Update app.py

app.py

@@ -130,9 +130,9 @@ if len(gene_list) > 1:
     df_shap = df_total[df_total.index.isin(gene_list)]
     df_shap.drop(columns='XGB_Score', inplace=True)
     shap_values = explainer.shap_values(df_shap)
-    #summary_plot = shap.summary_plot(shap_values, df_shap)
-    #st.caption("SHAP Summary Plot of All Input Genes")
-    #st.pyplot(fig=summary_plot)
+    summary_plot = shap.summary_plot(shap_values, df_shap)
+    st.caption("SHAP Summary Plot of All Input Genes")
+    st.pyplot(fig=summary_plot)
     st.caption("Interactive SHAP Summary Plot of All Input Genes")
     mpl_fig = shap_summary_plot(shap_values, df_shap, max_display=8, show=False, feature_names=df_shap.columns)
     plotly_fig = tls.mpl_to_plotly(mpl_fig)
@@ -150,6 +150,7 @@ if len(gene_list) > 1:
         plotly_fig['data'][i]['hoverinfo'] = 'text'
     colorbar_trace  = go.Scatter(x=[None],
                                  y=col_order, # [None],
+                                 visible=True,
                                  mode='markers',
                                  marker=dict(
                                      colorscale=red_blue, 
@@ -165,7 +166,7 @@ if len(gene_list) > 1:
     plotly_fig['layout']['height']=600
     plotly_fig['layout']['width']=500
     plotly_fig['layout']['xaxis'].update(zeroline=True, showline=True, ticklen=4, showgrid=False)
-    plotly_fig['layout']['yaxis'].update(dict(visible=True))
+    plotly_fig['layout']['yaxis'].update(y=col_order, dict(visible=True))
     plotly_fig.add_trace(colorbar_trace)
     plotly_fig.layout.update(
                              annotations=[dict(