[DATALAD RUNCMD] Do interactive fixing of some ambigous typos

=== Do not change lines below ===
{
 "chain": [],
 "cmd": "codespell -w -i 3 -C 2",
 "exit": 0,
 "extra_inputs": [],
 "inputs": [],
 "outputs": [],
 "pwd": "."
}
^^^ Do not change lines above ^^^

Author: yarikoptic

nnunetv2/evaluation/evaluate_predictions.py

@@ -227,7 +227,7 @@ def evaluate_folder_entry_point():
                         help='Output file. Optional. Default: pred_folder/summary.json')
     parser.add_argument('-np', type=int, required=False, default=default_num_processes,
                         help=f'number of processes used. Optional. Default: {default_num_processes}')
-    parser.add_argument('--chill', action='store_true', help='dont crash if folder_pred doesnt have all files that are present in folder_gt')
+    parser.add_argument('--chill', action='store_true', help='dont crash if folder_pred does not have all files that are present in folder_gt')
     args = parser.parse_args()
     compute_metrics_on_folder2(args.gt_folder, args.pred_folder, args.djfile, args.pfile, args.o, args.np, chill=args.chill)
 
@@ -245,7 +245,7 @@ def evaluate_simple_entry_point():
                         help='Output file. Optional. Default: pred_folder/summary.json')
     parser.add_argument('-np', type=int, required=False, default=default_num_processes,
                         help=f'number of processes used. Optional. Default: {default_num_processes}')
-    parser.add_argument('--chill', action='store_true', help='dont crash if folder_pred doesnt have all files that are present in folder_gt')
+    parser.add_argument('--chill', action='store_true', help='dont crash if folder_pred does not have all files that are present in folder_gt')
 
     args = parser.parse_args()
     compute_metrics_on_folder_simple(args.gt_folder, args.pred_folder, args.l, args.o, args.np, args.il, chill=args.chill)

nnunetv2/inference/export_prediction.py

@@ -31,7 +31,7 @@ def convert_predicted_logits_to_segmentation_with_correct_shape(predicted_logits
                                             properties_dict['shape_after_cropping_and_before_resampling'],
                                             current_spacing,
                                             properties_dict['spacing'])
-    # return value of resampling_fn_probabilities can be ndarray or Tensor but that doesnt matter because
+    # return value of resampling_fn_probabilities can be ndarray or Tensor but that does not matter because
     # apply_inference_nonlin will convert to torch
     predicted_probabilities = label_manager.apply_inference_nonlin(predicted_logits)
     del predicted_logits

nnunetv2/postprocessing/remove_connected_components.py

@@ -71,7 +71,7 @@ def determine_postprocessing(folder_predictions: str,
     if plans_file_or_dict is None:
         expected_plans_file = join(folder_predictions, 'plans.json')
         if not isfile(expected_plans_file):
-            raise RuntimeError(f"Expected plans file missing: {expected_plans_file}. The plans fils should have been "
+            raise RuntimeError(f"Expected plans file missing: {expected_plans_file}. The plans files should have been "
                                f"created while running nnUNetv2_predict. Sadge.")
         plans_file_or_dict = load_json(expected_plans_file)
     plans_manager = PlansManager(plans_file_or_dict)
@@ -80,7 +80,7 @@ def determine_postprocessing(folder_predictions: str,
         expected_dataset_json_file = join(folder_predictions, 'dataset.json')
         if not isfile(expected_dataset_json_file):
             raise RuntimeError(
-                f"Expected plans file missing: {expected_dataset_json_file}. The plans fils should have been "
+                f"Expected plans file missing: {expected_dataset_json_file}. The plans files should have been "
                 f"created while running nnUNetv2_predict. Sadge.")
         dataset_json_file_or_dict = load_json(expected_dataset_json_file)
 

nnunetv2/training/dataloading/nnunet_dataset.py

@@ -123,7 +123,7 @@ def load_case(self, key):
 
     # this should have the properties
     ds = nnUNetDataset(folder, num_images_properties_loading_threshold=1000)
-    # now rename the properties file so that it doesnt exist anymore
+    # now rename the properties file so that it does not exist anymore
     shutil.move(join(folder, 'liver_0.pkl'), join(folder, 'liver_XXX.pkl'))
     # now we should still be able to access the properties because they have already been loaded
     ks = ds['liver_0'].keys()
@@ -133,7 +133,7 @@ def load_case(self, key):
 
     # this should not have the properties
     ds = nnUNetDataset(folder, num_images_properties_loading_threshold=0)
-    # now rename the properties file so that it doesnt exist anymore
+    # now rename the properties file so that it does not exist anymore
     shutil.move(join(folder, 'liver_0.pkl'), join(folder, 'liver_XXX.pkl'))
     # now this should crash
     try:

nnunetv2/utilities/dataset_name_id_conversion.py

@@ -70,5 +70,5 @@ def maybe_convert_to_dataset_name(dataset_name_or_id: Union[int, str]) -> str:
         except ValueError:
             raise ValueError("dataset_name_or_id was a string and did not start with 'Dataset' so we tried to "
                              "convert it to a dataset ID (int). That failed, however. Please give an integer number "
-                             "('1', '2', etc) or a correct tast name. Your input: %s" % dataset_name_or_id)
-    return convert_id_to_dataset_name(dataset_name_or_id)
+                             "('1', '2', etc) or a correct dataset name. Your input: %s" % dataset_name_or_id)
+    return convert_id_to_dataset_name(dataset_name_or_id)