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laura/ntlab_create_dataset_description_json.py

+import json
+from collections import OrderedDict
+
+def create_dataset_description_json(path, name, bids_version="1.7.0", hed_version=None,
+                             dataset_type='raw', dataset_links=None, data_license=None,
+                             authors=None, acknowledgements=None,
+                             how_to_acknowledge=None, funding=None,
+                             ethics_approvals=None, references_and_links=None,
+                             doi=None, generated_by=None, source_datasets=None):
+
+    # Prepare dataset_description.json
+    description = OrderedDict([
+    ('Name', name),
+    ('BIDSVersion', bids_version),
+    ('HEDVersion', hed_version),
+    ('DatasetType', dataset_type),
+    ('DatasetLinks', dataset_links),
+    ('License', data_license),
+    ('Authors', authors),
+    ('Acknowledgements', acknowledgements),
+    ('HowToAcknowledge', how_to_acknowledge),
+    ('Funding', funding),
+    ('EthicsApprovals', ethics_approvals),
+    ('ReferencesAndLinks', references_and_links),
+    ('DatasetDOI', doi),
+    ('GeneratedBy', generated_by),
+    ('SourceDatasets', source_datasets)])
+
+    # Remove None values
+    pop_keys = [key for key, val in description.items() if val is None]
+    for key in pop_keys:
+        description.pop(key)
+    
+    # Only write data that is not None
+    with open(path, 'w') as outfile:
+        json.dump(description, outfile, indent=4)
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