#17 fix colors of piechart

app/index.py

@@ -211,11 +211,23 @@ def add_branch_information_to_dataframe(df: pd.DataFrame) -> pd.DataFrame:
 
 
 def create_plotly_figure_piechart(data_dict: dict) -> plotly.graph_objects.Figure:
+    marker_colors = []
+    for label in data_dict.keys():
+        if label == 'Scope 1':
+            marker_colors.append('#33cc33')  # Color for Scope 1
+        elif label == 'Scope 2':
+            marker_colors.append('#ffcc00')  # Color for Scope 2
+        elif label == 'Scope 3':
+            marker_colors.append('#3366ff')  # Color for Scope 3
+        else:
+            marker_colors.append('#000000')  # Default color for other labels
+
     plotly_figure = plotly.graph_objects.Figure(
         data=[
             plotly.graph_objects.Pie(
-                labels=[label for label in data_dict.keys()],
-                values=[value for value in data_dict.values()]
+                labels=list(data_dict.keys()),
+                values=list(data_dict.values()),
+                marker=dict(colors=marker_colors)  # Set the colors for the pie chart
             )
         ]
     )
@@ -564,6 +576,7 @@ def button_action_scope_analysis(event):
         else:
             if widget_float_slider_cutoff.value / 100 != panel_lca_class_instance.graph_traversal_cutoff:
                 perform_graph_traversal(event)
+                perform_scope_analysis(event)
             else:
                 panel_lca_class_instance.df_graph_traversal_nodes = widget_tabulator.value
                 perform_scope_analysis(event)
@@ -631,7 +644,7 @@ def button_action_scope_analysis(event):
 
 # https://panel.holoviz.org/reference/widgets/Button.html
 widget_button_graph = pn.widgets.Button(
-    name='Perform Scope Analysis',
+    name='Re-Perform Scope Analysis',
     icon='chart-donut-3',
     button_type='primary',
     sizing_mode='stretch_width'

dev/scope.py

@@ -30,9 +30,16 @@
     location = 'United States'
 )
 
+bike_act = bd.utils.get_node(
+    database = 'USEEIO-1.1',
+    name = 'Motorcycle, bicycle, and parts; at manufacturer',
+    type = 'product',
+    location = 'United States'
+)
+
 method_gcc = bd.Method(('Impact Potential', 'GCC'))
 lca = bc.LCA( 
-    demand={electricity_activity: 1}, 
+    demand={bike_act: 1}, 
     method = method_gcc.name # attention here: it's not the Method object, just its name!!!
 ) 
 lca.lci() 
@@ -68,6 +75,7 @@ def nodes_dict_to_dataframe(nodes: dict) -> pd.DataFrame:
                 'Cumulative': current_node.cumulative_score,
                 'Direct': current_node.direct_emissions_score,
                 'Depth': current_node.depth,
+                'activity_datapackage_id': current_node.activity_datapackage_id
             }
         )
     return pd.DataFrame(list_of_row_dicts)
@@ -118,8 +126,8 @@ def determine_scope_1_and_2_emissions(df: pd.DataFrame, uid_scope_2: int = 53) -
         dict_scope['Scope 2'] = df.loc[
             (df['Depth'] == 2)
             &
-            (df['UID'] == uid_scope_2)
-        ]['Cumulative'].values[0]
+            (df['activity_datapackage_id'] == uid_scope_2)
+        ]['Direct'].values[0]
     except:
         pass