Test

pages/1-samples_selection.py

@@ -225,12 +225,14 @@ if not spectra.empty:
             ax1 = st.selectbox("Component", options=dr_model.scores_.columns, index=3)
             leverage = dr_model.leverage_
             residuals = dr_model.residuals_
-            fig = px.scatter(x=leverage[ax1], y=residuals[ax1], color = leverage[ax1]*residuals[ax1]).update_layout(xaxis_title="Leverage",yaxis_title="Residuals")
-            st.plotly_chart(fig, use_container_width=True)
+            fig = px.scatter(x=leverage[ax1], y=residuals[ax1], color=leverage[ax1]*residuals[ax1], color_continuous_scale='Blues')
+            fig.update_layout(xaxis_title="Leverage", yaxis_title="Residuals")
+            st.plotly_chart(fig)
             img = pio.to_image(fig, format="png")
-            with open("./Report/figures/Influence_plot.png", "wb") as f:
+            with open("./Report/figures/graphe_influence.png", "wb") as f:
                 f.write(img)
 
+
         with hotelling:
             st.write('T²-Hotelling vs Q residuals plot')
             hotelling = dr_model.hotelling_
@@ -240,7 +242,7 @@ if not spectra.empty:
             fig = px.scatter(t, x=hotelling[ax2], y=residuals[ax2]).update_layout(xaxis_title="T²",yaxis_title="Residuals")
             st.plotly_chart(fig, use_container_width=True)
             fig.write_image("./Report/figures/graphe_hotelling.png", format="png")
-            
+
     if dim_red_method == dim_red_methods[2] and clus_method == cluster_methods[2]: # UMAP clustered by HDBSCAN
         with loadings: # Display some clustering metrics
             st.write('Clustering metrics:')