Cleaning

app.py

@@ -14,22 +14,26 @@ pn.extension("tabulator")
 
 def get_range(da):
     return  ( int(da.min().round() - 1), int(da.max().round() + 1),)
+
 @pn.cache(max_items=32,policy='LRU',per_session=True)
-def load_csv():
-    df = pd.read_csv('./data/zarr_table.csv',index_col=None)
+def load_csv(path='./data/zarr_table.csv'):
+    df = pd.read_csv(path,index_col=None)
     df.sort_values(by="year") #inplace=True)
     return df
 
 @pn.cache(max_items=4,policy='LRU',per_session=True)
-def load_bathymetry():
-    return xr.open_dataset('./data/bathy6min.nc', decode_times=False, use_cftime=True)
+def load_bathymetry(path='./data/bathy6min.nc'):
+    return xr.open_dataset(path, decode_times=False, use_cftime=True)
 
 @pn.cache(max_items=16,policy='LRU',per_session=True)
-def load_zarr(selected_file):
-    tree= open_datatree('./data/1H_file.zarr', engine='zarr')
+def load_zarr(path='./data/1H_file.zarr'):
+    return open_datatree(path, engine='zarr')
+
+def load_file(tree,selected_file):
     return tree[selected_file+"/"].ds
 
 def filter_df(sorted_df,selected_file):
+    # include  user_interface_url here
     dataframe = sorted_df[sorted_df["file_name"] == selected_file].drop(
                 columns=[
                     "file_name",
@@ -49,6 +53,7 @@ def filter_df(sorted_df,selected_file):
                     "data_type",
                 ]
             )
+    # include  LOCAL_CDI_ID here
     dataframe2 = sorted_df[sorted_df["file_name"] == selected_file].drop(
                 columns=[
                     "file_name",
@@ -87,8 +92,6 @@ def quiver_depth_filtered(ax, ds, depth_range, scale_factor, color="blue"):
     """
     # Filter data based on depth range
     ds = ds.sel( PROFZ=slice(depth_range[1],depth_range[0]))
-    #print('depth_range',depth_range)
-    #print(ds.PROFZ)
 
     # Calculate mean current vectors within the selected depth range
     u_mean = ds.UCUR.mean(dim="PROFZ", skipna=True)
@@ -208,15 +211,14 @@ def vectors_plot(ds, bathy, longitude_range, latitude_range ,
     # Set labels and close plot
     plt.ylabel("Latitude", fontsize=15, labelpad=35)
     plt.xlabel("Longitude", fontsize=15, labelpad=20)
-    plt.close(fig) #https://panel.holoviz.org/reference/panes/Matplotlib.html#using-the-matplotlib-pyplot-interface
-
+    #https://panel.holoviz.org/reference/panes/Matplotlib.html#using-the-matplotlib-pyplot-interface
+    plt.close(fig) 
     return fig
 
-#    return ( int(np.round(da.min().values)), int(np.round(da.max().values)),)
-
 class SADCP_Viewer(param.Parameterized):
     df = load_csv()
     bathy = load_bathymetry()
+    tree=load_zarr()
     file_names = df["file_name"].tolist()
     years = sorted(df["year"].unique())
 
@@ -234,19 +236,15 @@ class SADCP_Viewer(param.Parameterized):
     scale_factor_slider = pn.widgets.FloatSlider(start=0.1, end=1, step=0.1, value=0.5, name="Scale Factor")
     bathy_checkbox = pn.widgets.Checkbox(value=False, name="Bathy Checkbox")
 
-
-#    plot = pn.pane.HoloViews()
-#    plot_map = pn.pane.Matplotlib(width=800, height=600, sizing_mode="fixed")
-
+ 
     data_table = pn.widgets.Tabulator(width=400, height=200)
     metadata_table = pn.widgets.Tabulator(width=600, height=800)
-
+    # Download button is not working : TODO
     download_button = pn.widgets.Button(name="Download", button_type="primary")
-    # plot = pn.Column()
 
     def __init__(self, **params):
         super(SADCP_Viewer, self).__init__(**params)
-        self.file_dropdown.objects = self.get_file_list()
+        self.file_dropdown.objects = self.file_names
         self.file_dropdown.value = (
             self.file_dropdown.objects[0] if self.file_dropdown.objects else None
         )
@@ -286,7 +284,7 @@ class SADCP_Viewer(param.Parameterized):
             self.data_table.value, self.metadata_table.value = filter_df(sorted_df, selected_file)
             
             # Load selected file's data
-            self.ds = load_zarr(selected_file)
+            self.ds = load_file(self.tree,selected_file)
             
             # Update slider ranges for longitude, latitude, and depth
             for slider, coord in zip([self.longitude_slider, self.latitude_slider, self.depth_range_slider,
@@ -297,8 +295,7 @@ class SADCP_Viewer(param.Parameterized):
 
 
             # Close dataset to free up resources
-            # self.update_plots()
-            self.ds.close()
+            # self.ds.close()
 
     @param.depends(
         "year_slider.value",
@@ -313,8 +310,7 @@ class SADCP_Viewer(param.Parameterized):
         "num_vectors_slider.value",
         "scale_factor_slider.value",
         "bathy_checkbox.value",
-        watch=False,
-    )
+        watch=False,)
     def update_plots(self):
         """
         This function updates the plots based on the selected data and parameters.
@@ -327,8 +323,6 @@ class SADCP_Viewer(param.Parameterized):
         """
         # Filter the data
         self.ds_filtered = filter_data(self.ds,self.longitude_slider.value,self.latitude_slider.value)
-        # vector_plot = self.vectors_plot()
-
 
         # Prepare the plots shown in left
         # Update vector plots
@@ -342,38 +336,24 @@ class SADCP_Viewer(param.Parameterized):
                                    )
 
 
+        # Generate plots which will be plotted on the left row.
         self.plot_left = pn.Column(
                                #  '# Column',
                                #  vector_plot,
                                pn.pane.Matplotlib(vector_plot, dpi=144),
-                              #   vector_plot,
+                              #   add here the hvplot block of contour
                                 sizing_mode="stretch_both")
 
         # Generate additional plots which will be plotted on the right row.
-        other_plots = self.hvplot_plots()
-        # self.plot_map = pn.pane.Matplotlib(vector_plot, width=800, height=600, sizing_mode="fixed")
-
-        # Create a Column of additional plots
+        other_plots = bathy_uship_vship_bottom_depth(self.ds_filtered)
         self.plot_right = pn.Column(
             *(pn.pane.HoloViews(plot, width=400, height=200) for plot in other_plots),
             sizing_mode="stretch_width"
         )
-        # other_plots = self.plots()  # Update other plots
-        # self.plot.objects = [*(pn.pane.HoloViews(p, width=400, height=200) for p in other_plots)]
-        # self.plot.object=plot
 
         # Return a Panel row containing the updated map plot and additional plots
         return pn.Row(self.plot_left, self.plot_right, sizing_mode="stretch_both")
 
-        # pn.pane.Matplotlib(fig,width=800, height=600, sizing_mode="fixed", name="Plot")
-
-    # @param.depends( 'file_dropdown.value', 'longitude_slider.value', 'latitude_slider.value',  watch=True)
-    def hvplot_plots(self):
-        return bathy_uship_vship_bottom_depth(self.ds_filtered)
-
-    def get_file_list(self):
-        return self.file_names
-
 
 explorer = SADCP_Viewer()
 # Instantiate the SADCP_Viewer class and create a template
@@ -402,10 +382,12 @@ sidebar = [
     explorer.num_vectors_slider,
     explorer.scale_factor_slider,
     explorer.data_table,
-    """You can consult detailed information on this data at in the metadata tab shown on the right.
+    """You can consult detailed information on this data in the metadata tab shown on the right.
        To download full dataset, please go to https://cdi.seadatanet.org/search 
       and search with LOCAL_CDI_ID indicated above.""",
 ]
+
+pn.config.theme = 'dark'
 template = pn.template.FastListTemplate(
     title="SADCP data Viewer", sidebar=sidebar, main=[tabs]
 )