show corr plot on button click

folding_studio_demo/app.py

@@ -10,7 +10,7 @@ from gradio_molecule3d import Molecule3D
 from folding_studio_demo.correlate import (
     SCORE_COLUMNS,
     fake_predict_and_correlate,
-    select_correlation_plot,
+    make_correlation_plot,
 )
 from folding_studio_demo.predict import predict, predict_comparison
 
@@ -187,7 +187,7 @@ def create_correlation_tab():
     with gr.Row():
         # User can select the columns to display in the correlation plot
         correlation_column = gr.Dropdown(
-            label="Score data to display", choices=SCORE_COLUMNS, multiselect=False
+            label="Score data to display", choices=SCORE_COLUMNS, multiselect=False, value=SCORE_COLUMNS[0]
         )
         correlation_plot = gr.Plot(label="Correlation with binding affinity")
 
@@ -196,12 +196,12 @@ def create_correlation_tab():
             spr_data_with_scores, SCORE_COLUMNS, ["Antibody Name", "KD (nM)"]
         ),
         inputs=None,
-        outputs=[prediction_dataframe, correlation_ranking_plot],
+        outputs=[prediction_dataframe, correlation_ranking_plot, correlation_plot],
     )
 
     # Call function to update the correlation plot when the user selects the columns
     correlation_column.change(
-        fn=lambda score: select_correlation_plot(spr_data_with_scores, score),
+        fn=lambda score: make_correlation_plot(spr_data_with_scores, score),
         inputs=correlation_column,
         outputs=correlation_plot,
     )

folding_studio_demo/correlate.py

@@ -68,9 +68,11 @@ def fake_predict_and_correlate(spr_data_with_scores: pd.DataFrame, score_cols: l
     cols_to_show = main_cols[:]
     cols_to_show.extend(score_cols)
 
-    return spr_data_with_scores[cols_to_show].round(2), corr_ranking_plot
+    corr_plot = make_correlation_plot(spr_data_with_scores, score_cols[0])
 
-def select_correlation_plot(spr_data_with_scores: pd.DataFrame, score: str) -> go.Figure:
+    return spr_data_with_scores[cols_to_show].round(2), corr_ranking_plot, corr_plot
+
+def make_correlation_plot(spr_data_with_scores: pd.DataFrame, score: str) -> go.Figure:
     """Select the correlation plot to display."""
     # corr_plot is a scatter plot of the correlation between the binding affinity and each of the scores
     scatter =  go.Scatter(