correction of lookup label

bids2openminds/converter.py

@@ -3,12 +3,13 @@
 from openminds import Collection
 import os
 import click
+import re
 from . import main
 from . import utility
 from . import report
 
 
-def convert(input_path,  save_output=False, output_path=None, multiple_files=False, include_empty_properties=False, quiet=False):
+def convert(input_path,  save_output=False, output_path=None, multiple_files=False, include_empty_properties=False, quiet=False, short_name=None):
     if not (os.path.isdir(input_path)):
         raise NotADirectoryError(
             f"The input directory is not valid, you have specified {input_path} which is not a directory."
@@ -32,8 +33,42 @@ def convert(input_path,  save_output=False, output_path=None, multiple_files=Fal
 
     dataset_description = utility.read_json(dataset_description_path.iat[0, 0])
 
+    if short_name is None:
+        while True:
+            input_name = input(
+                "To convert this dataset, a short name is required.\n"
+                "Please enter an informative short name (less than 10 characters).\n"
+                "If you don't want to assign one now, press Enter, "
+                "lookup labels and internal identifiers will be the same.\n> "
+            ).strip()
+
+            # User pressed Enter → skip assigning
+            if not input_name:
+                short_name = None
+                break
+
+            # Check length
+            if len(input_name) < 10:
+                short_name = input_name
+                break
+            else:
+                print(
+                    "The short name must be fewer than 10 characters. Please try again.\n")
+
+    elif short_name is False:
+        # Explicit opt-out — skip prompt
+        short_name = None
+
+    else:
+        # Ensure the short name has no spaces and is under 10 characters
+        short_name = short_name.replace(" ", "")
+        if len(short_name) > 10:
+            while len(short_name) > 10:
+                short_name = input(
+                    "The short name must be fewer than 10 characters. Please try again.").strip()
+
     [subjects_dict, subject_state_dict, subjects_list] = main.create_subjects(
-        subjects_id, layout_df, bids_layout, collection)
+        subjects_id, layout_df, bids_layout, collection, short_name)
 
     behavioral_protocols, behavioral_protocols_dict = main.create_behavioral_protocol(
         bids_layout, collection)
@@ -42,10 +77,10 @@ def convert(input_path,  save_output=False, output_path=None, multiple_files=Fal
         layout_df, input_path, collection)
 
     dataset_version = main.create_dataset_version(
-        bids_layout, dataset_description, layout_df, subjects_list, file_repository, behavioral_protocols, collection)
+        bids_layout, dataset_description, layout_df, subjects_list, file_repository, behavioral_protocols, short_name, collection)
 
     dataset = main.create_dataset(
-        dataset_description, dataset_version, collection)
+        dataset_description, dataset_version, short_name, collection)
 
     failures = collection.validate(ignore=["required", "value"])
     assert len(failures) == 0
@@ -60,9 +95,13 @@ def convert(input_path,  save_output=False, output_path=None, multiple_files=Fal
         collection.save(output_path, individual_files=multiple_files,
                         include_empty_properties=include_empty_properties)
 
+        save_text = f"the openMINDS file is in {output_path}"
+    else:
+        save_text = save_text = "No files were saved; the function returned the output collection instead."
+
     if not quiet:
         print(report.create_report(dataset, dataset_version, collection,
-                                   dataset_description, input_path, output_path))
+                                   dataset_description, input_path, save_text))
 
     else:
         print("Conversion was successful")
@@ -77,9 +116,10 @@ def convert(input_path,  save_output=False, output_path=None, multiple_files=Fal
 @click.option("--multiple-files", "multiple_files", flag_value=True, help="Each node is saved into a separate file within the specified directory. 'output-path' if specified, must be a directory.")
 @click.option("-e", "--include-empty-properties", is_flag=True, default=False, help="Whether to include empty properties in the final file.")
 @click.option("-q", "--quiet", is_flag=True, default=False, help="Not generate the final report and no warning.")
-def convert_click(input_path, output_path, multiple_files, include_empty_properties, quiet):
+@click.option("-n", "--short-name", default=None, help="Short name for the dataset (less than 10 characters). If None, you'll be prompted (default); if False, no short name will be assigned.")
+def convert_click(input_path, output_path, multiple_files, include_empty_properties, quiet, short_name):
     convert(input_path, save_output=True, output_path=output_path,
-            multiple_files=multiple_files, include_empty_properties=include_empty_properties, quiet=quiet)
+            multiple_files=multiple_files, include_empty_properties=include_empty_properties, quiet=quiet, short_name=short_name)
 
 
 if __name__ == "__main__":

bids2openminds/main.py

@@ -184,7 +184,7 @@ def create_openminds_age(data_subject):
         return None
 
 
-def create_dataset_version(bids_layout, dataset_description, layout_df, studied_specimens, file_repository, behavioral_protocols, collection):
+def create_dataset_version(bids_layout, dataset_description, layout_df, studied_specimens, file_repository, behavioral_protocols, short_name, collection):
 
     # Fetch the dataset type from dataset description file
 
@@ -236,7 +236,7 @@ def create_dataset_version(bids_layout, dataset_description, layout_df, studied_
     dataset_version = omcore.DatasetVersion(
         digital_identifier=digital_identifier,
         experimental_approaches=experimental_approaches,
-        short_name=dataset_description["Name"],
+        short_name=short_name,
         full_name=dataset_description["Name"],
         studied_specimens=studied_specimens,
         authors=authors,
@@ -254,13 +254,13 @@ def create_dataset_version(bids_layout, dataset_description, layout_df, studied_
     return dataset_version
 
 
-def create_dataset(dataset_description, dataset_version, collection):
+def create_dataset(dataset_description, dataset_version, short_name, collection):
 
     dataset = omcore.Dataset(
         digital_identifier=dataset_version.digital_identifier,
         authors=dataset_version.authors,
         full_name=dataset_version.full_name,
-        short_name=dataset_version.short_name,
+        short_name=short_name,
         has_versions=dataset_version
     )
 
@@ -315,7 +315,13 @@ def sex_openminds(data_subject: pd.DataFrame):
         return None
 
 
-def create_subjects(subject_id, layout_df, layout, collection):
+def create_subjects(subject_id, layout_df, layout, collection, dataset_short_name):
+
+    if dataset_short_name:
+        dataset_short_name_ = dataset_short_name + "_"
+    else:
+        # If there is no short name, assign an empty string so lookup labels don’t include it
+        dataset_short_name_ = ""
 
     sessions = layout.get_sessions()
     subjects_dict = {}
@@ -333,9 +339,8 @@ def create_subjects(subject_id, layout_df, layout, collection):
             # dealing with condition that have no seasion
             if not sessions:
                 state = omcore.SubjectState(
-                    internal_identifier=f"Studied state {subject_name}".strip(
-                    ),
-                    lookup_label=f"Studied state {subject_name}".strip()
+                    lookup_label=f"{dataset_short_name_}{subject_name}_ses-01".strip(),
+                    internal_identifier=None
                 )
                 collection.add(state)
                 state_cache_dict[""] = state
@@ -345,17 +350,16 @@ def create_subjects(subject_id, layout_df, layout, collection):
                 for session in sessions:
                     if not (table_filter(table_filter(layout_df, session, "session"), subject, "subject").empty):
                         state = omcore.SubjectState(
-                            internal_identifier=f"Studied state {subject_name} {session}".strip(
-                            ),
-                            lookup_label=f"Studied state {subject_name} {session}".strip(
+                            lookup_label=f"{dataset_short_name_}{subject_name}_ses-{session}".strip(),
+                            internal_identifier=f"{subject_name}_ses-{session}".strip(
                             )
                         )
                         collection.add(state)
                         state_cache_dict[f"{session}"] = state
                         state_cache.append(state)
             subject_state_dict[f"{subject}"] = state_cache_dict
             subject_cache = omcore.Subject(
-                lookup_label=f"{subject_name}",
+                lookup_label=f"{dataset_short_name_}{subject_name}",
                 internal_identifier=f"{subject_name}",
                 studied_states=state_cache
             )
@@ -380,8 +384,8 @@ def create_subjects(subject_id, layout_df, layout, collection):
             state = omcore.SubjectState(
                 age=create_openminds_age(data_subject),
                 handedness=handedness_openminds(data_subject),
-                internal_identifier=f"Studied state {subject_name}".strip(),
-                lookup_label=f"Studied state {subject_name}".strip()
+                internal_identifier=None,
+                lookup_label=f"{dataset_short_name_}{subject_name}_ses-01".strip()
             )
             collection.add(state)
             state_cache_dict[""] = state
@@ -392,18 +396,16 @@ def create_subjects(subject_id, layout_df, layout, collection):
                     state = omcore.SubjectState(
                         age=create_openminds_age(data_subject),
                         handedness=handedness_openminds(data_subject),
-                        internal_identifier=f"Studied state {subject_name} {session}".strip(
-                        ),
-                        lookup_label=f"Studied state {subject_name} {session}".strip(
-                        )
+                        internal_identifier=f"{subject_name}_ses-{session}".strip(),
+                        lookup_label=f"{dataset_short_name_}{subject_name}_ses-{session}".strip()
                     )
                     collection.add(state)
                     state_cache_dict[f"{session}"] = state
                     state_cache.append(state)
             subject_state_dict[f"{subject}"] = state_cache_dict
         subject_cache = omcore.Subject(
             biological_sex=sex_openminds(data_subject),
-            lookup_label=f"{subject_name}",
+            lookup_label=f"{dataset_short_name_}{subject_name}",
             internal_identifier=f"{subject_name}",
             # TODO species should default to homo sapiens
             species=spices_openminds(data_subject),

bids2openminds/report.py

@@ -1,7 +1,7 @@
 import os
 
 
-def create_report(dataset, dataset_version, collection, dataset_description, input_path, output_path):
+def create_report(dataset, dataset_version, collection, dataset_description, input_path, save_text):
     subject_number = 0
     subject_state_numbers = []
     file_bundle_number = 0
@@ -60,9 +60,10 @@ def create_report(dataset, dataset_version, collection, dataset_description, inp
     report = f"""
 Conversion Report
 =================  
-Conversion was successful, the openMINDS file is in {output_path}
+Conversion was successful, {save_text}
 
-Dataset title : {dataset.full_name}
+Dataset full name : {dataset.full_name}
+Dataset short name: {dataset.short_name}
 
 
 Experimental approaches detected:

docs/source/usage.rst

@@ -13,7 +13,7 @@ The ``convert`` function processes a Brain Imaging Data Structure (BIDS) directo
 
 Function Signature
 ##################
->>> def convert(input_path, save_output=False, output_path=None, multiple_files=False, include_empty_properties=False, quiet=False):
+>>> def convert(input_path, save_output=False, output_path=None, short_name=None, multiple_files=False, include_empty_properties=False, quiet=False):
 
 Parameters
 ##########
@@ -23,6 +23,7 @@ Parameters
 - ``multiple_files`` (bool, default=False): If True, the OpenMINDS data will be saved into multiple files within the specified output_path.
 - ``include_empty_properties`` (bool, default=False): If True, includes all the openMINDS properties with empty values in the final output. Otherwise includes only properties that have a non `None` value.
 - ``quiet`` (bool, default=False): If True, suppresses warnings and the final report output. Only prints success messages.
+- ``short_name`` (str or bool, default=None): A short name for the dataset (less than 10 characters). If None, you'll be prompted (default); if False, no short name will be assigned.
 
 Returns
 #######
@@ -32,7 +33,7 @@ Example Usage
 #############
 >>> import bids2openminds.converter as converter
 >>> input_path = "/path/to/BIDS/dataset"
->>> collection = converter.convert(input_path, save_output=True, output_path="/path/to/output", multiple_files=False, include_empty_properties=False, quiet=False)
+>>> collection = converter.convert(input_path, save_output=True, short_name=ShortName, output_path="/path/to/output", multiple_files=False, include_empty_properties=False, quiet=False)
 
 Or one can chose the default parmetrs as following:
 
@@ -48,14 +49,23 @@ This function is also accessible via a command-line interface using the `click`
 
     Usage: bids2openminds [OPTIONS] INPUT_PATH
 
-    Arguments:
-        input-path   Path to the BIDS directory.
-
     Options:
-        -o, --output-path PATH      The output path or filename for OpenMINDS file/files.
-        --single-file               Save the entire collection into a single file (default).
-        --multiple-files            Save each node into a separate file within the specified directory.
-        -e, --include-empty-properties
-                                    Include empty properties in the final file.
-        -q, --quiet                 Suppress warnings and reports.
+    -o, --output-path PATH          The output path or filename for OpenMINDS
+                                    file/files.
+    --single-file                   Save the entire collection into a single
+                                    file (default).
+    --multiple-files                Each node is saved into a separate file
+                                    within the specified directory. 'output-
+                                    path' if specified, must be a directory.
+    -e, --include-empty-properties  Whether to include empty properties in the
+                                    final file.
+    -q, --quiet                     Not generate the final report and no
+                                    warning.
+    -n, --short-name TEXT           Short name for the dataset (less than 10
+                                    characters). If None, you'll be prompted
+                                    (default); if False, no short name will be
+                                    assigned.
+    --help                          Show this message and exit.
+
+