Cleaning

app.py

@@ -152,9 +152,9 @@ def corsen_data(ds, sample):
 
 
 
-def vectors_plot(ds, bathy, longitude_slider, latitude_slider,
-                 depth_range_slider, depth_2_range_slider, depth_3_range_slider,
-                 scale_factor_slider, sample,
+def vectors_plot(ds, bathy, longitude_range, latitude_range ,
+                 depth_range, depth_2_range, depth_3_range,
+                 scale_factor, sample,
                  depth_2_checkbox=False, depth_3_checkbox=False, bathy_checkbox=False):
     """
     Plot vectors filtered by depth on a map with specified features.
@@ -162,12 +162,12 @@ def vectors_plot(ds, bathy, longitude_slider, latitude_slider,
     Parameters:
         ds (xarray.Dataset): Dataset containing current data.
         bathy (xarray.Dataset): Dataset containing bathymetry data.
-        longitude_slider (tuple): Tuple containing the minimum and maximum longitude values.
-        latitude_slider (tuple): Tuple containing the minimum and maximum latitude values.
-        depth_range_slider (tuple): Tuple containing the minimum and maximum depth values for filtering.
-        depth_2_range_slider (tuple): Tuple containing the minimum and maximum depth values for filtering depth 2.
-        depth_3_range_slider (tuple): Tuple containing the minimum and maximum depth values for filtering depth 3.
-        scale_factor_slider (float): Scaling factor for the magnitude of the current vectors.
+        longitude_range (tuple): Tuple containing the minimum and maximum longitude values.
+        latitude_range  (tuple): Tuple containing the minimum and maximum latitude values.
+        depth_range (tuple): Tuple containing the minimum and maximum depth values for filtering.
+        depth_2_range (tuple): Tuple containing the minimum and maximum depth values for filtering depth 2.
+        depth_3_range (tuple): Tuple containing the minimum and maximum depth values for filtering depth 3.
+        scale_factor (float): Scaling factor for the magnitude of the current vectors.
         sample (int): Number of vectors used for downsampling.
         depth_2_checkbox (bool, optional): Whether to plot vectors for depth 2. Defaults to False.
         depth_3_checkbox (bool, optional): Whether to plot vectors for depth 3. Defaults to False.
@@ -183,11 +183,11 @@ def vectors_plot(ds, bathy, longitude_slider, latitude_slider,
     ds = corsen_data(ds, sample)
 
     # Plot vectors filtered by depth
-    quiver_depth_filtered(ax, ds, depth_range_slider, scale_factor_slider, color="blue")
+    quiver_depth_filtered(ax, ds, depth_range, scale_factor, color="blue")
     if depth_2_checkbox:
-        quiver_depth_filtered(ax, ds, depth_2_range_slider, scale_factor_slider, color="green")
+        quiver_depth_filtered(ax, ds, depth_2_range, scale_factor, color="green")
     if depth_3_checkbox:
-        quiver_depth_filtered(ax, ds, depth_3_range_slider, scale_factor_slider, color="red")
+        quiver_depth_filtered(ax, ds, depth_3_range, scale_factor, color="red")
 
     # Add map features
     ax.add_feature(cfeature.COASTLINE)
@@ -201,15 +201,14 @@ def vectors_plot(ds, bathy, longitude_slider, latitude_slider,
                    levels=contour_levels, colors="black", transform=ccrs.PlateCarree())
 
     # Set extent and add gridlines
-    ax.set_extent([longitude_slider[0], longitude_slider[1],
-                   latitude_slider[0], latitude_slider[1]])
+    ax.set_extent([longitude_range[0], longitude_range[1],
+                   latitude_range[0], latitude_range[1]])
     ax.gridlines(draw_labels=True)
 
     # Set labels and close plot
     plt.ylabel("Latitude", fontsize=15, labelpad=35)
     plt.xlabel("Longitude", fontsize=15, labelpad=20)
-    plt.figure(figsize=(400, 400))
-    plt.close()
+    plt.close(fig) #https://panel.holoviz.org/reference/panes/Matplotlib.html#using-the-matplotlib-pyplot-interface
 
     return fig
 
@@ -221,47 +220,27 @@ class SADCP_Viewer(param.Parameterized):
     file_names = df["file_name"].tolist()
     years = sorted(df["year"].unique())
 
-    year_slider = pn.widgets.IntRangeSlider(
-        name="Year Range", start=df["year"].min(), end=df["year"].max()
-    )
+    # Widgets
+    year_slider = pn.widgets.IntRangeSlider(name="Year Range", start=df["year"].min(), end=df["year"].max())
     file_dropdown = pn.widgets.Select(name="File Selector")
-    data_table = pn.widgets.Tabulator(df, name="metadata", height=200, width=300)
-    # data_table2 = pn.widgets.Tabulator(df2, name="metadata", height=900, width=400)
-
-    longitude_slider = pn.widgets.RangeSlider(
-        name="Longitude Range", start=-180, end=180, step=1
-    )
-    latitude_slider = pn.widgets.RangeSlider(
-        name="Latitude Range", start=-90, end=90, step=1
-    )
-
-    depth_range_slider = pn.widgets.IntRangeSlider(
-        start=100, end=300, value=(100, 300), step=1, name="Depth Range"
-    )
+    longitude_slider = pn.widgets.RangeSlider(name="Longitude Range", start=-180, end=180, step=1)
+    latitude_slider = pn.widgets.RangeSlider(name="Latitude Range", start=-90, end=90, step=1)
+    depth_range_slider = pn.widgets.IntRangeSlider(start=100, end=300, value=(100, 300), step=1, name="Depth Range")
     depth_2_checkbox = pn.widgets.Checkbox(value=False, name="Depth 2 Checkbox")
     depth_3_checkbox = pn.widgets.Checkbox(value=False, name="Depth 3 Checkbox")
-
-    depth_2_range_slider = pn.widgets.IntRangeSlider(
-        start=100, end=300, value=(100, 300), step=1, name="Depth 2 Range"
-    )
-    depth_3_range_slider = pn.widgets.IntRangeSlider(
-        start=100, end=300, value=(100, 300), step=1, name="Depth 3 Range"
-    )
-
-    num_vectors_slider = pn.widgets.IntSlider(
-        start=40, end=800, step=1, value=100, name="Number of Vectors"
-    )
-    scale_factor_slider = pn.widgets.FloatSlider(
-        start=0.1, end=1, step=0.1, value=0.5, name="Scale Factor"
-    )
+    depth_2_range_slider = pn.widgets.IntRangeSlider(start=100, end=300, value=(100, 300), step=1, name="Depth 2 Range")
+    depth_3_range_slider = pn.widgets.IntRangeSlider(start=100, end=300, value=(100, 300), step=1, name="Depth 3 Range")
+    num_vectors_slider = pn.widgets.IntSlider(start=40, end=800, step=1, value=100, name="Number of Vectors")
+    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)
+#    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 = pn.widgets.Button(name="Download", button_type="primary")
     # plot = pn.Column()
 
@@ -309,19 +288,13 @@ class SADCP_Viewer(param.Parameterized):
             # Load selected file's data
             self.ds = load_zarr(selected_file)
             
-            # Update longitude slider range
-            lon_range = get_range(self.ds.LONGITUDE)
-            self.longitude_slider.start, self.longitude_slider.end, self.longitude_slider.value = lon_range[0], lon_range[1], lon_range
-            
-            # Update latitude slider range
-            lat_range = get_range(self.ds.LATITUDE)
-            self.latitude_slider.start, self.latitude_slider.end, self.latitude_slider.value = lat_range[0], lat_range[1], lat_range
-            
-            # Update depth slider ranges for all three depths
-            depth_range = (int(self.ds.PROFZ.min()), int(self.ds.PROFZ.max()))
-            self.depth_range_slider.start, self.depth_range_slider.end, self.depth_range_slider.value = depth_range[0], depth_range[1], depth_range
-            self.depth_2_range_slider.start, self.depth_2_range_slider.end, self.depth_2_range_slider.value = depth_range[0], depth_range[1], depth_range
-            self.depth_3_range_slider.start, self.depth_3_range_slider.end, self.depth_3_range_slider.value = depth_range[0], depth_range[1], depth_range
+            # Update slider ranges for longitude, latitude, and depth
+            for slider, coord in zip([self.longitude_slider, self.latitude_slider, self.depth_range_slider,
+                          self.depth_2_range_slider, self.depth_3_range_slider],
+                         [self.ds.LONGITUDE, self.ds.LATITUDE, self.ds.PROFZ,self.ds.PROFZ,self.ds.PROFZ]):
+                coord_range = get_range(coord)
+                slider.start, slider.end, slider.value = coord_range[0], coord_range[1], coord_range
+
 
             # Close dataset to free up resources
             # self.update_plots()
@@ -372,7 +345,9 @@ class SADCP_Viewer(param.Parameterized):
         self.plot_left = pn.Column(
                                #  '# Column',
                                #  vector_plot,
-                                 vector_plot, sizing_mode="stretch_both")
+                               pn.pane.Matplotlib(vector_plot, dpi=144),
+                              #   vector_plot,
+                                sizing_mode="stretch_both")
 
         # Generate additional plots which will be plotted on the right row.
         other_plots = self.hvplot_plots()