generate images in different directory

Author: SimonBlanke

.github/workflows/generate-plots.yml

@@ -47,6 +47,6 @@ jobs:
       uses: stefanzweifel/git-auto-commit-action@v5
       with:
         commit_message: "🤖 Auto-update function visualization plots"
-        file_pattern: "doc/images/*.jpg"
+        file_pattern: "doc/images/mathematical/*.jpg doc/images/ml_functions/*.jpg"
         commit_user_name: "github-actions[bot]"
         commit_user_email: "github-actions[bot]@users.noreply.github.com"

scripts/generate_all_plots.py

@@ -17,10 +17,12 @@
 from surfaces.test_functions.mathematical.test_functions_nd import *
 from surfaces.visualize import matplotlib_heatmap, matplotlib_surface
 
-# Ensure output directory exists
+# Ensure output directories exist
 script_dir = os.path.dirname(os.path.abspath(__file__))
-output_dir = os.path.join(script_dir, '..', 'doc', 'images')
-os.makedirs(output_dir, exist_ok=True)
+main_output_dir = os.path.join(script_dir, '..', 'doc', 'images')
+mathematical_output_dir = os.path.join(main_output_dir, 'mathematical')
+os.makedirs(main_output_dir, exist_ok=True)
+os.makedirs(mathematical_output_dir, exist_ok=True)
 
 # Configuration for each function type
 FUNCTION_CONFIGS = {
@@ -163,7 +165,7 @@ def generate_plots():
                 title=f"{func_instance.name} - Heatmap" if hasattr(func_instance, 'name') else f"{func_name} - Heatmap",
                 norm=norm
             )
-            heatmap_path = os.path.join(output_dir, f"{file_name}_heatmap.jpg")
+            heatmap_path = os.path.join(mathematical_output_dir, f"{file_name}_heatmap.jpg")
             heatmap_fig.savefig(heatmap_path, dpi=150, bbox_inches='tight')
             heatmap_fig.close()
 
@@ -175,7 +177,7 @@ def generate_plots():
                 title=f"{func_instance.name} - Surface" if hasattr(func_instance, 'name') else f"{func_name} - Surface",
                 norm=norm
             )
-            surface_path = os.path.join(output_dir, f"{file_name}_surface.jpg")
+            surface_path = os.path.join(mathematical_output_dir, f"{file_name}_surface.jpg")
             surface_fig.savefig(surface_path, dpi=150, bbox_inches='tight')
             surface_fig.close()
 
@@ -185,7 +187,7 @@ def generate_plots():
             print(f"  ✗ Error generating plots for {func_name}: {e}")
             continue
 
-    print(f"\n✓ Mathematical function plot generation complete! Images saved to {output_dir}")
+    print(f"\n✓ Mathematical function plot generation complete! Images saved to {mathematical_output_dir}")
 
     # Generate ML function plots
     print("\nGenerating ML function plots...")

scripts/generate_ml_plots.py

@@ -24,10 +24,12 @@
 
 # Ensure output directories exist
 script_dir = os.path.dirname(os.path.abspath(__file__))
-output_dir = os.path.join(script_dir, '..', 'doc', 'images')
-ml_output_dir = os.path.join(output_dir, 'ml_functions')
-os.makedirs(output_dir, exist_ok=True)
-os.makedirs(ml_output_dir, exist_ok=True)
+main_images_dir = os.path.join(script_dir, '..', 'doc', 'images')
+ml_functions_dir = os.path.join(main_images_dir, 'ml_functions')
+ml_detailed_dir = os.path.join(ml_functions_dir, 'detailed')
+os.makedirs(main_images_dir, exist_ok=True)
+os.makedirs(ml_functions_dir, exist_ok=True)
+os.makedirs(ml_detailed_dir, exist_ok=True)
 
 # ML Function configurations with reduced parameter spaces for faster evaluation
 ML_FUNCTION_CONFIGS = {
@@ -100,9 +102,9 @@ def generate_ml_plots():
         reduced_space = config['reduced_search_space']
         ml_func = create_reduced_ml_function(func_class, reduced_space)
 
-        # Create function-specific output directory
-        func_output_dir = os.path.join(ml_output_dir, ml_func._name_)
-        os.makedirs(func_output_dir, exist_ok=True)
+        # Create function-specific detailed output directory
+        func_detailed_dir = os.path.join(ml_detailed_dir, ml_func._name_)
+        os.makedirs(func_detailed_dir, exist_ok=True)
 
         print(f"Search space: {ml_func.search_space()}")
 
@@ -116,13 +118,13 @@ def generate_ml_plots():
                 title=f"{ml_func.name} - {param1} vs {param2}"
             )
 
-            # Save as image
-            output_path = os.path.join(func_output_dir, f"{param1}_vs_{param2}_heatmap.jpg")
-            fig.write_image(output_path, format="jpeg", width=900, height=700)
+            # Save detailed image
+            detailed_path = os.path.join(func_detailed_dir, f"{param1}_vs_{param2}_heatmap.jpg")
+            fig.write_image(detailed_path, format="jpeg", width=900, height=700)
 
-            # Also save to main images directory for README
-            main_output_path = os.path.join(output_dir, f"{ml_func._name_}_{param1}_vs_{param2}_heatmap.jpg")
-            fig.write_image(main_output_path, format="jpeg", width=900, height=700)
+            # Save main image for README
+            main_path = os.path.join(ml_functions_dir, f"{ml_func._name_}_{param1}_vs_{param2}_heatmap.jpg")
+            fig.write_image(main_path, format="jpeg", width=900, height=700)
 
             print(f"    ✓ Saved {param1} vs {param2} heatmap")
 
@@ -136,21 +138,21 @@ def generate_ml_plots():
                 title=f"{ml_func.name} - Dataset vs {hyperparameter}"
             )
 
-            # Save as image
-            output_path = os.path.join(func_output_dir, f"dataset_vs_{hyperparameter}_analysis.jpg")
-            fig.write_image(output_path, format="jpeg", width=1000, height=700)
+            # Save detailed image
+            detailed_path = os.path.join(func_detailed_dir, f"dataset_vs_{hyperparameter}_analysis.jpg")
+            fig.write_image(detailed_path, format="jpeg", width=1000, height=700)
 
-            # Also save to main images directory for README
-            main_output_path = os.path.join(output_dir, f"{ml_func._name_}_dataset_vs_{hyperparameter}_analysis.jpg")
-            fig.write_image(main_output_path, format="jpeg", width=1000, height=700)
+            # Save main image for README
+            main_path = os.path.join(ml_functions_dir, f"{ml_func._name_}_dataset_vs_{hyperparameter}_analysis.jpg")
+            fig.write_image(main_path, format="jpeg", width=1000, height=700)
 
             print(f"    ✓ Saved dataset vs {hyperparameter} analysis")
 
         print(f"✓ Completed {func_name} analysis")
 
     print(f"\n✓ ML plot generation complete! Images saved to:")
-    print(f"  - Individual function plots: {ml_output_dir}")
-    print(f"  - README plots: {output_dir}")
+    print(f"  - Detailed function plots: {ml_detailed_dir}")
+    print(f"  - README plots: {ml_functions_dir}")
 
 def generate_sample_plots():
     """Generate a few sample plots for testing."""
@@ -175,15 +177,15 @@ def reduced_search_space_method(**kwargs):
         ml_func, 'n_neighbors', 'algorithm',
         title="Sample: KNN Hyperparameter Analysis"
     )
-    fig1.write_image(os.path.join(output_dir, "sample_knn_hyperparams.jpg"), 
+    fig1.write_image(os.path.join(ml_functions_dir, "sample_knn_hyperparams.jpg"), 
                     format="jpeg", width=900, height=700)
 
     print("Creating sample dataset analysis plot...")
     fig2 = plotly_dataset_hyperparameter_analysis(
         ml_func, 'n_neighbors',
         title="Sample: Dataset vs n_neighbors"
     )
-    fig2.write_image(os.path.join(output_dir, "sample_knn_datasets.jpg"), 
+    fig2.write_image(os.path.join(ml_functions_dir, "sample_knn_datasets.jpg"), 
                     format="jpeg", width=1000, height=700)
 
     print("✓ Sample plots generated successfully!")