diff pycaret_regression.py @ 0:1f20fe57fdee draft

planemo upload for repository https://github.com/goeckslab/Galaxy-Pycaret commit d79b0f722b7d09505a526d1a4332f87e548a3df1

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pycaret_regression.py	Wed Dec 11 04:59:43 2024 +0000
@@ -0,0 +1,134 @@
+import logging
+
+from base_model_trainer import BaseModelTrainer
+
+from dashboard import generate_regression_explainer_dashboard
+
+from pycaret.regression import RegressionExperiment
+
+from utils import add_hr_to_html, add_plot_to_html
+
+LOG = logging.getLogger(__name__)
+
+
+class RegressionModelTrainer(BaseModelTrainer):
+    def __init__(
+            self,
+            input_file,
+            target_col,
+            output_dir,
+            task_type,
+            random_seed,
+            test_file=None,
+            **kwargs):
+        super().__init__(
+            input_file,
+            target_col,
+            output_dir,
+            task_type,
+            random_seed,
+            test_file,
+            **kwargs)
+        self.exp = RegressionExperiment()
+
+    def save_dashboard(self):
+        LOG.info("Saving explainer dashboard")
+        dashboard = generate_regression_explainer_dashboard(self.exp,
+                                                            self.best_model)
+        dashboard.save_html("dashboard.html")
+
+    def generate_plots(self):
+        LOG.info("Generating and saving plots")
+        plots = ['residuals', 'error', 'cooks',
+                 'learning', 'vc', 'manifold',
+                 'rfe', 'feature', 'feature_all']
+        for plot_name in plots:
+            try:
+                plot_path = self.exp.plot_model(self.best_model,
+                                                plot=plot_name, save=True)
+                self.plots[plot_name] = plot_path
+            except Exception as e:
+                LOG.error(f"Error generating plot {plot_name}: {e}")
+                continue
+
+    def generate_plots_explainer(self):
+        LOG.info("Generating and saving plots from explainer")
+
+        from explainerdashboard import RegressionExplainer
+
+        X_test = self.exp.X_test_transformed.copy()
+        y_test = self.exp.y_test_transformed
+
+        explainer = RegressionExplainer(self.best_model, X_test, y_test)
+        self.expaliner = explainer
+        plots_explainer_html = ""
+
+        try:
+            fig_importance = explainer.plot_importances()
+            plots_explainer_html += add_plot_to_html(fig_importance)
+            plots_explainer_html += add_hr_to_html()
+        except Exception as e:
+            LOG.error(f"Error generating plot importance: {e}")
+
+        try:
+            fig_importance_permutation = \
+                explainer.plot_importances_permutation(
+                    kind="permutation")
+            plots_explainer_html += add_plot_to_html(
+                fig_importance_permutation)
+            plots_explainer_html += add_hr_to_html()
+        except Exception as e:
+            LOG.error(f"Error generating plot importance permutation: {e}")
+
+        try:
+            for feature in self.features_name:
+                fig_shap = explainer.plot_pdp(feature)
+                plots_explainer_html += add_plot_to_html(fig_shap)
+                plots_explainer_html += add_hr_to_html()
+        except Exception as e:
+            LOG.error(f"Error generating plot shap dependence: {e}")
+
+        # try:
+        #     for feature in self.features_name:
+        #         fig_interaction = explainer.plot_interaction(col=feature)
+        #         plots_explainer_html += add_plot_to_html(fig_interaction)
+        # except Exception as e:
+        #     LOG.error(f"Error generating plot shap interaction: {e}")
+
+        try:
+            for feature in self.features_name:
+                fig_interactions_importance = \
+                    explainer.plot_interactions_importance(
+                        col=feature)
+                plots_explainer_html += add_plot_to_html(
+                    fig_interactions_importance)
+                plots_explainer_html += add_hr_to_html()
+        except Exception as e:
+            LOG.error(f"Error generating plot shap summary: {e}")
+
+        # Regression specific plots
+        try:
+            fig_pred_actual = explainer.plot_predicted_vs_actual()
+            plots_explainer_html += add_plot_to_html(fig_pred_actual)
+            plots_explainer_html += add_hr_to_html()
+        except Exception as e:
+            LOG.error(f"Error generating plot prediction vs actual: {e}")
+
+        try:
+            fig_residuals = explainer.plot_residuals()
+            plots_explainer_html += add_plot_to_html(fig_residuals)
+            plots_explainer_html += add_hr_to_html()
+        except Exception as e:
+            LOG.error(f"Error generating plot residuals: {e}")
+
+        try:
+            for feature in self.features_name:
+                fig_residuals_vs_feature = \
+                    explainer.plot_residuals_vs_feature(feature)
+                plots_explainer_html += add_plot_to_html(
+                    fig_residuals_vs_feature)
+                plots_explainer_html += add_hr_to_html()
+        except Exception as e:
+            LOG.error(f"Error generating plot residuals vs feature: {e}")
+
+        self.plots_explainer_html = plots_explainer_html