Remove debug stuff

02_radiomics_features_extraction/extract_features_radiomics.py

@@ -26,7 +26,7 @@ PIXEL_SPACING = [1.0, 2.0, 3.0, 4.0, 5.0]
 #%%
 DATADIR = Path('data') / DATASET / 'processed' / 'bbox' / BBOX
 OUTDIR = Path('data') / DATASET / 'processed'
-OUTFILE = f'radiomics_features_{BBOX}_radnew21.csv'  # output file name
+OUTFILE = f'radiomics_features_{BBOX}.csv'  # output file name
 
 clinical = pd.read_csv(Path('data') / DATASET / 'processed' / f'clinical_{DATASET}.csv')
 
@@ -40,7 +40,7 @@ extractor_intensity = RadiomicsFeatureExtractor(params_intensity)
 params_texture = '02_radiomics_features_extraction/texture_new.yaml'  # param file to use to create the extractor
 extractor_texture = RadiomicsFeatureExtractor(params_texture)
 
-filenames = [f for f in os.listdir(DATADIR) if f.endswith('.npy')][:2]
+filenames = [f for f in os.listdir(DATADIR) if f.endswith('.npy')]
 
 exclude_list = []
 
@@ -60,8 +60,6 @@ def process_file(filename):
             curr_modality.SetSpacing(VOXEL_SPACING)
             modalities.append(curr_modality)
 
-        # print(data[-1, :, :, :] == data[1, :, :, :])
-        # print(np.max(data[-1, :, :, :]))
         has_label = np.max(data[-1, :, :, :]) > 0
 
         if has_label:
@@ -89,29 +87,32 @@ def process_file(filename):
                         for NB in N_BINS:
                             if not broken:
                                 extractor_texture.settings['binCount'] = NB
-
-                                # uniform binning
-                                extractor_texture.settings['binMode'] = 'uniform'
-
-                                result = extractor_texture.execute(
-                                    modality, segmentation
-                                )
-                                for key, value in result.items():
-                                    if not key.startswith("general_"):
-                                        feature[
-                                            f'{key}_{P}_{NB}_uniform_{name}'
-                                        ] = result[key]
-
-                                # equalized binning
-                                extractor_texture.settings['binMode'] = 'equal'
-                                result = extractor_texture.execute(
-                                    modality, segmentation
-                                )
-                                for key, value in result.items():
-                                    if not key.startswith("general_"):
-                                        feature[
-                                            f'{key}_{P}_{NB}_equalized_{name}'
-                                        ] = result[key]
+                                try:
+                                    # uniform binning
+                                    extractor_texture.settings['binMode'] = 'uniform'
+
+                                    result = extractor_texture.execute(
+                                        modality, segmentation
+                                    )
+                                    for key, value in result.items():
+                                        if not key.startswith("general_"):
+                                            feature[
+                                                f'{key}_{P}_{NB}_uniform_{name}'
+                                            ] = result[key]
+
+                                    # equalized binning
+                                    extractor_texture.settings['binMode'] = 'equal'
+                                    result = extractor_texture.execute(
+                                        modality, segmentation
+                                    )
+                                    for key, value in result.items():
+                                        if not key.startswith("general_"):
+                                            feature[
+                                                f'{key}_{P}_{NB}_equalized_{name}'
+                                            ] = result[key]
+                                except Exception as e:
+                                    print(e)
+                                    broken = True
 
             if not broken:
                 feature['filename'] = filename
@@ -126,18 +127,16 @@ def process_file(filename):
 
 
 #%% MULTIPROCESS
-result = []
-for file in filenames:
-    feat = process_file(file)
-    result.append(feat)
+# result = []
+# for file in filenames:
+#    feat = process_file(file)
+#    result.append(feat)
 
 
 # %%
-
-
-# multiproc = ListMultiprocessing(process_file, N_JOBS)
-# multiproc.execute(filenames)
-# result = multiproc.get_result()
+multiproc = ListMultiprocessing(process_file, N_JOBS)
+multiproc.execute(filenames)
+result = multiproc.get_result()
 
 # print('done')
 #%% Save features in a Pandas df
@@ -148,6 +147,4 @@ print('Number of files: ', features.shape[0])
 print('Number of features: ', features.shape[1] - 1)
 # %%
 features.to_csv(OUTDIR / OUTFILE)
-
-
 # %%