Update component plots when selecting data about explainerdashboard HOT 3 CLOSED

Hello, and sorry for the late response. I think I didn't explain properly what the problem was. What I want to do basically is to update the plot ShapSummaryComponent with a callback in my custom tab. Whenever I select an area in the preds_map, a new explainer should be created with the filtered data within the map, changing the calculated shap values of the features. WIth this new explainer, I would like to update the ShapSummaryComponent in order to provide insights about particular areas and which features had the biggest impact in these specific areas. Is this possible? Thanks in advance.

UPDATE: I managed to do it. What I did was basically use a callback in my map that recalculates the shap values for the selected area, re calculates the explainer and sets the new explainer for the shap summary component and updates a hidden "P" html element once its finished its calculations.
Then I added in the update_shap_summary_graph another input with this element that I named "shap-hidden-trigger" and every time this element changes, the callback is called again with the new explainer.

shap_components.py

        @app.callback(
            [
                Output("shap-summary-graph-" + self.name, "figure"),
                Output("shap-summary-index-col-" + self.name, "style"),
            ],
            [
                Input("shap-summary-type-" + self.name, "value"),
                Input("shap-summary-depth-" + self.name, "value"),
                Input("shap-summary-index-" + self.name, "value"),
                Input("pos-label-" + self.name, "value"),
                Input("shap-hidden-trigger", "children"),
            ],
        )
        def update_shap_summary_graph(summary_type, depth, index, pos_label, hidden_trigger):
         #rest of the code

my_custom_layout.py

  @app.callback(
            Output('shap-hidden-trigger', 'children'),
            Input('update-shap-button', 'n_clicks'),
            State('preds-map', 'selectedData'),
            prevent_initial_call=True,
        )
        def update_shap_summary(change_settings, selectedData):
             #some processing of the data that I skipped

                shap_explainer = shap.Explainer(predictor)
                shap_values = shap_explainer.shap_values(
                    new_X, 
                    check_additivity=False, 
                    approximate=False
                )
                base_values = shap_explainer.expected_value
                new_explainer = ClassifierExplainer(model=predictor, X=new_X, n_jobs=-1, index_name="Block ID", 
                                                    precision="float32", target="DEPVAR")
                new_explainer.set_shap_values(base_values, shap_values)
                self.shap_summary.explainer = new_explainer
                return "Turing" #just updating to whatever since its hidden

Thanks!

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Please show a screenshot or copy of the error you get, once we can see what your output is I could pair program with you to see if I can help.

from explainerdashboard.

It looks like you are reinstantiating all the sub components every time there is an update? I don't think that will work. All the components have to be there at the start of the dash app, and then the callbacks update the properties of the components, so the self.update_components() line is probably that breaks things. So get rid of that. The shap values have already been pre-calculated in the explainer that gets passed to the component, so you never reinstantiate the explainer and then recalculate.

So the callback should probably target Output('preds_map', 'figure') instead and then you simply generate the right plot for a subsample.

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