Compare commits
No commits in common. "671f66058cd5506401af483b9c11f827f4d5dabf" and "761dc9008caaf003f6a03671ac77c895367d1048" have entirely different histories.
671f66058c
...
761dc9008c
|
|
@ -389,6 +389,10 @@ class CreateTableForSaveAs:
|
|||
)
|
||||
)
|
||||
|
||||
logger.debug(f"stg.ind_bottom: {stg.ind_bottom[i]}")
|
||||
logger.debug(np.array([stg.ind_bottom[i]]),
|
||||
np.array(stg.ind_bottom[i]).shape)
|
||||
|
||||
# Commit the transaction after executing INSERT.
|
||||
cnx.commit()
|
||||
|
||||
|
|
@ -442,7 +446,7 @@ class CreateTableForSaveAs:
|
|||
|
||||
cur.execute(self.create_SedimentsFile)
|
||||
|
||||
if stg.path_fine != "" and stg.path_sand != "":
|
||||
if stg.path_fine != "" and path_sand != "":
|
||||
cur.execute(
|
||||
"""
|
||||
INSERT into SedimentsFile(
|
||||
|
|
|
|||
42
README.md
42
README.md
|
|
@ -1,23 +1,27 @@
|
|||
# AcouSed
|
||||
|
||||
AcouSed for **Acou**stic Backscattering for Concentration of Suspended **Sed**iments in Rivers is a software developped by INRAE, in collaboation with CNR.
|
||||
AcouSed for **Acou**stic Backscattering for Concentration of Suspended **Sed**iments in Rivers is a software developped by INRAE, in collaboation with CNR.
|
||||
|
||||
|
||||
|
||||
It is divided in six tabs:
|
||||
- Acoustic data : acoustic raw data are downloaded and visualised
|
||||
It is divided in six tabs:
|
||||
- Acoustic data : acoustic raw data are downloaded and visualised
|
||||
- Signal preprocessing : acoustic raw signal is preprocessed with filters
|
||||
- Sample data : fine and sand sediments samples data are downloaded and visualised
|
||||
- Sample data : fine and sand sediments samples data are downloaded and visualised
|
||||
- Calibration : calibration parameter are computed
|
||||
- Inversion : inversion method is calculated to provide fine and sand sediments fields
|
||||
|
||||
## Installation
|
||||
## Software documentation
|
||||
|
||||
### Installation
|
||||
|
||||
Acoused is developped for Linux and Windows on Python version 3.8 or
|
||||
greater. By default, Acoused is developped with Pypi package
|
||||
dependencies, but is also possible to use Guix package manager to run
|
||||
Acoused.
|
||||
|
||||
## Development documentation
|
||||
|
||||
### **TODO** Windows
|
||||
|
||||
### Linux
|
||||
|
|
@ -45,15 +49,16 @@ script `guix.sh` to run the program.
|
|||
guix shell sqlitebrowser -- ./guix.sh
|
||||
```
|
||||
|
||||
## Support files & References
|
||||
## License
|
||||
|
||||
- [ ] [Acoustic inversion method diagram](https://forgemia.inra.fr/theophile.terraz/acoused/-/blob/main/Acoustic_Inversion_theory.pdf?ref_type=heads)
|
||||
- [ ] [Tutorial AQUAscat software : AQUAtalk](https://forgemia.inra.fr/theophile.terraz/acoused/-/blob/main/Tutorial_AQUAscat_software.pdf?ref_type=heads)
|
||||
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.
|
||||
|
||||
- [ ] [Adrien Vergne thesis (2018)](https://theses.fr/2018GREAU046)
|
||||
- [ ] [Vergne A., Le Coz J., Berni C., & Pierrefeu G. (2020), Water Resources Research, 56(2)](https://doi.org/10.1029/2019WR024877)
|
||||
- [ ] [Vergne A., Berni C., Le Coz J., & Tencé F., (2021), Water Resources Research, 57(9)](https://doi.org/10.1029/2021WR029589)
|
||||
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 <https://www.gnu.org/licenses/>.
|
||||
|
||||
## Authors & Contacts
|
||||
|
||||
|
|
@ -63,16 +68,15 @@ script `guix.sh` to run the program.
|
|||
If you have any questions or suggestions, please contact us to celine.berni@inrae.fr and/or jerome.lecoz@inrae.fr.
|
||||
|
||||
## Acknowledgment (Funding)
|
||||
This study was conducted within the [Rhône Sediment Observatory](https://observatoire-sediments-rhone.fr/) (OSR), a multi-partner research program funded through the Plan Rhône by the European Regional Development Fund (ERDF), Agence de l’Eau RMC, CNR, EDF and three regional councils (Auvergne-Rhône-Alpes, PACA and Occitanie). It was also support by CNR.
|
||||
|
||||
This study was conducted within the [Rhône Sediment Observatory](https://observatoire-sediments-rhone.fr/) (OSR), a multi-partner research program funded through the Plan Rhône by the European Regional Development Fund (ERDF), Agence de l’Eau RMC, CNR, EDF and three regional councils (Auvergne-Rhône-Alpes, PACA and Occitanie). It was also support by CNR.
|
||||
## Support files & References
|
||||
|
||||
## License
|
||||
- [ ] [Acoustic inversion method diagram](https://forgemia.inra.fr/theophile.terraz/acoused/-/blob/main/Acoustic_Inversion_theory.pdf?ref_type=heads)
|
||||
- [ ] [Tutorial AQUAscat software : AQUAtalk](https://forgemia.inra.fr/theophile.terraz/acoused/-/blob/main/Tutorial_AQUAscat_software.pdf?ref_type=heads)
|
||||
|
||||
AcouSed
|
||||
Copyright (C) 2024-2025 - 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.
|
||||
- [ ] [Adrien Vergne thesis (2018)](https://theses.fr/2018GREAU046)
|
||||
- [ ] [Vergne A., Le Coz J., Berni C., & Pierrefeu G. (2020), Water Resources Research, 56(2)](https://doi.org/10.1029/2019WR024877)
|
||||
- [ ] [Vergne A., Berni C., Le Coz J., & Tencé F., (2021), Water Resources Research, 57(9)](https://doi.org/10.1029/2021WR029589)
|
||||
|
||||
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 <https://www.gnu.org/licenses/>.
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load Diff
|
|
@ -20,11 +20,16 @@
|
|||
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import os
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
from copy import deepcopy
|
||||
import pandas as pd
|
||||
from PyQt5.QtWidgets import (QWidget, QVBoxLayout, QHBoxLayout, QGroupBox, QComboBox,
|
||||
QLabel, QPushButton, QSpacerItem,
|
||||
QSlider, QLineEdit, QMessageBox, QFileDialog)
|
||||
|
||||
from PyQt5.QtCore import QCoreApplication, Qt
|
||||
from PyQt5.QtGui import QIcon, QPixmap
|
||||
|
||||
import numpy as np
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
|
|
@ -32,14 +37,9 @@ from matplotlib.colors import LogNorm
|
|||
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
|
||||
from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolBar
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QHBoxLayout, QGroupBox, QComboBox,
|
||||
QLabel, QPushButton, QSpacerItem, QSlider, QLineEdit,
|
||||
QMessageBox, QFileDialog
|
||||
)
|
||||
from os import chdir
|
||||
|
||||
from PyQt5.QtCore import QCoreApplication, Qt
|
||||
from PyQt5.QtGui import QIcon, QPixmap
|
||||
from copy import deepcopy
|
||||
|
||||
from View.checkable_combobox import CheckableComboBox
|
||||
|
||||
|
|
@ -1671,81 +1671,96 @@ class AcousticInversionTab(QWidget):
|
|||
self.figure_measured_vs_inverted_sand.canvas.draw_idle()
|
||||
|
||||
def save_result_in_excel_file(self):
|
||||
|
||||
if self.combobox_acoustic_data_choice.count() > 0:
|
||||
|
||||
name = QFileDialog.getSaveFileName(
|
||||
caption="Save As - Inversion results",
|
||||
directory="",
|
||||
filter="Excel Files (*.xlsx)",
|
||||
options=QFileDialog.DontUseNativeDialog
|
||||
)
|
||||
caption="Save As - Inversion results", directory="", filter="Excel Files (*.xlsx)",
|
||||
options=QFileDialog.DontUseNativeDialog)
|
||||
|
||||
if name[0]:
|
||||
dirname = os.path.dirname(name[0])
|
||||
filename = os.path.basename(name[0])
|
||||
os.chdir(dirname)
|
||||
|
||||
results = []
|
||||
dirname = "/".join(name[0].split("/")[:-1]) + "/"
|
||||
filename = name[0].split("/")[-1]
|
||||
chdir(dirname)
|
||||
|
||||
for k in range(self.combobox_acoustic_data_choice.count()):
|
||||
|
||||
if stg.time_cross_section[k].shape != (0,):
|
||||
time_data = stg.time_cross_section
|
||||
|
||||
if stg.depth_cross_section[k].shape != (0,):
|
||||
|
||||
t = np.repeat(stg.time_cross_section[k][stg.frequency_for_inversion[1]],
|
||||
stg.depth_cross_section[k].shape[1])
|
||||
|
||||
r = np.zeros((stg.depth_cross_section[k].shape[1] *stg.time_cross_section[k].shape[1],1))
|
||||
|
||||
for i in range(stg.time_cross_section[k].shape[1]):
|
||||
for j in range(stg.depth_cross_section[k].shape[1]):
|
||||
r[i * stg.depth_cross_section[k].shape[1] + j] = (
|
||||
stg.depth_cross_section[k][int(stg.frequency_for_inversion[1]), j])
|
||||
|
||||
if stg.SSC_fine[k].shape == (0,):
|
||||
stg.SSC_fine[k] = np.zeros(r.shape[0])
|
||||
if stg.SSC_sand[k].shape == (0,):
|
||||
stg.SSC_sand[k] = np.zeros(r.shape[0])
|
||||
|
||||
else:
|
||||
|
||||
t = np.repeat(stg.time_cross_section[k][stg.frequency_for_inversion[1]], stg.depth[k].shape[1])
|
||||
|
||||
r = np.zeros((stg.depth[k].shape[1] * stg.time_cross_section[k].shape[1], 1))
|
||||
for i in range(stg.time_cross_section[k].shape[1]):
|
||||
for j in range(stg.depth[k].shape[1]):
|
||||
r[i * stg.depth[k].shape[1] + j] = (
|
||||
stg.depth[k][int(stg.frequency_for_inversion[1]), j])
|
||||
|
||||
if stg.SSC_fine[k].shape == (0,):
|
||||
stg.SSC_fine[k] = np.zeros(r.shape[0])
|
||||
if stg.SSC_sand[k].shape == (0,):
|
||||
stg.SSC_sand[k] = np.zeros(r.shape[0])
|
||||
|
||||
else:
|
||||
time_data = stg.time
|
||||
|
||||
if stg.depth_cross_section[k].shape != (0,):
|
||||
depth_data = stg.depth_cross_section
|
||||
else:
|
||||
depth_data = stg.depth
|
||||
if stg.depth_cross_section[k].shape != (0,):
|
||||
|
||||
t = np.repeat(stg.time[k][stg.frequency_for_inversion[1]], stg.depth_cross_section[k].shape[1])
|
||||
|
||||
r = np.zeros((stg.depth_cross_section[k].shape[1] * stg.time[k].shape[1], 1))
|
||||
for i in range(stg.time[k].shape[1]):
|
||||
for j in range(stg.depth_cross_section[k].shape[1]):
|
||||
r[i * stg.depth_cross_section[k].shape[1] + j] = (
|
||||
stg.depth_cross_section[k][int(stg.frequency_for_inversion[1]), j])
|
||||
|
||||
if stg.SSC_fine[k].shape == (0,):
|
||||
stg.SSC_fine[k] = np.zeros(r.shape[0])
|
||||
if stg.SSC_sand[k].shape == (0,):
|
||||
stg.SSC_sand[k] = np.zeros(r.shape[0])
|
||||
|
||||
else:
|
||||
|
||||
t = np.repeat(stg.time[k][stg.frequency_for_inversion[1]], stg.depth[k].shape[1])
|
||||
|
||||
r = np.zeros(stg.depth[k].shape[1] * stg.time[k].shape[1])
|
||||
|
||||
for i in range(stg.time[k].shape[1]):
|
||||
for j in range(stg.depth[k].shape[1]):
|
||||
r[i * stg.depth[k].shape[1] + j] = (
|
||||
stg.depth[k][int(stg.frequency_for_inversion[1]), j])
|
||||
|
||||
if stg.SSC_fine[k].shape == (0,):
|
||||
stg.SSC_fine[k] = np.zeros(r.shape[0])
|
||||
if stg.SSC_sand[k].shape == (0,):
|
||||
stg.SSC_sand[k] = np.zeros(r.shape[0])
|
||||
|
||||
exec("result_" + str(k) + "= pd.DataFrame({'Time (sec)': t," +
|
||||
"'Depth (m)': r," +
|
||||
"'SSC_fine (g/L)': stg.SSC_fine[" + str(k) + "].reshape(t.shape[0])," +
|
||||
"'SSC_sand (g/L)': stg.SSC_sand[" + str(k) + "].reshape(t.shape[0])})")
|
||||
|
||||
|
||||
t = np.repeat(
|
||||
time_data[k][stg.frequency_for_inversion[1]],
|
||||
depth_data[k].shape[1]
|
||||
)
|
||||
|
||||
r = np.zeros(
|
||||
depth_data[k].shape[1] * time_data[k].shape[1]
|
||||
)
|
||||
|
||||
for i in range(time_data[k].shape[1]):
|
||||
for j in range(depth_data[k].shape[1]):
|
||||
r_id = i * depth_data[k].shape[1] + j
|
||||
|
||||
r[r_id] = (
|
||||
depth_data[k][
|
||||
int(stg.frequency_for_inversion[1]), j
|
||||
]
|
||||
)
|
||||
|
||||
if stg.SSC_fine[k].shape == (0,):
|
||||
stg.SSC_fine[k] = np.zeros(r.shape[0])
|
||||
if stg.SSC_sand[k].shape == (0,):
|
||||
stg.SSC_sand[k] = np.zeros(r.shape[0])
|
||||
|
||||
results.append(
|
||||
pd.DataFrame(
|
||||
{
|
||||
'Time (sec)': list(t),
|
||||
'Depth (m)': list(r),
|
||||
'SSC_fine (g/L)': list(
|
||||
stg.SSC_fine[k].reshape(t.shape[0])
|
||||
),
|
||||
'SSC_sand (g/L)': list(
|
||||
stg.SSC_sand[k].reshape(t.shape[0])
|
||||
),
|
||||
}
|
||||
)
|
||||
)
|
||||
|
||||
if os.path.splitext(filename)[1] != ".xlsx":
|
||||
filename += ".xlsx"
|
||||
|
||||
with pd.ExcelWriter(
|
||||
os.path.join(dirname, filename)
|
||||
) as writer:
|
||||
with pd.ExcelWriter(dirname + filename + '.xlsx') as writer:
|
||||
for k in range(self.combobox_acoustic_data_choice.count()):
|
||||
results[k].to_excel(
|
||||
writer, index=False,
|
||||
engine='xlsxwriter', na_rep='NA',
|
||||
sheet_name=stg.data_preprocessed[k],
|
||||
)
|
||||
eval("result_" + str(k) + ".to_excel(writer, index=False, " +
|
||||
"engine='xlsxwriter', na_rep='NA', " +
|
||||
"sheet_name=stg.data_preprocessed[" + str(k) + "])")
|
||||
|
|
|
|||
|
|
@ -147,14 +147,12 @@ class Ui_MainWindow(object):
|
|||
icon6.addPixmap(QtGui.QPixmap("icons/en.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
|
||||
self.actionEnglish.setIcon(icon6)
|
||||
self.actionEnglish.setObjectName("actionEnglish")
|
||||
self.actionEnglish.setEnabled(False)
|
||||
|
||||
self.actionFrench = QtWidgets.QAction(self.mainwindow)
|
||||
icon7 = QtGui.QIcon()
|
||||
icon7.addPixmap(QtGui.QPixmap("icons/fr.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
|
||||
self.actionFrench.setIcon(icon7)
|
||||
self.actionFrench.setObjectName("actionFrench")
|
||||
self.actionFrench.setEnabled(False)
|
||||
|
||||
self.action_ABSCalibrationConstant = QtWidgets.QAction(self.mainwindow)
|
||||
self.action_ABSCalibrationConstant.setText("ABS constant calibration kt")
|
||||
|
|
@ -270,10 +268,7 @@ class Ui_MainWindow(object):
|
|||
)
|
||||
|
||||
def save(self):
|
||||
if stg.dirname_save_as:
|
||||
UpdateTableForSave()
|
||||
else:
|
||||
self.save_as()
|
||||
UpdateTableForSave()
|
||||
|
||||
def open(self):
|
||||
reader = ReadTableForOpen()
|
||||
|
|
|
|||
|
|
@ -1716,18 +1716,14 @@ class SedimentCalibrationTab(QWidget):
|
|||
self.animaiton_groupbox_compute.start()
|
||||
|
||||
def import_calibration_file(self):
|
||||
|
||||
filename = QFileDialog.getOpenFileName(
|
||||
self, "Open calibration",
|
||||
[
|
||||
stg.path_calibration_file
|
||||
if stg.path_calibration_file
|
||||
else stg.path_BS_raw_data[-1]
|
||||
if self.combobox_acoustic_data_choice.count() > 0
|
||||
else ""
|
||||
][0],
|
||||
[stg.path_calibration_file if stg.path_calibration_file else
|
||||
stg.path_BS_raw_data[
|
||||
-1] if self.combobox_acoustic_data_choice.count() > 0 else ""][0],
|
||||
"Calibration file (*.xls, *.ods, *csv)",
|
||||
options=QFileDialog.DontUseNativeDialog
|
||||
)
|
||||
options=QFileDialog.DontUseNativeDialog)
|
||||
|
||||
dir_name = os.path.dirname(filename[0])
|
||||
name = os.path.basename(filename[0])
|
||||
|
|
@ -1740,188 +1736,114 @@ class SedimentCalibrationTab(QWidget):
|
|||
|
||||
self.lineEdit_import_calibration.setToolTip(dir_name)
|
||||
|
||||
self.compute_depth_2D()
|
||||
self.read_calibration_file_and_fill_parameter()
|
||||
|
||||
def update_label_freq1_for_calibration(self):
|
||||
self.label_freq1.clear()
|
||||
self.label_freq1.setText(
|
||||
str(self.combobox_freq1.currentText())
|
||||
)
|
||||
self.label_freq1.setText(str(self.combobox_freq1.currentText()))
|
||||
|
||||
def update_label_freq2_for_calibration(self):
|
||||
self.label_freq2.clear()
|
||||
self.label_freq2.setText(
|
||||
self.combobox_freq2.currentText()
|
||||
)
|
||||
self.label_freq2.setText(self.combobox_freq2.currentText())
|
||||
|
||||
def update_label_kt_value_for_calibration(self):
|
||||
print("self.combobox_freq1.currentIndex() ",
|
||||
self.combobox_freq1.currentIndex(),
|
||||
self.combobox_freq1.currentText())
|
||||
|
||||
freq_1 = self.combobox_freq1.currentIndex()
|
||||
freq_2 = self.combobox_freq2.currentIndex()
|
||||
|
||||
self.label_kt_freq1.clear()
|
||||
if stg.kt_corrected[freq_1] != stg.kt_read[freq_1]:
|
||||
self.label_kt_freq1.setText(
|
||||
str('%.4f' % stg.kt_corrected[freq_1])
|
||||
)
|
||||
print("self.combobox_freq1.currentIndex() ", self.combobox_freq1.currentIndex(), self.combobox_freq1.currentText())
|
||||
if stg.kt_corrected[self.combobox_freq1.currentIndex()] != stg.kt_read[self.combobox_freq1.currentIndex()]:
|
||||
self.label_kt_freq1.setText(str('%.4f' % stg.kt_corrected[self.combobox_freq1.currentIndex()]))
|
||||
else:
|
||||
self.label_kt_freq1.setText(
|
||||
str('%.4f' % stg.kt_read[freq_1])
|
||||
)
|
||||
self.label_kt_freq1.setText(str('%.4f' % stg.kt_read[self.combobox_freq1.currentIndex()]))
|
||||
|
||||
self.label_kt_freq2.clear()
|
||||
if stg.kt_corrected[freq_2] != stg.kt_read[freq_2]:
|
||||
self.label_kt_freq2.setText(
|
||||
str('%.4f' % stg.kt_corrected[freq_2])
|
||||
)
|
||||
if stg.kt_corrected[self.combobox_freq2.currentIndex()] != stg.kt_read[self.combobox_freq2.currentIndex()]:
|
||||
self.label_kt_freq2.setText(str('%.4f' % stg.kt_corrected[self.combobox_freq2.currentIndex()]))
|
||||
else:
|
||||
self.label_kt_freq2.setText(
|
||||
str('%.4f' % stg.kt_read[freq_2])
|
||||
)
|
||||
self.label_kt_freq2.setText(str('%.4f' % stg.kt_read[self.combobox_freq2.currentIndex()]))
|
||||
|
||||
def read_calibration_file_and_fill_parameter(self):
|
||||
if self.combobox_acoustic_data_choice.count() == 0:
|
||||
|
||||
msgBox = QMessageBox()
|
||||
msgBox.setWindowTitle("Calibration import error")
|
||||
msgBox.setIconPixmap(
|
||||
QPixmap(
|
||||
self._path_icon("no_approved.png")
|
||||
).scaledToHeight(32, Qt.SmoothTransformation)
|
||||
)
|
||||
QPixmap(self._path_icon("no_approved.png")).scaledToHeight(32, Qt.SmoothTransformation))
|
||||
msgBox.setText("Update data before importing calibration")
|
||||
msgBox.setStandardButtons(QMessageBox.Ok)
|
||||
msgBox.exec()
|
||||
|
||||
elif stg.filename_calibration_file == "":
|
||||
|
||||
pass
|
||||
|
||||
else:
|
||||
|
||||
# --- Read calibration file ---
|
||||
data = pd.read_csv(os.path.join(stg.path_calibration_file, stg.filename_calibration_file), header=0, index_col=0)
|
||||
data = pd.read_csv(stg.path_calibration_file + "/" + stg.filename_calibration_file, header=0, index_col=0)
|
||||
|
||||
# --- Fill spinboxes of calibration parameter ---
|
||||
self.label_temperature.clear()
|
||||
self.label_temperature.setText(
|
||||
"T = " + str(stg.temperature) + " °C"
|
||||
)
|
||||
self.label_temperature.setText("T = " + str(stg.temperature) + " °C")
|
||||
|
||||
self.label_freq1.clear()
|
||||
self.label_freq1.setText(data.columns[0])
|
||||
|
||||
data_id = self.combobox_acoustic_data_choice.currentIndex()
|
||||
|
||||
index_freq1 = np.where(
|
||||
np.asarray(
|
||||
stg.freq_text[data_id]
|
||||
) == data.columns[0]
|
||||
)[0][0]
|
||||
|
||||
index_freq1 = np.where(np.asarray(stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()]) ==
|
||||
data.columns[0])[0][0]
|
||||
stg.frequencies_for_calibration.clear()
|
||||
stg.frequencies_for_calibration.append(
|
||||
(
|
||||
stg.freq[data_id][index_freq1],
|
||||
index_freq1
|
||||
)
|
||||
)
|
||||
stg.frequencies_for_calibration.append((stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
index_freq1],
|
||||
index_freq1))
|
||||
|
||||
self.label_freq2.clear()
|
||||
self.label_freq2.setText(data.columns[1])
|
||||
|
||||
index_freq2 = np.where(
|
||||
np.asarray(
|
||||
stg.freq_text[data_id]
|
||||
) == data.columns[1]
|
||||
)[0][0]
|
||||
|
||||
stg.frequencies_for_calibration.append(
|
||||
(
|
||||
stg.freq[data_id][index_freq2],
|
||||
index_freq2
|
||||
)
|
||||
)
|
||||
index_freq2 = np.where(np.asarray(stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()]) ==
|
||||
data.columns[1])[0][0]
|
||||
stg.frequencies_for_calibration.append((stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
index_freq2],
|
||||
index_freq2))
|
||||
|
||||
stg.frequency_for_inversion = tuple()
|
||||
stg.frequency_for_inversion = (
|
||||
stg.freq[data_id][index_freq2],
|
||||
index_freq2
|
||||
)
|
||||
stg.frequency_for_inversion = (stg.freq[self.combobox_acoustic_data_choice.currentIndex()][index_freq2],
|
||||
index_freq2)
|
||||
|
||||
self.lineEdit_ks_freq1.clear()
|
||||
self.lineEdit_ks_freq1.setText(
|
||||
str("%.5f" % float(data.iloc[0][0]))
|
||||
)
|
||||
self.lineEdit_ks_freq1.setText(str("%.5f" % float(data.iloc[0][0])))
|
||||
|
||||
self.lineEdit_ks_freq2.clear()
|
||||
self.lineEdit_ks_freq2.setText(
|
||||
str("%.5f" % float(data.iloc[0][1]))
|
||||
)
|
||||
self.lineEdit_ks_freq2.setText(str("%.5f" % float(data.iloc[0][1])))
|
||||
|
||||
stg.ks.clear()
|
||||
stg.ks = [
|
||||
float(self.lineEdit_ks_freq1.text()),
|
||||
float(self.lineEdit_ks_freq2.text())
|
||||
]
|
||||
stg.ks = [float(self.lineEdit_ks_freq1.text()), float(self.lineEdit_ks_freq2.text())]
|
||||
|
||||
self.lineEdit_sv_freq1.clear()
|
||||
self.lineEdit_sv_freq1.setText(
|
||||
str("%.5f" % float(data.iloc[1][0]))
|
||||
)
|
||||
self.lineEdit_sv_freq1.setText(str("%.5f" % float(data.iloc[1][0])))
|
||||
|
||||
self.lineEdit_sv_freq2.clear()
|
||||
self.lineEdit_sv_freq2.setText(
|
||||
str("%.5f" % float(data.iloc[1][1]))
|
||||
)
|
||||
self.lineEdit_sv_freq2.setText(str("%.5f" % float(data.iloc[1][1])))
|
||||
|
||||
stg.sv.clear()
|
||||
stg.sv = [
|
||||
float(self.lineEdit_sv_freq1.text()),
|
||||
float(self.lineEdit_sv_freq2.text())
|
||||
]
|
||||
stg.sv = [float(self.lineEdit_sv_freq1.text()), float(self.lineEdit_sv_freq2.text())]
|
||||
|
||||
self.lineEdit_X.clear()
|
||||
self.lineEdit_X.setText(
|
||||
str("%.2f" % float(data.iloc[2][0]))
|
||||
)
|
||||
self.lineEdit_X.setText(str("%.2f" % float(data.iloc[2][0])))
|
||||
|
||||
stg.X_exponent.clear()
|
||||
stg.X_exponent.append(float(self.lineEdit_X.text()))
|
||||
|
||||
self.lineEdit_alphas_freq1.clear()
|
||||
self.lineEdit_alphas_freq1.setText(
|
||||
str("%.5f" % float(data.iloc[3][0]))
|
||||
)
|
||||
self.lineEdit_alphas_freq1.setText(str("%.5f" % float(data.iloc[3][0])))
|
||||
|
||||
self.lineEdit_alphas_freq2.clear()
|
||||
self.lineEdit_alphas_freq2.setText(
|
||||
str("%.5f" % float(data.iloc[3][1]))
|
||||
)
|
||||
self.lineEdit_alphas_freq2.setText(str("%.5f" % float(data.iloc[3][1])))
|
||||
|
||||
stg.alpha_s.clear()
|
||||
stg.alpha_s = [
|
||||
float(self.lineEdit_alphas_freq1.text()),
|
||||
float(self.lineEdit_alphas_freq2.text())
|
||||
]
|
||||
stg.alpha_s = [float(self.lineEdit_alphas_freq1.text()), float(self.lineEdit_alphas_freq2.text())]
|
||||
|
||||
self.lineEdit_zeta_freq1.clear()
|
||||
self.lineEdit_zeta_freq1.setText(
|
||||
str("%.5f" % float(data.iloc[4][0]))
|
||||
)
|
||||
self.lineEdit_zeta_freq1.setText(str("%.5f" % float(data.iloc[4][0])))
|
||||
|
||||
self.lineEdit_zeta_freq2.clear()
|
||||
self.lineEdit_zeta_freq2.setText(
|
||||
str("%.5f" % float(data.iloc[4][1]))
|
||||
)
|
||||
self.lineEdit_zeta_freq2.setText(str("%.5f" % float(data.iloc[4][1])))
|
||||
|
||||
stg.zeta.clear()
|
||||
stg.zeta = [
|
||||
float(self.lineEdit_zeta_freq1.text()),
|
||||
float(self.lineEdit_zeta_freq2.text())
|
||||
]
|
||||
stg.zeta = [float(self.lineEdit_zeta_freq1.text()), float(self.lineEdit_zeta_freq2.text())]
|
||||
|
||||
self.compute_kt2D_kt3D()
|
||||
self.compute_J_cross_section()
|
||||
|
|
@ -2009,8 +1931,8 @@ class SedimentCalibrationTab(QWidget):
|
|||
self.compute_zeta()
|
||||
|
||||
def compute_ks(self):
|
||||
data_id = self.combobox_acoustic_data_choice.currentIndex()
|
||||
|
||||
# --- Compute ks ---
|
||||
psd_number_of_particles = (
|
||||
self.inv_hc.compute_particle_size_distribution_in_number_of_particles(
|
||||
num_sample=stg.sand_sample_target[0][1],
|
||||
|
|
@ -2021,13 +1943,17 @@ class SedimentCalibrationTab(QWidget):
|
|||
|
||||
ks_freq1 = self.inv_hc.ks(
|
||||
proba_num=psd_number_of_particles,
|
||||
freq=stg.freq[data_id][self.combobox_freq1.currentIndex()],
|
||||
freq=stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
self.combobox_freq1.currentIndex()
|
||||
],
|
||||
C=stg.water_velocity
|
||||
)
|
||||
|
||||
ks_freq2 = self.inv_hc.ks(
|
||||
proba_num=psd_number_of_particles,
|
||||
freq=stg.freq[data_id][self.combobox_freq2.currentIndex()],
|
||||
freq=stg.freq[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
self.combobox_freq2.currentIndex()
|
||||
],
|
||||
C=stg.water_velocity
|
||||
)
|
||||
|
||||
|
|
@ -2035,12 +1961,12 @@ class SedimentCalibrationTab(QWidget):
|
|||
|
||||
logger.debug(
|
||||
"ks for frequency of "
|
||||
+ f"{stg.freq[data_id][self.combobox_freq1.currentIndex()]} : "
|
||||
+ f"{stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq1.currentIndex()]} : "
|
||||
+ f"{ks_freq1} m/kg^0.5 \n"
|
||||
)
|
||||
logger.debug(
|
||||
"ks for frequency of "
|
||||
+ f"{stg.freq[data_id][self.combobox_freq2.currentIndex()]} : " +
|
||||
+ f"{stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex()]} : " +
|
||||
f"{ks_freq2} m/kg^0.5"
|
||||
)
|
||||
|
||||
|
|
@ -2051,21 +1977,13 @@ class SedimentCalibrationTab(QWidget):
|
|||
self.lineEdit_ks_freq2.setText(str("%.5f" % ks_freq2))
|
||||
|
||||
def compute_sv(self):
|
||||
data_id = self.combobox_acoustic_data_choice.currentIndex()
|
||||
|
||||
sv_freq1 = self.inv_hc.sv(ks=stg.ks[0], M_sand=stg.Ctot_sand[stg.sand_sample_target[0][1]])
|
||||
sv_freq2 = self.inv_hc.sv(ks=stg.ks[1], M_sand=stg.Ctot_sand[stg.sand_sample_target[0][1]])
|
||||
|
||||
stg.sv = [sv_freq1, sv_freq2]
|
||||
|
||||
print(
|
||||
f"sv for frequency of {stg.freq[data_id][self.combobox_freq1.currentIndex()]}"
|
||||
+ f" : {sv_freq1:.8f} /m \n"
|
||||
)
|
||||
print(
|
||||
f"sv for frequency of {stg.freq[data_id][self.combobox_freq2.currentIndex()]}"
|
||||
+ f" : {sv_freq2:.8f} /m"
|
||||
)
|
||||
print(f"sv for frequency of {stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq1.currentIndex()]} : {sv_freq1:.8f} /m \n")
|
||||
print(f"sv for frequency of {stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex()]} : {sv_freq2:.8f} /m")
|
||||
|
||||
self.lineEdit_sv_freq1.clear()
|
||||
self.lineEdit_sv_freq1.setText(str("%.5f" % sv_freq1))
|
||||
|
|
@ -2074,13 +1992,9 @@ class SedimentCalibrationTab(QWidget):
|
|||
self.lineEdit_sv_freq2.setText(str("%.5f" % sv_freq2))
|
||||
|
||||
def compute_X(self):
|
||||
data_id = self.combobox_acoustic_data_choice.currentIndex()
|
||||
|
||||
X_exponent = self.inv_hc.X_exponent(
|
||||
freq1=stg.freq[data_id][self.combobox_freq1.currentIndex()],
|
||||
freq2=stg.freq[data_id][self.combobox_freq2.currentIndex()],
|
||||
sv_freq1=stg.sv[0], sv_freq2=stg.sv[1]
|
||||
)
|
||||
X_exponent = self.inv_hc.X_exponent(freq1=stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq1.currentIndex()],
|
||||
freq2=stg.freq[self.combobox_acoustic_data_choice.currentIndex()][self.combobox_freq2.currentIndex()],
|
||||
sv_freq1=stg.sv[0], sv_freq2=stg.sv[1])
|
||||
|
||||
stg.X_exponent.clear()
|
||||
stg.X_exponent.append(X_exponent)
|
||||
|
|
@ -2123,90 +2037,190 @@ class SedimentCalibrationTab(QWidget):
|
|||
)
|
||||
|
||||
def compute_J_cross_section(self):
|
||||
lst_bs_data = [
|
||||
stg.BS_stream_bed_pre_process_average,
|
||||
stg.BS_stream_bed_pre_process_SNR,
|
||||
stg.BS_stream_bed,
|
||||
stg.BS_cross_section_pre_process_average,
|
||||
stg.BS_cross_section_pre_process_SNR,
|
||||
stg.BS_cross_section,
|
||||
stg.BS_raw_data_pre_process_average,
|
||||
stg.BS_raw_data_pre_process_SNR,
|
||||
stg.BS_raw_data
|
||||
]
|
||||
|
||||
for i in range(self.combobox_acoustic_data_choice.count()):
|
||||
|
||||
J_cross_section_freq1 = np.array([])
|
||||
J_cross_section_freq2 = np.array([])
|
||||
|
||||
for data in lst_bs_data:
|
||||
if data[i].shape != (0,):
|
||||
bs_data = data
|
||||
break
|
||||
# --- Compute J ---
|
||||
if stg.BS_stream_bed_pre_process_average[i].shape != (0,):
|
||||
|
||||
print(f"{stg.depth_2D[i].shape}")
|
||||
print(f"{stg.depth_2D[i]}")
|
||||
J_cross_section_freq1 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_stream_bed_pre_process_average[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1],
|
||||
:, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
|
||||
|
||||
J_cross_section_freq1 = self.inv_hc.j_cross_section(
|
||||
BS = bs_data[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :
|
||||
],
|
||||
r2D = stg.depth_2D[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :
|
||||
],
|
||||
kt = stg.kt3D[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :
|
||||
]
|
||||
)
|
||||
J_cross_section_freq2 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_stream_bed_pre_process_average[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1],
|
||||
:, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
|
||||
|
||||
J_cross_section_freq2 = self.inv_hc.j_cross_section(
|
||||
BS = bs_data[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :
|
||||
],
|
||||
r2D = stg.depth_2D[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :
|
||||
],
|
||||
kt = stg.kt3D[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :
|
||||
]
|
||||
)
|
||||
elif stg.BS_stream_bed_pre_process_SNR[i].shape != (0,):
|
||||
|
||||
J_cross_section_freq1 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_stream_bed_pre_process_SNR[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1],
|
||||
:, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
|
||||
|
||||
J_cross_section_freq2 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_stream_bed_pre_process_SNR[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1],
|
||||
:, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
|
||||
|
||||
elif stg.BS_stream_bed[i].shape != (0,):
|
||||
|
||||
J_cross_section_freq1 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_stream_bed[i][stg.frequencies_for_calibration[0][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1], :, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
|
||||
|
||||
J_cross_section_freq2 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_stream_bed[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1], :, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
|
||||
|
||||
elif stg.BS_cross_section_pre_process_average[i].shape != (0,):
|
||||
|
||||
J_cross_section_freq1 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_cross_section_pre_process_average[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1],
|
||||
:, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
|
||||
|
||||
J_cross_section_freq2 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_cross_section_pre_process_average[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1],
|
||||
:, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
|
||||
|
||||
elif stg.BS_cross_section_pre_process_SNR[i].shape != (0,):
|
||||
|
||||
J_cross_section_freq1 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_cross_section_pre_process_SNR[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1],
|
||||
:, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
|
||||
|
||||
J_cross_section_freq2 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_cross_section_pre_process_SNR[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1],
|
||||
:, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
|
||||
|
||||
elif stg.BS_cross_section[i].shape != (0,):
|
||||
|
||||
J_cross_section_freq1 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_cross_section[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :],
|
||||
r2D=stg.depth_2D[i, :, :][stg.frequencies_for_calibration[0][1], :, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
|
||||
|
||||
J_cross_section_freq2 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_cross_section[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :],
|
||||
r2D=stg.depth_2D[i, :, :][stg.frequencies_for_calibration[1][1], :, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
|
||||
|
||||
elif stg.BS_raw_data_pre_process_average[i].shape != (0,):
|
||||
|
||||
J_cross_section_freq1 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_raw_data_pre_process_average[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1], :, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
|
||||
|
||||
J_cross_section_freq2 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_raw_data_pre_process_average[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1], :, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
|
||||
|
||||
elif stg.BS_raw_data_pre_process_SNR[i].shape != (0,):
|
||||
|
||||
J_cross_section_freq1 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_raw_data_pre_process_SNR[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1], :, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
|
||||
|
||||
J_cross_section_freq2 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_raw_data_pre_process_SNR[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1], :, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
|
||||
|
||||
elif stg.BS_raw_data:
|
||||
|
||||
J_cross_section_freq1 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_raw_data[i][
|
||||
stg.frequencies_for_calibration[0][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[0][1], :, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[0][1], :, :])
|
||||
|
||||
J_cross_section_freq2 = self.inv_hc.j_cross_section(
|
||||
BS=stg.BS_raw_data[i][
|
||||
stg.frequencies_for_calibration[1][1], :, :],
|
||||
r2D=stg.depth_2D[i][stg.frequencies_for_calibration[1][1], :, :],
|
||||
kt=stg.kt3D[i][stg.frequencies_for_calibration[1][1], :, :])
|
||||
|
||||
stg.J_cross_section[i][0] = J_cross_section_freq1
|
||||
stg.J_cross_section[i][1] = J_cross_section_freq2
|
||||
|
||||
def compute_alpha_s(self):
|
||||
data_id = self.combobox_acoustic_data_choice.currentIndex()
|
||||
freq_1 = self.combobox_freq1.currentIndex()
|
||||
freq_2 = self.combobox_freq2.currentIndex()
|
||||
|
||||
depth_data = stg.depth
|
||||
if stg.depth_cross_section[data_id].shape != (0,):
|
||||
depth_data = stg.depth_cross_section
|
||||
# --- Compute alpha_s ---
|
||||
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
alpha_s_freq1 = self.inv_hc.alpha_s(
|
||||
sv=stg.sv[0],
|
||||
j_cross_section=stg.J_cross_section[data_id][0][
|
||||
stg.sand_sample_target_indice[0][0],
|
||||
stg.sand_sample_target_indice[0][1]
|
||||
],
|
||||
depth=depth_data[data_id][
|
||||
freq_1, stg.sand_sample_target_indice[0][0]
|
||||
],
|
||||
alpha_w=stg.water_attenuation[data_id][freq_1]
|
||||
)
|
||||
alpha_s_freq1 = self.inv_hc.alpha_s(
|
||||
sv=stg.sv[0],
|
||||
j_cross_section=stg.J_cross_section[self.combobox_acoustic_data_choice.currentIndex()][0][
|
||||
stg.sand_sample_target_indice[0][0], stg.sand_sample_target_indice[0][1]],
|
||||
depth=stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
self.combobox_freq1.currentIndex(), stg.sand_sample_target_indice[0][0]],
|
||||
alpha_w=stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
self.combobox_freq1.currentIndex()])
|
||||
|
||||
alpha_s_freq2 = self.inv_hc.alpha_s(
|
||||
sv=stg.sv[1],
|
||||
j_cross_section=stg.J_cross_section[data_id][1][
|
||||
stg.sand_sample_target_indice[1][0],
|
||||
stg.sand_sample_target_indice[1][1]
|
||||
],
|
||||
depth=depth_data[data_id][
|
||||
freq_2, stg.sand_sample_target_indice[1][0]
|
||||
],
|
||||
alpha_w=stg.water_attenuation[data_id][freq_2]
|
||||
)
|
||||
alpha_s_freq2 = self.inv_hc.alpha_s(
|
||||
sv=stg.sv[1],
|
||||
j_cross_section=stg.J_cross_section[self.combobox_acoustic_data_choice.currentIndex()][1][
|
||||
stg.sand_sample_target_indice[1][0], stg.sand_sample_target_indice[1][1]],
|
||||
depth=stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[1][0]],
|
||||
alpha_w=stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
self.combobox_freq2.currentIndex()])
|
||||
|
||||
else:
|
||||
|
||||
alpha_s_freq1 = self.inv_hc.alpha_s(
|
||||
sv=stg.sv[0],
|
||||
j_cross_section=stg.J_cross_section[self.combobox_acoustic_data_choice.currentIndex()][0][
|
||||
stg.sand_sample_target_indice[0][0], stg.sand_sample_target_indice[0][1]],
|
||||
depth=stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
self.combobox_freq1.currentIndex(), stg.sand_sample_target_indice[0][0]],
|
||||
alpha_w=stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
self.combobox_freq1.currentIndex()])
|
||||
|
||||
alpha_s_freq2 = self.inv_hc.alpha_s(
|
||||
sv=stg.sv[1],
|
||||
j_cross_section=stg.J_cross_section[self.combobox_acoustic_data_choice.currentIndex()][1][
|
||||
stg.sand_sample_target_indice[1][0], stg.sand_sample_target_indice[1][1]],
|
||||
depth=stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
self.combobox_freq2.currentIndex(), stg.sand_sample_target_indice[1][0]],
|
||||
alpha_w=stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
||||
self.combobox_freq2.currentIndex()])
|
||||
|
||||
stg.alpha_s = [alpha_s_freq1, alpha_s_freq2]
|
||||
|
||||
|
|
|
|||
|
|
@ -447,8 +447,8 @@ class SignalProcessingTab(QWidget):
|
|||
# --------------------------------------------------------------------------------------------------------------
|
||||
|
||||
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.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)
|
||||
|
||||
|
|
@ -501,39 +501,26 @@ class SignalProcessingTab(QWidget):
|
|||
- 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()
|
||||
self.combobox_acoustic_data_choice.clear()
|
||||
self.combobox_acoustic_data_choice.addItems(stg.filename_BS_raw_data)
|
||||
|
||||
else:
|
||||
if stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 0:
|
||||
|
||||
self.combobox_acoustic_data_choice.clear()
|
||||
self.combobox_acoustic_data_choice.addItems(stg.filename_BS_raw_data)
|
||||
self.groupbox_download_noise_file.setChecked(True)
|
||||
self.groupbox_compute_noise_from_profile_tail.setChecked(False)
|
||||
self.groupbox_download_noise_file_toggle()
|
||||
|
||||
if stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 0:
|
||||
elif stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 1:
|
||||
|
||||
self.groupbox_download_noise_file.setChecked(True)
|
||||
self.groupbox_compute_noise_from_profile_tail.setChecked(False)
|
||||
self.groupbox_download_noise_file_toggle()
|
||||
self.groupbox_download_noise_file.setChecked(False)
|
||||
self.groupbox_compute_noise_from_profile_tail.setChecked(True)
|
||||
self.groupbox_option_profile_tail_toggle()
|
||||
|
||||
elif stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 1:
|
||||
self.combobox_freq_noise_from_profile_tail.clear()
|
||||
self.combobox_freq_noise_from_profile_tail.addItems(stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()])
|
||||
|
||||
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[self.combobox_acoustic_data_choice.currentIndex()])
|
||||
|
||||
self.combobox_acoustic_data_choice.currentIndexChanged.connect(self.combobox_acoustic_data_choice_change_index)
|
||||
|
||||
self.compute_average_profile_tail()
|
||||
self.plot_averaged_profile_tail()
|
||||
self.combobox_acoustic_data_choice.currentIndexChanged.connect(self.combobox_acoustic_data_choice_change_index)
|
||||
|
||||
def activate_list_of_pre_processed_data(self):
|
||||
for i in range(self.combobox_acoustic_data_choice.count()):
|
||||
|
|
@ -667,65 +654,45 @@ class SignalProcessingTab(QWidget):
|
|||
|
||||
# --- Plot averaged signal ---
|
||||
|
||||
if len(stg.filename_BS_raw_data) == 0:
|
||||
if stg.BS_mean[self.combobox_acoustic_data_choice.currentIndex()].shape != (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()
|
||||
self.verticalLayout_groupbox_plot_profile_tail.removeWidget(self.canvas_profile_tail)
|
||||
|
||||
elif self.combobox_acoustic_data_choice.count() == 0:
|
||||
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)
|
||||
|
||||
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()
|
||||
self.verticalLayout_groupbox_plot_profile_tail.addWidget(self.canvas_profile_tail)
|
||||
|
||||
else:
|
||||
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')
|
||||
|
||||
if stg.BS_mean[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
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="Ubuntu", 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="Ubuntu", 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="Ubuntu", c="black", alpha=0.5,
|
||||
horizontalalignment='right', verticalalignment='bottom',
|
||||
transform=self.axis_profile_tail.transAxes)
|
||||
|
||||
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="Ubuntu", 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="Ubuntu", 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="Ubuntu", c="black", alpha=0.5,
|
||||
horizontalalignment='right', verticalalignment='bottom',
|
||||
transform=self.axis_profile_tail.transAxes)
|
||||
|
||||
self.fig_profile_tail.canvas.draw_idle()
|
||||
self.fig_profile_tail.canvas.draw_idle()
|
||||
|
||||
# ------------------------------------------------------
|
||||
|
||||
|
|
@ -755,87 +722,82 @@ class SignalProcessingTab(QWidget):
|
|||
|
||||
def clear_noise_data(self):
|
||||
|
||||
if len(stg.filename_BS_raw_data) == 0:
|
||||
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.noise_method[self.combobox_acoustic_data_choice.currentIndex()] = 0
|
||||
stg.SNR_filter_value[self.combobox_acoustic_data_choice.currentIndex()] = 0
|
||||
|
||||
pass
|
||||
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([])
|
||||
|
||||
else:
|
||||
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_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_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([])
|
||||
|
||||
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([])
|
||||
if stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 0:
|
||||
self.lineEdit_noise_file.clear()
|
||||
|
||||
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([])
|
||||
elif stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 1:
|
||||
self.lineEdit_val1.clear()
|
||||
self.lineEdit_val1.setText("0.00")
|
||||
|
||||
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()
|
||||
self.lineEdit_val2.clear()
|
||||
self.lineEdit_val2.setText("0.00")
|
||||
|
||||
elif stg.noise_method[self.combobox_acoustic_data_choice.currentIndex()] == 1:
|
||||
self.lineEdit_val1.clear()
|
||||
self.lineEdit_val1.setText("0.00")
|
||||
self.lineEdit_profile_tail_value.clear()
|
||||
self.lineEdit_profile_tail_value.setText("0.0000")
|
||||
|
||||
self.lineEdit_val2.clear()
|
||||
self.lineEdit_val2.setText("0.00")
|
||||
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_profile_tail_value.clear()
|
||||
self.lineEdit_profile_tail_value.setText("0.0000")
|
||||
self.lineEdit_SNR_criterion.setText("0.00")
|
||||
self.lineEdit_horizontal_average.setText("0.00")
|
||||
|
||||
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)
|
||||
# --- Clear SNR plot ---
|
||||
self.verticalLayout_groupbox_plot_SNR.removeWidget(self.toolbar_SNR)
|
||||
self.verticalLayout_groupbox_plot_SNR.removeWidget(self.scroll_SNR)
|
||||
|
||||
self.lineEdit_SNR_criterion.setText("0.00")
|
||||
self.lineEdit_horizontal_average.setText("0.00")
|
||||
self.canvas_SNR = FigureCanvas()
|
||||
self.toolbar_SNR = NavigationToolBar(self.canvas_SNR, self)
|
||||
self.scroll_SNR.setWidget(self.canvas_SNR)
|
||||
|
||||
# --- Clear SNR plot ---
|
||||
self.verticalLayout_groupbox_plot_SNR.removeWidget(self.toolbar_SNR)
|
||||
self.verticalLayout_groupbox_plot_SNR.removeWidget(self.scroll_SNR)
|
||||
self.verticalLayout_groupbox_plot_SNR.addWidget(self.toolbar_SNR)
|
||||
self.verticalLayout_groupbox_plot_SNR.addWidget(self.scroll_SNR)
|
||||
|
||||
self.canvas_SNR = FigureCanvas()
|
||||
self.toolbar_SNR = NavigationToolBar(self.canvas_SNR, self)
|
||||
self.scroll_SNR.setWidget(self.canvas_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.verticalLayout_groupbox_plot_SNR.addWidget(self.toolbar_SNR)
|
||||
self.verticalLayout_groupbox_plot_SNR.addWidget(self.scroll_SNR)
|
||||
self.canvas_BS = FigureCanvas()
|
||||
self.toolbar_BS = NavigationToolBar(self.canvas_BS, self)
|
||||
self.scroll_BS.setWidget(self.canvas_BS)
|
||||
|
||||
# --- 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.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.canvas_BS = FigureCanvas()
|
||||
self.toolbar_BS = NavigationToolBar(self.canvas_BS, self)
|
||||
self.scroll_BS.setWidget(self.canvas_BS)
|
||||
self.combobox_frequency_profile.clear()
|
||||
|
||||
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.verticalLayout_groupbox_plot_profile.removeWidget(self.toolbar_profile)
|
||||
self.verticalLayout_groupbox_plot_profile.removeWidget(self.canvas_profile)
|
||||
|
||||
self.combobox_frequency_profile.clear()
|
||||
self.canvas_profile = FigureCanvas()
|
||||
self.toolbar_profile = NavigationToolBar(self.canvas_profile, self)
|
||||
|
||||
self.verticalLayout_groupbox_plot_profile.removeWidget(self.toolbar_profile)
|
||||
self.verticalLayout_groupbox_plot_profile.removeWidget(self.canvas_profile)
|
||||
self.verticalLayout_groupbox_plot_profile.addWidget(self.toolbar_profile)
|
||||
self.verticalLayout_groupbox_plot_profile.addWidget(self.canvas_profile)
|
||||
|
||||
self.canvas_profile = FigureCanvas()
|
||||
self.toolbar_profile = NavigationToolBar(self.canvas_profile, self)
|
||||
self.slider.setValue(1)
|
||||
self.slider.setMaximum(10)
|
||||
|
||||
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)
|
||||
self.slider.setValue(0)
|
||||
self.slider.setMaximum(10)
|
||||
|
||||
def open_dialog_box(self):
|
||||
|
||||
|
|
@ -1259,19 +1221,11 @@ class SignalProcessingTab(QWidget):
|
|||
|
||||
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:
|
||||
if 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.setText("Load Noise data from acoustic data tab before using SNR filter")
|
||||
msgBox.setStandardButtons(QMessageBox.Ok)
|
||||
msgBox.exec()
|
||||
|
||||
|
|
@ -1550,123 +1504,105 @@ class SignalProcessingTab(QWidget):
|
|||
|
||||
def compute_averaged_BS_data(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()
|
||||
kernel_avg = np.ones(2 * int(float(self.lineEdit_horizontal_average.text().replace(",", "."))) + 1)
|
||||
print(kernel_avg)
|
||||
|
||||
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()
|
||||
stg.Nb_cells_to_average_BS_signal[self.combobox_acoustic_data_choice.currentIndex()] = (
|
||||
float(self.lineEdit_horizontal_average.text().replace(",", ".")))
|
||||
|
||||
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_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
|
||||
elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
|
||||
else:
|
||||
|
||||
kernel_avg = np.ones(2 * int(float(self.lineEdit_horizontal_average.text().replace(",", "."))) + 1)
|
||||
print(kernel_avg)
|
||||
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
stg.Nb_cells_to_average_BS_signal[self.combobox_acoustic_data_choice.currentIndex()] = (
|
||||
float(self.lineEdit_horizontal_average.text().replace(",", ".")))
|
||||
x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
|
||||
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
|
||||
x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
if stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
|
||||
x_time = stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
|
||||
else:
|
||||
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
|
||||
kernel_avg))
|
||||
|
||||
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
y_depth = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
|
||||
elif stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
|
||||
x_time = stg.time[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
y_depth = stg.depth[self.combobox_acoustic_data_choice.currentIndex()]
|
||||
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
|
||||
kernel_avg))
|
||||
|
||||
if stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
|
||||
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
|
||||
kernel_avg))
|
||||
stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
|
||||
kernel_avg))
|
||||
|
||||
elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
elif stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
|
||||
|
||||
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
|
||||
kernel_avg))
|
||||
elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
|
||||
stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
|
||||
kernel_avg))
|
||||
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
elif stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
|
||||
kernel_avg))
|
||||
stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
|
||||
elif stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
|
||||
|
||||
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
|
||||
|
||||
elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()][f, i, :],
|
||||
kernel_avg))
|
||||
|
||||
elif stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
||||
|
||||
stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()] = (deepcopy(
|
||||
stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()]))
|
||||
|
||||
for f, _ in enumerate(stg.freq[self.combobox_acoustic_data_choice.currentIndex()]):
|
||||
for i in range(y_depth.shape[1]):
|
||||
stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()][f, i, :] = (
|
||||
convolve(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()][f, i, :], kernel_avg))
|
||||
|
||||
self.plot_pre_processed_BS_signal()
|
||||
self.update_plot_pre_processed_profile()
|
||||
self.plot_pre_processed_BS_signal()
|
||||
self.update_plot_pre_processed_profile()
|
||||
|
||||
def plot_pre_processed_profile(self):
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue