Updated efd and regionprops to match the new score_df return type (linear + randomforest)

Author: afoix

scripts/shapeembed/efd.py

@@ -86,9 +86,10 @@ def run_elliptic_fourier_descriptors(dataset, contour_size, logger):
   efd_df.to_csv(f"{clargs.output_dir}/{dataset.name}-efd-raw_df.csv")
   umap_plot(efd_df, f'{dataset.name}-efd', outputdir=clargs.output_dir)
 
-  efd_cm, efd_score_df = score_dataframe(efd_df, 'efd')
+  efd_cms, efd_score_df = score_dataframe(efd_df, 'efd')
 
   logger.info(f'-- efd on {dataset.name}, score\n{efd_score_df}')
   efd_score_df.to_csv(f"{clargs.output_dir}/{dataset.name}-efd-score_df.csv")
-  logger.info(f'-- confusion matrix:\n{efd_cm}')
-  confusion_matrix_plot(efd_cm, f'{dataset.name}-efd', clargs.output_dir)
+  for kind, efd_cm in efd_cms.items():
+    logger.info(f'-- {kind} confusion matrix:\n{efd_cm}')
+    confusion_matrix_plot(efd_cm, f'{dataset.name}-{kind}-efd', clargs.output_dir)

scripts/shapeembed/regionprops.py

@@ -91,9 +91,10 @@ def run_regionprops( dataset
   regionprops_df.to_csv(f"{clargs.output_dir}/{dataset.name}-regionprops-raw_df.csv")
   umap_plot(regionprops_df, f'{dataset.name}-regionprops', outputdir=clargs.output_dir)
 
-  regionprops_cm, regionprops_score_df = score_dataframe(regionprops_df, 'regionprops')
+  regionprops_cms, regionprops_score_df = score_dataframe(regionprops_df, 'regionprops')
 
   logger.info(f'-- regionprops on {dataset.name}, score\n{regionprops_score_df}')
   regionprops_score_df.to_csv(f"{clargs.output_dir}/{dataset.name}-regionprops-score_df.csv")
-  logger.info(f'-- confusion matrix:\n{regionprops_cm}')
-  confusion_matrix_plot(regionprops_cm, f'{dataset.name}-regionprops', clargs.output_dir)
+  for kind, regionprops_cm in regionprops_cms.items():
+    logger.info(f'-- {kind} confusion matrix:\n{regionprops_cm}')
+    confusion_matrix_plot(regionprops_cm, f'{dataset.name}-{kind}-regionprops', clargs.output_dir)