect ---
|
||||
self.canvas_plot_profile_position_on_transect = FigureCanvas()
|
||||
self.figure_plot_profile_position_on_transect, self.axis_plot_profile_position_on_transect = \
|
||||
plt.subplots(nrows=1, ncols=1, layout="constrained")
|
||||
plt.subplots(nrows=1, ncols=1, layout="constrained")
|
||||
self.canvas_plot_profile_position_on_transect = FigureCanvas(self.figure_plot_profile_position_on_transect)
|
||||
self.verticalLayout_groupbox_display_profile_position.addWidget(self.canvas_plot_profile_position_on_transect)
|
||||
|
||||
# if stg.r_bottom.size == 0:
|
||||
|
||||
val_min = np.min(stg.BS_data[:, stg.freq_bottom_detection, :])
|
||||
val_max = np.max(stg.BS_data[:, stg.freq_bottom_detection, :])
|
||||
# --- Plot transect with profile position ---
|
||||
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
|
||||
|
||||
pcm = self.axis_plot_profile_position_on_transect.pcolormesh(
|
||||
stg.t, -stg.r, stg.BS_data[:, stg.freq_bottom_detection, :],
|
||||
self.axis_plot_profile_position_on_transect.pcolormesh(
|
||||
stg.t, -stg.r, stg.BS_data_section[:, stg.freq_bottom_detection, :],
|
||||
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
|
||||
|
||||
if stg.r_bottom.size != 0:
|
||||
|
|
@ -684,38 +703,11 @@ class SignalProcessingTab(QWidget):
|
|||
stg.t[self.slider.value() - 1] * np.ones(stg.r.shape[0]), -stg.r,
|
||||
color='red', linestyle="solid", linewidth=2)
|
||||
|
||||
self.axis_plot_profile_position_on_transect.set_xticks([])
|
||||
self.axis_plot_profile_position_on_transect.set_yticks([])
|
||||
|
||||
self.figure_plot_profile_position_on_transect.canvas.draw_idle()
|
||||
|
||||
# else:
|
||||
|
||||
# stg.BS_data_section = deepcopy(stg.BS_data)
|
||||
|
||||
# for f in range(stg.freq.shape[0]):
|
||||
# for k in range(stg.r_bottom.shape[0]):
|
||||
# # print(k, np.where(stg.r >= stg.r_bottom[k])[0])
|
||||
# stg.BS_data_section[np.where(stg.r >= stg.r_bottom[k])[0], f, k] \
|
||||
# = np.nan
|
||||
# # print("----------------------------------------------------------")
|
||||
|
||||
# val_min = np.min(stg.BS_data_section[:, stg.freq_bottom_detection, :])
|
||||
# val_max = np.max(stg.BS_data_section[:, stg.freq_bottom_detection, :])
|
||||
# if val_min == 0:
|
||||
# val_min = 1e-5
|
||||
#
|
||||
# pcm = self.axis_plot_profile_position_on_transect.pcolormesh(
|
||||
# stg.t, -stg.r, stg.BS_data_section[:, stg.freq_bottom_detection, :],
|
||||
# cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
|
||||
#
|
||||
# if stg.r_bottom.size != 0:
|
||||
# self.axis_plot_profile_position_on_transect.plot(
|
||||
# stg.t, -stg.r_bottom, color='black', linewidth=1, linestyle="solid")
|
||||
#
|
||||
# self.axis_plot_profile_position_on_transect.plot(
|
||||
# stg.t[self.slider.value() - 1] * np.ones(stg.r.shape[0]), -stg.r,
|
||||
# color='red', linestyle="solid", linewidth=2)
|
||||
#
|
||||
# self.figure_plot_profile_position_on_transect.canvas.draw_idle()
|
||||
|
||||
def update_plot_profile_position_on_transect(self):
|
||||
|
||||
# --- Update label "Profile N / max(N)" ---
|
||||
|
|
@ -723,55 +715,96 @@ class SignalProcessingTab(QWidget):
|
|||
self.label_profile_number.setText("Profile " + str(self.slider.value()) + " / " + str(self.slider.maximum()))
|
||||
|
||||
# --- Update transect plot ---
|
||||
if self.canvas_plot_profile_position_on_transect != None:
|
||||
|
||||
# if stg.r_bottom.size != 0:
|
||||
if self.canvas_plot_profile_position_on_transect is None:
|
||||
msgBox = QMessageBox()
|
||||
msgBox.setWindowTitle("Plot transect Error")
|
||||
msgBox.setIcon(QMessageBox.Warning)
|
||||
msgBox.setText("Load and Plot transect before post process")
|
||||
msgBox.setStandardButtons(QMessageBox.Ok)
|
||||
msgBox.exec()
|
||||
|
||||
self.axis_plot_profile_position_on_transect.cla()
|
||||
elif self.canvas_plot_profile_position_on_transect != None:
|
||||
|
||||
val_min = np.min(stg.BS_data[:, self.combobox_frequency.currentIndex(), :])
|
||||
val_max = np.max(stg.BS_data[:, self.combobox_frequency.currentIndex(), :])
|
||||
if val_min == 0:
|
||||
val_min = 1e-5
|
||||
if (stg.BS_data_section_averaged.size == 0) and (stg.BS_data_section_SNR_filter.size == 0):
|
||||
|
||||
self.axis_plot_profile_position_on_transect.pcolormesh(
|
||||
stg.t, -stg.r, stg.BS_data[:, self.combobox_frequency.currentIndex(), :],
|
||||
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
|
||||
self.axis_plot_profile_position_on_transect.cla()
|
||||
|
||||
val_min = np.nanmin(stg.BS_data_section[:, self.combobox_frequency.currentIndex(), :])
|
||||
val_max = np.nanmax(stg.BS_data_section[:, self.combobox_frequency.currentIndex(), :])
|
||||
if val_min == 0:
|
||||
val_min = 1e-5
|
||||
|
||||
self.axis_plot_profile_position_on_transect.pcolormesh(
|
||||
stg.t, -stg.r, stg.BS_data_section[:, self.combobox_frequency.currentIndex(), :],
|
||||
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
|
||||
|
||||
if stg.r_bottom.size != 0:
|
||||
self.axis_plot_profile_position_on_transect.plot(stg.t, -stg.r_bottom,
|
||||
color='black', linewidth=1, linestyle="solid")
|
||||
|
||||
if stg.r_bottom.size != 0:
|
||||
self.axis_plot_profile_position_on_transect.plot(
|
||||
stg.t, -stg.r_bottom,
|
||||
color='black', linewidth=1, linestyle="solid")
|
||||
stg.t[self.slider.value()-1] * np.ones(stg.r.shape[0]), -stg.r,
|
||||
color='red', linestyle="solid", linewidth=2)
|
||||
|
||||
self.axis_plot_profile_position_on_transect.plot(
|
||||
stg.t[self.slider.value() - 1] * np.ones(stg.r.shape[0]), -stg.r,
|
||||
color='red', linestyle="solid", linewidth=2)
|
||||
self.axis_plot_profile_position_on_transect.set_xticks([])
|
||||
self.axis_plot_profile_position_on_transect.set_yticks([])
|
||||
|
||||
self.figure_plot_profile_position_on_transect.canvas.draw_idle()
|
||||
self.figure_plot_profile_position_on_transect.canvas.draw_idle()
|
||||
|
||||
# else:
|
||||
#
|
||||
# self.axis_plot_profile_position_on_transect.cla()
|
||||
#
|
||||
# val_min = np.min(stg.BS_data[:, self.combobox_frequency.currentIndex(), :])
|
||||
# val_max = np.max(stg.BS_data[:, self.combobox_frequency.currentIndex(), :])
|
||||
# if val_min == 0:
|
||||
# val_min = 1e-5
|
||||
#
|
||||
# pcm = self.axis_plot_profile_position_on_transect.pcolormesh(
|
||||
# stg.t, -stg.r, stg.BS_data[:, self.combobox_frequency.currentIndex(), :],
|
||||
# cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
|
||||
#
|
||||
# if stg.r_bottom.size != 0:
|
||||
# self.axis_plot_profile_position_on_transect.plot(
|
||||
# stg.t, -stg.r_bottom,
|
||||
# color='black', linewidth=1, linestyle="solid")
|
||||
#
|
||||
# self.axis_plot_profile_position_on_transect.plot(
|
||||
# stg.t[self.slider.value()-1] * np.ones(stg.r.shape[0]), -stg.r,
|
||||
# color='red', linestyle="solid", linewidth=2)
|
||||
#
|
||||
# self.figure_plot_profile_position_on_transect.canvas.draw_idle()
|
||||
elif (stg.BS_data_section_averaged.size != 0) and (stg.BS_data_section_SNR_filter.size == 0):
|
||||
|
||||
self.axis_plot_profile_position_on_transect.cla()
|
||||
|
||||
val_min = np.nanmin(stg.BS_data_section_averaged[:, self.combobox_frequency.currentIndex(), :])
|
||||
val_max = np.nanmax(stg.BS_data_section_averaged[:, self.combobox_frequency.currentIndex(), :])
|
||||
if val_min == 0:
|
||||
val_min = 1e-5
|
||||
|
||||
self.axis_plot_profile_position_on_transect.pcolormesh(
|
||||
stg.t, -stg.r, stg.BS_data_section_averaged[:, self.combobox_frequency.currentIndex(), :],
|
||||
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
|
||||
|
||||
if stg.r_bottom.size != 0:
|
||||
self.axis_plot_profile_position_on_transect.plot(stg.t, -stg.r_bottom,
|
||||
color='black', linewidth=1, linestyle="solid")
|
||||
|
||||
self.axis_plot_profile_position_on_transect.plot(
|
||||
stg.t[self.slider.value() - 1] * np.ones(stg.r.shape[0]), -stg.r,
|
||||
color='red', linestyle="solid", linewidth=2)
|
||||
|
||||
self.axis_plot_profile_position_on_transect.set_xticks([])
|
||||
self.axis_plot_profile_position_on_transect.set_yticks([])
|
||||
|
||||
self.figure_plot_profile_position_on_transect.canvas.draw_idle()
|
||||
|
||||
elif stg.BS_data_section_SNR_filter.size != 0:
|
||||
|
||||
self.axis_plot_profile_position_on_transect.cla()
|
||||
|
||||
val_min = np.nanmin(stg.BS_data_section_SNR_filter[:, self.combobox_frequency.currentIndex(), :])
|
||||
val_max = np.nanmax(stg.BS_data_section_SNR_filter[:, self.combobox_frequency.currentIndex(), :])
|
||||
if val_min == 0:
|
||||
val_min = 1e-5
|
||||
|
||||
self.axis_plot_profile_position_on_transect.pcolormesh(
|
||||
stg.t, -stg.r, stg.BS_data_section_SNR_filter[:, self.combobox_frequency.currentIndex(), :],
|
||||
cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))
|
||||
|
||||
if stg.r_bottom.size != 0:
|
||||
self.axis_plot_profile_position_on_transect.plot(stg.t, -stg.r_bottom,
|
||||
color='black', linewidth=1, linestyle="solid")
|
||||
|
||||
self.axis_plot_profile_position_on_transect.plot(
|
||||
stg.t[self.slider.value() - 1] * np.ones(stg.r.shape[0]), -stg.r,
|
||||
color='red', linestyle="solid", linewidth=2)
|
||||
|
||||
self.axis_plot_profile_position_on_transect.set_xticks([])
|
||||
self.axis_plot_profile_position_on_transect.set_yticks([])
|
||||
|
||||
self.figure_plot_profile_position_on_transect.canvas.draw_idle()
|
||||
|
||||
# -------------------------------------------------- PLOT PROFILE -------------------------------------------------
|
||||
|
||||
def plot_profile(self):
|
||||
|
||||
|
|
@ -784,185 +817,65 @@ class SignalProcessingTab(QWidget):
|
|||
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_profile[f].cla()
|
||||
self.axis_profile[f].plot(stg.BS_data[:, f, self.slider.value() - 1], -stg.r,
|
||||
self.axis_profile[f].plot(stg.BS_data_section[:, f, self.slider.value() - 1], -stg.r,
|
||||
linestyle='solid', color='k', linewidth=1)
|
||||
|
||||
if stg.r_bottom.size != 0:
|
||||
self.axis_profile[f].plot(
|
||||
np.array([0, np.nanmax(stg.BS_data[:, stg.freq_bottom_detection, self.slider.value() - 1])]),
|
||||
-stg.r_bottom[self.slider.value() - 1]*np.ones(2),
|
||||
linestyle='solid', color='red', linewidth=1)
|
||||
|
||||
self.axis_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
|
||||
self.figure_profile.canvas.draw_idle()
|
||||
|
||||
# # --- Raw averaged profile ---
|
||||
#
|
||||
# self.figure_averaged_profile, self.axis_averaged_profile \
|
||||
# = plt.subplots(nrows=1, ncols=stg.freq.shape[0], layout='constrained')
|
||||
# self.canvas_averaged_profile = FigureCanvas(self.figure_averaged_profile)
|
||||
# self.verticalLayout_groupbox_plot_averaged_profile.addWidget(self.canvas_averaged_profile)
|
||||
#
|
||||
# for f in range(stg.freq.shape[0]):
|
||||
# self.axis_averaged_profile[f].cla()
|
||||
# self.axis_averaged_profile[f].plot(stg.BS_data[:, f, self.slider.value() - 1], -stg.r,
|
||||
# linestyle='solid', color='k', linewidth=1)
|
||||
# self.axis_averaged_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
|
||||
# # --- Raw FCB profile ---
|
||||
#
|
||||
# self.figure_FCB_profile, self.axis_FCB_profile \
|
||||
# = plt.subplots(nrows=1, ncols=stg.freq.shape[0], layout='constrained')
|
||||
# self.canvas_FCB_profile = FigureCanvas(self.figure_FCB_profile)
|
||||
# self.verticalLayout_groupbox_plot_FCB_profile.addWidget(self.canvas_FCB_profile)
|
||||
|
||||
def update_plot_profile(self):
|
||||
|
||||
# if self.checkbox_SNR_criterion.isChecked():
|
||||
|
||||
# self.remove_point_with_snr_filter()
|
||||
|
||||
if stg.BS_data_filter_snr.size == 0:
|
||||
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_profile[f].cla()
|
||||
self.axis_profile[f].plot(stg.BS_data[:, f, self.slider.value()-1], -stg.r,
|
||||
linestyle='solid', color='k', linewidth=1)
|
||||
self.axis_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
|
||||
else:
|
||||
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_profile[f].cla()
|
||||
self.axis_profile[f].plot(stg.BS_data_filter_snr[:, f, self.slider.value()-1], -stg.r,
|
||||
linestyle='solid', color='k', linewidth=1)
|
||||
|
||||
# if stg.r_bottom.size != 0:
|
||||
# self.axis_profile[f].plot(
|
||||
# np.array([0, np.nanmax(stg.BS_data[:, stg.freq_bottom_detection, self.slider.value() - 1])]),
|
||||
# -stg.r_bottom[self.slider.value() - 1] * np.ones(2),
|
||||
# linestyle='dashed', color='red', linewidth=1)
|
||||
|
||||
self.axis_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
|
||||
# else:
|
||||
#
|
||||
# for f in range(stg.freq.shape[0]):
|
||||
# self.axis_profile[f].cla()
|
||||
# self.axis_profile[f].plot(stg.BS_data[:, f, self.slider.value()-1], -stg.r,
|
||||
# linestyle='solid', color='k', linewidth=1)
|
||||
|
||||
# if stg.r_bottom.size != 0:
|
||||
# self.axis_profile[f].plot(
|
||||
# np.array([0, np.nanmax(stg.BS_data[:, stg.freq_bottom_detection, self.slider.value() - 1])]),
|
||||
# -stg.r_bottom[self.slider.value() - 1] * np.ones(2),
|
||||
# linestyle='dashed', color='red', linewidth=1)
|
||||
|
||||
# self.axis_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
|
||||
self.figure_profile.canvas.draw_idle()
|
||||
|
||||
def compute_averaged_profile(self):
|
||||
filter_convolve = np.ones(self.spinbox_average.value())
|
||||
|
||||
if stg.BS_data_filter_snr.size == 0:
|
||||
stg.BS_data_averaged = np.zeros((stg.r.shape[0], stg.freq.shape[0], stg.t.shape[0]-self.spinbox_average.value()+1))
|
||||
for f in range(stg.freq.shape[0]):
|
||||
for i in range(stg.r.shape[0]):
|
||||
stg.BS_data_averaged[i, f, :] = np.convolve(stg.BS_data[i, f, :], filter_convolve, mode='valid')
|
||||
# stg.BS_data_averaged = np.concatenate((stg.BS_data[:, :, :np.int(self.spinbox_average.value()/2)],
|
||||
# stg.BS_data_averaged,
|
||||
# stg.BS_data[:, :, -np.int(self.spinbox_average.value()/2):]),
|
||||
# axis=2)
|
||||
# print(stg.BS_data_averaged.shape)
|
||||
else:
|
||||
stg.BS_data_averaged = np.zeros((stg.r.shape[0], stg.freq.shape[0], stg.t.shape[0]-self.spinbox_average.value()+1))
|
||||
for f in range(stg.freq.shape[0]):
|
||||
for i in range(stg.r.shape[0]):
|
||||
stg.BS_data_averaged[i, f, :] = np.convolve(stg.BS_data_filter_snr[i, f, :], filter_convolve,
|
||||
mode='valid')
|
||||
|
||||
self.label_cells.clear()
|
||||
self.label_cells.setText("cells = +/- " + str((self.spinbox_average.value() // 2)*(1/stg.nb_profiles_per_sec)) + " sec")
|
||||
|
||||
def plot_averaged_profile(self):
|
||||
# fig, ax = plt.subplots(nrows=1, ncols=1)
|
||||
# ax.pcolormesh(stg.t[8:2232], -stg.r, stg.BS_data_averaged[:, 0, :],
|
||||
# cmap='viridis',
|
||||
# norm=LogNorm(vmin=1e-5, vmax=np.max(stg.BS_data_averaged[:, 0, :])))
|
||||
# plt.show()
|
||||
|
||||
if self.canvas_averaged_profile != None:
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_averaged_profile[f].cla()
|
||||
# --- Raw averaged profile ---
|
||||
|
||||
self.figure_averaged_profile, self.axis_averaged_profile \
|
||||
= plt.subplots(nrows=1, ncols=stg.freq.shape[0], layout='constrained')
|
||||
= plt.subplots(nrows=1, ncols=stg.freq.shape[0], layout='constrained')
|
||||
self.canvas_averaged_profile = FigureCanvas(self.figure_averaged_profile)
|
||||
self.verticalLayout_groupbox_plot_averaged_profile.addWidget(self.canvas_averaged_profile)
|
||||
|
||||
if stg.BS_data_filter_snr.size == 0:
|
||||
# --- Raw FCB profile ---
|
||||
|
||||
BS_concatenate = stg.BS_data_averaged = np.concatenate((stg.BS_data[:, :, :np.int(self.spinbox_average.value()/2)],
|
||||
stg.BS_data_averaged,
|
||||
stg.BS_data[:, :, -np.int(self.spinbox_average.value()/2):]),
|
||||
axis=2)
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_averaged_profile[f].cla()
|
||||
self.axis_averaged_profile[f].plot(BS_concatenate[:, f, self.slider.value()-1], -stg.r,
|
||||
self.figure_FCB_profile, self.axis_FCB_profile \
|
||||
= plt.subplots(nrows=1, ncols=stg.freq.shape[0], layout='constrained')
|
||||
self.canvas_FCB_profile = FigureCanvas(self.figure_FCB_profile)
|
||||
self.verticalLayout_groupbox_plot_FCB_profile.addWidget(self.canvas_FCB_profile)
|
||||
|
||||
def update_plot_profile(self):
|
||||
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_profile[f].cla()
|
||||
self.axis_profile[f].plot(stg.BS_data_section[:, f, self.slider.value() - 1], -stg.r,
|
||||
linestyle='solid', color='k', linewidth=1)
|
||||
|
||||
self.figure_profile.canvas.draw_idle()
|
||||
|
||||
# --------------------------------- PLOT AVERAGED PROFILE FILTERED OR NOT WITH SNR ---------------------------------
|
||||
|
||||
def plot_averaged_profile(self):
|
||||
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_averaged_profile[f].cla()
|
||||
self.axis_averaged_profile[f].plot(stg.BS_data_section_averaged[:, f, self.slider.value()-1], -stg.r,
|
||||
linestyle='solid', color='k', linewidth=1)
|
||||
self.axis_averaged_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
else:
|
||||
BS_concatenate = stg.BS_data_averaged = np.concatenate((stg.BS_data_filter_snr[:, :, :np.int(self.spinbox_average.value() / 2)],
|
||||
stg.BS_data_averaged,
|
||||
stg.BS_data_filter_snr[:, :, -np.int(self.spinbox_average.value() / 2):]),
|
||||
axis=2)
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_averaged_profile[f].cla()
|
||||
self.axis_averaged_profile[f].plot(BS_concatenate[:, f, self.slider.value() - 1], -stg.r,
|
||||
linestyle='solid', color='k', linewidth=1)
|
||||
self.axis_averaged_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
self.axis_averaged_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
|
||||
self.figure_averaged_profile.canvas.draw_idle()
|
||||
|
||||
def update_plot_averaged_profile(self):
|
||||
if self.canvas_averaged_profile == None:
|
||||
|
||||
msgBox = QMessageBox()
|
||||
msgBox.setWindowTitle("Plot averaged profile Error")
|
||||
msgBox.setIcon(QMessageBox.Warning)
|
||||
msgBox.setText("Compute acoustic backscatter averaged data")
|
||||
msgBox.setStandardButtons(QMessageBox.Ok)
|
||||
msgBox.exec()
|
||||
if stg.BS_data_section_SNR_filter.size == 0:
|
||||
|
||||
else:
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_averaged_profile[f].cla()
|
||||
self.axis_averaged_profile[f].plot(stg.BS_data_section_averaged[:, f, self.slider.value() - 1], -stg.r,
|
||||
linestyle='solid', color='k', linewidth=1)
|
||||
self.axis_averaged_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
|
||||
if stg.BS_data_filter_snr.size == 0:
|
||||
self.figure_averaged_profile.canvas.draw_idle()
|
||||
|
||||
BS_concatenate = stg.BS_data_averaged = np.concatenate(
|
||||
(stg.BS_data[:, :, :np.int(self.spinbox_average.value() / 2)],
|
||||
stg.BS_data_averaged,
|
||||
stg.BS_data[:, :, -np.int(self.spinbox_average.value() / 2):]),
|
||||
axis=2)
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_averaged_profile[f].cla()
|
||||
self.axis_averaged_profile[f].plot(BS_concatenate[:, f, self.slider.value() - 1], -stg.r,
|
||||
linestyle='solid', color='k', linewidth=1)
|
||||
self.axis_averaged_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
else:
|
||||
BS_concatenate = stg.BS_data_averaged = np.concatenate(
|
||||
(stg.BS_data_filter_snr[:, :, :np.int(self.spinbox_average.value() / 2)],
|
||||
stg.BS_data_averaged,
|
||||
stg.BS_data_filter_snr[:, :, -np.int(self.spinbox_average.value() / 2):]),
|
||||
axis=2)
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_averaged_profile[f].cla()
|
||||
self.axis_averaged_profile[f].plot(BS_concatenate[:, f, self.slider.value() - 1], -stg.r,
|
||||
linestyle='solid', color='k', linewidth=1)
|
||||
self.axis_averaged_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
elif stg.BS_data_section_SNR_filter.size != 0:
|
||||
|
||||
self.figure_averaged_profile.canvas.draw_idle()
|
||||
for f in range(stg.freq.shape[0]):
|
||||
self.axis_averaged_profile[f].cla()
|
||||
self.axis_averaged_profile[f].plot(stg.BS_data_section_SNR_filter[:, f, self.slider.value() - 1], -stg.r,
|
||||
linestyle='solid', color='k', linewidth=1)
|
||||
self.axis_averaged_profile[f].set_ylim(-np.max(stg.r), np.min(stg.r))
|
||||
|
||||
self.figure_averaged_profile.canvas.draw_idle()
|
||||
|
||||
# def plot_transect_bottom_with_profile_position(self, profile_position):
|
||||
# frequency = self.model.Freq[0]
|
||||
|
|
@ -1029,28 +942,6 @@ class SignalProcessingTab(QWidget):
|
|||
# self.figure_FCBoptions.canvas.draw_idle()
|
||||
# # self.figure_FCBoptions.canvas.flush_events()
|
||||
|
||||
# def linear(self, figure, axis, i):
|
||||
# # for i in range(4):
|
||||
# # axis[i].plot([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], '*-')
|
||||
# # figure.tight_layout()
|
||||
# for i in range(4):
|
||||
# axis[i].plot(self.model.BS_raw_cross_section.V[:, i, 800], self.model.r, c='k')
|
||||
#
|
||||
# def polynome(self, figure, axis):
|
||||
# # for i in range(4):
|
||||
# # axis[i].plot([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100], '*-')
|
||||
# # figure.tight_layout()
|
||||
# for i in range(4):
|
||||
# axis[i].plot(self.model.BS_averaged_cross_section.V[:, i, 800], self.model.r, c='b')
|
||||
#
|
||||
# def cubique(self, figure, axis):
|
||||
# # for i in range(4):
|
||||
# # axis[i].plot([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [0, 1, 8, 27, 64, 125, 216, 343, 512, 729, 1000], '*-')
|
||||
# # figure.tight_layout()
|
||||
# for i in range(4):
|
||||
# axis[i].plot(self.model.FCB[:, i, 800], self.model.r, c='r')
|
||||
#
|
||||
#
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
15
settings.py
15
settings.py
|
|
@ -7,7 +7,7 @@ import datetime
|
|||
# --- load raw data ---
|
||||
path_BS_raw_data = ""
|
||||
filename_BS_raw_data = ""
|
||||
BS_raw_data = np.array([])
|
||||
BS_raw_data = np.array([]) # BS raw data : all measurement (go and back)
|
||||
r = np.array([])
|
||||
r_2D = np.array([])
|
||||
freq = np.array([])
|
||||
|
|
@ -47,7 +47,7 @@ DataFrame_acoustic = pd.DataFrame()
|
|||
|
||||
# --- Processed data in Acoustic Data Tab and used in Acoustic processing tab ---
|
||||
BS_data = np.array([]) # BS data limited with tmin and tmax values of spin box
|
||||
BS_data_section = np.array([])
|
||||
BS_data_section = np.array([]) # BS data in the section. Values NaN outside the bottom of the section are deleted
|
||||
Noise_data = np.array([])
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SNR_data = np.array([])
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t = np.array([])
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@ -56,9 +56,14 @@ val_bottom = np.array([])
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ind_bottom = np.array([])
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freq_bottom_detection = 0
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BS_data_subtract_noise = np.array([])
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BS_data_filter_snr = np.array([])
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BS_data_averaged = np.array([])
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# --- Processed data in Signal Processing Tab ---
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BS_data_section_SNR_filter = np.array([]) # BS data filtered with SNR values (remove point if SNR < value)
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BS_data_section_averaged = np.array([]) # BS data averaged
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time_average = np.array([])
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SNR_data_average = np.array([])
|
||||
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||||
water_attenuation = 0
|
||||
sediment_attenuation = 0
|
||||
|
||||
# --- Sample Data ---
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue