Acoustic inversion: Close plot and add ods and csv results export.

View/acoustic_inversion_tab.py

@@ -21,6 +21,7 @@
 # -*- coding: utf-8 -*-
 
 import os
+import gc
 import logging
 import numpy as np
 import pandas as pd
@@ -408,7 +409,7 @@ class AcousticInversionTab(QWidget):
         self.pushbutton_run_inversion\
             .clicked.connect(self.function_run_inversion)
         self.pushbutton_save_result\
-            .clicked.connect(self.save_result_in_excel_file)
+            .clicked.connect(self.save_result)
 
         self.pushbutton_left_to_begin_fine\
             .clicked.connect(self.slider_profile_number_to_begin_fine)
@@ -601,6 +602,7 @@ class AcousticInversionTab(QWidget):
 
             if self.figure_SSC_fine is not None:
                 self.figure_SSC_fine.clear()
+                plt.close(fig=self.figure_SSC_fine)
 
             self.figure_SSC_fine, self.axis_SSC_fine = plt.subplots(
                 nrows=1, ncols=1, layout="constrained"
@@ -729,6 +731,7 @@ class AcousticInversionTab(QWidget):
 
             if self.figure_vertical_profile_SSC_fine is not None:
                 self.figure_vertical_profile_SSC_fine.clear()
+                plt.close(fig=self.figure_vertical_profile_SSC_fine)
 
             fig, ax = plt.subplots(nrows=1, ncols=1, layout="constrained")
             self.figure_vertical_profile_SSC_fine = fig
@@ -1013,6 +1016,7 @@ class AcousticInversionTab(QWidget):
         else:
             if self.figure_measured_vs_inverted_fine is not None:
                 self.figure_measured_vs_inverted_fine.clear()
+                plt.close(fig=self.figure_measured_vs_inverted_fine)
 
             fig, ax = plt.subplots(nrows=1, ncols=1, layout="constrained")
 
@@ -1156,6 +1160,7 @@ class AcousticInversionTab(QWidget):
         else:
             if self.figure_SSC_sand is not None:
                 self.figure_SSC_sand.clear()
+                plt.close(fig=self.figure_SSC_sand)
 
             self.figure_SSC_sand, self.axis_SSC_sand = plt.subplots(
                 nrows=1, ncols=1, layout="constrained"
@@ -1283,6 +1288,7 @@ class AcousticInversionTab(QWidget):
 
                 if self.figure_vertical_profile_SSC_sand is not None:
                     self.figure_vertical_profile_SSC_sand.clear()
+                    plt.close(fig=self.figure_vertical_profile_SSC_sand)
 
                 fig, ax = plt.subplots(
                     nrows=1, ncols=1, layout="constrained"
@@ -1573,6 +1579,7 @@ class AcousticInversionTab(QWidget):
 
                 if self.figure_measured_vs_inverted_sand is not None:
                     self.figure_measured_vs_inverted_sand.clear()
+                    plt.close(fig=self.figure_measured_vs_inverted_sand)
 
                 fig, ax = plt.subplots(nrows=1, ncols=1, layout="constrained")
                 self.figure_measured_vs_inverted_sand = fig
@@ -1663,24 +1670,50 @@ class AcousticInversionTab(QWidget):
 
                 self.figure_measured_vs_inverted_sand.canvas.draw_idle()
 
-    def save_result_in_excel_file(self):
+    def save_result(self):
-        if self.combobox_acoustic_data_choice.count() > 0:
+        if self.combobox_acoustic_data_choice.count() <= 0:
-            name, _ = QFileDialog.getSaveFileName(
+            return
-                caption="Save As - Inversion results",
-                directory="",
-                filter="Excel Files (*.xlsx)",
-                options=QFileDialog.DontUseNativeDialog
-            )
 
-            if name == '':
+        file_type = {
-                return
+            "CSV Files (*.csv)": (self.save_result_in_csv_file, ".csv"),
+            "Excel Files (*.xlsx)": (self.save_result_in_excel_file, ".xlsx"),
+            # "LibreOffice Calc Files (*.ods)": (self.save_result_in_excel_file, ".ods"),
+        }
 
-            dirname = os.path.dirname(name)
+        name, type_ext = QFileDialog.getSaveFileName(
-            filename = os.path.basename(name)
+            caption="Save As - Inversion results",
-            os.chdir(dirname)
+            directory="",
+            filter=";;".join(file_type),
+            options=QFileDialog.DontUseNativeDialog
+        )
 
-            results = []
+        if name == '':
+            return
 
+        dirname = os.path.dirname(name)
+        filename = os.path.basename(name)
+        _, ext = os.path.splitext(filename)
+
+        os.chdir(dirname)
+
+        fun, t_ext = file_type[type_ext]
+        if t_ext not in filename:
+            filename += t_ext
+
+        logger.info(f"Export results to {os.path.join(dirname, filename)}")
+        fun(dirname, filename)
+        logger.info(f"... export done")
+
+    def save_result_in_excel_file(self, dirname, filename):
+        if ".ods" in filename:
+            engine = "odf"
+        else:
+            engine = 'xlsxwriter'
+
+        with pd.ExcelWriter(
+                os.path.join(dirname, filename),
+                engine=engine
+        ) as writer:
             for k in range(self.combobox_acoustic_data_choice.count()):
                 if stg.time_cross_section[k].shape != (0,):
                     time_data = stg.time_cross_section
@@ -1705,41 +1738,99 @@ class AcousticInversionTab(QWidget):
                     for j in range(depth_data[k].shape[1]):
                         r_id = i * depth_data[k].shape[1] + j
 
-                        r[r_id] = (
+                        r[r_id] = depth_data[k][
-                            depth_data[k][
+                            int(stg.frequency_for_inversion[1]), j
-                                int(stg.frequency_for_inversion[1]), j
+                        ]
-                            ]
-                        )
 
                 if stg.SSC_fine[k].shape == (0,):
                     stg.SSC_fine[k] = np.zeros(r.shape[0])
                 if stg.SSC_sand[k].shape == (0,):
                     stg.SSC_sand[k] = np.zeros(r.shape[0])
 
-                results.append(
+                result = pd.DataFrame(
-                    pd.DataFrame(
+                    {
-                        {
+                        'Time (sec)': list(t),
-                            'Time (sec)': list(t),
+                        'Depth (m)': list(r),
-                            'Depth (m)': list(r),
+                        'SSC_fine (g/L)': list(
-                            'SSC_fine (g/L)': list(
+                            stg.SSC_fine[k].reshape(t.shape[0])
-                                stg.SSC_fine[k].reshape(t.shape[0])
+                        ),
-                            ),
+                        'SSC_sand (g/L)': list(
-                            'SSC_sand (g/L)': list(
+                            stg.SSC_sand[k].reshape(t.shape[0])
-                                stg.SSC_sand[k].reshape(t.shape[0])
+                        ),
-                            ),
+                    }
-                        }
-                    )
                 )
 
-            if os.path.splitext(filename)[1] != ".xlsx":
+                gc.collect() # Force garbade collection
-                filename += ".xlsx"
 
-            with pd.ExcelWriter(
+                result.to_excel(
-                    os.path.join(dirname, filename)
+                    writer, index=False, na_rep='NA',
-            ) as writer:
+                    sheet_name=stg.data_preprocessed[k],
-                for k in range(self.combobox_acoustic_data_choice.count()):
+                )
-                    results[k].to_excel(
+
-                        writer, index=False,
+    def save_result_in_csv_file(self, dirname, filename):
-                        engine='xlsxwriter', na_rep='NA',
+        d_id = []
-                        sheet_name=stg.data_preprocessed[k],
+        t = []
+        r = []
+        ssc_fine = []
+        ssc_sand = []
+
+        for k in range(self.combobox_acoustic_data_choice.count()):
+            if stg.time_cross_section[k].shape != (0,):
+                time_data = stg.time_cross_section
+            else:
+                time_data = stg.time
+
+            if stg.depth_cross_section[k].shape != (0,):
+                depth_data = stg.depth_cross_section
+            else:
+                depth_data = stg.depth
+
+            time_shape = time_data[k].shape[1]
+            depth_shape = depth_data[k].shape[1]
+
+            d_id += np.repeat(k, depth_shape * time_shape).tolist()
+
+            tmp_t = np.repeat(
+                time_data[k][stg.frequency_for_inversion[1]],
+                depth_shape
+            )
+
+            tmp_r = np.zeros(
+                depth_shape * time_shape
+            )
+
+            for i in range(time_shape):
+                for j in range(depth_shape):
+                    r_id = i * depth_shape + j
+
+                    tmp_r[r_id] = (
+                        depth_data[k][
+                            int(stg.frequency_for_inversion[1]), j
+                        ]
                     )
+
+            t += tmp_t.tolist()
+            r += tmp_r.tolist()
+
+            if stg.SSC_fine[k].shape == (0,):
+                stg.SSC_fine[k] = np.zeros(tmp_r.shape[0])
+            if stg.SSC_sand[k].shape == (0,):
+                stg.SSC_sand[k] = np.zeros(tmp_r.shape[0])
+
+            ssc_fine += stg.SSC_fine[k].reshape(tmp_r.shape[0]).tolist()
+            ssc_sand += stg.SSC_sand[k].reshape(tmp_r.shape[0]).tolist()
+
+        results = pd.DataFrame(
+            {
+                'acoustic data': d_id,
+                'Time (sec)': t,
+                'Depth (m)': r,
+                'SSC_fine (g/L)': ssc_fine,
+                'SSC_sand (g/L)': ssc_sand,
+            }
+        )
+
+        results.to_csv(
+            os.path.join(dirname, filename),
+            index=False
+        )