correction fusion

windows comand to zip the file is added
Merge branch 'dev-parouby' into dev
2025-03-20 13:23:15 +01:00 · 2025-03-20 13:20:23 +01:00 · 2025-03-20 11:56:28 +01:00 · 2025-03-20 11:55:26 +01:00 · 2025-03-20 11:06:08 +01:00 · 2025-03-20 11:01:14 +01:00
33 changed files with 3638 additions and 10401 deletions
--- a/.gitignore
+++ b/.gitignore
@ -1,6 +1,9 @@
 TAGS
 Error_file.txt

+# Windows executable file
+*.exe
+
 # Created by https://www.toptal.com/developers/gitignore/api/python
 # Edit at https://www.toptal.com/developers/gitignore?templates=python

--- a/Model/AquascatDataLoader.py
+++ b/Model/AquascatDataLoader.py
@ -721,14 +721,14 @@ class RawAquascatData:
                elif pktType == 41:
                    chan = st.unpack("H", f.read(2))[0] + 1
                    # Increase the Index
-       
+

                    AbsIndex[chan-1] = AbsIndex[chan-1] + 1
                    Tmp = [st.unpack(
                            "h", f.read(2))[0] for ui in np.arange(
                                    1, 2 * AbsNumBins[chan-1]+1)]
                    sss = [x / 32768 for x in Tmp]
-                    
+
                    AbsData[:, int(
                            AbsIndex[chan-1]), int(chan-1)] = np.abs(np.array(sss[0::2])+complex(0,1)*np.array(sss[1::2]))

@ -1097,19 +1097,3 @@ class MeanAquascatProfile:

        file.close()

-# ------------------------- Test  --------------------------------------#
-start_time = time.time()
-
-if __name__ == "__main__":
-#     path1 = r'C:\Users\vergne\Documents\Donnees_aquascat\2017_juillet - experience cuve sediments fins\2017_07_19 - mercredi eau claire\20170719114700.aqa'
-    path1 = r'//home/brahim.moudjed/Documents/3 Software_Project/river_inversion_project/Data/Aquascat data test/20171213135800.aqa'
-    data1 = RawAquascatData(path1)
-    
-#     path2 = r'C:\Users\vergne\Documents\Donnees_aquascat\2017_juillet - experience cuve sediments fins\2017_07_19 - mercredi eau claire\20170719114700.aqa.txt'
-    path2 = r'//home/brahim.moudjed/Documents/3 Software_Project/river_inversion_project/Data/Aquascat data test/20171213135800.txt'
-    data2 = RawAquascatData(path2)
-
-    print(data1.PingRate)
-    print(data2.PingRate)
-
-print("Computational time: %.2f min" %((time.time() - start_time)/60) )
--- a/Model/acoustic_data_loader.py
+++ b/Model/acoustic_data_loader.py
@ -5,35 +5,25 @@ import pandas as pd
 import matplotlib.pyplot as plt
 from matplotlib.colors import LogNorm

-# path_BS_raw_data = "/home/bmoudjed/Documents/2 Data/Confluence_Rhône_Isere_2018/Acoustic_data/20180107123500.aqa"
-# path_BS_raw_data = "/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/" \
-#                        "Data/AcousticNoise_data/20180107121600.aqa"
-

 class AcousticDataLoader:

    def __init__(self, path_BS_raw_data: str):

        self.path_BS_raw_data = path_BS_raw_data
-        print(self.path_BS_raw_data)
        # --- Load Backscatter acoustic raw data with RawAquascatData class ---

        self._data_BS = RawAquascatData(self.path_BS_raw_data)
-        print(self._data_BS.V.shape)
        self._BS_raw_data = np.swapaxes(self._data_BS.V, 0, 1)
-        print(f"BS raw data shape = {self._BS_raw_data.shape}")

        self._freq = self._data_BS.Freq
-        print(f"freq shape = {self._freq.shape}")
        self._freq_text = self._data_BS.freqText

        self._r = np.repeat(np.transpose(self._data_BS.r), self._freq.shape[0], axis=0)
-        print(f"r shape = {self._r.shape}")

        self._time = np.repeat(
            np.transpose(np.array([t / self._data_BS.PingRate for t in range(self._data_BS.NumProfiles)])[:, np.newaxis]),
            self._freq.shape[0], axis=0)
-        print(f"time shape = {self._time.shape}")

        self._date = self._data_BS.date.date()
        self._hour = self._data_BS.date.time()
@ -48,97 +38,30 @@ class AcousticDataLoader:
        self._gain_rx = self._data_BS.RxGain.tolist()
        self._gain_tx = self._data_BS.TxGain.tolist()

-        # print((self._cell_size))
-        # print((self._nb_pings_averaged_per_profile))
-
-        # print(self._r[0, :][1] - self._r[1, :][0])
-        # print(type(self._nb_cells), self._nb_cells)
-
-        # self._snr = np.array([])
-        # self._snr_reshape = np.array([])
-        # self._time_snr = np.array([])
-
-        # print(type(self._gain_tx))
-
-        # print(["BS - " + f for f in self._freq_text])
-        # print(self._time.shape[0]*self._r.shape[0]*4)
-
-        # print(self._time[np.where(np.floor(self._time) == 175)])
-        # print(np.where((self._time) == 155)[0][0])
-
-        # fig, ax = plt.subplots(nrows=1, ncols=1)
-        # # ax.pcolormesh(self._time[0, :2200], -self._r[0, :], (self._BS_raw_data[0, :, :2200]),
-        # #               cmap='viridis',
-        # #               norm=LogNorm(vmin=1e-5, vmax=np.max(self._BS_raw_data[0, :, :2200])))  # , shading='gouraud')
-        # ax.pcolormesh(range(self._BS_raw_data.shape[2]), range(self._BS_raw_data.shape[1]), self._BS_raw_data[2, :, :], cmap='viridis',
-        #               norm=LogNorm(vmin=1e-5, vmax=np.max(self._BS_raw_data[:, 0, :])))  # , shading='gouraud')
-        # ax.set_xticks([])
-        # ax.set_yticks([])
-        # plt.show()
-
-        # --- Plot vertical profile for bottom detection ---
-        # fig2, ax2 = plt.subplots(nrows=1, ncols=1, layout="constrained")
-        # ax2.plot(self._BS_raw_data[0, :, 1], -self._r[0], "k.-")
-        # plt.show()
-
-        # fig, ax = plt.subplots(nrows=1, ncols=1)
-        # ax.plot(self._BS_raw_data[:, 0, 100] , self._r)
-        # ax.set_ylim(2, 20)
-        # plt.show()
-
-        # print(self.reshape_BS_raw_cross_section()[0, 0])
-        # self.reshape_BS_raw_cross_section()
-        # self.reshape_r()
-        # self.reshape_t()
-        # self.compute_r_2D()
-
    def reshape_BS_raw_data(self):
        BS_raw_cross_section = np.reshape(self._BS_raw_data,
                                          (self._r.shape[1] * self._time.shape[1], self._freq.shape[0]),
                                          order="F")
-        print(BS_raw_cross_section.shape)
        return BS_raw_cross_section

    def reshape_r(self):
-        # r = np.reshape(np.repeat(self._r[0, :], self._time.shape[0], axis=1),
-        #                self._r.shape[0]*self._time.shape[0],
-        #                order="F")
        r = np.zeros((self._r.shape[1] * self._time.shape[1], self._freq.shape[0]))
        for i, _ in enumerate(self._freq):
            for j in range(self._time.shape[1]):

                r[j*self._r.shape[1]:(j+1)*self._r.shape[1], i] = self._r[i, :]
-
-            # r[:, i] = np.repeat(self._r[i, :], self._time.shape[1])
-        print(r.shape)
        return r

    def compute_r_2D(self):
        r2D = np.zeros((self._freq.shape[0], self._r.shape[1], self._time.shape[1]))
        for f, _ in enumerate(self._freq):
            r2D[f, :, :] = np.repeat(np.transpose(self._r[f, :])[:, np.newaxis], self._time.shape[1], axis=1)
-        print(r2D.shape)
        return r2D

    def reshape_t(self):
-        # t = np.reshape(np.repeat(self._time, self._r.shape[0]), (self._time.shape[0]*self._r.shape[0], 1))
        t = np.zeros((self._r.shape[1] * self._time.shape[1], self._freq.shape[0]))
        for i, _ in enumerate(self._freq):
            t[:, i] = np.repeat(self._time[i, :], self._r.shape[1])
-        print(t.shape)
        return t

-    # def concatenate_data(self):
-    #     self.reshape_t()
-    #     self.reshape_BS_raw_cross_section()
-    #     # print(self.reshape_t().shape)
-    #     # print(se.lf.reshape_BS_raw_cross_section().shape)
-    #     df = pd.DataFrame(np.concatenate((self.reshape_t(), self.reshape_BS_raw_cross_section()), axis=1),
-    #                       columns=["time"] + self._freq_text)
-    #     return df
-
-
-# if __name__ == "__main__":
-#     AcousticDataLoader(path_BS_raw_data)
-

--- a/Model/acoustic_data_loader_UBSediFlow.py
+++ b/Model/acoustic_data_loader_UBSediFlow.py
@ -1,49 +1,35 @@
+# ============================================================================== #
+    # acoustic_data_loder_UBSediFlow.py - AcouSed                                   #
+    # Copyright (C) 2024  INRAE                                              #
+    #                                                                        #
+    # This program is free software: you can redistribute it and/or modify   #
+    # it under the terms of the GNU General Public License as published by   #
+    # the Free Software Foundation, either version 3 of the License, or      #
+    # (at your option) any later version.                                    #
+    #                                                                        #
+    # This program is distributed in the hope that it will be useful,        #
+    # but WITHOUT ANY WARRANTY; without even the implied warranty of         #
+    # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the          #
+    # GNU General Public License for more details.                           #
+    #                                                                        #
+    # You should have received a copy of the GNU General Public License      #
+    # along with this program.  If not, see <https://www.gnu.org/licenses/>. #
+
+    #                                                      by Brahim MOUDJED #
+# ============================================================================== #
+
+# -*- coding: utf-8 -*-
+

 import numpy as np
-import pandas as pd
-import datetime
-import matplotlib.pyplot as plt
-from matplotlib.colors import LogNorm, BoundaryNorm
-from copy import deepcopy
-
-from scipy.signal import savgol_filter

 from Model.udt_extract.raw_extract import raw_extract
-# raw_20210519_102332.udt raw_20210520_135452.udt raw_20210525_092759.udt raw_20210525_080454.udt
-
-# path_BS_raw_data0 = ("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/APAVER_2021/Raw_data_udt/")
-# filename0 = "raw_20210519_135400.udt"
-
-# path_BS_raw_data0 = ("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/"
-#                      "APAVER_2021/transect_ubsediflow/01-raw_20210519_115128/Raw_data_udt/")
-# filename0 = "raw_20210519_115128.udt"
-
-# path_BS_raw_data0 = ("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/"
-#                      "APAVER_2021/transect_ubsediflow/02-bb0077eda128f3f7887052eb3e8b0884/Raw_data_udt/")
-# filename0 = "raw_20210519_161400.udt"
-
-# path_BS_raw_data0 = ("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/"
-#                      "APAVER_2021/transect_ubsediflow/04-fb53d0e92c9c88e2a6cf45e0320fbc76/Raw_data_udt/")
-# filename0 = "raw_20210520_133200.udt"
-
-    # ("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/APAVER_2021/"
-    #                 "Rhone_20210519/Rhone_20210519/record/")
-
-# path_BS_raw_data0 = ("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/Raw_data_udt/")
-# filename0 = "raw_20210519_130643.udt"
-
-# path_BS_raw_data0 = ("/home/bmoudjed/Documents/2 Data/APAVER_2021/Raw_data_udt/")
-# filename0 = "raw_20210520_085958.udt"
-
-# filename = "raw_20210519_115128.udt"
-    # "raw_20210526_153310.udt"


 class AcousticDataLoaderUBSediFlow:

    def __init__(self, path_BS_raw_data: str):

-        # path_BS_raw_data = path_BS_raw_data0 + filename0
        self.path_BS_raw_data = path_BS_raw_data

        # --- Extract Backscatter acoustic raw data with  class ---
@ -53,23 +39,10 @@ class AcousticDataLoaderUBSediFlow:
        device_name, time_begin, time_end, param_us_dicts, data_us_dicts, data_dicts, settings_dict \
            = raw_extract(self.path_BS_raw_data)

-        print(f"device_name : {device_name}")
-        print(f"date begin : {time_begin.date()}")
-        print(f"time begin : {time_begin.time()}")
-        print(f"settings_dict : {settings_dict}")
-
        # # --- Date and Hour of measurements read on udt data file ---
-        # filename = self.path_BS_raw_data[-23:]
-        # date_and_time = datetime.datetime(year=int(filename[4:8]),
-        #                                   month=int(filename[8:10]),
-        #                                   day=int(filename[10:12]),
-        #                                   hour=int(filename[13:15]),
-        #                                   minute=int(filename[15:17]),
-        #                                   second=int(filename[17:19]))
+
        self._date = time_begin.date()
-        print(f"date : {self._date}")
        self._hour = time_begin.time()
-        print(f"time : {self._hour}")

        self._freq = np.array([[]])

@ -88,19 +61,11 @@ class AcousticDataLoaderUBSediFlow:
        self._time = np.array([[]])
        self._time_snr = np.array([[]])
        self._BS_raw_data = np.array([[[]]])
-        # self._SNR_data = np.array([[[]]])
        time_len = []
-        time_snr_len = []

        for config in param_us_dicts.keys():
-            # print("-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x")
-            # print(f"config : {config} \n")
+
            for channel in param_us_dicts[config].keys():
-                print("-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x")
-                # print(f"channel : {channel} \n")
-                # print("param_us_dicts[config][channel] ", param_us_dicts[config][channel])
-                # print("param_us_dicts ", param_us_dicts)
-                # print(data_us_dicts[config][channel]['echo_avg_profile'])

                # --- Frequencies ---
                self._freq = np.append(self._freq, param_us_dicts[config][channel]['f0'])
@ -115,31 +80,19 @@ class AcousticDataLoaderUBSediFlow:
                self._gain_tx = np.append(self._gain_tx, param_us_dicts[config][channel]['a1'])

                # --- Depth for each frequencies ---
-                print("r_dcell : ", param_us_dicts[config][channel]['r_dcell'])
-                print("n_cell : ", param_us_dicts[config][channel]['n_cell'])
                depth = [param_us_dicts[config][channel]['r_dcell'] * i
                         for i in list(range(param_us_dicts[config][channel]['n_cell']))]
-                print(f"depth : {depth}")
-                print(f"lenght of depth : {len(depth)}")
+
                if self._r.shape[1] == 0:
                    self._r = np.array([depth])
                else:
                    if len(depth) == self._r.shape[1]:
-                        print("Je suis là")
-                        print(f"depth lenght : {len(depth)}")
-                        print(f"r shape : {self._r.shape}")
                        self._r = np.append(self._r, np.array([depth]), axis=0)
-                        print("C'est encore moi")
                    elif len(depth) < self._r.shape[1]:
-                        print(f"depth lenght : {len(depth)}")
                        self._r = self._r[:, :len(depth)]
                        self._r = np.append(self._r, np.array([depth]), axis=0)
-                        print(f"r shape : {self._r.shape}")
                    elif len(depth) > self._r.shape[1]:
-                        print(f"depth lenght : {len(depth)}")
                        self._r = np.append(self._r, np.array([depth[:self._r.shape[1]]]), axis=0)
-                        print(f"r shape : {self._r.shape}")
-                print(f"self._r : {self._r.shape}")

                # --- BS Time for each frequencies ---
                time = [[(t - data_us_dicts[config][channel]['echo_avg_profile']['time'][0]).total_seconds()
@ -147,69 +100,28 @@ class AcousticDataLoaderUBSediFlow:
                time_len = np.append(time_len, len(time[0]))

                if len(time_len) == 1:
-                    print(f"1 time length : {len(time[0])}")
                    self._time = np.array(time)
-                    print(f"self._time.shape {self._time.shape}")
                elif self._time.shape[1] == len(time[0]):
-                    print(f"2 time length : {len(time[0])}")
                    self._time = np.append(self._time, time, axis=0)
-                    print(f"self._time.shape {self._time.shape}")
                elif self._time.shape[1] > len(time[0]):
-                    print(f"3 time length : {len(time[0])}")
-                    # print(f"self._time.shape {self._time.shape}")
-                    # print([int(np.min(time_len)) + int(i) - 1 for i in range(1, int(np.max(time_len))-int(np.min(time_len))+1)])
                    self._time = np.delete(self._time,
                                           [int(np.min(time_len)) + int(i) - 1 for i in range(1, int(np.max(time_len))-int(np.min(time_len))+1)],
                                           axis=1)
                    self._time = np.append(self._time, time, axis=0)
-                    print(f"self._time.shape {self._time.shape}")
                elif self._time.shape[1] < len(time[0]):
-                    print(f"4 time length : {len(time[0])}")
                    time = time[:int(np.max(time_len)) - (int(np.max(time_len)) - int(np.min(time_len)))]
                    self._time = np.append(self._time, time, axis=0)
-                    print(f"self._time.shape {self._time.shape}")

                self._nb_profiles = np.append(self._nb_profiles, self._time.shape[1])
                self._nb_profiles_per_sec = np.append(self._nb_profiles_per_sec,
                                                      param_us_dicts[config][channel]['n_avg'])

-                # --- SNR Time for each frequencies ---
-                # time_snr = [[(t - data_us_dicts[config][channel]['snr_doppler_avg_profile']['time'][0]).total_seconds()
-                #          for t in data_us_dicts[config][channel]['snr_doppler_avg_profile']['time']]]
-                # time_snr_len = np.append(time_snr_len, len(time_snr[0]))
-                #
-                # if len(time_snr_len) == 1:
-                #     # print(f"1 time length : {len(time[0])}")
-                #     self._time_snr = np.array(time_snr)
-                #     # print(f"self._time.shape {self._time.shape}")
-                # elif self._time_snr.shape[1] == len(time_snr[0]):
-                #     # print(f"2 time length : {len(time[0])}")
-                #     self._time_snr = np.append(self._time_snr, time_snr, axis=0)
-                #     # print(f"self._time.shape {self._time.shape}")
-                # elif self._time_snr.shape[1] > len(time_snr[0]):
-                #     # print(f"3 time length : {len(time[0])}")
-                #     # print(f"self._time.shape {self._time.shape}")
-                #     # print([int(np.min(time_len)) + int(i) - 1 for i in range(1, int(np.max(time_len))-int(np.min(time_len))+1)])
-                #     self._time_snr = np.delete(self._time_snr,
-                #                             [int(np.min(time_snr_len)) + int(i) - 1 for i in
-                #                             range(1, int(np.max(time_snr_len)) - int(np.min(time_snr_len)) + 1)],
-                #                             axis=1)
-                #     self._time_snr = np.append(self._time_snr, time_snr, axis=0)
-                #     # print(f"self._time.shape {self._time.shape}")
-                # elif self._time_snr.shape[1] < len(time_snr[0]):
-                #     # print(f"4 time length : {len(time[0])}")
-                #     time_snr = time_snr[:int(np.max(time_snr_len)) - (int(np.max(time_snr_len)) - int(np.min(time_snr_len)))]
-                #     self._time_snr = np.append(self._time_snr, time_snr, axis=0)
-                #     # print(f"self._time.shape {self._time.shape}")
-
                # --- US Backscatter raw signal ---
                BS_data = np.array([[]])

                if config == 1:

                    BS_data = np.array([data_us_dicts[config][channel]['echo_avg_profile']['data'][0]])
-                    print(f"cas 1 : BS_raw_data shape = {self._BS_raw_data.shape}")
-                    print(f"cas 1 : BS_data shape = {BS_data.shape}")

                    for i in range(self._time.shape[1]):
                        BS_data = np.append(BS_data,
@ -218,27 +130,21 @@ class AcousticDataLoaderUBSediFlow:
                                            axis=0)

                    self._BS_raw_data = np.array([BS_data[:self._time.shape[1], :].transpose()])
-                    #                     print(f"a) BS_data shape = {BS_data.shape}")
-                    #                     print(f"a) BS_raw_data shape = {BS_raw_data.shape}")

                else:

                    BS_data = np.array([data_us_dicts[config][channel]['echo_avg_profile']['data'][0]])
-                    print(f"{config}) BS_data shape = {BS_data.shape}")
+
                    for j in range(self._time.shape[1]):
                        BS_data = np.append(BS_data,
                                            np.array(
                                                [data_us_dicts[config][channel]['echo_avg_profile']['data'][j]]),
                                            axis=0)
                    BS_data = np.array([BS_data.transpose()])
-                    print(f"xxxx BS_data shape = {BS_data.shape}")
-                        #                     print(f"b) BS_raw_data shape = {BS_raw_data.shape}")

                    # 1- time shape > BS data shape
                    #    <=> data recorded with the frequency are longer than data recorded with the other lower frequencies
                    if (BS_data.shape[2] > self._BS_raw_data.shape[2]):
-                        print(f"cas 2 : BS_raw_data shape = {self._BS_raw_data.shape}")
-                        print(f"cas 2 : BS_data shape = {BS_data.shape}")

                        if (BS_data.shape[1] > self._BS_raw_data.shape[1]):
                                #                         print(f"BS_data shape[0] = {BS_data.shape[0]}")
@ -260,8 +166,6 @@ class AcousticDataLoaderUBSediFlow:
                    # 2- time shape < BS data shape
                    #    <=> data recorded with the frequency are shorter than data recorded with the other lower frequencies
                    elif BS_data.shape[2] < self._BS_raw_data.shape[2]:
-                        print(f"cas 3 : BS_raw_data shape = {self._BS_raw_data.shape}")
-                        print(f"cas 3 : BS_data shape = {BS_data.shape}")

                        if (BS_data.shape[1] > self._BS_raw_data.shape[1]):
                            self._BS_raw_data = np.append(self._BS_raw_data[:, :, BS_data.shape[2]],
@ -277,16 +181,11 @@ class AcousticDataLoaderUBSediFlow:
                            self._BS_raw_data = np.append(self._BS_raw_data[:, :, BS_data.shape[0]],
                                                    BS_data,
                                                    axis=0)
-                        #                     print(f"d) BS_data shape = {BS_data.shape}")
-                        #                     print(f"d) BS_raw_data shape = {BS_raw_data.shape}")

                    # 3- time shape = BS data shape
                    #    <=> data recorded with the frequency have the same duration than data recorded with the other lower frequency
                    else:

-                        print(f"cas 4 : BS_raw_data shape = {self._BS_raw_data.shape}")
-                        print(f"cas 4 : BS_data shape = {BS_data.shape}")
-
                        if (BS_data.shape[1] > self._BS_raw_data.shape[1]):

                            self._BS_raw_data = np.append(self._BS_raw_data,
@ -301,115 +200,6 @@ class AcousticDataLoaderUBSediFlow:

                            self._BS_raw_data = np.append(self._BS_raw_data,
                                                        BS_data, axis=0)
-                    #                     print(f"e) BS_data shape = {BS_data.shape}")
-
-                print("Final BS_raw_data shape = ", self._BS_raw_data.shape)
-
-            print("********************************************")
-
-            #                 # --- US Backscatter raw signal + SNR data ---
-#                 BS_data = np.array([[]])
-#
-#                 if config == 1:
-#                     BS_data = np.array([data_us_dicts[config][channel]['echo_avg_profile']['data'][0]])
-#                     # print("BS_data shape ", BS_data.shape)
-#                     # print("******************************")
-#                     # date_list = [np.abs(datetime.datetime(2021, 5, 19, 14, 10, 00).timestamp()
-#                     #       - date.timestamp()) for date in data_us_dicts[config][channel]['echo_avg_profile']['time']]
-#                     # print(date_list)
-#                     # print(np.where(date_list == np.min(date_list)))
-#                     # print((data_us_dicts[config][channel]['echo_avg_profile']['time'][np.where(date_list == np.min(date_list))[0][0]] -
-#                     #       data_us_dicts[config][channel]['echo_avg_profile']['time'][0]).total_seconds())
-#                     # # == datetime.datetime(2021, 5, 19, 14, 10, 2, 644000))
-#                     # print("******************************")
-#
-#                     for i in range(self._time.shape[1]):
-#                         BS_data = np.append(BS_data,
-#                                             np.array([data_us_dicts[config][channel]['echo_avg_profile']['data'][i]]),
-#                                             axis=0)
-#                     print("0. BS_data shape ", BS_data.shape)
-#
-#                     self._BS_raw_data = np.array([BS_data[:self._time.shape[1], :].transpose()])
-#
-#                     print("0. BS_raw_data shape ", self._BS_raw_data.shape)
-#
-#                     # fig, ax = plt.subplots(nrows=1, ncols=1, layout="constrained")
-#                     # pcm = ax.pcolormesh(list(range(self._BS_raw_data.shape[2])), list(range(self._BS_raw_data.shape[1])),
-#                     #                     np.log(self._BS_raw_data[0, :, :]),
-#                     #                     cmap='Blues')
-#                     # fig.colorbar(pcm, ax=ax, shrink=1, location='right')
-#                     # plt.show()
-#
-#                 else:
-#
-#                     BS_data = np.array([data_us_dicts[config][channel]['echo_avg_profile']['data'][0]])
-#                     # print("BS_data shape ", BS_data.shape)
-#                     for i in range(self._time.shape[1]):
-#                         BS_data = np.append(BS_data,
-#                                             np.array(
-#                                                 [data_us_dicts[config][channel]['echo_avg_profile']['data'][i]]),
-#                                             axis=0)
-#                     print("1. BS_data shape ", BS_data.shape)
-#
-# #-----------------------------------------------------------------------------------------------------------------------
-#                     # Ici il faut écrire les conditions sur les tailles selon r et selon time
-#                     # donc sur BS_data.shape[0] (time) et BS_data.shape[1] (depth)
-# #-----------------------------------------------------------------------------------------------------------------------
-#
-#                     # 1- time shape > BS data shape
-#                     #    <=> data recorded with the frequency are longer than data recorded with the other lower frequencies
-#                     if (BS_data.shape[0] > self._BS_raw_data.shape[2]):
-#                         self._BS_raw_data = np.append(self._BS_raw_data,
-#                                                       np.array([BS_data[:self._BS_raw_data.shape[2], :].transpose()]),
-#                                                       axis=0)
-#
-#                     # 2- time shape < BS data shape
-#                     #    <=> data recorded with the frequency are shorter than data recorded with the other lower frequencies
-#                     elif BS_data.shape[0] < self._BS_raw_data.shape[2]:
-#                         self._BS_raw_data = np.append(self._BS_raw_data[config-1, :, BS_data.shape[0]],
-#                                                       np.array([BS_data.transpose()]),
-#                                                       axis=0)
-#
-#                     # 3- time shape = BS data shape
-#                     #    <=> data recorded with the frequency have the same duration than data recorded with the other lower frequency
-#                     else:
-#                         self._BS_raw_data = np.append(self._BS_raw_data, np.array([BS_data.transpose()]), axis=0)
-#
-#
-#                     print("1. BS_raw_data shape ", self._BS_raw_data.shape)
-#
-#                     # if f == 0:
-#                     #     print(np.array(data_us_dicts[config][channel]['echo_avg_profile']['data'][0]).shape)
-#                     #     self._BS_raw_data[f, :, :] = np.array([data_us_dicts[config][channel]['echo_avg_profile']['data'][0]])
-#                     #     # self._BS_raw_data = np.array([np.reshape(data_us_dicts[config][channel]['echo_avg_profile']['data'],
-#                     #     #                                (self._time.shape[1], self._r.shape[1])).transpose()])
-#                     #     print("self._BS_raw_data.shape ", self._BS_raw_data.shape)
-#                     #     self._SNR_data = np.array(
-#                     #         [np.reshape(np.abs(data_us_dicts[config][channel]['snr_doppler_avg_profile']['data']),
-#                     #                     (self._time.shape[1], self._r.shape[1])).transpose()])
-#                     # else:
-#                     #     # self._BS_raw_data = np.append(self._BS_raw_data,
-#                     #     #                               np.array(data_us_dicts[config][channel]['echo_avg_profile']['data']),
-#                     #     #                                   (self._r.shape[1], self._time.shape[1]))]),
-#                     #     #                               axis=0)
-#                     #     # self._BS_raw_data = np.append(self._BS_raw_data,
-#                     #     #                               np.array([np.reshape(np.array(
-#                     #     #                                   data_us_dicts[config][channel]['echo_avg_profile']['data']),
-#                     #     #                                         (self._time.shape[1], self._r.shape[1])).transpose()]),
-#                     #     #                               axis=0)
-#                     #
-#                     #     self._SNR_data = np.append(self._SNR_data,
-#                     #                                   np.array([np.reshape(np.array(
-#                     #                                       np.abs(data_us_dicts[config][channel]['snr_doppler_avg_profile']['data'])),
-#                     #                                       (self._time.shape[1], self._r.shape[1])).transpose()]),
-#                     #                                   axis=0)
-#                     #     # print(self._BS_raw_data.shape)
-#
-#                     # --- US Backscatter raw signal ---
-#
-#
-#                 # print(len(self._BS_raw_data))
-#                 # print(self._BS_raw_data)

        if self._time.shape[1] > self._BS_raw_data.shape[2]:
            self._time = self._time[:, :self._BS_raw_data.shape[2]]
@ -420,275 +210,39 @@ class AcousticDataLoaderUBSediFlow:
            self._BS_raw_data = self._BS_raw_data

        self._time = self._time[:, :self._BS_raw_data.shape[2]]
-        print("self._time.shape ", self._time.shape)
-        # print(f"time : {self._time}")
-        # print("****************************")
-        # for i in range(len(self._time[0, :])-1):
-        #     print(self._time[0, i+1] - self._time[0, i])
-        # print("****************************")
-
-        print("self._r.shape ", self._r.shape)

        self._freq_text = np.array([str(f) + " MHz" for f in [np.round(f*1e-6, 2) for f in self._freq]])
-        print("self._freq_text ", self._freq_text)
-        print("self._freq_text ", self._freq)
-
-        # self._BS_raw_data = np.array(np.reshape(self._BS_raw_data, (len(self._freq), self._r.shape[1], self._time.shape[1])))
-        print("self._BS_raw_data.shape ", self._BS_raw_data.shape)
-
-        # print("self._SNR_data.shape ", self._SNR_data.shape)
-        # print(self._SNR_data)
-
-        # print("device_name ", device_name, "\n")
-
-        # print("time_begin ", time_begin, "\n")
-
-        # print("time_end ", time_end, "\n")
-
-        # print(f"param_dicts keys {param_us_dicts.keys()} \n")
-        # print(param_us_dicts, "\n")
-
-        # for i in range(len(list(param_us_dicts.keys()))):
-        #     print(f"param_us_dicts {i} : {list(param_us_dicts.items())[i]} \n")
-
-        # # print("settings_dict ", settings_dict, "\n")
-        # print(f"keys in data_us_dicts {data_us_dicts[1][1].keys()} \n")
-        # # les clés du dictionnaire data_us_dicts :
-        # # dict_keys(['echo_avg_profile', 'saturation_avg_profile', 'velocity_avg_profile', 'snr_doppler_avg_profile',
-        # #            'velocity_std_profile', 'a1_param', 'a0_param', 'noise_g_high', 'noise_g_low'])
-
-        # print(f"data_us_dicts keys in echo avg profile {data_us_dicts[1][1]['echo_avg_profile'].keys()} \n")
-        # print(f"number of profiles {len(data_us_dicts[1][1]['echo_avg_profile']['data'])} \n")
-        # print(f"number of cells {data_us_dicts[1][1]['echo_avg_profile']['data'][0].shape} \n")
-
-        # self._data_BS = RawAquascatData(self.path_BS_raw_data)
-
-        # self._nb_profiles = self._data_BS.NumProfiles
-        # self._nb_profiles_per_sec = self._data_BS.ProfileRate
-        # self._nb_cells = self._data_BS.NumCells
-        # self._cell_size = self._data_BS.cellSize
-        # self._pulse_length = self._data_BS.TxPulseLength
-        # self._nb_pings_per_sec = self._data_BS.PingRate
-        # self._nb_pings_averaged_per_profile = self._data_BS.Average
-        # self._kt = self._data_BS.Kt
-        # self._gain_rx = self._data_BS.RxGain
-        # self._gain_tx = self._data_BS.TxGain
-
-        # self._snr = np.array([])
-        # self._snr_reshape = np.array([])
-        # self._time_snr = np.array([])
-
-        # print(type(self._gain_tx))
-
-        # print(["BS - " + f for f in self._freq_text])
-        # print(self._time.shape[0]*self._r.shape[0]*4)
-
-        # print(self._time[np.where(np.floor(self._time) == 175)])
-        # print(np.where((self._time) == 155)[0][0])
-
-        # --- Plot Backscatter US data ---
-
-        # fig, ax = plt.subplots(nrows=1, ncols=1, layout="constrained")
-        # pcm = ax.pcolormesh(self._time[0, :], -self._r[0, :], np.log(self._BS_raw_data[0, :, :]),
-        #                            cmap='plasma')#, shading='gouraud')
-        # # pcm = ax.pcolormesh(list(range(self._BS_raw_data.shape[2])), list(range(self._BS_raw_data.shape[1])),
-        # #                     np.log(self._BS_raw_data[0, :, :]),
-        # #                     cmap='Blues')  # , shading='gouraud')
-        #     # norm=LogNorm(vmin=np.min(self._BS_raw_data[f, :, :]), vmax=np.max(self._BS_raw_data[f, :, :])), shading='gouraud')
-        #     # ax.pcolormesh(range(self._BS_raw_data.shape[2]), range(self._BS_raw_data.shape[0]), self._BS_raw_data[:, 1, :], cmap='viridis',
-        #     #               norm=LogNorm(vmin=1e-5, vmax=np.max(self._BS_raw_data[:, 0, :])))  # , shading='gouraud')
-        # fig.colorbar(pcm, ax=ax, shrink=1, location='right')
-        # plt.show()
-        
-        # fig, ax = plt.subplots(nrows=len(self._freq), ncols=1, layout="constrained")
-        # for f, freq in enumerate(self._freq):
-        #     print(f"{f} : {freq} \n")
-        #     # pcm = ax[f].imshow(np.log(self._BS_raw_data[f, :, :self._time.shape[1]]),
-        #     #              cmap='Blues')
-        #     # pcm = ax[f].pcolormesh(list(range(self._BS_raw_data.shape[2])), list(range(self._BS_raw_data.shape[1])),
-        #     #                        np.log(self._BS_raw_data[f, :, :]),
-        #     #                        cmap='Blues', shading='gouraud')
-        #     pcm = ax[f].pcolormesh(self._time[f, 50:247], -self._r[f, :], np.log(self._BS_raw_data[f, :, 50:247]),
-        #                         cmap='Blues')#, shading='gouraud')
-        #                         # norm=LogNorm(vmin=np.min(self._BS_raw_data[f, :, :]), vmax=np.max(self._BS_raw_data[f, :, :])), shading='gouraud')
-        #     # ax.pcolormesh(range(self._BS_raw_data.shape[2]), range(self._BS_raw_data.shape[0]), self._BS_raw_data[:, 1, :], cmap='viridis',
-        #     #               norm=LogNorm(vmin=1e-5, vmax=np.max(self._BS_raw_data[:, 0, :])))  # , shading='gouraud')
-        # fig.colorbar(pcm, ax=ax[:], shrink=1, location='right')
-        # # plt.show()
-        #
-        # # --- Smooth value with savgol_filter ---
-        # BS_smooth = deepcopy(self._BS_raw_data[0, :, :])
-        # for k in range(self._time[0, :].shape[0]):
-        #     BS_smooth[:, k] = savgol_filter(BS_smooth[:, k], 10, 2)
-        #
-        # fig1, ax1 = plt.subplots(nrows=1, ncols=1, layout="constrained")
-        # pcm1 = ax1.pcolormesh(self._time[0, :], -self._r[0, :], np.log(BS_smooth[:, :]), cmap='Blues')
-        # fig1.colorbar(pcm1, ax=ax1, shrink=1, location='right')
-
-        # print("find value in depth", np.where(np.abs(self._r - 3.3) == np.min(np.abs(self._r - 3.3))))
-        #
-        # fig, ax = plt.subplots(nrows=1, ncols=1, layout="constrained")
-        # ax.plot(self._r[0, :], self._BS_raw_data[0, :, 766])
-        # plt.show()
-
-        # # --- Plot vertical profile for bottom detection ---
-        # n = 60
-        # t0 = 200
-        # t1 = np.where(np.abs(self._time[0, :] - t0) == np.nanmin(np.abs(self._time[0, :] - t0)))[0][0]
-        # # print(np.abs(self._time[0, :] - 200))
-        # # print(f"x0 = {x0}")
-        # r1 = 98
-        # r2 = 150
-        # fig2, ax2 = plt.subplots(nrows=1, ncols=n, layout="constrained")
-        # for i in range(n):
-        #     ax2[i].plot(self._BS_raw_data[0, r1:r2, t1+i], -self._r[0, r1:r2], 'b')
-        #     ax2[i].plot(BS_smooth[r1:r2, t1+i], -self._r[0, r1:r2], 'r')
-        #     ax2[i].set_xticks([])
-        #     if i != 0:
-        #         ax2[i].set_yticks([])
-        # plt.show()
-
-        # --- Plot SNR data ---
-        # fig_snr, ax_snr = plt.subplots(nrows=len(self._freq), ncols=1)
-        #
-        # x, y = np.meshgrid(self._time[0, :], self._r[0, :])
-        #
-        # for f, freq in enumerate(self._freq):
-        #
-        #     val_min = np.nanmin(abs(self._SNR_data[f, :, :]))
-        #     print(f"val_min = {val_min}")
-        #     val_max = np.nanmax(self._SNR_data[f, :, :])
-        #     print(f"val_max = {val_max}")
-        #     if int(val_min) == 0:
-        #         val_min = 1e-5
-        #     if int(val_max) < 1000:
-        #         levels = np.array([00.1, 1, 2, 10, 100, 1000, 1e6])
-        #         bounds = [00.1, 1, 2, 10, 100, 1000, 1e6, 1e6 * 1.2]
-        #     else:
-        #         levels = np.array([00.1, 1, 2, 10, 100, val_max])
-        #         bounds = [00.1, 1, 2, 10, 100, 1000, val_max, val_max * 1.2]
-        #     norm = BoundaryNorm(boundaries=bounds, ncolors=300)
-        #
-        #     print(f"levels = {levels}")
-        #     print(f"norm = {norm.boundaries}")
-        #
-        #     cf = ax_snr[f].contourf(x, y, self._SNR_data[f, :, :])#, levels, cmap='gist_rainbow', norm=norm)
-        #
-        #     ax_snr[f].text(1, .70, self._freq_text[f],
-        #                           fontsize=14, fontweight='bold', fontname="Ubuntu", c="black", alpha=0.5,
-        #                           horizontalalignment='right', verticalalignment='bottom',
-        #                           transform=ax_snr[f].transAxes)
-        #
-        # fig_snr.supxlabel('Time (sec)', fontsize=10)
-        # fig_snr.supylabel('Depth (m)', fontsize=10)
-        # cbar = fig_snr.colorbar(cf, ax=ax_snr[:], shrink=1, location='right')
-        # cbar.set_label(label='Signal to Noise Ratio', rotation=270, labelpad=10)
-        # # cbar.set_ticklabels(['0', '1', '2', '10', '100', r'10$^3$', r'10$^6$'])
-        # plt.show()
-
-        # fig, ax = plt.subplots(nrows=1, ncols=1)
-        # ax.plot(list(range(self._time.shape[1])), self._time[0, :])
-        # # ax.set_ylim(2, 20)
-        # plt.show()
-
-        # print(self.reshape_BS_raw_cross_section())
-
-        # self.reshape_BS_raw_cross_section()
-        # self.reshape_r()
-        # self.reshape_t()
-        # self.compute_r_2D()
-
-        # Lecture du fichier excel
-
-        # path = ("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/APAVER_2021/"
-        #         "transect_ubsediflow/01-raw_20210519_115128/Raw_data_csv/config_1/"
-        #         "echo_avg_profile_1_1_20210519_115128.csv")
-        #
-        # df = pd.read_csv(path, sep="\t")
-        #
-        # arr = []
-        # for column in df.columns:
-        #     arr.append(df[column].to_numpy())
-        #     # arr = np.append(arr, np.array([df[column].to_numpy()]), axis=0)
-        # arr = arr[1:]
-        # print(len(arr))
-        #
-        # matrix = np.array([arr[0]])
-        # print(matrix.shape)
-        # for i in range(len(arr)-1):
-        #     matrix = np.append(matrix, np.array([arr[i]]), axis=0)
-        # print(matrix.shape)
-
-        # fig, ax = plt.subplots(nrows=1, ncols=1, layout="constrained")
-        # pcm = ax.pcolormesh(list(range(matrix.shape[1])), list(range(matrix.shape[0])), np.log(matrix),
-        #                            cmap='Blues')#, shading='gouraud')
-        #     # norm=LogNorm(vmin=np.min(self._BS_raw_data[f, :, :]), vmax=np.max(self._BS_raw_data[f, :, :])), shading='gouraud')
-        #     # ax.pcolormesh(range(self._BS_raw_data.shape[2]), range(self._BS_raw_data.shape[0]), self._BS_raw_data[:, 1, :], cmap='viridis',
-        #     #               norm=LogNorm(vmin=1e-5, vmax=np.max(self._BS_raw_data[:, 0, :])))  # , shading='gouraud')
-        # fig.colorbar(pcm, ax=ax, shrink=1, location='right')
-        # plt.show()

    def reshape_BS_raw_data(self):
        BS_raw_cross_section = np.reshape(self._BS_raw_data,
                                          (self._r.shape[1]*self._time.shape[1], len(self._freq)),
                                          order="F")
-        # print(BS_raw_cross_section.shape)
        return BS_raw_cross_section

-    # def reshape_SNR_data(self):
-    #     SNR_data = np.reshape(self._SNR_data,
-    #                                       (self._r.shape[1]*self._time.shape[1], len(self._freq)),
-    #                                       order="F")
-    #     # print(BS_raw_cross_section.shape)
-    #     return SNR_data
-
    def reshape_r(self):
        r = np.zeros((self._r.shape[1]*self._time.shape[1], len(self._freq)))
        for i, _ in enumerate(self._freq):
            r[:, i] = np.repeat(self._r[i, :], self._time.shape[1])
-        # print(r.shape)
        return r

    def compute_r_2D(self):
        r2D = np.zeros((self._freq.shape[0], self._r.shape[1], self._time.shape[1]))
        for f, _ in enumerate(self._freq):
            r2D[f, :, :] = np.repeat(np.transpose(self._r[0, :])[:, np.newaxis], self._time.shape[1], axis=1)
-        print("r2D.shape ", r2D.shape)
        return r2D

-    # def compute_r_2D(self):
-    #     r2D = np.repeat(self._r, self._time.size, axis=1)
-    #     return r2D
-
    def reshape_t(self):
        t = np.zeros((self._r.shape[1]*self._time.shape[1], len(self._freq)))
        for i, _ in enumerate(self._freq):
            t[:, i] = np.repeat(self._time[i, :], self._r.shape[1])
-        # print(t.shape)
        return t

    def reshape_t_snr(self):
        t = np.zeros((self._r.shape[1]*self._time_snr.shape[1], len(self._freq)))
        for i, _ in enumerate(self._freq):
            t[:, i] = np.repeat(self._time_snr[i, :], self._r.shape[1])
-        # print(t.shape)
        return t

-    def detect_bottom(self):
-        rmin = 2.5
-        rmax = 3.5
-
-
-
-    # def concatenate_data(self):
-
-    #     self.reshape_BS_raw_cross_section()
-    #     # print(self.reshape_t().shape)
-    #     # print(se.lf.reshape_BS_raw_cross_section().shape)
-    #     df = pd.DataFrame(np.concatenate((self.reshape_t(), self.reshape_BS_raw_cross_section()), axis=1),
-    #                       columns=["time"] + self._freq_text)
-    #     return df
-

 # if __name__ == "__main__":
 #     AcousticDataLoaderUBSediFlow(path_BS_raw_data0 + filename0)
--- a/Model/acoustic_inversion_method_high_concentration.py
+++ b/Model/acoustic_inversion_method_high_concentration.py
@ -21,7 +21,6 @@
 # -*- coding: utf-8 -*-


-import matplotlib.pyplot as plt
 import numpy as np
 import settings as stg
 from Model.GrainSizeTools import demodul_granulo, mix_gaussian_model
@ -58,17 +57,6 @@ class AcousticInversionMethodHighConcentration():
                    (np.log(10) / 20) * (freq * 1e-3) ** 2
        return alpha

-    # ---------- Conmpute FBC ----------
-    # def compute_FCB(self):
-    #     # print(self.BS_averaged_cross_section_corr.V.shape)
-    #     # print(self.r_2D.shape)
-    #     FCB = np.zeros((256, 4, 1912))
-    #     for f in range(4):
-    #         # print(self.alpha_w_function(self.Freq[f], self.temperature))
-    #         FCB[:, f, :] = np.log(self.BS_averaged_cross_section_corr.V[:, f, :]) + np.log(self.r_3D[:, f, :]) + \
-    #                        np.log(2 * self.alpha_w_function(self.Freq[f], self.temperature) * self.r_3D[:, f, :])
-    #     return FCB
-
    # --- Gaussian mixture ---
    def compute_particle_size_distribution_in_number_of_particles(self, num_sample, r_grain, frac_vol_cumul):
        min_demodul = 1e-6
@ -82,15 +70,6 @@ class AcousticInversionMethodHighConcentration():
                                               sample_demodul.demodul_data_list[2].sigma_list,
                                               sample_demodul.demodul_data_list[2].w_list)

-        # N_modes = 3
-        # sample_demodul.print_mode_data(N_modes)
-        # sample_demodul.plot_interpolation()
-        # sample_demodul.plot_modes(N_modes)
-
-        # print(f"mu_list : {sample_demodul.demodul_data_list[3 - 1].mu_list}")
-        # print(f"sigma_list : {sample_demodul.demodul_data_list[3 - 1].sigma_list}")
-        # print(f"w_list : {sample_demodul.demodul_data_list[3 - 1].w_list}")
-
        proba_vol_demodul = proba_vol_demodul / np.sum(proba_vol_demodul)
        ss = np.sum(proba_vol_demodul / np.exp(resampled_log_array) ** 3)
        proba_num = proba_vol_demodul / np.exp(resampled_log_array) ** 3 / ss
@ -106,23 +85,9 @@ class AcousticInversionMethodHighConcentration():
        x = k * a
        f = (x ** 2 * (1 - 0.25 * np.exp(-((x - 1.5) / 0.35) ** 2)) * (1 + 0.6 * np.exp(-((x - 2.9) / 1.15) ** 2))) / (
                    42 + 28 * x ** 2)
-        # print(f"form factor = {f}")
        return f

-    # def ks(self, num_sample_sand, radius_grain_sand, frac_vol_sand_cumul, freq, C):
    def ks(self, proba_num, freq, C):
-        # --- Calcul de la fonction de form ---
-        # form_factor = self.form_factor_function_MoateThorne2012(a, freq)
-        # print(f"form_factor shape = {form_factor}")
-        # print(f"form_factor = {form_factor}")
-
-        #--- Particle size distribution ---
-        # proba_num = (
-        #     self.compute_particle_size_distribution_in_number_of_particles(
-        #         num_sample=num_sample_sand, r_grain=radius_grain_sand, frac_vol_cumul=frac_vol_sand_cumul[num_sample_sand]))
-
-        # print(f"proba_num : {proba_num}")
-
        # --- Compute k_s by dividing two integrals ---
        resampled_log_array = np.log(np.logspace(-10, -2, 3000))
        a2f2pdf = 0
@ -132,28 +97,17 @@ class AcousticInversionMethodHighConcentration():
            a2f2pdf += a**2 * self.form_factor_function_MoateThorne2012(a, freq, C)**2 * proba_num[i]
            a3pdf += a**3 * proba_num[i]

-        #     print("form factor ", self.form_factor_function_MoateThorne2012(a, freq, C))
-        # print(f"a2f2pdf = {a2f2pdf}")
-        # print(f"a3pdf = {a3pdf}")
-
        ks = np.sqrt(a2f2pdf / a3pdf)

-        # ks = np.array([0.04452077, 0.11415143, 0.35533713, 2.47960051])
-        # ks = ks0[ind]
        return ks

    # ------------- Computing sv ------------- #
    def sv(self, ks, M_sand):
-        # print(f"ks = {ks}")
-        # print(f"M_sand = {M_sand}")
        sv = (3 / (16 * np.pi)) * (ks ** 2) * M_sand
-        # sv = np.full((stg.r.shape[1], stg.t.shape[1]), sv0)
        return sv

    # ------------- Computing X ------------- #
    def X_exponent(self, freq1, freq2, sv_freq1, sv_freq2):
-        # X0 = [3.450428714146802, 3.276478927777019, 3.6864638665972893, 0]
-        # X = X0[ind]
        X = np.log(sv_freq1 / sv_freq2) / np.log(freq1 / freq2)
        return X

@ -174,165 +128,43 @@ class AcousticInversionMethodHighConcentration():
        gain = 10 ** ((RxGain + TxGain) / 20)
        # Computing Kt
        kt = kt_ref * gain * np.sqrt(tau * cel / (tau_ref * c_ref))    # 1D numpy array
-        # kt = np.reshape(kt0, (1, 2))     # convert to 2d numpy array to compute J_cross_section
-        # print(f"kt = {kt}")
-        # kt_2D = np.repeat(np.array([kt]), stg.r.shape[1], axis=0)
-        # print("kt 2D ", kt_2D)
-        # print("kt 2D shape ", kt_2D.shape)
-        # # kt_3D = np.zeros((kt_2D.shape[1], kt_2D.shape[0], stg.t.shape[1]))
-        # # for k in range(kt_2D.shape[1]):
-        # #     kt_3D[k, :, :] = np.repeat(kt_2D, stg.t.shape[1], axis=1)[:, k * stg.t.shape[1]:(k + 1) * stg.t.shape[1]]
-        # kt_3D = np.repeat(kt_2D.transpose()[:, :, np.newaxis], stg.t.shape[1], axis=2)
-        # # print("kt 3D ", kt_3D)
-        # print("kt 3D shape ", kt_3D.shape)
-
        return kt

    # ------------- Computing J_cross_section ------------- #
    def j_cross_section(self, BS, r2D, kt):
-        # J_cross_section = np.zeros((1, BS.shape[1], BS.shape[2]))       # 2 because it's a pair of frequencies
-        # print("BS.shape", BS.shape)
-        # print("r2D.shape", r2D.shape)
-        # print("kt.shape", kt.shape)
-
-        # if stg.ABS_name == "Aquascat 1000R":
-        # print("--------------------------------")
-        # print("BS : ", BS)
-        # print("BS min : ", np.nanmin(BS))
-        # print("BS max : ", np.nanmax(BS))
-        # print("r2D : ", r2D)
-        # print("kt shape : ", kt.shape)
-        # print("kt : ", kt)
-        # print("--------------------------------")
-            # for k in range(1):
-            #     J_cross_section[k, :, :] = (3 / (16 * np.pi)) * ((BS[k, :, :]**2 * r2D[k, :, :]**2) / kt[k, :, :]**2)
        J_cross_section = (3 / (16 * np.pi)) * ((BS**2 * r2D**2) / kt**2)
-            # J_cross_section[J_cross_section == 0] = np.nan
-            # print("J_cross_section.shape", J_cross_section.shape)
-        # elif stg.ABS_name == "UB-SediFlow":
-        #     for k in range(1):
-        #         J_cross_section[k, :, :] = (3 / (16 * np.pi)) * ((BS[k, :, :]**2 * r2D[0, :, :]**2) / kt[k, :, :]**2)
-        # print("compute j_cross_section finished")
        return J_cross_section

    # ------------- Computing alpha_s ------------- #
    def alpha_s(self, sv, j_cross_section, depth, alpha_w):
        alpha_s = (np.log(sv / j_cross_section) / (4 * depth)) - alpha_w
-        print("----------------------------")
-        print(f"sv = {sv}")
-        print(f"j_cross_section = {j_cross_section}")
-        print(f"depth = {depth}")
-        print(f"alpha_w = {alpha_w}")
-        print(f"(np.log(sv / j_cross_section) / (4 * depth)) = {(np.log(sv / j_cross_section) / (4 * depth))}")
-        print(f"alpha_s {alpha_s}")
-
        return alpha_s

-    # ------------- Computing interpolation of fine SSC data obtained from water sampling -------------
-    # -------------           collected at various depth in the vertical sample           -------------
-    # def M_profile_SCC_fine_interpolated(self, sample_depth, M_profile, range_cells, r_bottom):
-    #     res = np.zeros((len(range_cells),)) * np.nan
-    #     for i in range(len(M_profile) - 1):
-    #         # print(f"i = {i}")
-    #         r_ini = sample_depth[i]
-    #         # print(f"r_ini = {r_ini}")
-    #         c_ini = M_profile[i]
-    #         # print(f"c_ini = {c_ini}")
-    #         r_end = sample_depth[i + 1]
-    #         # print(f"r_end = {r_end}")
-    #         c_end = M_profile[i + 1]
-    #         # print(f"c_end = {c_end}")
-    #
-    #         # Computing the linear equation
-    #         a = (c_end - c_ini) / (r_end - r_ini)
-    #         # print(f"a = {a}")
-    #         b = c_ini - a * r_ini
-    #         # print(f"b = {b}")
-    #
-    #         # Finding the indices of r_ini and r_end in the interpolated array
-    #         # print(f"range_cells = {range_cells}")
-    #         loc = (range_cells >= r_ini) * (range_cells < r_end)
-    #         # print(f"loc = {loc}")
-    #         # print(f"loc shape = {len(loc)}")
-    #
-    #         # Filling the array with interpolation values
-    #         res[loc] = range_cells[loc] * a + b
-    #         # print(res.shape)
-    #         # print(f"res = {res}")
-    #         # print(f"1. res.shape = {res.shape}")
-    #
-    #     # Filling first and last values
-    #     i = 0
-    #     while np.isnan(res[i]):
-    #         res[i] = M_profile[0]
-    #         i += 1
-    #
-    #     # Filling the last values
-    #     i = -1
-    #     while np.isnan(res[i]):
-    #         res[i] = M_profile[-1]
-    #         i += -1
-    #     # print(f"res.shape = {res.shape}")
-    #     # print(f"res = {res}")
-    #     # print(f"r_bottom.shape = {r_bottom.shape}")
-    #     # print(f" = {res}")
-    #
-    #     if r_bottom.shape != (0,):
-    #         res[np.where(range_cells > r_bottom)] = np.nan
-    #
-    #     loc_point_lin_interp0 = range_cells[np.where((range_cells > sample_depth[0]) & (range_cells < sample_depth[-1]))]
-    #     # print(f"range_cells : {range_cells}")
-    #     # print(f"loc_point_lin_interp0 shape : {len(loc_point_lin_interp0)}")
-    #     # print(f"loc_point_lin_interp0 : {loc_point_lin_interp0}")
-    #     res0 = res[np.where((range_cells > sample_depth[0]) & (range_cells < sample_depth[-1]))]
-    #
-    #     loc_point_lin_interp = loc_point_lin_interp0[np.where(loc_point_lin_interp0 > range_cells[0])]
-    #     # print(f"loc_point_lin_interp shape : {len(loc_point_lin_interp)}")
-    #     # print(f"loc_point_lin_interp : {loc_point_lin_interp}")
-    #     res = res0[np.where(loc_point_lin_interp0 > range_cells[0])]
-    #
-    #     # fig, ax = plt.subplots(nrows=1, ncols=1)
-    #     # ax.plot(loc_point_lin_interp, res[:len(loc_point_lin_interp)], marker="*", mfc="blue")
-    #     # ax.plot(sample_depth, M_profile, marker="o", mfc="k", mec="k")
-    #     # plt.show()
-    #
-    #     return (loc_point_lin_interp, res)
+    # ------------- Computing interpolation of fine SSC -------------

    def M_profile_SCC_fine_interpolated(self, sample_depth, M_profile, range_cells, r_bottom):
+        '''Computing interpolation of fine SSC data obtained from water sampling
+        collected at various depth in the vertical sample'''
        res = np.zeros((len(range_cells),)) * np.nan
-        print("range_cells ", range_cells.shape)
        l0 = sample_depth
-        print("l0 = ", l0)
        l1 = [l0.index(x) for x in sorted(l0)]
-        print("l1 = ", l1)
        l2 = [l0[k] for k in l1]
-        print("l2 = ", l2)
        c1 = [list(M_profile)[j] for j in l1]
-        print("c1 = ", c1)
        for i in range(len(c1) - 1):
            # print("i = ", i)
            r_ini = l2[i]
            c_ini = c1[i]
            r_end = l2[i + 1]
            c_end = c1[i + 1]
-            print("r_ini ", r_ini, "c_ini ", c_ini, "r_end ", r_end, "c_end ", c_end)
            # Computing the linear equation
            a = (c_end - c_ini) / (r_end - r_ini)
            b = c_ini - a * r_ini
-            print("range_cells ", (range_cells))

            # Finding the indices of r_ini and r_end in the interpolated array
            loc = (range_cells >= r_ini) * (range_cells < r_end)
-            print("range_cells >= r_ini ", range_cells >= r_ini)
-            print("range_cells < r_end ", range_cells < r_end)
-            print("loc ", loc)
            # Filling the array with interpolation values
            res[loc] = range_cells[loc] * a + b

-        print("a = ", a, "b = ", b)
-
-        print("res ", res)
-
        # Filling first and last values
        i = 0
        while np.isnan(res[i]):
@ -346,9 +178,6 @@ class AcousticInversionMethodHighConcentration():
            i += -1

        if r_bottom.size != 0:
-            print("res ", res.shape)
-            print("range_cells ", len(range_cells))
-            # print("r_bottom ", len(r_bottom))
            res[np.where(range_cells > r_bottom)] = np.nan

        loc_point_lin_interp0 = range_cells[np.where((range_cells > l2[0]) & (range_cells < l2[-1]))]
@ -357,13 +186,6 @@ class AcousticInversionMethodHighConcentration():
        loc_point_lin_interp = loc_point_lin_interp0[np.where(loc_point_lin_interp0 > l2[0])]
        res = res0[np.where(loc_point_lin_interp0 > l2[0])]

-        # fig, ax = plt.subplots(nrows=1, ncols=1)
-        # ax.plot(res[:len(loc_point_lin_interp)], -loc_point_lin_interp, marker="*", mfc="blue")
-        # ax.plot(c1, [-x for x in l2], marker="o", mfc="k", mec="k", ls="None")
-        # ax.set_xlabel("Concentration (g/L)")
-        # ax.set_ylabel("Depth (m)")
-        # plt.show()
-
        return (loc_point_lin_interp, res)

    # ------------- Computing zeta ------------- #
@ -372,39 +194,6 @@ class AcousticInversionMethodHighConcentration():
        delta_r = r[1] - r[0]
        zeta = alpha_s / (np.sum(np.array(M_profile_fine)*delta_r))

-        # print(f"np.sum(M_profile_fine*delta_r) : {np.sum(M_profile_fine*delta_r)}")
-        # zeta0 = np.array([0.021, 0.035, 0.057, 0.229])
-        # zeta = zeta0[ind]
-        # zeta0 = np.array([0.04341525, 0.04832906, 0.0847188, np.nan])
-        # zeta = zeta0[[ind1, ind2]]
-
-        # for k in range(3):
-        #     for p in range(3):
-        #         if np.isnan(ind_X_min_around_sample[p, k]):
-        #             zeta_list_exp.append(np.nan)
-        #         else:
-        #             ind_X_min = int(ind_X_min_around_sample[p, k])
-        #             ind_X_max = int(ind_X_max_around_sample[p, k])
-        #             ind_r_min = int(ind_r_min_around_sample[p, k])
-        #             ind_r_max = int(ind_r_max_around_sample[p, k])
-        #
-        #             R_temp = R_cross_section[ind_r_min:ind_r_max, :, ind_X_min:ind_X_max]
-        #             J_temp = J_cross_section[ind_r_min:ind_r_max, :, ind_X_min:ind_X_max]
-        #             aw_temp = aw_cross_section[ind_r_min:ind_r_max, :, ind_X_min:ind_X_max]
-        #             sv_temp_1 = np.repeat([sv_list_temp[3 * k + p]], np.shape(R_temp)[0], axis=0)
-        #             sv_temp = np.swapaxes(np.swapaxes(np.repeat([sv_temp_1], np.shape(R_temp)[2], axis=0), 1, 0), 2, 1)
-        #             ind_depth = np.where(R_cross_section[:, 0, 0] >= M_list_temp[k][0, p + 1])[0][0]
-        #             # Using concentration profile
-        #             zeta_temp = alpha_s / ((1 / M_list_temp[k][0, p + 1]) * (R_cross_section[0, 0, 0] * M_list_temp[k][1, 0] +
-        #                                             delta_r * np.sum(M_interpolate_list[k][:ind_depth])))
-        #             zeta_temp = (1 / (4 * R_temp) *
-        #                          np.log(sv_temp / J_temp) - aw_temp) / ((1 / M_list_temp[k][0, p + 1]) *
-        #                                                                 (R_cross_section[0, 0, 0] * M_list_temp[k][
-        #                                                                     1, 0] +
-        #                                                                  delta_r * np.sum(
-        #                                                                             M_interpolate_list[k][:ind_depth])))
-        #             zeta_list_exp.append(np.mean(np.mean(zeta_temp, axis=0), axis=1))
-
        return zeta

    # ------------- Computing VBI ------------- #
@ -415,21 +204,6 @@ class AcousticInversionMethodHighConcentration():
                          water_attenuation_freq1, water_attenuation_freq2,
                          X):

-        # print('self.zeta_exp[ind_j].shape', self.zeta_exp[ind_j])
-        # print('np.log(self.j_cross_section[:, ind_i, :]).shape', np.log(self.j_cross_section[:, ind_i, :]).shape)
-        # print('self.r_3D[:, ind_i, :]', self.r_3D[:, ind_i, :].shape)
-        # print('self.water_attenuation[ind_i]', self.water_attenuation[ind_i])
-        # print('self.x_exp[0.3-1 MHz]', self.x_exp['0.3-1 MHz'].values[0])
-        # print("start computing VBI")
-        # print("================================")
-        # print(f"zeta_freq2 : {zeta_freq2}")
-        # print(f"j_cross_section_freq1 : {j_cross_section_freq1.shape}")
-        # print(f"r2D : {r2D.shape}")
-        # print(f"water_attenuation_freq1 : {water_attenuation_freq1}")
-        # print(f"freq1 : {freq1}")
-        # print(f"X : {X}")
-        # print("================================")
-
        logVBI = ((zeta_freq2 *
                  np.log(j_cross_section_freq1 * np.exp(4 * r2D * water_attenuation_freq1) /
                         (freq1 ** X)) -
@ -438,31 +212,16 @@ class AcousticInversionMethodHighConcentration():
                         (freq2 ** X))) /
                  (zeta_freq2 - zeta_freq1))

-        # logVBI = (freq2**2 * np.log(j_cross_section_freq1 / freq1**X) -
-        #           freq1**2 * np.log(j_cross_section_freq2 / freq2**X)) / (freq2**2 - freq1**2)
-
-        # logVBI = (( np.full((stg.r.shape[1], stg.t.shape[1]), zeta_freq2) *
-        #            np.log(j_cross_section_freq1 * np.exp(4 * r2D * np.full((stg.r.shape[1], stg.t.shape[1]), water_attenuation_freq1)) /
-        #                   (freq1 ** X)) -
-        #            np.full((stg.r.shape[1], stg.t.shape[1]), zeta_freq1) *
-        #            np.log(j_cross_section_freq2 * np.exp(4 * r2D * np.full((stg.r.shape[1], stg.t.shape[1]), water_attenuation_freq2)) /
-        #                   (freq2 ** X))) /
-        #           (zeta_freq2 - zeta_freq1))
-
-        print("compute VBI finished")
-
        return np.exp(logVBI)

    # ------------- Computing SSC fine ------------- #
    def SSC_fine(self, zeta, r2D, VBI, freq, X, j_cross_section, alpha_w):
        SSC_fine = (1/zeta) * ( 1/(4 * r2D) * np.log((VBI * freq**X) / j_cross_section) - alpha_w)
-        print("compute SSC fine finished")
        return SSC_fine

    # ------------- Computing SSC sand ------------- #
    def SSC_sand(self, VBI, freq, X, ks):
        SSC_sand = (16 * np.pi * VBI * freq ** X) / (3 * ks**2)
-        print("compute SSC sand finished")
        return SSC_sand


--- a/Model/calibration_constant_kt.py
+++ b/Model/calibration_constant_kt.py
@ -25,7 +25,6 @@ from PyQt5.QtWidgets import (QWidget, QVBoxLayout, QDialog, QTabWidget, QGridLay
                             QFileDialog, QMessageBox, QLabel)
 from PyQt5.QtCore import Qt

-
 class CalibrationConstantKt(QDialog):

    def __init__(self, parent=None):
@ -113,11 +112,3 @@ class CalibrationConstantKt(QDialog):
                eval("self.gridLayout_tab_" + str(t_index) + ".addWidget(self.label_kt_" + str(x) + "_ABS_" + str(t_index) +
                     ", " + str(x+1) + ", 1, 1, 1, Qt.AlignCenter)")

-
-# if __name__ == "__main__":
-#     app = QApplication(sys.argv)
-#     cal = CalibrationConstantKt()
-#     cal.show()
-#     # sys.exit(app.exec_())
-#     app.exec()
-
--- a/Model/create_table_for_save_as.py
+++ b/Model/create_table_for_save_as.py
@ -20,168 +20,199 @@

 # -*- coding: utf-8 -*-

+import os
+import time
+import sqlite3
+import logging

 import numpy as np
-from PyQt5.QtWidgets import QFileDialog, QApplication, QMessageBox
-import sqlite3
-import settings as stg
-from os import chdir
-import time

+from PyQt5.QtWidgets import QFileDialog, QApplication, QMessageBox
+
+import settings as stg
 from settings import ABS_name

+logger = logging.getLogger("acoused")
+
 class CreateTableForSaveAs:

    def __init__(self):
+        self.create_AcousticFile = """
+        CREATE TABLE AcousticFile(
+          ID INTEGER PRIMARY KEY AUTOINCREMENT,
+          acoustic_data INTEGER,
+          acoustic_file STRING,
+          ABS_name STRING,
+          path_BS_noise_data STRING,
+          filename_BS_noise_data STRING,
+          noise_method FLOAT,
+          noise_value FLOAT,
+          data_preprocessed STRING
+        )
+        """

-        self.create_AcousticFile = """CREATE TABLE AcousticFile(
-                                                ID INTEGER PRIMARY KEY AUTOINCREMENT, 
-                                                acoustic_data INTEGER,                  
-                                                acoustic_file STRING, 
-                                                ABS_name STRING, 
-                                                path_BS_noise_data STRING, 
-                                                filename_BS_noise_data STRING, 
-                                                noise_method FLOAT, 
-                                                noise_value FLOAT, 
-                                                data_preprocessed STRING
-                                                )
-                                                """
+        self.create_Measure = """
+        CREATE TABLE Measure(
+          ID INTEGER PRIMARY KEY AUTOINCREMENT,
+          acoustic_data INTEGER,
+          Date DATE,
+          Hour TIME,
+          frequency FLOAT,
+          sound_attenuation FLOAT,
+          kt_read FLOAT,
+          kt_corrected FLOAT,
+          NbProfiles FLOAT,
+          NbProfilesPerSeconds FLOAT,
+          NbCells FLOAT,
+          CellSize FLOAT,
+          PulseLength FLOAT,
+          NbPingsPerSeconds FLOAT,
+          NbPingsAveragedPerProfile FLOAT,
+          GainRx FLOAT,
+          GainTx FLOAT
+        )
+        """

-        self.create_Measure = """ CREATE TABLE Measure(
-                                    ID INTEGER PRIMARY KEY AUTOINCREMENT,
-                                    acoustic_data INTEGER, 
-                                    Date DATE, 
-                                    Hour TIME, 
-                                    frequency FLOAT,
-                                    sound_attenuation FLOAT,  
-                                    kt_read FLOAT,
-                                    kt_corrected FLOAT, 
-                                    NbProfiles FLOAT, 
-                                    NbProfilesPerSeconds FLOAT, 
-                                    NbCells FLOAT, 
-                                    CellSize FLOAT, 
-                                    PulseLength FLOAT, 
-                                    NbPingsPerSeconds FLOAT, 
-                                    NbPingsAveragedPerProfile FLOAT, 
-                                    GainRx FLOAT, 
-                                    GainTx FLOAT
-                                    )
-                                    """
+        self.create_BSRawData = """
+        CREATE TABLE BSRawData(
+          ID INTEGER PRIMARY KEY AUTOINCREMENT,
+          acoustic_data INTEGER,
+          time BLOB, depth BLOB, BS_raw_data BLOB,
+          time_reshape BLOB, depth_reshape BLOB, BS_raw_data_reshape BLOB,
+          time_cross_section BLOB, depth_cross_section BLOB,
+          BS_cross_section BLOB, BS_stream_bed BLO  B,
+          depth_bottom, val_bottom, ind_bottom,
+          time_noise BLOB, depth_noise BLOB, BS_noise_raw_data BLOB,
+          SNR_raw_data BLOB, SNR_cross_section BLOB, SNR_stream_bed BLOB,
+          BS_raw_data_pre_process_SNR BLOB,
+          BS_raw_data_pre_process_average BLOB,
+          BS_cross_section_pre_process_SNR BLOB,
+          BS_cross_section_pre_process_average BLOB,
+          BS_stream_bed_pre_process_SNR BLOB,
+          BS_stream_bed_pre_process_average BLOB,
+          BS_mean BLOB
+        )
+        """

-        self.create_BSRawData = '''CREATE TABLE BSRawData(
-                                    ID INTEGER PRIMARY KEY AUTOINCREMENT,
-                                    acoustic_data INTEGER,
-                                    time BLOB, depth BLOB, BS_raw_data BLOB, 
-                                    time_reshape BLOB, depth_reshape BLOB, BS_raw_data_reshape BLOB,
-                                    time_cross_section BLOB, depth_cross_section BLOB, BS_cross_section BLOB, BS_stream_bed BLOB,
-                                    depth_bottom, val_bottom, ind_bottom, 
-                                    time_noise BLOB, depth_noise BLOB, BS_noise_raw_data BLOB, 
-                                    SNR_raw_data BLOB, SNR_cross_section BLOB, SNR_stream_bed BLOB,
-                                    BS_raw_data_pre_process_SNR BLOB, BS_raw_data_pre_process_average BLOB, 
-                                    BS_cross_section_pre_process_SNR BLOB, BS_cross_section_pre_process_average BLOB, 
-                                    BS_stream_bed_pre_process_SNR BLOB, BS_stream_bed_pre_process_average BLOB, 
-                                    BS_mean BLOB
-                                    )'''
+        self.create_Settings = """
+        CREATE TABLE Settings(
+          ID INTEGER PRIMARY KEY AUTOINCREMENT,
+          acoustic_data INTEGER,
+          temperature FLOAT,
+          tmin_index FLOAT, tmin_value FLOAT,
+          tmax_index FLOAT, tmax_value FLOAT,
+          rmin_index FLOAT, rmin_value FLOAT,
+          rmax_index FLOAT, rmax_value FLOAT,
+          freq_bottom_detection_index FLOAT,
+          freq_bottom_detection_value STRING,
+          SNR_filter_value FLOAT, Nb_cells_to_average_BS_signal FLOAT
+        )
+        """

-        self.create_Settings = '''CREATE TABLE Settings(
-                                    ID INTEGER PRIMARY KEY AUTOINCREMENT,
-                                    acoustic_data INTEGER,
-                                    temperature FLOAT,
-                                    tmin_index FLOAT, tmin_value FLOAT, tmax_index FLOAT, tmax_value FLOAT,
-                                    rmin_index FLOAT, rmin_value FLOAT, rmax_index FLOAT, rmax_value FLOAT, 
-                                    freq_bottom_detection_index FLOAT, freq_bottom_detection_value STRING, 
-                                    SNR_filter_value FLOAT, Nb_cells_to_average_BS_signal FLOAT
-                                    )'''
+        self.create_SedimentsFile = """
+        CREATE TABLE SedimentsFile(
+          ID INTEGER PRIMARY KEY AUTOINCREMENT,
+          path_fine STRING,
+          filename_fine STRING,
+          radius_grain_fine BLOB,
+          path_sand STRING,
+          filename_sand STRING,
+          radius_grain_sand BLOB,
+          time_column_label STRING,
+          distance_from_bank_column_label STRING,
+          depth_column_label STRING,
+          Ctot_fine_column_label STRING,
+          D50_fine_column_label STRING,
+          Ctot_sand_column_label STRING,
+          D50_sand_column_label STRING
+        )
+        """

-        self.create_SedimentsFile = """CREATE TABLE SedimentsFile(
-                                                       ID INTEGER PRIMARY KEY AUTOINCREMENT,                  
-                                                       path_fine STRING, 
-                                                       filename_fine STRING, 
-                                                       radius_grain_fine BLOB,
-                                                       path_sand STRING, 
-                                                       filename_sand STRING, 
-                                                       radius_grain_sand BLOB, 
-                                                       time_column_label STRING, 
-                                                       distance_from_bank_column_label STRING, 
-                                                       depth_column_label STRING, 
-                                                       Ctot_fine_column_label STRING, 
-                                                       D50_fine_column_label STRING,
-                                                       Ctot_sand_column_label STRING, 
-                                                       D50_sand_column_label STRING
-                                                       )
-                                                       """
+        self.create_SedimentsData = """
+        CREATE TABLE SedimentsData(
+          ID INTEGER PRIMARY KEY AUTOINCREMENT,
+          sample_fine_name STRING,
+          sample_fine_index INTEGER,
+          distance_from_bank_fine FLOAT,
+          depth_fine FLOAT,
+          time_fine FLOAT,
+          Ctot_fine FLOAT,
+          Ctot_fine_per_cent FLOAT,
+          D50_fine FLOAT,
+          frac_vol_fine BLOB,
+          frac_vol_fine_cumul BLOB,
+          sample_sand_name STRING,
+          sample_sand_index INTEGER,
+          distance_from_bank_sand FLOAT,
+          depth_sand FLOAT,
+          time_sand FLOAT,
+          Ctot_sand FLOAT,
+          Ctot_sand_per_cent FLOAT,
+          D50_sand FLOAT,
+          frac_vol_sand BLOB,
+          frac_vol_sand_cumul BLOB
+        )
+        """

-        self.create_SedimentsData = """CREATE TABLE SedimentsData(
-                                                ID INTEGER PRIMARY KEY AUTOINCREMENT,                  
-                                                sample_fine_name STRING, 
-                                                sample_fine_index INTEGER,
-                                                distance_from_bank_fine FLOAT, 
-                                                depth_fine FLOAT, 
-                                                time_fine FLOAT, 
-                                                Ctot_fine FLOAT,
-                                                Ctot_fine_per_cent FLOAT, 
-                                                D50_fine FLOAT, 
-                                                frac_vol_fine BLOB, 
-                                                frac_vol_fine_cumul BLOB, 
-                                                sample_sand_name STRING, 
-                                                sample_sand_index INTEGER,
-                                                distance_from_bank_sand FLOAT, 
-                                                depth_sand FLOAT, 
-                                                time_sand FLOAT, 
-                                                Ctot_sand FLOAT,
-                                                Ctot_sand_per_cent FLOAT, 
-                                                D50_sand FLOAT, 
-                                                frac_vol_sand BLOB, 
-                                                frac_vol_sand_cumul BLOB
-                                                )
-                                                """
+        self.create_Calibration = """
+        CREATE TABLE Calibration(
+          ID INTEGER PRIMARY KEY AUTOINCREMENT,
+          path_calibration_file STRING,
+          filename_calibration_file STRING,
+          range_lin_interp BLOB,
+          M_profile_fine BLOB,
+          ks BLOB,
+          sv BLOB,
+          X_exponent BLOB,
+          alpha_s BLOB,
+          zeta BLOB,
+          FCB BLOB,
+          depth_real BLOB,
+          lin_reg BLOB
+        )
+        """

-        self.create_Calibration = """CREATE TABLE Calibration(
-                                                        ID INTEGER PRIMARY KEY AUTOINCREMENT, 
-                                                        path_calibration_file STRING, 
-                                                        filename_calibration_file STRING,                 
-                                                        range_lin_interp BLOB, 
-                                                        M_profile_fine BLOB, 
-                                                        ks BLOB,
-                                                        sv BLOB, 
-                                                        X_exponent BLOB, 
-                                                        alpha_s BLOB, 
-                                                        zeta BLOB, 
-                                                        FCB BLOB, 
-                                                        depth_real BLOB, 
-                                                        lin_reg BLOB
-                                                        )"""
-
-        self.create_Inversion = """CREATE TABLE Inversion(
-                                                          ID INTEGER PRIMARY KEY AUTOINCREMENT, 
-                                                          J_cross_section_freq1 BLOB,
-                                                          J_cross_section_freq2 BLOB,
-                                                          VBI_cross_section BLOB, 
-                                                          SSC_fine BLOB, 
-                                                          SSC_sand BLOB
-                                                          )"""
+        self.create_Inversion = """
+        CREATE TABLE Inversion(
+          ID INTEGER PRIMARY KEY AUTOINCREMENT,
+          J_cross_section_freq1 BLOB,
+          J_cross_section_freq2 BLOB,
+          VBI_cross_section BLOB,
+          SSC_fine BLOB,
+          SSC_sand BLOB
+        )
+        """

        self.open_file_dialog()


    def open_file_dialog(self):
-        options = QFileDialog.Options()
-        name = QFileDialog.getSaveFileName(
-            caption="Save As", directory="", filter="AcouSed Files (*.acd)", options=QFileDialog.DontUseNativeDialog)
+        name, _ = QFileDialog.getSaveFileName(
+            caption="Save As",
+            directory="",
+            filter="AcouSed Files (*.acd)",
+            options=QFileDialog.DontUseNativeDialog
+        )

-        if name[0]:
+        if name != "":
+            filename = os.path.basename(name)
+            if os.path.splitext(filename)[1] != ".acd":
+                filename += ".acd"

-            stg.dirname_save_as = "/".join(name[0].split("/")[:-1]) + "/"
-            stg.filename_save_as = name[0].split("/")[-1]
+            logger.debug(f"selected save file: '{filename}'")

-            chdir(stg.dirname_save_as)
+            stg.dirname_save_as = os.path.dirname(name)
+            stg.filename_save_as = filename
+
+            try:
+                os.chdir(stg.dirname_save_as)
+            except OSError as e:
+                logger.warning(f"chdir: {str(e)}")

            start = time.time()
            self.create_table()
            print(f"end : {time.time() - start} sec")
-
        else:
-
            msgBox = QMessageBox()
            msgBox.setWindowTitle("Save Error")
            msgBox.setIcon(QMessageBox.Warning)
@ -190,18 +221,24 @@ class CreateTableForSaveAs:
            msgBox.exec()

    def create_table(self):
-        
-        # Create a new database and open a database connection to allow sqlite3 to work with it.
-        cnx = sqlite3.connect(stg.filename_save_as + '.acd')
-
-        # Create database cursor to execute SQL statements and fetch results from SQL queries.
+        cnx = sqlite3.connect(stg.filename_save_as)
        cur = cnx.cursor()

-        # --------------------------------------------------------------------------------------------------------------
-                                                # +++++++++++++++++++++++++++
-                                                # --- Table Acoustic File ---
-                                                # +++++++++++++++++++++++++++
+        self.create_table_acoustic_file(cnx, cur)
+        self.create_table_measure(cnx, cur)
+        self.create_table_BSRawData(cnx, cur)
+        self.create_table_settings(cnx, cur)
+        self.create_table_sediments_file(cnx, cur)
+        self.create_table_sediments_data(cnx, cur)
+        self.create_table_calibration(cnx, cur)
+        self.create_table_inversion(cnx, cur)

+        cnx.commit()
+
+        cur.close()
+        cnx.close()
+
+    def create_table_acoustic_file(self, cnx, cur):
        start_table_File = time.time()

        cur.execute("DROP TABLE if exists AcousticFile")
@ -209,28 +246,42 @@ class CreateTableForSaveAs:
        cur.execute(self.create_AcousticFile)

        for i in stg.acoustic_data:
-            print("stg.acoustic_data ", stg.acoustic_data[i])
-            print("stg.filename_BS_raw_data ", stg.filename_BS_raw_data[i])
-            print('stg.ABS_name', stg.ABS_name)
-            print("stg.path_BS_raw_data ", stg.path_BS_raw_data[i])
+            logger.debug(f"stg.acoustic_data: {stg.acoustic_data[i]}")
+            logger.debug("stg.filename_BS_raw_data: "
+                         + f"{stg.filename_BS_raw_data[i]}")
+            logger.debug(f"stg.ABS_name: {stg.ABS_name}")
+            logger.debug(f"stg.path_BS_raw_data: {stg.path_BS_raw_data[i]}")

-            cur.execute(''' INSERT into AcousticFile(acoustic_data, acoustic_file, ABS_name, path_BS_noise_data, 
-                                                 filename_BS_noise_data, noise_method, noise_value, data_preprocessed) 
-                                    VALUES(?, ?, ?, ?, ?, ?, ?, ?)''',
-                        (stg.acoustic_data[i], stg.filename_BS_raw_data[i].split('.')[0], stg.ABS_name[i],
-                        stg.path_BS_noise_data[i], stg.filename_BS_noise_data[i], stg.noise_method[i],
-                        stg.noise_value[i], stg.data_preprocessed[i])
-                        )
+            cur.execute(
+                """
+                INSERT into AcousticFile(
+                  acoustic_data,
+                  acoustic_file,
+                  ABS_name,
+                  path_BS_noise_data,
+                  filename_BS_noise_data,
+                  noise_method,
+                  noise_value,
+                  data_preprocessed)
+                VALUES(?, ?, ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    stg.acoustic_data[i],
+                    stg.filename_BS_raw_data[i].split('.')[0],
+                    stg.ABS_name[i],
+                    stg.path_BS_noise_data[i],
+                    stg.filename_BS_noise_data[i],
+                    stg.noise_method[i],
+                    stg.noise_value[i],
+                    stg.data_preprocessed[i]
+                )
+            )

        cnx.commit()

-        print(f"table File : {time.time() - start_table_File} sec")
-
-        # --------------------------------------------------------------------------------------------------------------
-                                                # +++++++++++++++++++++
-                                                # --- Table Measure ---
-                                                # +++++++++++++++++++++
+        logger.info(f"table File : {time.time() - start_table_File} sec")

+    def create_table_measure(self, cnx, cur):
        start_table_Measure = time.time()

        # Drop Table if exists
@ -238,35 +289,52 @@ class CreateTableForSaveAs:

        # Execute the CREATE TABLE statement
        cur.execute(self.create_Measure)
-        print("stg.date ", stg.date, "stg.hour ", stg.hour)
-        # Fill the table Measure
+
+        logger.debug(f"stg.date: {stg.date}, stg.hour: {stg.hour}")
+
        for i in stg.acoustic_data:
-
            for j in range(stg.freq[i].shape[0]):
-
-                cur.execute(''' INSERT into Measure(acoustic_data, Date, Hour, frequency, sound_attenuation, kt_read, kt_corrected, 
-                                                        NbProfiles, NbProfilesPerSeconds, NbCells, CellSize, PulseLength, 
-                                                        NbPingsPerSeconds, NbPingsAveragedPerProfile, GainRx, GainTx 
-                                                        )
-                                    VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
-                            (stg.acoustic_data[i], #stg.date[i], stg.hour[i],
-                             str(stg.date[i].year) + str('-') + str(stg.date[i].month) + str('-') + str(stg.date[i].day),
-                             str(stg.hour[i].hour) + str(':') + str(stg.hour[i].minute),
-                             stg.freq[i][j], stg.water_attenuation[i][j], stg.kt_read[j], stg.kt_corrected[j],
-                             stg.nb_profiles[i][j], stg.nb_profiles_per_sec[i][j], stg.nb_cells[i][j],
-                             stg.cell_size[i][j], stg.pulse_length[i][j], stg.nb_pings_per_sec[i][j],
-                             stg.nb_pings_averaged_per_profile[i][j], stg.gain_rx[i][j], stg.gain_tx[i][j]))
+                cur.execute(
+                    """
+                    INSERT into Measure(
+                      acoustic_data,
+                      Date, Hour,
+                      frequency,
+                      sound_attenuation,
+                      kt_read, kt_corrected,
+                      NbProfiles, NbProfilesPerSeconds,
+                      NbCells, CellSize,
+                      PulseLength,
+                      NbPingsPerSeconds,
+                      NbPingsAveragedPerProfile,
+                      GainRx, GainTx
+                    )
+                    VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                    """,
+                    (
+                        stg.acoustic_data[i], #stg.date[i], stg.hour[i],
+                        str(stg.date[i].year) + str('-')
+                        + str(stg.date[i].month) + str('-')
+                        + str(stg.date[i].day),
+                        str(stg.hour[i].hour) + str(':') + str(stg.hour[i].minute),
+                        stg.freq[i][j],
+                        stg.water_attenuation[i][j],
+                        stg.kt_read[j], stg.kt_corrected[j],
+                        stg.nb_profiles[i][j], stg.nb_profiles_per_sec[i][j],
+                        stg.nb_cells[i][j], stg.cell_size[i][j],
+                        stg.pulse_length[i][j],
+                        stg.nb_pings_per_sec[i][j],
+                        stg.nb_pings_averaged_per_profile[i][j],
+                        stg.gain_rx[i][j], stg.gain_tx[i][j]
+                    )
+                )

        # Commit the transaction after executing INSERT.
        cnx.commit()

-        print(f"table Measure : {time.time() - start_table_Measure} sec")
-
-        # --------------------------------------------------------------------------------------------------------------
-                                                # +++++++++++++++++++++++++
-                                                # --- Table BSRawData_i ---
-                                                # +++++++++++++++++++++++++
+        logger.info(f"table Measure : {time.time() - start_table_Measure} sec")

+    def create_table_BSRawData(self, cnx, cur):
        start_table_BSRawData = time.time()

        cur.execute('DROP TABLE if exists BSRawData')
@ -275,105 +343,136 @@ class CreateTableForSaveAs:
        cur.execute(self.create_BSRawData)

        for i in stg.acoustic_data:
+            cur.execute(
+                """
+                INSERT into BSRawData(
+                  acoustic_data,
+                  time, depth,
+                  BS_raw_data,
+                  time_reshape,
+                  depth_reshape,
+                  BS_raw_data_reshape,
+                  time_cross_section, depth_cross_section,
+                  BS_cross_section, BS_stream_bed,
+                  depth_bottom, val_bottom, ind_bottom,
+                  time_noise, depth_noise, BS_noise_raw_data,
+                  SNR_raw_data, SNR_cross_section, SNR_stream_bed,
+                  BS_raw_data_pre_process_SNR, BS_raw_data_pre_process_average,
+                  BS_cross_section_pre_process_SNR, BS_cross_section_pre_process_average,
+                  BS_stream_bed_pre_process_SNR, BS_stream_bed_pre_process_average,
+                  BS_mean
+                )
+                VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?,
+                       ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    stg.acoustic_data[i], stg.time[i].tobytes(),
+                    stg.depth[i].tobytes(), stg.BS_raw_data[i].tobytes(),
+                    stg.time_reshape[i].tobytes(), stg.depth_reshape[i].tobytes(),
+                    stg.BS_raw_data_reshape[i].tobytes(),
+                    stg.time_cross_section[i].tobytes(),
+                    stg.depth_cross_section[i].tobytes(),
+                    stg.BS_cross_section[i].tobytes(), stg.BS_stream_bed[i].tobytes(),
+                    stg.depth_bottom[i].tobytes(), np.array(stg.val_bottom[i]).tobytes(),
+                    np.array(stg.ind_bottom[i]).tobytes(),
+                    stg.time_noise[i].tobytes(), stg.depth_noise[i].tobytes(),
+                    stg.BS_noise_raw_data[i].tobytes(),
+                    stg.SNR_raw_data[i].tobytes(), stg.SNR_cross_section[i].tobytes(),
+                    stg.SNR_stream_bed[i].tobytes(),
+                    stg.BS_raw_data_pre_process_SNR[i].tobytes(),
+                    stg.BS_raw_data_pre_process_average[i].tobytes(),
+                    stg.BS_cross_section_pre_process_SNR[i].tobytes(),
+                    stg.BS_cross_section_pre_process_average[i].tobytes(),
+                    stg.BS_stream_bed_pre_process_SNR[i].tobytes(),
+                    stg.BS_stream_bed_pre_process_average[i].tobytes(),
+                    stg.BS_mean[i].tobytes()
+                )
+            )

-            cur.execute(''' INSERT into BSRawData(acoustic_data, time, depth, BS_raw_data, 
-                                                      time_reshape, depth_reshape, BS_raw_data_reshape,
-                                                      time_cross_section, depth_cross_section, 
-                                                      BS_cross_section, BS_stream_bed, 
-                                                      depth_bottom, val_bottom, ind_bottom,
-                                                      time_noise, depth_noise, BS_noise_raw_data, 
-                                                      SNR_raw_data, SNR_cross_section, SNR_stream_bed,
-                                                      BS_raw_data_pre_process_SNR, BS_raw_data_pre_process_average, 
-                                                      BS_cross_section_pre_process_SNR, BS_cross_section_pre_process_average, 
-                                                      BS_stream_bed_pre_process_SNR, BS_stream_bed_pre_process_average, 
-                                                      BS_mean)
-                                VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
-                        (stg.acoustic_data[i], stg.time[i].tobytes(),
-                         stg.depth[i].tobytes(), stg.BS_raw_data[i].tobytes(),
-                         stg.time_reshape[i].tobytes(), stg.depth_reshape[i].tobytes(), stg.BS_raw_data_reshape[i].tobytes(),
-                         stg.time_cross_section[i].tobytes(), stg.depth_cross_section[i].tobytes(),
-                         stg.BS_cross_section[i].tobytes(), stg.BS_stream_bed[i].tobytes(),
-                         stg.depth_bottom[i].tobytes(), np.array(stg.val_bottom[i]).tobytes(), np.array(stg.ind_bottom[i]).tobytes(),
-                         stg.time_noise[i].tobytes(), stg.depth_noise[i].tobytes(), stg.BS_noise_raw_data[i].tobytes(),
-                         stg.SNR_raw_data[i].tobytes(), stg.SNR_cross_section[i].tobytes(), stg.SNR_stream_bed[i].tobytes(),
-                         stg.BS_raw_data_pre_process_SNR[i].tobytes(), stg.BS_raw_data_pre_process_average[i].tobytes(),
-                         stg.BS_cross_section_pre_process_SNR[i].tobytes(), stg.BS_cross_section_pre_process_average[i].tobytes(),
-                         stg.BS_stream_bed_pre_process_SNR[i].tobytes(), stg.BS_stream_bed_pre_process_average[i].tobytes(),
-                         stg.BS_mean[i].tobytes()
-                         )
-                        )
-
-        print("stg.ind_bottom ", stg.ind_bottom[i])
-        print(np.array([stg.ind_bottom[i]]), np.array(stg.ind_bottom[i]).shape)
-            # Commit the transaction after executing INSERT.
+        # Commit the transaction after executing INSERT.
        cnx.commit()

-        print(f"table BSRawData : {time.time() - start_table_BSRawData} sec")
-
-        # --------------------------------------------------------------------------------------------------------------
-                                                # ++++++++++++++++++++++
-                                                # --- Table Settings ---
-                                                # ++++++++++++++++++++++
+        logger.info(f"table BSRawData : {time.time() - start_table_BSRawData} sec")

+    def create_table_settings(self, cnx, cur):
        start_table_Settings = time.time()

        cur.execute("DROP TABLE if exists Settings")

        cur.execute(self.create_Settings)

-        print(stg.acoustic_data, stg.temperature, stg.rmin, stg.rmax, stg.tmin, stg.tmax)
+        logger.debug(f"acoustic_data: {stg.acoustic_data}")
+        logger.debug(f"temperature: {stg.temperature}")
+        logger.debug(f"rmin: {stg.rmin}, rmax: {stg.rmax}")
+        logger.debug(f"tmin: {stg.tmin}, tmax: {stg.tmax}")

        for i in stg.acoustic_data:
-            cur.execute('''INSERT into Settings(acoustic_data, temperature,
-                        tmin_index, tmin_value, tmax_index, tmax_value,
-                        rmin_index, rmin_value, rmax_index, rmax_value,
-                        freq_bottom_detection_index, freq_bottom_detection_value, 
-                        SNR_filter_value, Nb_cells_to_average_BS_signal
-                        ) 
-                        VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
-                        (stg.acoustic_data[i], stg.temperature,
-                         stg.tmin[i][0], stg.tmin[i][1], stg.tmax[i][0], stg.tmax[i][1],
-                         stg.rmin[i][0], stg.rmin[i][1], stg.rmax[i][0], stg.rmax[i][1],
-                         stg.freq_bottom_detection[i][0], stg.freq_bottom_detection[i][1],
-                         stg.SNR_filter_value[i], stg.Nb_cells_to_average_BS_signal[i]
-                         )
-                        )
+            cur.execute(
+                """
+                INSERT into Settings(
+                  acoustic_data, temperature,
+                  tmin_index, tmin_value, tmax_index, tmax_value,
+                  rmin_index, rmin_value, rmax_index, rmax_value,
+                  freq_bottom_detection_index, freq_bottom_detection_value,
+                  SNR_filter_value, Nb_cells_to_average_BS_signal
+                )
+                VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    stg.acoustic_data[i], stg.temperature,
+                    stg.tmin[i][0], stg.tmin[i][1],
+                    stg.tmax[i][0], stg.tmax[i][1],
+                    stg.rmin[i][0], stg.rmin[i][1],
+                    stg.rmax[i][0], stg.rmax[i][1],
+                    stg.freq_bottom_detection[i][0],
+                    stg.freq_bottom_detection[i][1],
+                    stg.SNR_filter_value[i],
+                    stg.Nb_cells_to_average_BS_signal[i]
+                )
+            )

        cnx.commit()

-        print(f"table Settings : {time.time() - start_table_Settings} sec")
-
-        # --------------------------------------------------------------------------------------------------------------
-                                                # ++++++++++++++++++++++++++++
-                                                # --- Table Sediments File ---
-                                                # ++++++++++++++++++++++++++++
+        logger.info(f"table Settings : {time.time() - start_table_Settings} sec")

+    def create_table_sediments_file(self, cnx, cur):
        start_table_SedimentsFile = time.time()

        cur.execute("DROP TABLE if exists SedimentsFile")

        cur.execute(self.create_SedimentsFile)

-        cur.execute('''INSERT into SedimentsFile(path_fine, filename_fine, radius_grain_fine,
-                                                     path_sand, filename_sand, radius_grain_sand, 
-                                                     time_column_label, distance_from_bank_column_label, 
-                                                     depth_column_label, Ctot_fine_column_label, D50_fine_column_label,
-                                                     Ctot_sand_column_label, D50_sand_column_label)
-                                              VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
-                    (stg.path_fine, stg.filename_fine, stg.radius_grain_fine.tobytes(),
-                     stg.path_sand, stg.filename_sand, stg.radius_grain_sand.tobytes(),
-                     stg.columns_fine[0], stg.columns_fine[1], stg.columns_fine[2],
-                     stg.columns_fine[3], stg.columns_fine[4], stg.columns_sand[3], stg.columns_sand[4]))
+        if stg.path_fine != "" and stg.path_sand != "":
+            cur.execute(
+                """
+                INSERT into SedimentsFile(
+                  path_fine, filename_fine, radius_grain_fine,
+                  path_sand, filename_sand, radius_grain_sand,
+                  time_column_label, distance_from_bank_column_label,
+                  depth_column_label, Ctot_fine_column_label,
+                  D50_fine_column_label,
+                  Ctot_sand_column_label, D50_sand_column_label
+                )
+                VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    stg.path_fine, stg.filename_fine,
+                    stg.radius_grain_fine.tobytes(),
+                    stg.path_sand, stg.filename_sand,
+                    stg.radius_grain_sand.tobytes(),
+                    stg.columns_fine[0], stg.columns_fine[1],
+                    stg.columns_fine[2], stg.columns_fine[3],
+                    stg.columns_fine[4],
+                    stg.columns_sand[3], stg.columns_sand[4]
+                )
+            )

        cnx.commit()

-        print(f"table SedimentsFile : {time.time() - start_table_SedimentsFile} sec")
+        logger.info(f"table SedimentsFile : {time.time() - start_table_SedimentsFile} sec")

-        # --------------------------------------------------------------------------------------------------------------
-                                                # ++++++++++++++++++++++++++++
-                                                # --- Table Sediments Data ---
-                                                # ++++++++++++++++++++++++++++

+    def create_table_sediments_data(self, cnx, cur):
        start_table_SedimentsData = time.time()

        cur.execute("DROP TABLE if exists SedimentsData")
@ -381,59 +480,79 @@ class CreateTableForSaveAs:
        cur.execute(self.create_SedimentsData)

        for f in range(len(stg.sample_fine)):
-            cur.execute('''INSERT into SedimentsData(sample_fine_name, sample_fine_index, distance_from_bank_fine,
-                                    depth_fine, time_fine, Ctot_fine, Ctot_fine_per_cent, D50_fine, 
-                                    frac_vol_fine, frac_vol_fine_cumul, 
-                                    sample_sand_name, sample_sand_index, distance_from_bank_sand,
-                                    depth_sand, time_sand, Ctot_sand, Ctot_sand_per_cent, D50_sand, 
-                                    frac_vol_sand, frac_vol_sand_cumul 
-                                    )
-                        VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
-                    (stg.sample_fine[f][0] , stg.sample_fine[f][1],
-                     stg.distance_from_bank_fine[f], stg.depth_fine[f], stg.time_fine[f], stg.Ctot_fine[f],
-                     stg.Ctot_fine_per_cent[f], stg.D50_fine[f],
-                     stg.frac_vol_fine[f].tobytes(), stg.frac_vol_fine_cumul[f].tobytes(),
-                     stg.sample_sand[f][0], stg.sample_sand[f][1],
-                     stg.distance_from_bank_sand[f], stg.depth_sand[f], stg.time_sand[f], stg.Ctot_sand[f],
-                     stg.Ctot_sand_per_cent[f], stg.D50_sand[f],
-                     stg.frac_vol_sand[f].tobytes(), stg.frac_vol_sand_cumul[f].tobytes()))
+            cur.execute(
+                """
+                INSERT into SedimentsData(
+                  sample_fine_name, sample_fine_index,
+                  distance_from_bank_fine,
+                  depth_fine, time_fine, Ctot_fine,
+                  Ctot_fine_per_cent, D50_fine,
+                  frac_vol_fine, frac_vol_fine_cumul,
+                  sample_sand_name, sample_sand_index,
+                  distance_from_bank_sand,
+                  depth_sand, time_sand, Ctot_sand,
+                  Ctot_sand_per_cent, D50_sand,
+                  frac_vol_sand, frac_vol_sand_cumul
+                )
+                VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?,
+                       ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    stg.sample_fine[f][0] , stg.sample_fine[f][1],
+                    stg.distance_from_bank_fine[f], stg.depth_fine[f],
+                    stg.time_fine[f], stg.Ctot_fine[f],
+                    stg.Ctot_fine_per_cent[f], stg.D50_fine[f],
+                    stg.frac_vol_fine[f].tobytes(),
+                    stg.frac_vol_fine_cumul[f].tobytes(),
+                    stg.sample_sand[f][0], stg.sample_sand[f][1],
+                    stg.distance_from_bank_sand[f], stg.depth_sand[f],
+                    stg.time_sand[f], stg.Ctot_sand[f],
+                    stg.Ctot_sand_per_cent[f], stg.D50_sand[f],
+                    stg.frac_vol_sand[f].tobytes(),
+                    stg.frac_vol_sand_cumul[f].tobytes()
+                )
+            )

        cnx.commit()

-        print(f"table SedimentsData : {time.time() - start_table_SedimentsData} sec")
-
-        # --------------------------------------------------------------------------------------------------------------
-                                                # ++++++++++++++++++++++++++++++
-                                                # --- Table Calibration ---
-                                                # ++++++++++++++++++++++++++++++
+        logger.info(f"table SedimentsData : {time.time() - start_table_SedimentsData} sec")

+    def create_table_calibration(self, cnx, cur):
        start_table_Calibration = time.time()

        cur.execute("DROP TABLE if exists Calibration")

        cur.execute(self.create_Calibration)

-        cur.execute('''INSERT into Calibration(path_calibration_file, filename_calibration_file, 
-                                                    range_lin_interp, M_profile_fine,
-                                                    ks, sv, X_exponent, alpha_s, zeta,
-                                                    FCB, depth_real, lin_reg) 
-                            VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
-                    (stg.path_calibration_file, stg.filename_calibration_file,
-                     stg.range_lin_interp.tobytes(), stg.M_profile_fine.tobytes(),
-                     np.array(stg.ks).tobytes(), np.array(stg.sv).tobytes(), np.array(stg.X_exponent).tobytes(),
-                     np.array(stg.alpha_s).tobytes(), np.array(stg.zeta).tobytes(),
-                     stg.FCB.tobytes(), stg.depth_real.tobytes(), np.array(stg.lin_reg).tobytes())
-                    )
+        if len(stg.range_lin_interp) != 0:
+            cur.execute(
+                """
+                INSERT into Calibration(
+                  path_calibration_file, filename_calibration_file,
+                  range_lin_interp, M_profile_fine,
+                  ks, sv, X_exponent, alpha_s, zeta,
+                  FCB, depth_real, lin_reg
+                )
+                VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    stg.path_calibration_file, stg.filename_calibration_file,
+                    stg.range_lin_interp.tobytes(),
+                    stg.M_profile_fine.tobytes(),
+                    np.array(stg.ks).tobytes(), np.array(stg.sv).tobytes(),
+                    np.array(stg.X_exponent).tobytes(),
+                    np.array(stg.alpha_s).tobytes(),
+                    np.array(stg.zeta).tobytes(),
+                    stg.FCB.tobytes(), stg.depth_real.tobytes(),
+                    np.array(stg.lin_reg).tobytes()
+                )
+            )

        cnx.commit()

-        print(f"table Calibration : {time.time() - start_table_Calibration} sec")
-
-        # --------------------------------------------------------------------------------------------------------------
-                                                # ++++++++++++++++++++++++++++++
-                                                # --- Table Inversion ---
-                                                # ++++++++++++++++++++++++++++++
+        logger.info(f"table Calibration : {time.time() - start_table_Calibration} sec")

+    def create_table_inversion(self, cnx, cur):
        start_table_Inversion = time.time()

        cur.execute("DROP TABLE if exists Inversion")
@ -441,24 +560,23 @@ class CreateTableForSaveAs:
        cur.execute(self.create_Inversion)

        for i in range(len(stg.SSC_fine)):
-            cur.execute('''INSERT into Inversion(J_cross_section_freq1, J_cross_section_freq2, 
-                                                    VBI_cross_section, SSC_fine, SSC_sand) 
-                                VALUES(?, ?, ?, ?, ?)''',
-                        (stg.J_cross_section[i][0].tobytes(), stg.J_cross_section[i][1].tobytes(),
-                         stg.VBI_cross_section[i].tobytes(), stg.SSC_fine[i].tobytes(), stg.SSC_sand[i].tobytes())
-                    )
+            cur.execute(
+                """
+                INSERT into Inversion(
+                  J_cross_section_freq1, J_cross_section_freq2,
+                  VBI_cross_section, SSC_fine, SSC_sand
+                )
+                VALUES(?, ?, ?, ?, ?)
+                """,
+                (
+                    stg.J_cross_section[i][0].tobytes(),
+                    stg.J_cross_section[i][1].tobytes(),
+                    stg.VBI_cross_section[i].tobytes(),
+                    stg.SSC_fine[i].tobytes(),
+                    stg.SSC_sand[i].tobytes()
+                )
+            )

        cnx.commit()

-        print(f"table Inversion : {time.time() - start_table_Inversion} sec")
-
-        # --------------------------------------------------------------------------------------------------------------
-
-        # Close database cursor
-        cur.close()
-
-        # Close database connection
-        cnx.close()
-
-
-
+        logger.info(f"table Inversion : {time.time() - start_table_Inversion} sec")
--- a/Model/granulo_loader.py
+++ b/Model/granulo_loader.py
@ -1,7 +1,5 @@
-import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-from Model.GrainSizeTools import demodul_granulo, mix_gaussian_model

 class GranuloLoader:

@ -16,8 +14,7 @@ class GranuloLoader:
        self._y = self._data.iloc[:, 1].tolist()                        # distance from left bank (m)
        self._z = self._data.iloc[:, 2].tolist()                        # depth (m)

-        self._r_grain = 1e-6 * np.array(self._data.columns.values)[5:].astype(float) / 2
-        # self._r_grain = 1e-6 * np.array(self._data.columns.values)[5:].astype(float) / 2         # grain radius (m)
+        self._r_grain = 1e-6 * np.array(self._data.columns.values)[5:].astype(float) / 2        # grain radius (m)

        self._Ctot = self._data.iloc[:, 3].tolist()                # Total concentration (g/L)
        self._D50 = self._data.iloc[:, 4].tolist()               # median diameter (um)
@ -25,147 +22,3 @@ class GranuloLoader:

        self._frac_vol_cumul = np.cumsum(self._frac_vol, axis=1)    # Cumulated volume fraction (%)

-        # print(type(self._frac_vol_cumul), self._frac_vol_cumul.shape, self._frac_vol_cumul)
-
-        # # --- Load sand sediments data file ---
-        # self.path_sand = path_sand
-        # self._data_sand = pd.read_excel(self.path_sand, engine="odf", header=0)
-        #
-        # self._Ctot_sand = np.array(self._data_sand.iloc[:, 2])                # Total concentration (g/L)
-        # self._D50_sand = np.array(self._data_sand.iloc[:, 3])                 # median diameter (um)
-        # self._frac_vol_sand = np.array(self._data_sand.iloc[:, 4:])           # Volume fraction (%)
-        #
-        # self._frac_vol_sand_cumul = np.cumsum(self._frac_vol_sand, axis=1)    # Cumulated volume fraction (%)
-        #
-        # # --- Compute % of fine and % of sand sediment in total concentration ---
-        #
-        # self._Ctot_fine_per_cent = 100 * self._Ctot_fine / (self._Ctot_fine + self._Ctot_sand)
-        # self._Ctot_sand_per_cent = 100 * self._Ctot_sand / (self._Ctot_fine + self._Ctot_sand)
-
-        # ==============================================================================================================
-        # ==============================================================================================================
-
-#         N_sample = 0
-# #
-#         fig, ax = plt.subplots(1, 2)
-#         ax[0].plot(self._r_grain, self._frac_vol[N_sample, :], color="k", marker='.')
-#         ax[0].set_xscale('log')
-#         ax[0].set_xlabel('Radius ($\mu m$)')
-#         ax[0].set_ylabel('Class size volume fraction')
-#
-#         ax[1].plot([self._r_grain[i+1]-self._r_grain[i] for i in range(self._r_grain.shape[0]-1)], list(range(self._r_grain.shape[0]-1)), color="k", marker="x")
-#         ax[1].set_xlabel('Ecart inter-class')
-#         ax[1].set_ylabel('n° échantillon')
-#
-#         plt.show()
-#
-#         print(f"self._r_grain.shape : {self._r_grain.shape}")
-#         print(f"self._r_grain : {self._r_grain}")
-#         print(f"self._frac_vol_cumul.shape : {self._frac_vol_cumul[N_sample, :].shape}")
-#         print(f"self._frac_vol_cumul[N_sample, :] : {self._frac_vol_cumul[N_sample, :]}")
-#         print(np.where(self._frac_vol_cumul[N_sample, :] > 0))
-# #
-#         min_demodul = 1e-6
-#         max_demodul = 500e-6
-#         sample_demodul = demodul_granulo(self._r_grain[:],
-#                                               self._frac_vol_cumul[N_sample, :],
-#                                               min_demodul, max_demodul)
-#
-#         print(f"sample_demodul : {sample_demodul.demodul_data_list}")
-
-#         N_modes = 3
-#         sample_demodul.print_mode_data(N_modes)
-#         sample_demodul.plot_interpolation()
-#         sample_demodul.plot_modes(N_modes)
-#
-#         print(f"mu_list : {sample_demodul.demodul_data_list[3 - 1].mu_list}")
-#         print(f"sigma_list : {sample_demodul.demodul_data_list[3 - 1].sigma_list}")
-#         print(f"w_list : {sample_demodul.demodul_data_list[3 - 1].w_list}")
-#
-#         resampled_log_array = np.log(np.logspace(-10, -2, 3000))
-#         proba_vol_demodul = mix_gaussian_model(resampled_log_array,
-#                                                sample_demodul.demodul_data_list[2].mu_list,
-#                                                sample_demodul.demodul_data_list[2].sigma_list,
-#                                                sample_demodul.demodul_data_list[2].w_list)
-#
-#
-#
-#         proba_vol_demodul = proba_vol_demodul / np.sum(proba_vol_demodul)
-#         ss = np.sum(proba_vol_demodul / np.exp(resampled_log_array) ** 3)
-#         proba_num = proba_vol_demodul / np.exp(resampled_log_array) ** 3 / ss
-#
-#         print(f"proba_num : {proba_num}")
-#         freq = 5e6
-#
-#         a2f2pdf = 0
-#         a3pdf = 0
-#         for i in range(len(resampled_log_array)):
-#             a = np.exp(resampled_log_array)[i]
-#             a2f2pdf += a**2 * form_factor_function_MoateThorne2012(a, freq)**2 * proba_num[i]
-#             a3pdf += a**3 * proba_num[i]
-#
-#         print(f"a2f2pdf = {a2f2pdf}")
-#         print(f"a3pdf = {a3pdf}")
-#
-#         ks = (a2f2pdf / a3pdf)
-#
-#         print(f"ks = {ks}")
-#
-#
-# def form_factor_function_MoateThorne2012(a_s, freq, C=1500):
-#     """This function computes the form factor based on the equation of
-#     Moate and Thorne (2012)"""
-#     # computing the wave number
-#     k = 2 * np.pi * freq / C
-#     x = k * a_s
-#     f = (x ** 2 * (1 - 0.25 * np.exp(-((x - 1.5) / 0.35) ** 2)) * (
-#             1 + 0.6 * np.exp(-((x - 2.9) / 1.15) ** 2))) / (
-#                 42 + 28 * x ** 2)
-#     return f
-
-
-# if __name__ == "__main__":
-#     GranuloLoader("/home/bmoudjed/Documents/2 Data/Confluence_Rhône_Isere_2018/Granulo_data/fine_sample_file.ods")
-    # GranuloLoader("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/Granulo_data/"
-    #               "sand_sample_file.ods")
-    # GranuloLoader("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/"
-    #               "pt_acoused_cnr_7nov2023/echantil/fine_new_file_acoused_101RDS 3.ods")
-    # GranuloLoader("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/"
-    #               "pt_acoused_cnr_7nov2023/echantil/sand_new_file_acoused_101RDS 3.ods")
-
-
-
-
-
-
-
-
-
-
-# # form_factor = form_factor_function_MoateThorne2012(GranuloLoader.)
-#
-# def ks(a_s, rho_s, freq, pdf):
-#     # --- Calcul de la fonction de form ---
-#     form_factor = form_factor_function_MoateThorne2012(a_s, freq)
-#     print(f"form_factor shape = {len(form_factor)}")
-#     # print(f"form_factor = {form_factor}")
-#
-#     # --- Gaussian mixture ---
-#     # sample_demodul = demodul_granulo(a_s.astype(float), pdf, 0.17e-6, 200e-6)
-#     # sample_demodul.plot_interpolation()
-#
-#     # ss = np.sum(pdf / a_s ** 3)
-#     # proba_num = (pdf / a_s ** 3) / ss
-#
-#     # --- Compute k_s by dividing two integrals ---
-#     a2f2pdf = 0
-#     a3pdf = 0
-#     for i in range(len(pdf)):
-#         a2f2pdf += a_s[i] ** 2 * form_factor[i] * proba_num[i]
-#         a3pdf += a_s[i] ** 3 * proba_num[i]
-#
-#     ks = np.sqrt(a2f2pdf / (rho_s * a3pdf))
-#
-#     # ks = np.array([0.04452077, 0.11415143, 0.35533713, 2.47960051])
-#     # ks = ks0[ind]
-#     return ks
--- a/Model/read_table_for_open.py
+++ b/Model/read_table_for_open.py
@ -20,37 +20,50 @@

 # -*- coding: utf-8 -*-

-
+import os
 import sys
-import numpy as np
-from PyQt5.QtWidgets import QFileDialog, QApplication, QWidget, QTabWidget
 import sqlite3
-from os import path, chdir
+import logging
+import numpy as np
+
+from PyQt5.QtWidgets import QFileDialog, QApplication, QWidget, QTabWidget
+
 import settings as stg
 from settings import BS_raw_data, acoustic_data

 from View.acoustic_data_tab import AcousticDataTab

+
+logger = logging.getLogger("acoused")
+
 class ReadTableForOpen:

    def __init__(self):
+        self.opened = False

-        pass
+        self.open_file_dialog()

    def open_file_dialog(self):
+        name, _ = QFileDialog.getOpenFileName(
+            caption="Open Acoused file",
+            directory="",
+            filter="Acoused file (*.acd)",
+            options=QFileDialog.DontUseNativeDialog
+        )

-        name = QFileDialog.getOpenFileName(caption="Open Acoused file", directory="", filter="Acoused file (*.acd)",
-                                           options=QFileDialog.DontUseNativeDialog)
+        if name != "":
+            stg.dirname_open = os.path.dirname(name)
+            stg.filename_open = os.path.basename(name)

-        if name:
+            try:
+                os.chdir(stg.dirname_open)
+            except OSError as e:
+                logger.warning(f"chdir: {str(e)}")

-            stg.dirname_open = path.dirname(name[0])
-            stg.filename_open = path.basename(name[0])
-
-            chdir(stg.dirname_open)
            self.sql_file_to_open = open(stg.filename_open)
-
            self.read_table()
+            self.opened = True
+

    def read_table(self):

@ -76,7 +89,7 @@ class ReadTableForOpen:

        for k in range(len(stg.acoustic_data)):
            print("hello")
-            query = f'''SELECT acoustic_data, acoustic_file, ABS_name, path_BS_noise_data, filename_BS_noise_data, 
+            query = f'''SELECT acoustic_data, acoustic_file, ABS_name, path_BS_noise_data, filename_BS_noise_data,
            noise_method, noise_value, data_preprocessed FROM AcousticFile WHERE (acoustic_data = {k})'''
            data = cur.execute(query).fetchall()
            print("data acoustic file", data)
@ -101,8 +114,8 @@ class ReadTableForOpen:
        stg.hour = [0]*len(stg.acoustic_data)
        for i in range(len(stg.acoustic_data)):
            print("i = ", i)
-            query1 = f'''SELECT acoustic_data, Date, Hour, frequency, sound_attenuation, kt_read, kt_corrected, NbProfiles, 
-            NbProfilesPerSeconds, NbCells, CellSize, PulseLength, NbPingsPerSeconds, NbPingsAveragedPerProfile, 
+            query1 = f'''SELECT acoustic_data, Date, Hour, frequency, sound_attenuation, kt_read, kt_corrected, NbProfiles,
+            NbProfilesPerSeconds, NbCells, CellSize, PulseLength, NbPingsPerSeconds, NbPingsAveragedPerProfile,
            GainRx, GainTx FROM Measure WHERE (acoustic_data = {i})'''
            data1 = cur.execute(query1).fetchall()

@ -140,16 +153,16 @@ class ReadTableForOpen:
        print("len stg.acoustic_data ", len(stg.acoustic_data))
        for j in range(len(stg.acoustic_data)):
            print(f"j = {j}")
-            query2 = f'''SELECT acoustic_data, time, depth, BS_raw_data, 
+            query2 = f'''SELECT acoustic_data, time, depth, BS_raw_data,
                                time_reshape, depth_reshape, BS_raw_data_reshape,
-                                time_cross_section, depth_cross_section, 
-                                BS_cross_section, BS_stream_bed, 
+                                time_cross_section, depth_cross_section,
+                                BS_cross_section, BS_stream_bed,
                                depth_bottom, val_bottom, ind_bottom,
-                                time_noise, depth_noise, BS_noise_raw_data, 
+                                time_noise, depth_noise, BS_noise_raw_data,
                                SNR_raw_data, SNR_cross_section, SNR_stream_bed,
-                                BS_raw_data_pre_process_SNR, BS_raw_data_pre_process_average, 
-                                BS_cross_section_pre_process_SNR, BS_cross_section_pre_process_average, 
-                                BS_stream_bed_pre_process_SNR, BS_stream_bed_pre_process_average, BS_mean 
+                                BS_raw_data_pre_process_SNR, BS_raw_data_pre_process_average,
+                                BS_cross_section_pre_process_SNR, BS_cross_section_pre_process_average,
+                                BS_stream_bed_pre_process_SNR, BS_stream_bed_pre_process_average, BS_mean
                        FROM BSRawData WHERE (acoustic_data = {j})'''

            data2 = cur.execute(query2).fetchall()
@ -270,10 +283,10 @@ class ReadTableForOpen:
                                                # +++++++++++++++++++++++

        for s in range(len(stg.acoustic_data)):
-            query3 = f'''SELECT acoustic_data, temperature, 
+            query3 = f'''SELECT acoustic_data, temperature,
                        tmin_index, tmin_value, tmax_index, tmax_value,
                        rmin_index, rmin_value, rmax_index, rmax_value,
-                        freq_bottom_detection_index, freq_bottom_detection_value, 
+                        freq_bottom_detection_index, freq_bottom_detection_value,
                        SNR_filter_value, Nb_cells_to_average_BS_signal
                        FROM Settings WHERE (acoustic_data = {s})'''

@ -293,10 +306,10 @@ class ReadTableForOpen:
                                                # --- Table Sediment File ---
                                                # +++++++++++++++++++++++++++

-        query4 = f'''SELECT path_fine, filename_fine, radius_grain_fine, path_sand, filename_sand, radius_grain_sand, 
-                            time_column_label, distance_from_bank_column_label, depth_column_label, 
-                            Ctot_fine_column_label, D50_fine_column_label, 
-                            Ctot_sand_column_label, D50_sand_column_label 
+        query4 = f'''SELECT path_fine, filename_fine, radius_grain_fine, path_sand, filename_sand, radius_grain_sand,
+                            time_column_label, distance_from_bank_column_label, depth_column_label,
+                            Ctot_fine_column_label, D50_fine_column_label,
+                            Ctot_sand_column_label, D50_sand_column_label
                        from SedimentsFile'''

        data4 = cur.execute(query4).fetchall()
@ -321,10 +334,10 @@ class ReadTableForOpen:
                                                # --- Table Sediment Data ---
                                                # +++++++++++++++++++++++++++

-        query5 = f'''SELECT sample_fine_name, sample_fine_index, distance_from_bank_fine, depth_fine, time_fine, 
+        query5 = f'''SELECT sample_fine_name, sample_fine_index, distance_from_bank_fine, depth_fine, time_fine,
                            Ctot_fine, Ctot_fine_per_cent, D50_fine, frac_vol_fine, frac_vol_fine_cumul,
-                            sample_sand_name, sample_sand_index, distance_from_bank_sand, depth_sand, time_sand, 
-                            Ctot_sand, Ctot_sand_per_cent, D50_sand, frac_vol_sand, frac_vol_sand_cumul 
+                            sample_sand_name, sample_sand_index, distance_from_bank_sand, depth_sand, time_sand,
+                            Ctot_sand, Ctot_sand_per_cent, D50_sand, frac_vol_sand, frac_vol_sand_cumul
                     from SedimentsData'''

        data5 = cur.execute(query5).fetchall()
@ -428,4 +441,3 @@ class ReadTableForOpen:

            stg.BS_raw_data.append(np.reshape(stg.BS_raw_data_reshape[i],
                                              (len(stg.freq[i]), stg.depth[i].shape[1], stg.time[i].shape[1])))
-
--- a/Model/udt_extract/raw_extract.py
+++ b/Model/udt_extract/raw_extract.py
@ -43,7 +43,7 @@ def raw_extract(_raw_file):
        while 1:
            flag, size, data = fileraw.read_chunk()

-            # Pour raw UDT005 (ie. UB-Lab P, UB-SediFlow, UB-Lab 3C) on peut 
+            # Pour raw UDT005 (ie. UB-Lab P, UB-SediFlow, UB-Lab 3C) on peut
            # rencontrer 4 flags: const, settings json, configs (HW), profils
            if flag == CONST_TAG:
                try:
@ -55,7 +55,6 @@ def raw_extract(_raw_file):
                        .replace("True", "true")
                        .replace("False", "false")
                    )
-                print("const: %s" % const_dict)

                ubt_data = ubt_raw_data( const_dict )

@ -70,12 +69,9 @@ def raw_extract(_raw_file):
                        .replace("True", "true")
                        .replace("False", "false")
                    )
-                print("settings: %s" % settings_dict)

                ubt_data.set_config(settings_dict)

-                print("ubt_data.set_config(settings_dict) : ", ubt_data.set_config(settings_dict))
-
            if flag == CONFIG_TAG:
                # what is needed from here and which is not in param_us_dict is only blind_ca0 and blind_ca1
                # note: this is not useful on APF06, but could be used for double check
@ -100,7 +96,7 @@ def raw_extract(_raw_file):

    #print("%d profiles read" % profile_id)
    # last timestamp of udt file for time_end definition of run:
-    # based on the last profile processed 
+    # based on the last profile processed
    time_end = timestamp

    return (
@ -111,4 +107,4 @@ def raw_extract(_raw_file):
        ubt_data.data_us_dicts,
        ubt_data.data_dicts,
        settings_dict,
-    )
+    )
--- a/Model/update_table_for_save.py
+++ b/Model/update_table_for_save.py
@ -51,7 +51,7 @@ class UpdateTableForSave:
    def update_table(self):

        # Create a new database and open a database connection to allow sqlite3 to work with it.
-        cnx = sqlite3.connect(stg.filename_save_as + '.acd')
+        cnx = sqlite3.connect(stg.filename_save_as)

        # Create database cursor to execute SQL statements and fetch results from SQL queries.
        cur = cnx.cursor()
@ -67,12 +67,12 @@ class UpdateTableForSave:

        cur.execute("""CREATE TABLE AcousticFile(ID INTEGER PRIMARY KEY AUTOINCREMENT,
                                                 acoustic_data INTEGER,
-                                                 acoustic_file STRING, 
+                                                 acoustic_file STRING,
                                                 ABS_name STRING,
                                                 path_BS_noise_data STRING,
                                                 filename_BS_noise_data STRING,
                                                 noise_method FLOAT,
-                                                 noise_value FLOAT, 
+                                                 noise_value FLOAT,
                                                 data_preprocessed STRING
                                                 )"""
                    )
@ -83,8 +83,8 @@ class UpdateTableForSave:
            print('stg.ABS_name', stg.ABS_name)
            print("stg.path_BS_raw_data ", stg.path_BS_raw_data[i])

-            cur.execute(''' INSERT into AcousticFile(acoustic_data, acoustic_file, ABS_name, path_BS_noise_data, 
-                                                         filename_BS_noise_data, noise_method, noise_value, data_preprocessed) 
+            cur.execute(''' INSERT into AcousticFile(acoustic_data, acoustic_file, ABS_name, path_BS_noise_data,
+                                                         filename_BS_noise_data, noise_method, noise_value, data_preprocessed)
                                            VALUES(?, ?, ?, ?, ?, ?, ?, ?)''',
                        (stg.acoustic_data[i], stg.filename_BS_raw_data[i].split('.')[0], stg.ABS_name[i],
                         stg.path_BS_noise_data[i], stg.filename_BS_noise_data[i], stg.noise_method[i],
@ -104,42 +104,72 @@ class UpdateTableForSave:
        # Drop Table if exists
        cur.execute("DROP TABLE if exists Measure")

-        cur.execute("""CREATE TABLE Measure(ID INTEGER PRIMARY KEY AUTOINCREMENT,
-                                            acoustic_data INTEGER, 
-                                            Date STRING, 
-                                            Hour STRING,
-                                            frequency FLOAT,
-                                            sound_attenuation FLOAT, 
-                                            kt_read FLOAT,
-                                            kt_corrected FLOAT, 
-                                            NbProfiles FLOAT, 
-                                            NbProfilesPerSeconds FLOAT, 
-                                            NbCells FLOAT, 
-                                            CellSize FLOAT, 
-                                            PulseLength FLOAT, 
-                                            NbPingsPerSeconds FLOAT, 
-                                            NbPingsAveragedPerProfile FLOAT, 
-                                            GainRx FLOAT, 
-                                            GainTx FLOAT
-                                            )
-                                            """)
+        cur.execute(
+            """
+            CREATE TABLE Measure(
+              ID INTEGER PRIMARY KEY AUTOINCREMENT,
+              acoustic_data INTEGER,
+              Date STRING,
+              Hour STRING,
+              frequency FLOAT,
+              sound_attenuation FLOAT,
+              kt_read FLOAT,
+              kt_corrected FLOAT,
+              NbProfiles FLOAT,
+              NbProfilesPerSeconds FLOAT,
+              NbCells FLOAT,
+              CellSize FLOAT,
+              PulseLength FLOAT,
+              NbPingsPerSeconds FLOAT,
+              NbPingsAveragedPerProfile FLOAT,
+              GainRx FLOAT,
+              GainTx FLOAT
+            )"""
+        )

        # Fill the table Measure
        for i in stg.acoustic_data:
-
            for j in range(stg.freq[i].shape[0]):
-                cur.execute(''' INSERT into Measure(acoustic_data, Date, Hour, frequency, sound_attenuation, kt_read, kt_corrected, NbProfiles, 
-                                                                NbProfilesPerSeconds, NbCells, CellSize, PulseLength, 
-                                                                NbPingsPerSeconds, NbPingsAveragedPerProfile, GainRx, GainTx, 
-                                                                )
-                                            VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
-                            (stg.acoustic_data[i], stg.freq[i][j], stg.water_attenuation[i][j], stg.kt_read[j], stg.kt_corrected[j],
-                             stg.nb_profiles[i][j], stg.nb_profiles_per_sec[i][j], stg.nb_cells[i][j],
-                             stg.cell_size[i][j], stg.pulse_length[i][j], stg.nb_pings_per_sec[i][j],
-                             stg.nb_pings_averaged_per_profile[i][j], stg.gain_rx[i][j], stg.gain_tx[i][j],
-                             str(stg.date[i].year) + str('-') + str(stg.date[i].month) + str('-') + str(stg.date[i].day),
-                             str(stg.hour[i].hour) + str(':') + str(stg.hour[i].minute)
-                             ))
+                cur.execute(
+                    '''
+                    INSERT into Measure(
+                      acoustic_data,
+                      Date, Hour,
+                      frequency,
+                      sound_attenuation,
+                      kt_read, kt_corrected,
+                      NbProfiles, NbProfilesPerSeconds,
+                      NbCells, CellSize,
+                      PulseLength,
+                      NbPingsPerSeconds,
+                      NbPingsAveragedPerProfile,
+                      GainRx, GainTx
+                    ) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
+                    (
+                        stg.acoustic_data[i],
+                        (
+                            str(stg.date[i].year) + str('-') +
+                            str(stg.date[i].month) + str('-') +
+                            str(stg.date[i].day)
+                        ),
+                        (
+                            str(stg.hour[i].hour) + str(':') +
+                            str(stg.hour[i].minute)
+                        ),
+                        stg.freq[i][j],
+                        stg.water_attenuation[i][j],
+                        stg.kt_read[j],
+                        stg.kt_corrected[j],
+                        stg.nb_profiles[i][j],
+                        stg.nb_profiles_per_sec[i][j],
+                        stg.nb_cells[i][j],
+                        stg.cell_size[i][j],
+                        stg.pulse_length[i][j],
+                        stg.nb_pings_per_sec[i][j],
+                        stg.nb_pings_averaged_per_profile[i][j],
+                        stg.gain_rx[i][j], stg.gain_tx[i][j]
+                    )
+                )

        # Commit the transaction after executing INSERT.
        cnx.commit()
@ -150,7 +180,7 @@ class UpdateTableForSave:
                                                # +++++++++++++++++++++++++++
                                                # --- Table Acoustic Data ---
                                                # +++++++++++++++++++++++++++
-        
+
        start_table_BSRawData = time.time()

        cur.execute(''' DROP TABLE BSRawData ''')
@ -158,29 +188,29 @@ class UpdateTableForSave:
        cur.execute('''CREATE TABLE BSRawData(ID INTEGER PRIMARY KEY AUTOINCREMENT,
                                                acoustic_data INTEGER,
                                                time BLOB, depth BLOB, BS_raw_data BLOB,
-                                                time_reshape BLOB, depth_reshape BLOB, BS_raw_data_reshape BLOB, 
+                                                time_reshape BLOB, depth_reshape BLOB, BS_raw_data_reshape BLOB,
                                                time_cross_section BLOB, depth_cross_section BLOB, BS_cross_section BLOB, BS_stream_bed BLOB,
-                                                depth_bottom, val_bottom, ind_bottom, 
-                                                time_noise BLOB, depth_noise BLOB, BS_noise_raw_data BLOB, 
+                                                depth_bottom, val_bottom, ind_bottom,
+                                                time_noise BLOB, depth_noise BLOB, BS_noise_raw_data BLOB,
                                                SNR_raw_data BLOB, SNR_cross_section BLOB, SNR_stream_bed BLOB,
-                                                BS_raw_data_pre_process_SNR BLOB, BS_raw_data_pre_process_average BLOB, 
-                                                BS_cross_section_pre_process_SNR BLOB, BS_cross_section_pre_process_average BLOB, 
-                                                BS_stream_bed_pre_process_SNR BLOB, BS_stream_bed_pre_process_average BLOB, 
+                                                BS_raw_data_pre_process_SNR BLOB, BS_raw_data_pre_process_average BLOB,
+                                                BS_cross_section_pre_process_SNR BLOB, BS_cross_section_pre_process_average BLOB,
+                                                BS_stream_bed_pre_process_SNR BLOB, BS_stream_bed_pre_process_average BLOB,
                                                BS_mean BLOB
                                                )''')

        for i in stg.acoustic_data:

-            cur.execute(''' INSERT into BSRawData(acoustic_data, time, depth, BS_raw_data, 
+            cur.execute(''' INSERT into BSRawData(acoustic_data, time, depth, BS_raw_data,
                                                      time_reshape, depth_reshape, BS_raw_data_reshape,
-                                                      time_cross_section, depth_cross_section, 
-                                                      BS_cross_section, BS_stream_bed, 
-                                                      depth_bottom, val_bottom, ind_bottom, 
-                                                      time_noise, depth_noise, BS_noise_raw_data, 
+                                                      time_cross_section, depth_cross_section,
+                                                      BS_cross_section, BS_stream_bed,
+                                                      depth_bottom, val_bottom, ind_bottom,
+                                                      time_noise, depth_noise, BS_noise_raw_data,
                                                      SNR_raw_data, SNR_cross_section, SNR_stream_bed,
-                                                      BS_raw_data_pre_process_SNR, BS_raw_data_pre_process_average, 
-                                                      BS_cross_section_pre_process_SNR, BS_cross_section_pre_process_average, 
-                                                      BS_stream_bed_pre_process_SNR, BS_stream_bed_pre_process_average, 
+                                                      BS_raw_data_pre_process_SNR, BS_raw_data_pre_process_average,
+                                                      BS_cross_section_pre_process_SNR, BS_cross_section_pre_process_average,
+                                                      BS_stream_bed_pre_process_SNR, BS_stream_bed_pre_process_average,
                                                      BS_mean)
                                    VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
                            (stg.acoustic_data[i], stg.time[i].tobytes(), stg.depth[i].tobytes(), stg.BS_raw_data[i].tobytes(),
@ -219,8 +249,8 @@ class UpdateTableForSave:
                                             acoustic_data INTEGER,
                                             temperature FLOAT,
                                             tmin_index FLOAT, tmin_value FLOAT, tmax_index FLOAT, tmax_value FLOAT,
-                                             rmin_index FLOAT, rmin_value FLOAT, rmax_index FLOAT, rmax_value FLOAT, 
-                                             freq_bottom_detection_index FLOAT, freq_bottom_detection_value STRING, 
+                                             rmin_index FLOAT, rmin_value FLOAT, rmax_index FLOAT, rmax_value FLOAT,
+                                             freq_bottom_detection_index FLOAT, freq_bottom_detection_value STRING,
                                             SNR_filter_value FLOAT, Nb_cells_to_average_BS_signal FLOAT
                                             )'''
                    )
@ -229,8 +259,8 @@ class UpdateTableForSave:
            cur.execute('''INSERT into Settings(acoustic_data, temperature,
                        tmin_index, tmin_value, tmax_index, tmax_value,
                        rmin_index, rmin_value, rmax_index, rmax_value,
-                        freq_bottom_detection_index, freq_bottom_detection_value, 
-                        SNR_filter_value, Nb_cells_to_average_BS_signal) 
+                        freq_bottom_detection_index, freq_bottom_detection_value,
+                        SNR_filter_value, Nb_cells_to_average_BS_signal)
                        VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
                        (stg.acoustic_data[i], stg.temperature,
                         stg.tmin[i][0], stg.tmin[i][1], stg.tmax[i][0], stg.tmax[i][1],
@ -252,29 +282,29 @@ class UpdateTableForSave:

        cur.execute("DROP TABLE if exists SedimentsFile")

-        cur.execute("""CREATE TABLE SedimentsFile(ID INTEGER PRIMARY KEY AUTOINCREMENT,                  
-                                                          path_fine STRING, 
-                                                          filename_fine STRING, 
-                                                          radius_grain_fine BLOB, 
-                                                          path_sand STRING, 
+        cur.execute("""CREATE TABLE SedimentsFile(ID INTEGER PRIMARY KEY AUTOINCREMENT,
+                                                          path_fine STRING,
+                                                          filename_fine STRING,
+                                                          radius_grain_fine BLOB,
+                                                          path_sand STRING,
                                                          filename_sand STRING,
-                                                          radius_grain_sand BLOB, 
-                                                          time_column_label STRING, 
-                                                          distance_from_bank_column_label STRING, 
-                                                          depth_column_label STRING, 
-                                                          Ctot_fine_column_label STRING, 
+                                                          radius_grain_sand BLOB,
+                                                          time_column_label STRING,
+                                                          distance_from_bank_column_label STRING,
+                                                          depth_column_label STRING,
+                                                          Ctot_fine_column_label STRING,
                                                          D50_fine_column_label STRING,
-                                                          Ctot_sand_column_label STRING, 
+                                                          Ctot_sand_column_label STRING,
                                                          D50_sand_column_label STRING
                                                          )"""
                    )

-        cur.execute('''INSERT into SedimentsFile(path_fine, filename_fine, radius_grain_fine, 
-                                                     path_sand, filename_sand, radius_grain_sand, 
-                                                     time_column_label, distance_from_bank_column_label, 
-                                                     depth_column_label, Ctot_fine_column_label, 
-                                                     D50_fine_column_label, Ctot_sand_column_label, 
-                                                     D50_sand_column_label) 
+        cur.execute('''INSERT into SedimentsFile(path_fine, filename_fine, radius_grain_fine,
+                                                     path_sand, filename_sand, radius_grain_sand,
+                                                     time_column_label, distance_from_bank_column_label,
+                                                     depth_column_label, Ctot_fine_column_label,
+                                                     D50_fine_column_label, Ctot_sand_column_label,
+                                                     D50_sand_column_label)
                            VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
                    (stg.path_fine, stg.filename_fine, stg.radius_grain_fine.tobytes(),
                     stg.path_sand, stg.filename_sand, stg.radius_grain_sand.tobytes(),
@ -294,26 +324,26 @@ class UpdateTableForSave:

        cur.execute("DROP TABLE if exists SedimentsData")

-        cur.execute("""CREATE TABLE SedimentsData(ID INTEGER PRIMARY KEY AUTOINCREMENT,                  
-                                                  sample_fine_name STRING, 
+        cur.execute("""CREATE TABLE SedimentsData(ID INTEGER PRIMARY KEY AUTOINCREMENT,
+                                                  sample_fine_name STRING,
                                                  sample_fine_index INTEGER,
-                                                  distance_from_bank_fine FLOAT, 
-                                                  depth_fine FLOAT, 
-                                                  time_fine FLOAT, 
+                                                  distance_from_bank_fine FLOAT,
+                                                  depth_fine FLOAT,
+                                                  time_fine FLOAT,
                                                  Ctot_fine FLOAT,
-                                                  Ctot_fine_per_cent FLOAT, 
-                                                  D50_fine FLOAT, 
-                                                  frac_vol_fine BLOB, 
-                                                  frac_vol_fine_cumul BLOB, 
-                                                  sample_sand_name STRING, 
+                                                  Ctot_fine_per_cent FLOAT,
+                                                  D50_fine FLOAT,
+                                                  frac_vol_fine BLOB,
+                                                  frac_vol_fine_cumul BLOB,
+                                                  sample_sand_name STRING,
                                                  sample_sand_index INTEGER,
-                                                  distance_from_bank_sand FLOAT, 
-                                                  depth_sand FLOAT, 
-                                                  time_sand FLOAT, 
+                                                  distance_from_bank_sand FLOAT,
+                                                  depth_sand FLOAT,
+                                                  time_sand FLOAT,
                                                  Ctot_sand FLOAT,
-                                                  Ctot_sand_per_cent FLOAT, 
-                                                  D50_sand FLOAT, 
-                                                  frac_vol_sand BLOB, 
+                                                  Ctot_sand_per_cent FLOAT,
+                                                  D50_sand FLOAT,
+                                                  frac_vol_sand BLOB,
                                                  frac_vol_sand_cumul BLOB
                                                  )"""
                    )
@ -321,7 +351,7 @@ class UpdateTableForSave:
        for f in range(len(stg.sample_fine)):
            cur.execute('''INSERT into SedimentsData(sample_fine_name, sample_fine_index, distance_from_bank_fine,
                                            depth_fine, time_fine, Ctot_fine, Ctot_fine_per_cent, D50_fine, frac_vol_fine,
-                                            frac_vol_fine_cumul, 
+                                            frac_vol_fine_cumul,
                                            sample_sand_name, sample_sand_index, distance_from_bank_sand,
                                            depth_sand, time_sand, Ctot_sand, Ctot_sand_per_cent, D50_sand, frac_vol_sand,
                                            frac_vol_sand_cumul)
@ -349,26 +379,26 @@ class UpdateTableForSave:

        cur.execute("DROP TABLE if exists Calibration")

-        cur.execute("""CREATE TABLE Calibration(ID INTEGER PRIMARY KEY AUTOINCREMENT, 
-                                                path_calibration_file STRING, 
-                                                filename_calibration_file STRING,                 
-                                                range_lin_interp BLOB, 
-                                                M_profile_fine BLOB, 
+        cur.execute("""CREATE TABLE Calibration(ID INTEGER PRIMARY KEY AUTOINCREMENT,
+                                                path_calibration_file STRING,
+                                                filename_calibration_file STRING,
+                                                range_lin_interp BLOB,
+                                                M_profile_fine BLOB,
                                                ks BLOB,
-                                                sv BLOB, 
-                                                X_exponent BLOB, 
-                                                alpha_s BLOB, 
-                                                zeta BLOB, 
-                                                FCB BLOB, 
-                                                depth_real BLOB, 
+                                                sv BLOB,
+                                                X_exponent BLOB,
+                                                alpha_s BLOB,
+                                                zeta BLOB,
+                                                FCB BLOB,
+                                                depth_real BLOB,
                                                lin_reg BLOB
                                                )"""
                    )

-        cur.execute('''INSERT into Calibration(path_calibration_file, filename_calibration_file, 
+        cur.execute('''INSERT into Calibration(path_calibration_file, filename_calibration_file,
                                                            range_lin_interp, M_profile_fine,
                                                            ks, sv, X_exponent, alpha_s, zeta,
-                                                            FCB, depth_real, lin_reg) 
+                                                            FCB, depth_real, lin_reg)
                                    VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
                    (stg.path_calibration_file, stg.filename_calibration_file,
                     stg.range_lin_interp.tobytes(), stg.M_profile_fine.tobytes(),
@ -390,17 +420,17 @@ class UpdateTableForSave:

        cur.execute("DROP TABLE if exists Inversion")

-        cur.execute("""CREATE TABLE Inversion(ID INTEGER PRIMARY KEY AUTOINCREMENT, 
+        cur.execute("""CREATE TABLE Inversion(ID INTEGER PRIMARY KEY AUTOINCREMENT,
                                              J_cross_section_freq1 BLOB,
                                              J_cross_section_freq2 BLOB,
-                                              VBI_cross_section BLOB, 
-                                              SSC_fine BLOB, 
+                                              VBI_cross_section BLOB,
+                                              SSC_fine BLOB,
                                              SSC_sand BLOB
                                              )""")

        for i in range(len(stg.SSC_fine)):
-            cur.execute('''INSERT into Inversion(J_cross_section_freq1, J_cross_section_freq2, 
-                                                            VBI_cross_section, SSC_fine, SSC_sand) 
+            cur.execute('''INSERT into Inversion(J_cross_section_freq1, J_cross_section_freq2,
+                                                            VBI_cross_section, SSC_fine, SSC_sand)
                                        VALUES(?, ?, ?, ?, ?)''',
                        (stg.J_cross_section[i][0].tobytes(), stg.J_cross_section[i][1].tobytes(),
                         stg.VBI_cross_section[i].tobytes(), stg.SSC_fine[i].tobytes(), stg.SSC_sand[i].tobytes())
@ -417,6 +447,3 @@ class UpdateTableForSave:

        # Close database connection
        cnx.close()
-
-
-
--- a/README.md
+++ b/README.md
@ -1,92 +1,134 @@
 # AcouSed

+AcouSed for **Acou**stic Backscattering for Concentration of Suspended **Sed**iments in Rivers is a software developped by INRAE, in collaboation with CNR.

+<p>
+  <img src="logos/AcouSed.png" align="center" width=20% height=20% >
+</p>

-## Getting started
-
-To make it easy for you to get started with GitLab, here's a list of recommended next steps.
-
-Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
-
-## Add your files
-
- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
-
-```
-cd existing_repo
-git remote add origin https://gitlab.irstea.fr/brahim/acoused.git
-git branch -M main
-git push -uf origin main
-```
-
-## Integrate with your tools
-
- [ ] [Set up project integrations](https://gitlab.irstea.fr/brahim/acoused/-/settings/integrations)
-
-## Collaborate with your team
-
- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
- [ ] [Automatically merge when pipeline succeeds](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
-
-## Test and Deploy
-
-Use the built-in continuous integration in GitLab.
-
- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing(SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
-
-***
-
-# Editing this README
-
-When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thank you to [makeareadme.com](https://www.makeareadme.com/) for this template.
-
-## Suggestions for a good README
-Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
-
-## Name
-Choose a self-explaining name for your project.
-
-## Description
-Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
-
-## Badges
-On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
-
-## Visuals
-Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
+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
+- Calibration : calibration parameter are computed
+- Inversion : inversion method is calculated to provide fine and sand sediments fields

 ## Installation
-Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.

-## Usage
-Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
+### Standalone software

-## Support
-Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
+AcouSed can be launched with python installation. An executable is available on [River Hydraulics](https://riverhydraulics.riverly.inrae.fr/outils/logiciels-pour-la-mesure/acoused) teams website. 
+The user needs to download the folder "acoused-packaging" including :
+- icons and logos folder
+- _internal folder (python packages)
+- executable file
+- calibration constant file
+- documentation

-## Roadmap
-If you have ideas for releases in the future, it is a good idea to list them in the README.
+Acoused.exe file must be launched from this folder. 
+Test data can be dowloaded from the [INRAE nextcloud](https://nextcloud.inrae.fr/s/3zZdieztrx7nwYa)

-## Contributing
-State if you are open to contributions and what your requirements are for accepting them.
+### Python environment

-For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.
+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.

-You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
+#### Windows
+
+You can use Pypi to get correct software environment and run the
+program.
+
+```shell
+python -m venv env
+env\Scripts\activate.bat
+python -m pip install -U -r ..\virtualenv\requirements.txt
+python main.py
+```
+
+#### Linux
+
+You can use Pypi to get correct software environment and run the
+program.
+
+```shell
+  python3 -m venv venv
+  source ./venv/bin/activate
+  python3 -m pip install -r requirement.txt
+  python3 main.py
+```
+
+#### Linux with Guix
+
+To run Acoused within a [GNU Guix](https://guix.gnu.org/) software
+environment, you need Guix installed on your computer and run the
+script `guix.sh` to run the program.
+
+```shell
+  ./guix.sh
+
+  # If you need sqlitebrowser, use this command
+  guix shell sqlitebrowser -- ./guix.sh
+```
+
+## Support files & References
+
+- [ ] [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)
+
+
+- [ ] [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)
+
+## Authors & Contacts
+
+- Brahim MOUDJED  2022-2025 ([INRAE](https://www.inrae.fr/))
+- Pierre-Antoine ROUBY  2025 ([TECC](https://parouby.fr))
+
+If you have any questions or suggestions, please contact us to celine.berni@inrae.fr and/or jerome.lecoz@inrae.fr.
+
+## Acknowledgment
+
+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). 
+
+<p>
+  <img src="logos/OSR.png" align="center" width=10% height=10% >
+</p>
+
+## Industrial partners
+
+[CNR](https://www.cnr.tm.fr/)
+
+<p>
+  <img src="logos/CNR.png" align="center" width=10% height=10% >
+</p>
+
+[UBERTONE](https://ubertone.com/)
+
+<p>
+  <img src="logos/Ubertone.jpeg" align="center" width=10% height=10% >
+</p>
+
+
+[EDF](https://www.edf.fr/hydraulique-isere-drome)
+<p>
+  <img src="logos/EDF.png" align="center" width=10% height=10% >
+</p>

-## Authors and acknowledgment
-Show your appreciation to those who have contributed to the project.

 ## License
-For open source projects, say how it is licensed.

-## Project status
-If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
+AcouSed
+Copyright (C) 2024-2025 - INRAE
+
+<p>
+  <img src="logos/BlocMarque-INRAE-Inter.jpg" align="center" width=10% height=10% >
+</p>
+
+This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
+
+This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License along with this program.  If not, see <https://www.gnu.org/licenses/>.
--- a/View/about_window.py
+++ b/View/about_window.py
@ -31,13 +31,13 @@ class AboutWindow(QDialog):

        super().__init__()

-        self.logo_path = "./Logo"
-        self.logo_AcouSed = QPixmap(self.logo_path + "/" + "Logo_AcouSed_AboutAcouSedWindow.png")
+        self.logo_path = "./logos"
+        self.logo_AcouSed = QPixmap(self.logo_path + "/" + "AcouSed.png")
        self.logo_AcouSed.scaled(16, 16, Qt.KeepAspectRatio, Qt.SmoothTransformation)

        self.logo_INRAE = QPixmap(self.logo_path + "/" + "BlocMarque-INRAE-Inter.jpg")

-        self.setGeometry(400, 200, 300, 200)
+        self.setGeometry(400, 200, 350, 200)

        self.setWindowTitle("About AcouSed")

@ -51,7 +51,7 @@ class AboutWindow(QDialog):

        self.label_logo_AcouSed = QLabel()
        self.label_logo_AcouSed.setPixmap(self.logo_AcouSed.scaledToHeight(128, Qt.SmoothTransformation))
-        self.gridLayout.addWidget(self.label_logo_AcouSed, 0, 0, 3, 1, Qt.AlignCenter)
+        self.gridLayout.addWidget(self.label_logo_AcouSed, 0, 0, 5, 1, Qt.AlignCenter)

        self.label_acoused = QLabel()
        self.label_acoused.setText("Acoused 2.0")
@ -70,7 +70,13 @@ class AboutWindow(QDialog):
        self.label_contact = QLabel()
        self.label_contact.setText("Contact : celine.berni@inrae.fr \n"
                                   "                   jerome.lecoz@inrae.fr")
-        self.gridLayout.addWidget(self.label_contact, 3, 1, 1, 1, Qt.AlignLeft)
+        self.gridLayout.addWidget(self.label_contact, 3, 1, 1, 1, Qt.AlignCenter)
+
+        self.label_link = QLabel()
+        self.label_link.setText("< a href = https://forgemia.inra.fr/theophile.terraz/acoused > "
+                                "https://forgemia.inra.fr/theophile.terraz/acoused </a>")
+        self.label_link.setOpenExternalLinks(True)
+        self.gridLayout.addWidget(self.label_link, 4, 1, 1, 1, Qt.AlignCenter)

        # ----------------------------------------------------------

@ -179,7 +185,7 @@ class Support(QDialog):

        super().__init__()

-        self.logo_path = "./Logo"
+        self.logo_path = "./logos"

        self.logo_OSR = QPixmap(self.logo_path + '/' + "OSR.png")
        self.logo_CNR = QPixmap(self.logo_path + '/' + "CNR.png")
--- a/View/acoustic_data_tab.py
+++ b/View/acoustic_data_tab.py
--- a/View/acoustic_inversion_tab.py
+++ b/View/acoustic_inversion_tab.py
--- a/View/mainwindow.py
+++ b/View/mainwindow.py
@ -39,12 +39,11 @@ from View.about_window import AboutWindow
 import settings as stg

 import numpy as np
-from subprocess import check_call, run
+import pandas as pd
+from subprocess import Popen

 import time

-from View.acoustic_data_tab import AcousticDataTab
-

 class Ui_MainWindow(object):
    def setupUi(self, MainWindow):
@ -55,10 +54,13 @@ class Ui_MainWindow(object):
        self.mainwindow.setDocumentMode(False)
        self.mainwindow.setDockNestingEnabled(False)
        self.mainwindow.setUnifiedTitleAndToolBarOnMac(False)
+
        self.centralwidget = QtWidgets.QWidget(self.mainwindow)
        self.centralwidget.setObjectName("centralwidget")
+
        self.verticalLayout = QtWidgets.QVBoxLayout(self.centralwidget)
        self.verticalLayout.setObjectName("verticalLayout")
+
        self.tabWidget = QtWidgets.QTabWidget(self.centralwidget)
        self.tabWidget.setAutoFillBackground(False)
        self.tabWidget.setLocale(QtCore.QLocale(QtCore.QLocale.French, QtCore.QLocale.France))
@ -66,115 +68,127 @@ class Ui_MainWindow(object):
        self.tabWidget.setTabsClosable(False)
        self.tabWidget.setTabBarAutoHide(False)
        self.tabWidget.setObjectName("tabWidget")
+
        self.tab1 = QtWidgets.QWidget()
        self.tab1.setContextMenuPolicy(QtCore.Qt.ActionsContextMenu)
        self.tab1.setObjectName("tab1")
        self.tabWidget.addTab(self.tab1, "")
+
        self.tab2 = QtWidgets.QWidget()
        self.tab2.setObjectName("tab2")
        self.tabWidget.addTab(self.tab2, "")
+
        self.tab3 = QtWidgets.QWidget()
        self.tab3.setObjectName("tab3")
        self.tabWidget.addTab(self.tab3, "")
+
        self.tab4 = QtWidgets.QWidget()
        self.tab4.setObjectName("tab4")
        self.tabWidget.addTab(self.tab4, "")
+
        self.tab5 = QtWidgets.QWidget()
        self.tab5.setObjectName("tab5")
        self.tabWidget.addTab(self.tab5, "")
+
        self.tab6 = QtWidgets.QWidget()
        self.tab6.setObjectName("tab6")
        self.tabWidget.addTab(self.tab6, "")
-        # self.tab7 = QtWidgets.QWidget()
-        # self.tab7.setObjectName("tab7")
-        # self.tabWidget.addTab(self.tab7, "")
+
        self.verticalLayout.addWidget(self.tabWidget)
        self.mainwindow.setCentralWidget(self.centralwidget)
+
        self.menubar = QtWidgets.QMenuBar(self.mainwindow)
        self.menubar.setGeometry(QtCore.QRect(0, 0, 898, 22))
        self.menubar.setObjectName("menubar")
+
        self.menuFile = QtWidgets.QMenu(self.menubar)
        self.menuFile.setLocale(QtCore.QLocale(QtCore.QLocale.French, QtCore.QLocale.France))
        self.menuFile.setObjectName("menuFile")
+
        self.menuSettings = QtWidgets.QMenu(self.menuFile)
        self.menuSettings.setObjectName("menuSettings")
+
        self.menuLanguage = QtWidgets.QMenu(self.menuSettings)
        self.menuLanguage.setObjectName("menuLanguage")
+
        self.menuExport = QtWidgets.QMenu(self.menuFile)
        self.menuExport.setObjectName("menuExport")
+
        self.menuTools = QtWidgets.QMenu(self.menubar)
        self.menuTools.setLocale(QtCore.QLocale(QtCore.QLocale.French, QtCore.QLocale.France))
        self.menuTools.setObjectName("menuTools")
+
        self.menuHelp = QtWidgets.QMenu(self.menubar)
        self.menuHelp.setObjectName("menuHelp")
+
        self.mainwindow.setMenuBar(self.menubar)
+
        self.statusbar = QtWidgets.QStatusBar(self.mainwindow)
        self.statusbar.setObjectName("statusbar")
        self.mainwindow.setStatusBar(self.statusbar)
+
        self.toolBar = QtWidgets.QToolBar(self.mainwindow)
        self.toolBar.setObjectName("toolBar")
        self.mainwindow.addToolBar(QtCore.Qt.TopToolBarArea, self.toolBar)
-        # self.actionNew = QtWidgets.QAction(self.mainwindow)
-        # icon = QtGui.QIcon()
-        # icon.addPixmap(QtGui.QPixmap("icons/new.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
-        # self.actionNew.setIcon(icon)
-        # self.actionNew.setObjectName("actionNew")
+
        self.actionOpen = QtWidgets.QAction(self.mainwindow)
        icon1 = QtGui.QIcon()
        icon1.addPixmap(QtGui.QPixmap("icons/icon_folder.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
        self.actionOpen.setIcon(icon1)
        self.actionOpen.setObjectName("actionOpen")
+
        self.actionSave = QtWidgets.QAction(self.mainwindow)
        icon2 = QtGui.QIcon()
        icon2.addPixmap(QtGui.QPixmap("icons/save.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
        self.actionSave.setIcon(icon2)
        self.actionSave.setObjectName("actionSave")
-        # self.actionCopy = QtWidgets.QAction(self.mainwindow)
-        # icon3 = QtGui.QIcon()
-        # icon3.addPixmap(QtGui.QPixmap("icons/copy.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
-        # self.actionCopy.setIcon(icon3)
-        # self.actionCopy.setObjectName("actionCopy")
-        # self.actionCut = QtWidgets.QAction(self.mainwindow)
-        # icon4 = QtGui.QIcon()
-        # icon4.addPixmap(QtGui.QPixmap("icons/cut.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
-        # self.actionCut.setIcon(icon4)
-        # self.actionCut.setObjectName("actionCut")
-        # self.actionPaste = QtWidgets.QAction(self.mainwindow)
-        # icon5 = QtGui.QIcon()
-        # icon5.addPixmap(QtGui.QPixmap("icons/paste.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
-        # self.actionPaste.setIcon(icon5)
-        # self.actionPaste.setObjectName("actionPaste")
+
        self.actionEnglish = QtWidgets.QAction(self.mainwindow)
        icon6 = QtGui.QIcon()
        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")
+
        self.actionTable_of_Backscatter_values = QtWidgets.QAction(self.mainwindow)
        self.actionTable_of_Backscatter_values.setObjectName("actionTable_of_Backscatter_values")
+
        self.actionSave_As = QtWidgets.QAction(self.mainwindow)
        self.actionSave_As.setObjectName("actionSave_As")
+
        self.actionAbout = QtWidgets.QAction(self.mainwindow)
        self.actionAbout.setObjectName("actionAbout")
+
        self.actionUserManual = QtWidgets.QAction(self.mainwindow)
        self.actionUserManual.setText("User Manual")
+
        self.action_AcousticInversionTheory = QtWidgets.QAction(self.mainwindow)
        self.action_AcousticInversionTheory.setText("Acoustic inversion theory")
+
        self.action_AQUAscatUserManual = QtWidgets.QAction(self.mainwindow)
        self.action_AQUAscatUserManual.setText("Tutorial AQUAscat software")
+
        self.actionDB_Browser_for_SQLite = QtWidgets.QAction(self.mainwindow)
        self.actionDB_Browser_for_SQLite.setObjectName("actionDB_Browser_for_SQLite")
+
        self.menuLanguage.addAction(self.actionEnglish)
        self.menuLanguage.addAction(self.actionFrench)
+
        self.menuSettings.addAction(self.menuLanguage.menuAction())
        self.menuSettings.addAction(self.action_ABSCalibrationConstant)
+
        self.menuExport.addAction(self.actionTable_of_Backscatter_values)
+
        self.menuFile.addAction(self.actionOpen)
        self.menuFile.addAction(self.actionSave)
        self.menuFile.addAction(self.actionSave_As)
@ -182,21 +196,21 @@ class Ui_MainWindow(object):
        self.menuFile.addAction(self.menuSettings.menuAction())
        self.menuFile.addSeparator()
        self.menuFile.addAction(self.menuExport.menuAction())
+
        self.menuTools.addAction(self.actionDB_Browser_for_SQLite)
+
        self.menuHelp.addAction(self.actionAbout)
        self.menuHelp.addAction(self.actionUserManual)
        self.menuHelp.addAction(self.action_AcousticInversionTheory)
        self.menuHelp.addAction(self.action_AQUAscatUserManual)
+
        self.menubar.addAction(self.menuFile.menuAction())
        self.menubar.addAction(self.menuTools.menuAction())
        self.menubar.addAction(self.menuHelp.menuAction())
-        # self.toolBar.addAction(self.actionNew)
+
        self.toolBar.addAction(self.actionOpen)
        self.toolBar.addAction(self.actionSave)
        self.toolBar.addSeparator()
-        # self.toolBar.addAction(self.actionCopy)
-        # self.toolBar.addAction(self.actionCut)
-        # self.toolBar.addAction(self.actionPaste)
        self.toolBar.addSeparator()
        self.toolBar.addAction(self.actionEnglish)
        self.toolBar.addAction(self.actionFrench)
@ -251,61 +265,82 @@ class Ui_MainWindow(object):

    def save_as(self):
        CreateTableForSaveAs()
-        self.mainwindow.setWindowTitle("AcouSed - " + stg.filename_save_as + ".acd")
+        self.mainwindow.setWindowTitle(
+            "AcouSed - " +
+            stg.filename_save_as
+        )

    def save(self):
-        UpdateTableForSave()
+        if stg.dirname_save_as:
+            UpdateTableForSave()
+        else:
+            self.save_as()

    def open(self):
-        pass
-        # ReadTableForOpen()
-
-        # acoustic_data_tab = AcousticDataTab()
-        #
-        # acoustic_data_tab.fileListWidget.addItems(stg.acoustic_data)
+        reader = ReadTableForOpen()
+        if reader.opened:
+            self.mainwindow.open_study_update_tabs()

    def load_calibration_constant_values(self):
        cc_kt = CalibrationConstantKt()
        cc_kt.exec()

    def db_browser_for_sqlite(self):
-        check_call("/usr/bin/sqlitebrowser")
+        try:
+            Popen("sqlitebrowser")
+        except OSError as e:
+            msg_box = QtWidgets.QMessageBox()
+            msg_box.setWindowTitle("DB Browser for SQLite Error")
+            msg_box.setIcon(QtWidgets.QMessageBox.Critical)
+            msg_box.setText(f"DB Browser for SQLite Error:\n  {str(e)}")
+            msg_box.setStandardButtons(QtWidgets.QMessageBox.Ok)
+            msg_box.exec()

    def about_window(self):
        print("about")
        aw = AboutWindow()
        aw.exec()

+    def current_file_path(self, filename):
+        return os.path.abspath(
+            os.path.join(
+                os.path.dirname(__file__),
+                "..", filename
+            )
+        )
+
+    def open_doc_file(self, filename):
+        QtGui.QDesktopServices.openUrl(
+            QtCore.QUrl(
+                f"file://{self.current_file_path(filename)}"
+            )
+        )
+
    def user_manual(self):
-        open('AcouSed_UserManual.pdf')
-        run(["open", 'AcouSed_UserManual.pdf'])
+        self.open_doc_file('AcouSed_UserManual.pdf')

    def inversion_acoustic_theory(self):
-        open('Acoustic_Inversion_theory.pdf')
-        run(["open", 'Acoustic_Inversion_theory.pdf'])
+        self.open_doc_file('Acoustic_Inversion_theory.pdf')

    def tutorial_AQUAscat_software(self):
-        open('Tutorial_AQUAscat_software.pdf')
-        run(["open", 'Tutorial_AQUAscat_software.pdf'])
+        self.open_doc_file('Tutorial_AQUAscat_software.pdf')

    def export_table_of_acoustic_BS_values_to_excel_or_libreOfficeCalc_file(self):
-
        if len(stg.BS_raw_data_reshape) != 0:
-
-            # --- Open file dialog to select the directory ---
-
-            name = QtWidgets.QFileDialog.getExistingDirectory(caption="Select Directory - Acoustic BS raw data Table")
+            name = QtWidgets.QFileDialog.getExistingDirectory(
+                caption="Select Directory - Acoustic BS raw data Table"
+            )
            print("name table to save ", name)

-            # --- Save the raw acoustic backscatter data from a Dataframe to csv file ---
+            # --- Save the raw acoustic backscatter data from a
+            # --- Dataframe to csv file ---

            t0 = time.time()
-            print("len(stg.BS_raw_data_reshape) ", len(stg.BS_raw_data_reshape))
+            print("len(stg.BS_raw_data_reshape) ",
+                  len(stg.BS_raw_data_reshape))

            if name:
-
                for i in range(len(stg.BS_raw_data_reshape)):
-
                    header_list = []
                    header_list.clear()
                    table_data = np.array([[]])
@ -315,34 +350,42 @@ class Ui_MainWindow(object):
                        header_list.append("BS - " + freq_value)

                        if freq_ind == 0:
-                            table_data = np.vstack((np.vstack((stg.time_reshape[i][:, freq_ind],
-                                                               stg.depth_reshape[i][:, freq_ind])),
-                                                               stg.BS_raw_data_reshape[i][:, freq_ind]))
+                            table_data = np.vstack(
+                                (
+                                    np.vstack(
+                                        (stg.time_reshape[i][:, freq_ind],
+                                         stg.depth_reshape[i][:, freq_ind])),
+                                    stg.BS_raw_data_reshape[i][:, freq_ind]
+                                )
+                            )

                        else:
-                            table_data = np.vstack((table_data,
-                                                    np.vstack((np.vstack(
-                                                        (stg.time_reshape[i][:, freq_ind],
-                                                         stg.depth_reshape[i][:, freq_ind])),
-                                                         stg.BS_raw_data_reshape[i][:, freq_ind]))
-                                                    ))
+                            table_data = np.vstack(
+                                (
+                                    table_data,
+                                    np.vstack((
+                                        np.vstack((
+                                            stg.time_reshape[i][:, freq_ind],
+                                            stg.depth_reshape[i][:, freq_ind]
+                                        )),
+                                        stg.BS_raw_data_reshape[i][:, freq_ind]
+                                    ))
+                                )
+                            )

-                    exec("DataFrame_acoustic_" + str(i) + "= pd.DataFrame(None)")
-                    exec("DataFrame_acoustic_" + str(i) + "= pd.DataFrame(data=table_data.transpose(), columns=header_list)")
+                    DataFrame_acoustic = pd.DataFrame(None)
+                    DataFrame_acoustic = pd.DataFrame(
+                        data=table_data.transpose(), columns=header_list
+                    )

-                # exec("DataFrame_acoustic_" + str(i) + ".to_csv(" +
-                #         "excel_writer=" +
-                #         '/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/BS_raw_data_table.xlsx' + "," +
-                #         "sheet_name=stg.filename_BS_raw_data[i]," +
-                #         "header=DataFrame_acoustic.columns," +
-                #         "engine=" + "xlsxwriter" + ")")
-
-                    exec("DataFrame_acoustic_" + str(i) + ".to_csv(" +
-                         "path_or_buf=" +
-                         "'" + name + "/" + "Table_" +
-                         str(stg.filename_BS_raw_data[i][:-4]) + ".csv'" + ", " +
-                         "sep=" + "',' " + ", " +
-                         "header=DataFrame_acoustic_" + str(i) + ".columns" + ")")
+                    DataFrame_acoustic.to_csv(
+                        path_or_buf=os.path.join(
+                            name,
+                            f"Table_{str(stg.filename_BS_raw_data[i][:-4])}.csv"
+                        ),
+                        header=DataFrame_acoustic.columns,
+                        sep=',',
+                    )

            t1 = time.time() - t0
            print("time duration export BS ", t1)
@ -357,7 +400,6 @@ class Ui_MainWindow(object):
        self.tabWidget.setTabText(self.tabWidget.indexOf(self.tab4), _translate("MainWindow", "Sediment Calibration"))
        self.tabWidget.setTabText(self.tabWidget.indexOf(self.tab5), _translate("MainWindow", "Acoustic inversion"))
        self.tabWidget.setTabText(self.tabWidget.indexOf(self.tab6), _translate("MainWindow", "Note"))
-        # self.tabWidget.setTabText(self.tabWidget.indexOf(self.tab7), _translate("MainWindow", "User manual"))
        self.menuFile.setTitle(_translate("MainWindow", "File"))
        self.menuSettings.setTitle(_translate("MainWindow", "Settings"))
        self.menuLanguage.setTitle(_translate("MainWindow", "Language"))
@ -365,12 +407,8 @@ class Ui_MainWindow(object):
        self.menuTools.setTitle(_translate("MainWindow", "Tools"))
        self.menuHelp.setTitle(_translate("MainWindow", "Help"))
        self.toolBar.setWindowTitle(_translate("MainWindow", "toolBar"))
-        # self.actionNew.setText(_translate("MainWindow", "New"))
        self.actionOpen.setText(_translate("MainWindow", "Open ..."))
        self.actionSave.setText(_translate("MainWindow", "Save"))
-        # self.actionCopy.setText(_translate("MainWindow", "Copy"))
-        # self.actionCut.setText(_translate("MainWindow", "Cut"))
-        # self.actionPaste.setText(_translate("MainWindow", "Paste"))
        self.actionEnglish.setText(_translate("MainWindow", "English"))
        self.actionFrench.setText(_translate("MainWindow", "French"))
        self.actionTable_of_Backscatter_values.setText(_translate("MainWindow", "Table of Backscatter values"))
--- a/View/note_tab.py
+++ b/View/note_tab.py
@ -1,7 +1,8 @@
-import sys
-
-from PyQt5.QtWidgets import QApplication, QWidget, QVBoxLayout, QHBoxLayout, QTextEdit, QPushButton, QSpacerItem, \
-                            QSpinBox, QSizePolicy, QFontComboBox, QColorDialog
+from PyQt5.QtWidgets import (
+    QApplication, QWidget, QVBoxLayout, QHBoxLayout,
+    QTextEdit, QPushButton, QSpacerItem, QSpinBox,
+    QSizePolicy, QFontComboBox, QColorDialog
+)
 from PyQt5.QtGui import QPixmap, QIcon, QFont
 from PyQt5.QtCore import Qt

@ -189,27 +190,21 @@ class NoteTab(QWidget):
        self.textEdit.setAlignment(Qt.AlignJustify)

    def print_settings(self):
+        self.textEdit.setText(
+            "Acoustic data: \n\n"
+            f"   ABS raw data file: {stg.path_BS_raw_data}/{stg.filename_BS_raw_data} \n"
+            f"   ABS noise data file: {stg.path_BS_noise_data}/{stg.filename_BS_noise_data} \n"
+            "\n\n"
+            "------------------------------------------------------------------------- \n\n\n"

-        self.textEdit.setText("Acoustic data: \n\n"
-                              f"   ABS raw data file: {stg.path_BS_raw_data}/{stg.filename_BS_raw_data} \n"
-                              f"   ABS noise data file: {stg.path_BS_noise_data}/{stg.filename_BS_noise_data} \n"
-                              "\n\n"
-                              "------------------------------------------------------------------------- \n\n\n"
+            "Particle size data: \n"
+            f"   Fine sediments data file: {stg.path_fine}/{stg.filename_fine} \n"
+            f"   Sand sediments data file: {stg.path_sand}/{stg.filename_sand} \n"
+            "\n\n"
+            "------------------------------------------------------------------------- \n\n\n"
+        )

-                              "Particle size data: \n"
-                              f"   Fine sediments data file: {stg.fine_sediment_path}/{stg.fine_sediment_filename} \n"
-                              f"   Sand sediments data file: {stg.sand_sediment_path}/{stg.sand_sediment_filename} \n"
-                              "\n\n"
-                              "------------------------------------------------------------------------- \n\n\n")
-                              
-                              # "Acoustic Inversion parameters: \n"
-                              # f"   frequencies to compute VBI: {stg.freq_text[int(stg.frequencies_to_compute_VBI[0, 0])]}, "
-                              # f"{stg.freq_text[int(stg.frequencies_to_compute_VBI[1, 0])]} \n"
-                              # f"   frequency to compute SSC: {stg.freq_text[int(stg.frequency_to_compute_SSC[0])]}")
-
-
-# if __name__ == "__main__":
-#     app = QApplication(sys.argv)
-#     window = NoteTab()
-#     window.show()
-#     sys.exit(app.exec_())
+        # "Acoustic Inversion parameters: \n"
+        # f"   frequencies to compute VBI: {stg.freq_text[int(stg.frequencies_to_compute_VBI[0, 0])]}, "
+        # f"{stg.freq_text[int(stg.frequencies_to_compute_VBI[1, 0])]} \n"
+        # f"   frequency to compute SSC: {stg.freq_text[int(stg.frequency_to_compute_SSC[0])]}")
--- a/View/plot_noise_window.py
+++ b/View/plot_noise_window.py
@ -1,9 +1,7 @@
-import sys

 from PyQt5.QtGui import QIcon, QPixmap
 from PyQt5.QtWidgets import (QWidget, QLabel, QHBoxLayout, QVBoxLayout, QApplication, QMainWindow, QGridLayout,
-                             QDialog, QDialogButtonBox, QPushButton, QTextEdit, QFrame, QTabWidget, QScrollArea)
-from PyQt5.QtCore import Qt
+                             QDialog, QFrame, QTabWidget, QScrollArea)

 import numpy as np

@ -12,13 +10,8 @@ from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
 from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolBar
 from matplotlib.colors import LogNorm, BoundaryNorm

-import datetime
-
 import settings as stg

-from Translation.constant_string import HORIZONTAL
-from settings import depth_cross_section
-

 class PlotNoiseWindow(QDialog):

@ -56,12 +49,10 @@ class PlotNoiseWindow(QDialog):
                    val_min = np.nanmin(stg.BS_noise_raw_data[i][freq_ind, :, :])
                    val_max = np.nanmax(stg.BS_noise_raw_data[i][freq_ind, :, :])

-                    print("val_min = ", val_min, "val_max = ", val_max)
-
                    if val_min == val_max:
                        exec("pcm = self.ax" + str(i) + "[" + str(freq_ind) + "]" + ".pcolormesh(" +
-                             "stg.time[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                             "-stg.depth[" + str(i) + "][" + str(freq_ind) + ", :]," +
+                             "stg.time_noise[" + str(i) + "][" + str(freq_ind) + ", :]," +
+                             "-stg.depth_noise[" + str(i) + "][" + str(freq_ind) + ", :]," +
                             "stg.BS_noise_raw_data[" + str(i) + "][" + str(freq_ind) + ", :, :]," +
                             "cmap='hsv')")
                    else:
@ -72,74 +63,6 @@ class PlotNoiseWindow(QDialog):
                             "-stg.depth_noise[" + str(i) + "][" + str(freq_ind) + ", :]," +
                             "stg.BS_noise_raw_data[" + str(i) + "][" + str(freq_ind) + ", :, :]," +
                             "cmap='hsv')")
-                    # , norm = LogNorm(vmin=val_min, vmax=val_max)
-
-                    # if stg.time_cross_section[i].shape != (0,):
-                    #
-                    #     if depth_cross_section[i].shape != (0,):
-                    #         if val_min == val_max:
-                    #             exec("pcm = self.ax" + str(i) + "[" + str(freq_ind) + "]" + ".pcolormesh(" +
-                    #                         "stg.time_cross_section[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                         "-stg.depth_cross_section[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                         "stg.BS_noise_raw_data[" + str(i) + "][" + str(freq_ind) + ", :, :]," +
-                    #                         "cmap='viridis')" )
-                    #         else:
-                    #             val_min = 0
-                    #             val_max = 1e-5
-                    #             exec("pcm = self.ax" + str(i) + "[" + str(freq_ind) + "]" + ".pcolormesh(" +
-                    #                          "stg.time_cross_section[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                          "-stg.depth_cross_section[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                          "stg.BS_noise_raw_data[" + str(i) + "][" + str(freq_ind) + ", :, :]," +
-                    #                          "cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))")
-                    #     else:
-                    #         if val_min == val_max:
-                    #             exec("pcm = self.ax" + str(i) + "[" + str(freq_ind) + "]" + ".pcolormesh(" +
-                    #                         "stg.time_cross_section[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                         "-stg.depth[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                         "stg.BS_noise_raw_data[" + str(i) + "][" + str(freq_ind) + ", :, :]," +
-                    #                         "cmap='viridis')" )
-                    #         else:
-                    #             val_min = 0
-                    #             val_max = 1e-5
-                    #             exec("pcm = self.ax" + str(i) + "[" + str(freq_ind) + "]" + ".pcolormesh(" +
-                    #                          "stg.time_cross_section[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                          "-stg.depth[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                          "stg.BS_noise_averaged_data[" + str(i) + "][" + str(freq_ind) + ", :, :]," +
-                    #                          "cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))")
-                    #
-                    # else:
-                    #
-                    #     if depth_cross_section[i].shape != (0,):
-                    #         if val_min == val_max:
-                    #             exec("pcm = self.ax" + str(i) + "[" + str(freq_ind) + "]" + ".pcolormesh(" +
-                    #                         "stg.time[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                         "-stg.depth_cross_section[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                         "stg.BS_noise_averaged_data[" + str(i) + "][" + str(freq_ind) + ", :, :]," +
-                    #                         "cmap='viridis')" )
-                    #         else:
-                    #             val_min = 0
-                    #             val_max = 1e-5
-                    #             exec("pcm = self.ax" + str(i) + "[" + str(freq_ind) + "]" + ".pcolormesh(" +
-                    #                      "stg.time[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                      "-stg.depth_cross_section[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                      "stg.BS_noise_averaged_data[" + str(i) + "][" + str(freq_ind) + ", :, :]," +
-                    #                      "cmap='viridis', norm=LogNorm(vmin=val_min, vmax=val_max))")
-                    #     else:
-                    #         if val_min == val_max:
-                    #             exec("pcm = self.ax" + str(i) + "[" + str(freq_ind) + "]" + ".pcolormesh(" +
-                    #                     "stg.time[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                     "-stg.depth[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                     "stg.BS_noise_averaged_data[" + str(i) + "][" + str(freq_ind) + ", :, :]," +
-                    #                     "cmap='viridis')" )
-                    #         else:
-                    #             val_min = 0
-                    #             val_max = 1e-5
-                    #             exec("pcm = self.ax" + str(i) + "[" + str(freq_ind) + "]" + ".pcolormesh(" +
-                    #                      "stg.time[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                      "-stg.depth[" + str(i) + "][" + str(freq_ind) + ", :]," +
-                    #                      "stg.BS_noise_averaged_data[" + str(i) + "][" + str(freq_ind) + ", :, :]," +
-                    #                      "cmap='viridis')")
-                    # # , norm = LogNorm(vmin=val_min, vmax=val_max)

                    eval("self.ax" + str(i) + "[" + str(freq_ind) + "]" + ".text(1, .70, stg.freq_text[" + str(i) +
                                        "][" + str(freq_ind) + "]," +
@ -160,8 +83,6 @@ class PlotNoiseWindow(QDialog):

                pass

-            # self.axis_noise.tick_params(axis='both', which='minor', labelsize=10)
-
            exec("self.canvas" + str(i) + "= FigureCanvas(self.fig" + str(i) + ")")
            exec("self.toolbar" + str(i) + "= NavigationToolBar(self.canvas" + str(i) + ", self)")

@ -171,10 +92,3 @@ class PlotNoiseWindow(QDialog):
            exec("self.verticalLayout_tab" + str(i) + ".addWidget(self.toolbar" + str(i) + ")")
            exec("self.verticalLayout_tab" + str(i) + ".addWidget(self.scroll" + str(i) + ")")

-
-        # self.tab1 = QWidget()
-        # self.tab.addTab(self.tab1, "Tab 1")
-
-
-
-        # ----------------------------------------------------------
--- a/View/sample_data_tab.py
+++ b/View/sample_data_tab.py
--- a/View/sediment_calibration_tab.py
+++ b/View/sediment_calibration_tab.py
--- a/View/signal_processing_tab.py
+++ b/View/signal_processing_tab.py
--- a/logos/AcouSed.png
+++ b/logos/AcouSed.png
--- a/logos/BlocMarque-INRAE-Inter.jpg
+++ b/logos/BlocMarque-INRAE-Inter.jpg
--- a/logos/CNR.png
+++ b/logos/CNR.png
--- a/logos/EDF.png
+++ b/logos/EDF.png
--- a/logos/OSR.png
+++ b/logos/OSR.png
--- a/logos/Ubertone.jpeg
+++ b/logos/Ubertone.jpeg
--- a/main.py
+++ b/main.py
@ -1,4 +1,5 @@
 import sys
+import logging
 import traceback

 from PyQt5.QtWidgets import QApplication, QMainWindow
@ -26,6 +27,14 @@ import matplotlib.pyplot as plt
 PERCENT_SCREEN_SIZE = 0.85
 _translate = QCoreApplication.translate

+logging.basicConfig(
+    level=logging.INFO,
+    format=('[AcouSed][%(levelname)s] %(message)s')
+)
+
+logger = logging.getLogger("acoused")
+logger.setLevel(logging.DEBUG)
+#logger.setLevel(logging.INFO)

 class MainApplication(QMainWindow):

@ -41,15 +50,17 @@ class MainApplication(QMainWindow):
        height = size.height()
        self.resize(int(PERCENT_SCREEN_SIZE*width), int(PERCENT_SCREEN_SIZE*height))
        try:
-            self.read_table_open = ReadTableForOpen()
            # **************************************************
            # -------------- Acoustic data tab ---------------

            self.acoustic_data_tab = AcousticDataTab(self.ui_mainwindow.tab1)
-            print("0 AcousticDataTab ", id(AcousticDataTab))

-            self.acoustic_data_tab.combobox_ABS_system_choice.editTextChanged.connect(
-                self.acoustic_data_tab.ABS_system_choice)
+            self.acoustic_data_tab\
+                .combobox_ABS_system_choice\
+                .editTextChanged\
+                .connect(
+                    self.acoustic_data_tab.ABS_system_choice
+                )

            # **************************************************
            # --------- Signal pre-processing data tab ----------
@ -84,20 +95,19 @@ class MainApplication(QMainWindow):

            # self.user_manual_tab = UserManualTab(self.ui_mainwindow.tab7)

-            self.ui_mainwindow.actionOpen.triggered.connect(self.trig_open)
-
        # **************************************************
        # ---------------- Text File Error -----------------

        except Exception as e:
+            logger.error(str(e))
+            logger.error(traceback.format_exc())
+
            with open("Error_file.txt", "w", encoding="utf-8") as sortie:
                sortie.write(str(e))
                sortie.write(traceback.format_exc())
                # traceback.TracebackException.from_exception(e).print(file=sortie)

-    def trig_open(self):
-        self.read_table_open.open_file_dialog()
-
+    def open_study_update_tabs(self):
        self.acoustic_data_tab.combobox_ABS_system_choice.setCurrentText(stg.ABS_name[0])
        self.acoustic_data_tab.fileListWidget.addFilenames(stg.filename_BS_raw_data)

@ -108,7 +118,6 @@ class MainApplication(QMainWindow):
        self.sample_data_tab.lineEdit_fine_sediment.setToolTip(stg.path_fine)
        # self.sample_data_tab.fill_table_fine()

-
 if __name__ == '__main__':
    # print("sys.argv:", [arg for arg in sys.argv])
    # app = MainApplication(sys.argv)
--- a/manifest.scm
+++ b/manifest.scm
@ -210,4 +210,4 @@ user-defined extensions).")
              "python-scipy" "python-scikit-learn"
              "python-pyqt@5" "python-pyqt5-sip"
              "python-numpy@1" "python-pandas@1.5"
-              "python-matplotlib"))))
+              "python-matplotlib" "python-odfpy"))))
--- a/packages/debug.bat
+++ b/packages/debug.bat
@ -0,0 +1,5 @@
+
+@ECHO OFF
+
+start cmd /c test3\Acoused.exe
+
--- a/packages/windows.bat
+++ b/packages/windows.bat
@ -0,0 +1,35 @@
+
+@ECHO OFF
+
+rem Python environment (-U = update python packages / -r = texte file)
+python -m pip install -U -r ..\virtualenv\requirements.txt
+
+rem Build windows version
+mkdir acoused_packaging
+pyinstaller --name "acoused" ..\main.py -y
+
+rem Icons
+mkdir acoused_packaging\icons
+copy /y ..\icons\*.png acoused_packaging\icons
+
+rem Logos
+mkdir acoused_packaging\logos
+copy /y ..\logos\* acoused_packaging\logos
+
+rem Doc
+copy /y ..\ABS_calibration_constant_kt.xlsx acoused_packaging
+copy /y ..\AcouSed_UserManual.pdf acoused_packaging
+copy /y ..\Acoustic_Inversion_theory.pdf acoused_packaging
+copy /y ..\Tutorial_AQUAscat_software.pdf acoused_packaging
+
+rem move exe
+move /y dist\AcouSed\acoused.exe acoused_packaging
+move /y dist\acoused\_internal acoused_packaging
+copy debug.bat acoused_packaging
+rmdir /s /q build
+rmdir /s /q dist
+del /q AcouSed.spec
+
+set PATH=%PATH%;C:\Program Files (x86)/7-Zip
+7z a -tzip acoused_packaging.zip acoused_packaging
+
--- a/tools.py
+++ b/tools.py
@ -0,0 +1,45 @@
+import os
+import time
+import logging
+import traceback
+
+from datetime import datetime, timedelta
+from pathlib import Path
+
+from functools import wraps
+
+###########
+# LOGGING #
+###########
+
+logger = logging.getLogger("acoused")
+
+#########
+# WRAPS #
+#########
+
+def trace(func):
+    @wraps(func)
+    def wrapper(*args, **kwargs):
+        t = time.time()
+        head = f"[TRACE]"
+        logger.debug(
+            f"{head} Call {func.__module__}." +
+            f"{func.__qualname__}({args}, {kwargs})"
+        )
+
+        value = func(*args, **kwargs)
+
+        t1 = time.time()
+        logger.debug(
+            f"{head} Return {func.__module__}." +
+            f"{func.__qualname__}: {value}"
+        )
+        logger.debug(
+            f"{head}[TIME] {func.__module__}." +
+            f"{func.__qualname__}: {t1-t} sec"
+        )
+
+        return value
+
+    return wrapper
--- a/virtual_env/requirements.txt
+++ b/virtual_env/requirements.txt
@ -1,3 +1,5 @@
+astropy==6.1.7
+astropy-iers-data==0.2025.3.3.0.34.45
 contourpy==1.0.7
 cycler==0.11.0
 defusedxml==0.7.1
@ -16,15 +18,21 @@ packaging==23.0
 pandas==1.5.3
 Pillow==9.4.0
 profilehooks==1.12.0
+pyerfa==2.0.1.5
 pyparsing==3.0.9
 pyqt-checkbox-table-widget==0.0.14
+pyqt-file-list-widget==0.0.1
+pyqt-files-already-exists-dialog==0.0.1
+pyqt-tooltip-list-widget==0.0.1
 PyQt5==5.15.9
 PyQt5-Qt5==5.15.2
 PyQt5-sip==12.11.0
 python-dateutil==2.8.2
 pytz==2022.7.1
+PyYAML==6.0.2
 scikit-learn==1.2.1
 scipy==1.10.0
+simplePyQt5==0.0.1
 six==1.16.0
 threadpoolctl==3.1.0
 utm==0.7.0
Author	SHA1	Message	Date
brahim	60b367b7ef	correction fusion	2025-03-20 13:23:15 +01:00
brahim	ac1ffcef58	windows comand to zip the file is added	2025-03-20 13:20:23 +01:00
Pierre-Antoine	dea9042ed1	Merge branch 'dev-parouby' into dev	2025-03-20 11:56:28 +01:00
Pierre-Antoine	b52acafd29	Sediment calibration: Add test on fine data selection for interpolate.	2025-03-20 11:55:26 +01:00
brahim	e87bb9731d	fusion repared	2025-03-20 11:06:08 +01:00
brahim	d076054375	fusion finished	2025-03-20 11:01:14 +01:00
Pierre-Antoine	998e1e7f8f	Signal processing: Fix #8 and clean debug display code.	2025-03-20 10:33:16 +01:00
brahim	1e9116bd0d	File requirements.txt and folder vritual_env are deleted	2025-03-20 10:06:00 +01:00
Pierre-Antoine	be7627d93f	Signal processing: Refactoring with recompute and replot method.	2025-03-19 18:08:33 +01:00
brahim	1fffdc714e	scripts to generate acoused release	2025-03-19 16:14:25 +01:00
Pierre-Antoine	225c40c6c1	Signal processing: Some minor refactoring.	2025-03-19 16:13:15 +01:00
MOUDJED Brahim	fbc46f3344	Update README.md	2025-03-19 15:59:21 +01:00
MOUDJED Brahim	43d586bf05	Update README.md	2025-03-19 15:58:55 +01:00
MOUDJED Brahim	089a7657ab	Update README.md	2025-03-19 15:57:59 +01:00
MOUDJED Brahim	0eb10fea10	Update README.md	2025-03-19 15:55:03 +01:00
MOUDJED Brahim	d3afd2900e	Update README.md	2025-03-19 15:51:59 +01:00
MOUDJED Brahim	f1b196dba2	Update README.md	2025-03-19 15:50:41 +01:00
MOUDJED Brahim	a877cf86d7	Update README.md	2025-03-19 15:50:12 +01:00
MOUDJED Brahim	9e7f34238e	Update README.md	2025-03-19 15:49:25 +01:00
MOUDJED Brahim	887a152fff	Update README.md	2025-03-19 15:47:37 +01:00
Pierre-Antoine	8a39bba7b1	Signal processing: Some refactoring.	2025-03-19 15:31:06 +01:00
Pierre-Antoine	ad865e2829	tools: Add new file.	2025-03-19 15:30:56 +01:00
Pierre-Antoine	99ff7c5fed	Acoused: Use a specific logger.	2025-03-19 14:12:35 +01:00
Pierre-Antoine	64230540c7	Signal processing: Change plot font.	2025-03-19 13:44:53 +01:00
Pierre-Antoine	44bf348ee5	Signal processing: Block signals during tab update.	2025-03-19 13:43:37 +01:00
Pierre-Antoine	c521738567	Acoutic data: Minor change.	2025-03-17 18:06:09 +01:00
Pierre-Antoine	b5338366cf	Merge branch 'dev-parouby' into dev	2025-03-17 17:34:25 +01:00
Pierre-Antoine	752697db86	gitignore: Add '.exe' files.	2025-03-17 17:26:50 +01:00
brahim	b99e950a8e	If values of sediment attenuation parameters are infinite, a warning is added and inversion computatio is not allowed #41	2025-03-17 17:25:55 +01:00
Pierre-Antoine	b9669d9cbf	Acoustic data: Refactorise 'remove_file_from_ListWidget' method.	2025-03-17 17:25:19 +01:00
Pierre-Antoine	b9ca307c59	Acoustic data: Remove useless 'eval' or 'exec'.	2025-03-17 17:18:02 +01:00
Pierre-Antoine	f0150443e3	Acoustic data: Clear 'clear_files_from_ListWidget' method.	2025-03-17 17:14:00 +01:00
Pierre-Antoine	4c024cbb42	Acoustic data: Disable unused distance from bank (#39 ).	2025-03-17 16:35:32 +01:00
Pierre-Antoine	496937bde2	Acoustic data: Disable unused groupbox gps.	2025-03-17 16:26:50 +01:00
Pierre-Antoine	11ced0a263	Mainwindow: Minor change.	2025-03-17 10:44:49 +01:00
Pierre-Antoine	5cf87a5e7b	Mainwindow: Fix table export.	2025-03-17 10:41:38 +01:00
brahim	477ad00cf8	hyperlink of git deposit is added in about window	2025-03-14 17:22:19 +01:00
brahim	1c409531a1	logger added to print computed values of calibration parameters	2025-03-14 16:42:23 +01:00
brahim	5734f6e614	Clear button works when only one acoustic file is downloaded and crash when more than one acoustic file is downloaded #34	2025-03-14 16:33:08 +01:00
brahim	22cd451b24	Error message is added when user click on import/compute calibration without acoustic data #37	2025-03-14 11:52:27 +01:00
brahim	22be597d75	Correction of Delete acoustic data issue (#34 ) generates others issues in measurements information box. To be continued ...	2025-03-14 11:40:44 +01:00
brahim	671f66058c	the clear button is partially corrected	2025-03-13 17:11:10 +01:00
brahim	2d6c950dfe	the delete button is corrected	2025-03-13 17:01:13 +01:00
brahim	fe9ac2d65c	Some correction : Profile and display option wasn't filled when the user download an acoustic file	2025-03-13 16:03:51 +01:00
brahim	bdeca2b44e	Correction when the user clicks on the clear button (clear profile tail) #36	2025-03-13 15:41:04 +01:00
brahim	06056d4865	Correction of average filter button (if no acoustic data) #33	2025-03-13 15:22:49 +01:00
brahim	df68a862fc	Correction of SNR filter button (if no acoustic data) #33	2025-03-13 15:19:30 +01:00
brahim	7a5f6d41f7	Correction of the profile tail button (if no acoustic data) #33	2025-03-13 15:07:31 +01:00
brahim	eef048b197	Correction of the red cross button (if no acoustic data) #33	2025-03-13 14:19:44 +01:00
brahim	3c78777179	Correction of reload button (if no acoustic data) #33	2025-03-13 13:34:57 +01:00
brahim	b84f58ca2c	Resolving confilct	2025-03-13 12:23:30 +01:00
brahim	0df253d70f	Resolve merge conflict by incorporating both suggestions	2025-03-13 12:05:27 +01:00
brahim	2715d225af	Crash corrected if any calibration file is selected (Click Cancel)	2025-03-13 11:38:21 +01:00
Pierre-Antoine	571ac20d37	Acoustic data: refactoring plot and fix #17 .	2025-03-12 16:36:53 +01:00
Pierre-Antoine	5f0fb9ad53	Acoustic data: Refactoring.	2025-03-12 15:51:44 +01:00
Pierre-Antoine	cb94bb3c5d	Acoustic data: Refactoring.	2025-03-12 15:02:02 +01:00
Pierre-Antoine	56a26c04b6	Acoustic data: Minor refactoring.	2025-03-12 11:45:03 +01:00
Pierre-Antoine	de54303e0b	README.md: Minor change.	2025-03-12 11:17:16 +01:00
Pierre-Antoine	43ed93584f	Mainwindow: Set translate button to disabled.	2025-03-12 11:05:30 +01:00
Pierre-Antoine	d1b311d1a3	Merge branch 'dev-parouby' into dev	2025-03-12 10:51:32 +01:00
Pierre-Antoine	607aed3f11	Mainwindow: 'save' call 'save_as' when study are never saved before.	2025-03-12 10:49:04 +01:00
Pierre-Antoine	487f5e9ac8	Sediment calibration: Code refactoring and fix #14 .	2025-03-12 10:17:38 +01:00
brahim	761dc9008c	compute interpolation can be done without detect bottom	2025-03-11 17:32:00 +01:00
brahim	372d002277	resolve conflict	2025-03-11 17:10:56 +01:00
brahim	b28978311c	correction merge and correction interpolate fine profile	2025-03-11 16:44:14 +01:00
Pierre-Antoine	8c7c4cafbc	Inversion: Excel export: Fix depth column shape and filename extention.	2025-03-11 16:15:06 +01:00
brahim	baebe2e8cc	interpolate Mifine profile is corrected with depth_bottom	2025-03-11 15:32:39 +01:00
Pierre-Antoine	8dd50f9373	Inversion: Fix #13 .	2025-03-11 15:12:31 +01:00
Pierre-Antoine	bcdae43d10	SQL: Remove unused logs.	2025-03-11 14:39:22 +01:00
Pierre-Antoine	0c141b8d24	SQL: Minor fix.	2025-03-11 14:28:49 +01:00
Pierre-Antoine	ba0557294e	Inversion: Refactoring 'save_result_in_excel_file' method.	2025-03-11 14:19:18 +01:00
brahim	73bf3cf9d3	The user can reload signal processing after acoustic data boundaries values modification without crash #8	2025-03-11 11:39:09 +01:00
Pierre-Antoine	12fea4e182	Merge branch 'dev-parouby' into dev	2025-03-11 11:37:22 +01:00
Pierre-Antoine	a5268c6214	Sample data: Fix #29 .	2025-03-11 11:35:52 +01:00
Pierre-Antoine	2697acddfe	Sample data: Refactoring some functions.	2025-03-11 10:20:18 +01:00
Pierre-Antoine	f872b625c2	SQL: Minor change.	2025-03-10 17:14:11 +01:00
Pierre-Antoine	87098ff152	SQL: Some refactoring.	2025-03-10 17:12:45 +01:00
Pierre-Antoine	f5eb9a18c6	SQL: Fix empty/partiel study save #12 .	2025-03-10 17:04:31 +01:00
Pierre-Antoine	b7ae9dfe69	Sediment calibration: Some refactoring and fix #6 .	2025-03-10 15:48:00 +01:00
Pierre-Antoine	0ce60afd04	Sediment calibration: Skip crash compute button without data.	2025-03-10 15:17:19 +01:00
Pierre-Antoine	86b9f85ec6	Sediment calibration: Skip somme crash and refactoring.	2025-03-10 15:14:09 +01:00
brahim	6de578a07e	time noise and depth noise variable are used instead of time and depth to avoid size incompatibility #9	2025-03-10 15:12:49 +01:00
Pierre-Antoine	5eb78b812d	Fix interpolate button action without correct data.	2025-03-10 14:43:36 +01:00
brahim	320971160d	Plot of SNR field is corrected when the user set a profile tail level #4	2025-03-10 14:30:45 +01:00
Pierre-Antoine	8f7e679598	Sediment calibration: Refactoring method 'interpolate_Mfine_profile'.	2025-03-10 14:23:29 +01:00
Pierre-Antoine	6628d610de	Sediment calibration: Refactoring __init__ and minor change.	2025-03-10 12:05:07 +01:00
brahim	190c0f0b80	The readme file is modified and will be completed by Brahim.	2025-03-10 11:38:47 +01:00
brahim	2ffb9a21e6	read table for open cleaned	2025-03-10 10:16:03 +01:00
MOUDJED Brahim	2ec5584860	Update README.md	2025-03-07 17:19:16 +01:00
MOUDJED Brahim	6d4fb5fae6	Update README.md	2025-03-07 12:14:46 +01:00
Pierre-Antoine	2b84fab38d	README.md: Add some information and global file scheme #27 .	2025-03-06 15:49:48 +01:00
Pierre-Antoine	17619f15ac	Fix save method on existing file #16 .	2025-03-06 14:33:30 +01:00
Pierre-Antoine	b26d8a2906	Fix note tab click on 'edit settings' button #10 .	2025-03-06 14:13:35 +01:00
Pierre-Antoine	52b612ba3e	Fix acoustic data loading without selection #3 .	2025-03-06 10:47:54 +01:00
brahim	65a9422f71	acoustic inversion method high concentration file is cleaned from useless commented lines and useless print	2025-03-06 10:23:27 +01:00
brahim	cea9e35498	acoustic data loader file is cleaned from useless commented lines and useless print	2025-03-06 10:18:46 +01:00
Pierre-Antoine	5ebd842346	Fix open and save as method (#2 and #18 ).	2025-03-06 10:13:00 +01:00
Pierre-Antoine	4af3c4c9ea	Fix #7 with exception handler.	2025-03-06 09:18:04 +01:00
Pierre-Antoine	b80e0f3c8e	Merge branch 'dev-parouby' into dev	2025-03-05 15:40:00 +01:00
Pierre-Antoine	1c3f6fb015	main: Add 'logging' basic config.	2025-03-05 14:53:29 +01:00
brahim	9ecb70b955	plot noise program is cleaned from useless commented lines and useless print	2025-03-05 14:28:00 +01:00
brahim	0879520fd2	mainwindow program is cleaned from useless commented lines and useless print	2025-03-05 14:24:00 +01:00
brahim	030213608d	line from PyQt5.QtCore import Qt was removed by mistake	2025-03-05 14:17:17 +01:00
brahim	329639e064	granulo loader program is cleaned from useless commented lines and useless print	2025-03-05 13:40:22 +01:00
brahim	5d16adc521	calibration constant program is cleaned from useless commented lines	2025-03-05 13:37:59 +01:00
brahim	9fcbe0e306	ubsediflow raw extract is cleaned from useless test	2025-03-05 13:36:37 +01:00
brahim	77f28462e6	ubsediflow raw extract is cleaned from useless print	2025-03-05 13:35:13 +01:00
brahim	2e9f9c3a3c	acoustic data loader ubsediflow is cleaned from useless commented lines and useless print	2025-03-05 12:56:55 +01:00
brahim	80d570796a	acoustic inversion tab is cleaned from useless commented lines and useless print	2025-03-05 12:48:45 +01:00
brahim	40d14a2ffb	Sediment calibration tab is cleaned from useless commented lines and useless print	2025-03-05 12:02:59 +01:00
brahim	d3234bff5d	Sample data tab is cleaned from useless commented lines and useless print	2025-03-05 11:50:38 +01:00
brahim	f2db89eef8	signal processing tab is cleaned from useless commented lines and useless print	2025-03-05 11:32:21 +01:00
Pierre-Antoine	3e5ef5d2bc	Mainwindow: Revert 'sqlitebrowser' QProcess to Popen (run as async).	2025-03-05 11:22:06 +01:00
Pierre-Antoine	9c5b76e451	Mainwindow: Fix #11 pdf file open, use QDesktopServices instead of open cmd.	2025-03-05 09:40:18 +01:00
Pierre-Antoine	769fd8581e	Mainwindow: Fix #7 sqlitebrowser call with QProcess.	2025-03-05 09:27:54 +01:00
brahim	153b136812	acoustic data tab is cleaned from useless commented lines and useless print	2025-03-04 15:38:20 +01:00
brahim	6b22562e57	astropy library is added	2025-03-04 14:39:53 +01:00
Pierre-Antoine	dc9264cd65	git: Update project depencencies to fix #5 .	2025-03-04 13:35:10 +01:00