Update app.py

app.py

@@ -78,36 +78,6 @@ def convert_df(df):
    return df.to_csv(index=False).encode('utf-8')
 
 
-cdict1 = {
-    'red': ((0.0, 0.11764705882352941, 0.11764705882352941),
-            (1.0, 0.9607843137254902, 0.9607843137254902)),
-
-    'green': ((0.0, 0.5333333333333333, 0.5333333333333333),
-              (1.0, 0.15294117647058825, 0.15294117647058825)),
-
-    'blue': ((0.0, 0.8980392156862745, 0.8980392156862745),
-             (1.0, 0.3411764705882353, 0.3411764705882353)),
-
-    'alpha': ((0.0, 1, 1),
-              (0.5, 1, 1),
-              (1.0, 1, 1))
-}  # #1E88E5 -> #ff0052
-red_blue = LinearSegmentedColormap('RedBlue', cdict1)
-
-'''
-def matplotlib_to_plotly(cmap, pl_entries):
-    h = 1.0/(pl_entries-1)
-    pl_colorscale = []
-
-    for k in range(pl_entries):
-        C = list(map(np.uint8, np.array(cmap(k*h)[:3])*255))
-        pl_colorscale.append([k*h, 'rgb'+str((C[0], C[1], C[2]))])
-
-    return pl_colorscale
-
-red_blue = matplotlib_to_plotly(red_blue, 255)
-'''
-
 if len(gene_list) > 1:
     df = df_total[df_total.index.isin(gene_list)]
     df['Gene'] = df.index
@@ -137,60 +107,6 @@ if len(gene_list) > 1:
     feature_order = np.argsort(np.sum(np.abs(shap_values), axis=0)[:-1])
     feature_order = feature_order[-min(8, len(feature_order)):]
     col_order = [df_shap.columns[i] for i in feature_order]
-    '''
-    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=col_order)
-    plotly_fig = tls.mpl_to_plotly(mpl_fig)
-    plotly_fig['layout'] = {'xaxis': {'title': 'SHAP value (impact on model output)'}}
-    max_display=8
-    feature_names=df_shap.columns
-    gene_index = df_shap.index
-    for i in range(1, len(plotly_fig['data']), 2):
-        t = gene_index #plotly_fig['data']
-        plotly_fig['data'][i]['name'] = ''
-        plotly_fig['data'][i]['text'] = t
-        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, 
-                                     showscale=True,
-                                     cmin=-5,
-                                     cmax=5,
-                                     colorbar=dict(thickness=5, tickvals=[-5, 5], ticktext=['Low', 'High'], outlinewidth=0)
-                                 ),
-                                 hoverinfo='none'
-                                )
-    plotly_fig['layout']['showlegend'] = False
-    plotly_fig['layout']['hovermode'] = 'closest' 
-    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.add_trace(colorbar_trace)
-    plotly_fig.layout.update(
-                             annotations=[dict(
-                                  x=1.18,
-                                  align="right",
-                                  valign="top",
-                                  text='Feature value',
-                                  showarrow=False,
-                                  xref="paper",
-                                  yref="paper",
-                                  xanchor="right",
-                                  yanchor="middle",
-                                  textangle=-90,
-                                  font=dict(family='Calibri', size=14),
-                                )
-                             ],
-                             margin=dict(t=20)
-                            )
-
-
-    st.plotly_chart(plotly_fig)
-'''
 else:
     pass