QoL update

code/classes/gui.py

@@ -8,6 +8,7 @@
 from satellite_tle import fetch_tle_from_celestrak
 import matplotlib.pyplot as plt
 from matplotlib.lines import Line2D
+from matplotlib.patches import Patch
 from tkcalendar import DateEntry
 import numpy as np
 from datetime import timedelta, datetime
@@ -22,7 +23,6 @@
 from functions.country import get_country_name, get_poly_coordinate
 from functions.coordinates_converter import latlong_to_cartesian
 from functions.save_result import save_gs_visibility, save_poi_visibility, general_result
-from functions.find_tm import centroid
 from functions.itur_model import get_attenuation
 
 #############################################################################################
@@ -1422,12 +1422,22 @@ def poi_visibility(self, miss, chosen_sat):
                         elevation_fin = zenith_angle.loc[date_fin.strftime("%Y-%m-%d %H:%M:%S")].elevation
                         mean_elevation = (elevation_ini+elevation_fin)/2
                         visibility.append((chosen_sat.get_name(), poi.get_name(), date_ini, date_fin, delta.seconds, mean_elevation))
-
+                sza_condition = []
+                for i in range(len(visibility)):
+                    if visibility[i][5] >= miss.get_minsza():
+                        sza_condition.append(True)
+                    else:
+                        sza_condition.append(False)
+                sza_color = ['green' if condition else 'red' for condition in sza_condition]
                 #Plot les durées de visibilité
                 ax_2D_3 = fig2d.add_subplot(313)
-                ax_2D_3.bar([date.strftime('%Y-%m-%d %H:%M:%S') for date in date_ini_list], timedelta_list, width=0.35, color=list_colors, align='center')
+                ax_2D_3.bar([date.strftime('%Y-%m-%d %H:%M:%S') for date in date_ini_list], timedelta_list, width=0.35, color=sza_color, align='center')
                 ax_2D_3.set_ylabel('Times (s)')
-                ax_2D_3.legend()
+                legend_patches = [
+                Patch(color='green', label=f'Date meeting SZA >= {miss.get_minsza()}'),
+                Patch(color='red', label=f'Date not meeting SZA >= {miss.get_minsza()}')
+                ]
+                ax_2D_3.legend(handles=legend_patches)
                 plt.title(f"Visibilities duration at {poi.get_name()} with a swath of {chosen_sat.get_swath()} km")
                 plt.grid(True)
                 plt.xticks(rotation=45)
@@ -1477,16 +1487,19 @@ def visibility_grid(self, poi, chosen_sat, miss):
         green = Line2D([0], [0], marker='o', color='w', markerfacecolor='green', markersize=10, label='Observation possible')
         orange = Line2D([0], [0], marker='o', color='w', markerfacecolor='orange', markersize=10, label='Area visible but minimum sza not reached')
         red =Line2D([0], [0], marker='o', color='w', markerfacecolor='red', markersize=10, label='Observation impossible')
+        prct = 0
         for i in range(len(square_visible)):
             if square_visible[i][0]:
                 if square_visible[i][1]:
                     gpd.GeoSeries(square_visible[i][2]).plot(ax=ax, color="green")
+                    prct += 1
                 else:
                     gpd.GeoSeries(square_visible[i][2]).plot(ax=ax, color="orange")
             else:
                 gpd.GeoSeries(square_visible[i][2]).plot(ax=ax, color="red")
         ax.legend(handles=[green, orange, red])
-        plt.title(f"Visibility map of {poi.get_name()}")
+        prct = (prct*100)/len(square_visible)
+        plt.title(f"{prct:.2f}% of {poi.get_name()} covered during the simulation ")
         fig.savefig(result_folder / miss.get_name() / f"Result {poi.get_name()} visibility ({chosen_sat.get_name()}) figure.png")
 
     def save_result(self):
@@ -1562,6 +1575,7 @@ def save_result(self):
                     gs_visibility.append((sat[j].get_name(), len(interval)))
                 gs_opportunities.append((gs[i].get_name(), gs_visibility))
             general_result(mission, gs_opportunities, poi_opportunities)
+            showinfo("Message", "Mission report created successfully")
 
 #############################################################################################
 # Additional windows

code/functions/save_result.py

@@ -118,9 +118,10 @@ def plot_result_gs(opportunities):
 
     def plot_result_poi(opportunities):
         temp = opportunities
-        visi_list = []
-        color = []
+
         if temp[1][0][0]:
+            visi_list = []
+            color = []
             fig, ax = plt.subplots(figsize=(15, 15))
             if temp[1][1][4]:
                 grid_poi = temp[1][1][3]
@@ -176,21 +177,24 @@ def plot_result_poi(opportunities):
                                     pass
                 if i==0:
                     color.append(color_temp)
+            prct = 0
             for i in range(len(color)):
                 for j in range(len(color[i])):
                     if color[i][j][0]==2:
                         gpd.GeoSeries(color[i][j][1]).plot(ax=ax, color="green")
+                        prct += 1
                     elif color[i][j][0]==1:
                         gpd.GeoSeries(color[i][j][1]).plot(ax=ax, color="orange")
                     else:
                         gpd.GeoSeries(color[i][j][1]).plot(ax=ax, color="red")
             green = Line2D([0], [0], marker='o', color='w', markerfacecolor='green', markersize=10, label='Observation possible')
             orange = Line2D([0], [0], marker='o', color='w', markerfacecolor='orange', markersize=10, label='Area visible but minimum sza not reached')
             red =Line2D([0], [0], marker='o', color='w', markerfacecolor='red', markersize=10, label='Observation impossible')
+            prct = (prct*100)/len(color[0])
             ax.legend(handles=[green, orange, red])
-            ax.set_title(f"Visibility map of {title}")
-            fig.savefig(result_folder / mission.get_name() / f"Visibility at {title}.png", bbox_inches='tight')
-            img = Image(result_folder / mission.get_name() / f"Visibility at {title}.png", width=400, height=300)
+            ax.set_title(f"{prct:.2f}% of {title} covered during the simulation ")
+            fig.savefig(result_folder / mission.get_name() / f"Coverage map of {title}.png", bbox_inches='tight')
+            img = Image(result_folder / mission.get_name() / f"coverage map of {title}.png", width=400, height=300)
             return img
         else:
             fig2d = plt.figure(figsize=(10, 6))