Merge pull request #34 from Peyman-N/deleting_globals

apdavison · web-flow · commit 3bb6c144d13d · 2024-04-30T14:43:00.000+02:00
Resolve Issue of Global Object Dependency by Implementing Local Collection in Converter Function
diff --git a/bids2openminds/converter.py b/bids2openminds/converter.py
@@ -1,19 +1,20 @@
 from warnings import warn
 from bids import BIDSLayout, BIDSValidator
+from openminds import Collection
 import os
 import click
 from . import main
 from . import utility
-from . import globals
 
-def convert(input_path, output_path=None, multiple_files=False, include_empty_properties=False):  
+
+def convert(input_path, output_path=None, multiple_files=False, include_empty_properties=False):
     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."
         )
     # if not(BIDSValidator().is_bids(input_path)):
     #  raise NotADirectoryError(f"The input directory is not valid, you have specified {input_path} which is not a BIDS directory.")
-
+    collection = Collection()
     bids_layout = BIDSLayout(input_path)
 
     layout_df = bids_layout.to_df()
@@ -27,42 +28,43 @@ def convert(input_path, output_path=None, multiple_files=False, include_empty_pr
 
     dataset_description = utility.read_json(dataset_description_path.iat[0, 0])
 
-    [subjects_dict, subject_state_dict, subjects_list] = main.create_subjects(subjects_id, layout_df, bids_layout)
+    [subjects_dict, subject_state_dict, subjects_list] = main.create_subjects(
+        subjects_id, layout_df, bids_layout, collection)
 
-    [files_list, file_repository] = main.create_file(layout_df, input_path)
+    [files_list, file_repository] = main.create_file(
+        layout_df, input_path, collection)
 
     dataset_version = main.create_dataset_version(
-        bids_layout, dataset_description, layout_df, subjects_list, file_repository
-    )
+        bids_layout, dataset_description, layout_df, subjects_list, file_repository, collection)
+
+    dataset = main.create_dataset(
+        dataset_description, dataset_version, collection)
 
-    dataset = main.create_dataset(dataset_description, dataset_version)
-    
-    failures = globals.collection.validate(ignore=["required", "value"])
+    failures = collection.validate(ignore=["required", "value"])
     assert len(failures) == 0
 
     if output_path is None:
         if multiple_files:
-            output_path=os.path.join(input_path, "openminds")
+            output_path = os.path.join(input_path, "openminds")
         else:
             output_path = os.path.join(input_path, "openminds.jsonld")
 
-    globals.collection.save(output_path,individual_files=multiple_files,include_empty_properties=include_empty_properties)
+    collection.save(output_path, individual_files=multiple_files,
+                    include_empty_properties=include_empty_properties)
 
     print(f"Conversion was successful, the openMINDS file is in {output_path}")
 
 
-
 @click.command()
-@click.argument("input-path", type=click.Path(file_okay=False,exists=True))
-@click.option("-o","--output-path",default=None,type=click.Path(file_okay=True,writable=True),help="The output path or filename for OpenMINDS file/files.")
-@click.option("--single-file","multiple_files",flag_value=False,default=False,help="Save the entire collection into a single file (default).")
-@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.argument("input-path", type=click.Path(file_okay=False, exists=True))
+@click.option("-o", "--output-path", default=None, type=click.Path(file_okay=True, writable=True), help="The output path or filename for OpenMINDS file/files.")
+@click.option("--single-file", "multiple_files", flag_value=False, default=False, help="Save the entire collection into a single file (default).")
+@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.")
 def convert_click(input_path, output_path, multiple_files, include_empty_properties):
     convert(input_path, output_path, multiple_files, include_empty_properties)
 
 
-
 if __name__ == "__main__":
     input_path = input("Enter the BIDS directory path: ")
     convert(input_path)
diff --git a/bids2openminds/globals.py b/bids2openminds/globals.py
diff --git a/bids2openminds/main.py b/bids2openminds/main.py
@@ -10,22 +10,23 @@
 
 from .utility import table_filter, pd_table_value, file_hash, file_storage_size
 from .mapping import bids2openminds_instance
-from . import globals
 
 
 def create_techniques(layout_df):
     suffixs = layout_df["suffix"].unique().tolist()
     techniques = []
     not_techniques_index = ["description", "participants", "events"]
     for suffix in suffixs:
-        #excluding the None and non thechnique indexes
+        # excluding the None and non thechnique indexes
         if not (pd.isna(suffix) or (suffix in not_techniques_index)):
-            openminds_techniques_cache=bids2openminds_instance(suffix, "MAP_2_TECHNIQUES")
-            #Excluding the suffixs that are not in the library or flagged as non technique suffixes
+            openminds_techniques_cache = bids2openminds_instance(
+                suffix, "MAP_2_TECHNIQUES")
+            # Excluding the suffixs that are not in the library or flagged as non technique suffixes
             if not pd.isna(openminds_techniques_cache):
                 techniques.extend(openminds_techniques_cache)
             else:
-                warn(f"The {suffix} suffix is currently considered an auxiliary file for already existing techniques or a non technique file.")
+                warn(
+                    f"The {suffix} suffix is currently considered an auxiliary file for already existing techniques or a non technique file.")
 
     return techniques or None
 
@@ -35,12 +36,13 @@ def create_approaches(layout_df):
     approaches = set([])
     for datatype in datatypes:
         if not (pd.isna(datatype)):
-            approaches.update(bids2openminds_instance(datatype, "MAP_2_EXPERIMENTAL_APPROACHES"))
+            approaches.update(bids2openminds_instance(
+                datatype, "MAP_2_EXPERIMENTAL_APPROACHES"))
 
     return list(approaches) or None
 
 
-def create_dataset_version(bids_layout, dataset_description, layout_df, studied_specimens, file_repository):
+def create_dataset_version(bids_layout, dataset_description, layout_df, studied_specimens, file_repository, collection):
 
     # Fetch the dataset type from dataset description file
 
@@ -49,7 +51,8 @@ def create_dataset_version(bids_layout, dataset_description, layout_df, studied_
     # Fetch the digitalIdentifier from dataset description file
 
     if "DatasetDOI" in dataset_description:
-        digital_identifier = omcore.DOI(identifier=dataset_description["DatasetDOI"])
+        digital_identifier = omcore.DOI(
+            identifier=dataset_description["DatasetDOI"])
     else:
         digital_identifier = None
 
@@ -92,32 +95,34 @@ def create_dataset_version(bids_layout, dataset_description, layout_df, studied_
         techniques=techniques,
         how_to_cite=how_to_cite,
         repository=file_repository,
-        #other_contributions=other_contribution  # needs to be a Contribution object
+        # other_contributions=other_contribution  # needs to be a Contribution object
         # version_identifier
     )
 
-    globals.collection.add(dataset_version)
+    collection.add(dataset_version)
 
     return dataset_version
 
 
-def create_dataset(dataset_description, dataset_version):
+def create_dataset(dataset_description, dataset_version, collection):
 
     if "DatasetDOI" in dataset_description:
-        digital_identifier = omcore.DOI(identifier=dataset_description["DatasetDOI"])
+        digital_identifier = omcore.DOI(
+            identifier=dataset_description["DatasetDOI"])
     else:
         digital_identifier = None
 
     dataset = omcore.Dataset(
-        digital_identifier=digital_identifier, full_name=dataset_description["Name"], has_versions=dataset_version
+        digital_identifier=digital_identifier, full_name=dataset_description[
+            "Name"], has_versions=dataset_version
     )
 
-    globals.collection.add(dataset)
+    collection.add(dataset)
 
     return dataset
 
 
-def create_subjects(subject_id, layout_df, layout):
+def create_subjects(subject_id, layout_df, layout, collection):
 
     sessions = layout.get_sessions()
     subjects_dict = {}
@@ -126,30 +131,33 @@ def create_subjects(subject_id, layout_df, layout):
 
     # Find the participants files in the files table
     participants_paths = table_filter(layout_df, "participants")
-    if  participants_paths.empty:
-        #creating emphty subjects just based on file structure
+    if participants_paths.empty:
+        # creating emphty subjects just based on file structure
         for subject in subject_id:
             subject_name = f"sub-{subject}"
             state_cache_dict = {}
             state_cache = []
-            #dealing with condition that have no seasion
+            # dealing with condition that have no seasion
             if not sessions:
                 state = omcore.SubjectState(
-                    internal_identifier=f"Studied state {subject_name}".strip(),
+                    internal_identifier=f"Studied state {subject_name}".strip(
+                    ),
                     lookup_label=f"Studied state {subject_name}".strip()
                 )
-                globals.collection.add(state)
+                collection.add(state)
                 state_cache_dict[""] = state
                 state_cache.append(state)
             else:
-                #create a subject state for each state
+                # create a subject state for each state
                 for session in sessions:
-                    if not(table_filter(table_filter(layout_df,session,"session"),subject,"subject").empty):
+                    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()
+                            internal_identifier=f"Studied state {subject_name} {session}".strip(
+                            ),
+                            lookup_label=f"Studied state {subject_name} {session}".strip(
+                            )
                         )
-                        globals.collection.add(state)
+                        collection.add(state)
                         state_cache_dict[f"{session}"] = state
                         state_cache.append(state)
             subject_state_dict[f"{subject}"] = state_cache_dict
@@ -159,20 +167,21 @@ def create_subjects(subject_id, layout_df, layout):
             )
             subjects_dict[f"{subject}"] = subject_cache
             subjects_list.append(subject_cache)
-            globals.collection.add(subject_cache)
-
+            collection.add(subject_cache)
 
         return subjects_dict, subject_state_dict, subjects_list
 
-
     # Select the tsv file of the table
-    participants_path_tsv = pd_table_value(table_filter(participants_paths, ".tsv", "extension"), "path")
-    participants_path_json = pd_table_value(table_filter(participants_paths, ".json", "extension"), "path")
+    participants_path_tsv = pd_table_value(table_filter(
+        participants_paths, ".tsv", "extension"), "path")
+    participants_path_json = pd_table_value(table_filter(
+        participants_paths, ".json", "extension"), "path")
 
     participants_table = pd.read_csv(participants_path_tsv, sep="\t", header=0)
     for subject in subject_id:
         subject_name = f"sub-{subject}"
-        data_subject = table_filter(participants_table, subject_name, "participant_id")
+        data_subject = table_filter(
+            participants_table, subject_name, "participant_id")
         state_cache_dict = {}
         state_cache = []
         if not sessions:
@@ -181,74 +190,84 @@ def create_subjects(subject_id, layout_df, layout):
                     value=pd_table_value(data_subject, "age"),
                     unit=controlled_terms.UnitOfMeasurement.year
                 ),
-                handedness=bids2openminds_instance(pd_table_value(data_subject, "handedness"), "MAP_2_HANDEDNESS", is_list=False),
+                handedness=bids2openminds_instance(pd_table_value(
+                    data_subject, "handedness"), "MAP_2_HANDEDNESS", is_list=False),
                 internal_identifier=f"Studied state {subject_name}".strip(),
                 lookup_label=f"Studied state {subject_name}".strip()
-                )
-            globals.collection.add(state)
+            )
+            collection.add(state)
             state_cache_dict[""] = state
             state_cache.append(state)
         else:
             for session in sessions:
-                if not(table_filter(table_filter(layout_df,session,"session"),subject,"subject").empty):
+                if not (table_filter(table_filter(layout_df, session, "session"), subject, "subject").empty):
                     state = omcore.SubjectState(
                         age=omcore.QuantitativeValue(
                             value=pd_table_value(data_subject, "age"),
                             unit=controlled_terms.UnitOfMeasurement.year
                         ),
-                        handedness=bids2openminds_instance(pd_table_value(data_subject, "handedness"), "MAP_2_HANDEDNESS", is_list=False),
-                        internal_identifier=f"Studied state {subject_name} {session}".strip(),
-                        lookup_label=f"Studied state {subject_name} {session}".strip()
+                        handedness=bids2openminds_instance(pd_table_value(
+                            data_subject, "handedness"), "MAP_2_HANDEDNESS", is_list=False),
+                        internal_identifier=f"Studied state {subject_name} {session}".strip(
+                        ),
+                        lookup_label=f"Studied state {subject_name} {session}".strip(
+                        )
                     )
-                    globals.collection.add(state)
+                    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=bids2openminds_instance(pd_table_value(data_subject, "sex"), "MAP_2_SEX", is_list=False),
+            biological_sex=bids2openminds_instance(pd_table_value(
+                data_subject, "sex"), "MAP_2_SEX", is_list=False),
             lookup_label=f"{subject_name}",
             internal_identifier=f"{subject_name}",
             # TODO species should default to homo sapiens
-            species=bids2openminds_instance(pd_table_value(data_subject, "species"), "MAP_2_SPECIES", is_list=False),
+            species=bids2openminds_instance(pd_table_value(
+                data_subject, "species"), "MAP_2_SPECIES", is_list=False),
             studied_states=state_cache
         )
         subjects_dict[f"{subject}"] = subject_cache
         subjects_list.append(subject_cache)
-        globals.collection.add(subject_cache)
+        collection.add(subject_cache)
 
     return subjects_dict, subject_state_dict, subjects_list
 
 
-def create_file(layout_df, BIDS_path):
+def create_file(layout_df, BIDS_path, collection):
 
     BIDS_directory_path = os.path.dirname(BIDS_path)
     file_repository = omcore.FileRepository()
-    globals.collection.add(file_repository)
+    collection.add(file_repository)
     files_list = []
     for index, file in layout_df.iterrows():
         file_format = None
         content_description = None
         data_types = None
         extension = file["extension"]
         path = file["path"]
-        iri=IRI(pathlib.Path(path).as_uri())
-        name=os.path.basename(path)
+        iri = IRI(pathlib.Path(path).as_uri())
+        name = os.path.basename(path)
         hashes = file_hash(path)
         storage_size = file_storage_size(path)
         if pd.isna(file["subject"]):
             if file["suffix"] == "participants":
                 if extension == ".json":
                     content_description = f"A JSON metadata file of participants TSV."
-                    data_types = controlled_terms.DataType.by_name("associative array")
-                    file_format = omcore.ContentType.by_name("application/json")
+                    data_types = controlled_terms.DataType.by_name(
+                        "associative array")
+                    file_format = omcore.ContentType.by_name(
+                        "application/json")
                 elif extension == [".tsv"]:
                     content_description = f"A metadata table for participants."
                     data_types = controlled_terms.DataType.by_name("table")
-                    file_format = omcore.ContentType.by_name("text/tab-separated-values")
+                    file_format = omcore.ContentType.by_name(
+                        "text/tab-separated-values")
         else:
             if extension == ".json":
                 content_description = f"A JSON metadata file for {file['suffix']} of subject {file['subject']}"
-                data_types = controlled_terms.DataType.by_name("associative array")
+                data_types = controlled_terms.DataType.by_name(
+                    "associative array")
                 file_format = omcore.ContentType.by_name("application/json")
             elif extension in [".nii", ".nii.gz"]:
                 content_description = f"Data file for {file['suffix']} of subject {file['subject']}"
@@ -257,8 +276,10 @@ def create_file(layout_df, BIDS_path):
             elif extension == [".tsv"]:
                 if file["suffix"] == "events":
                     content_description = f"Event file for {file['suffix']} of subject {file['subject']}"
-                    data_types = controlled_terms.DataType.by_name("event sequence")
-                    file_format = omcore.ContentType.by_name("text/tab-separated-values")
+                    data_types = controlled_terms.DataType.by_name(
+                        "event sequence")
+                    file_format = omcore.ContentType.by_name(
+                        "text/tab-separated-values")
         file = omcore.File(
             iri=iri,
             content_description=content_description,
@@ -271,7 +292,7 @@ def create_file(layout_df, BIDS_path):
             # special_usage_role
             storage_size=storage_size,
         )
-        globals.collection.add(file)
+        collection.add(file)
         files_list.append(file)
 
     return files_list, file_repository
