WIP 1

clinica/iotools/converters/oasis_to_bids/oasis_to_bids.py

@@ -108,18 +108,16 @@ def _create_sessions_tsv(
         bids_dir: Path,
         bids_ids: list[str],
     ) -> dict:
-        from oasis_to_bids_utils import create_sessions_dict, write_sessions_tsv
-
-        from clinica.iotools.bids_utils import StudyName
+        from .oasis_to_bids_utils import create_sessions_dict, write_sessions_tsv
 
         sessions_dict = create_sessions_dict(
             clinical_data_dir=clinical_data_dir,
             bids_dir=bids_dir,
-            study_name=StudyName.OASIS,
             clinical_specifications_folder=Path(__file__).parents[1] / "specifications",
             bids_ids=bids_ids,
-            name_column_ids="ID",
         )
+
+        # todo : when tested add to create_sessions_dict bc specific to oasis1
         for bids_id in bids_ids:
             sessions_dict[bids_id]["M000"]["diagnosis"] = (
                 "AD" if sessions_dict[bids_id]["M000"]["diagnosis"] > 0 else "CN"

clinica/iotools/converters/oasis_to_bids/oasis_to_bids_utils.py

@@ -14,14 +14,11 @@
 def create_sessions_dict(
     clinical_data_dir: Path,
     bids_dir: Path,
-    study_name: StudyName,
     clinical_specifications_folder: Path,
     bids_ids: list[str],
-    name_column_ids: str,
     subj_to_remove: Optional[list[str]] = None,
-    participants_df: Optional[pd.DataFrame] = None,
 ) -> dict:
-    """Extract the information regarding the sessions and store them in a dictionary (session M00 only).
+    """Extract the information regarding the sessions and store them in a dictionary (session M000 only).
 
     Parameters
     ----------
@@ -31,34 +28,25 @@ def create_sessions_dict(
     bids_dir : Path
         The path to the BIDS directory.
 
-    study_name : StudyName
-        The name of the study (Ex: ADNI).
-
     clinical_specifications_folder : Path
         The path to the clinical file.
 
     bids_ids : list of str
         The list of bids ids.
 
-    name_column_ids : str
-        The name of the column where the subject ids are stored.
-
     subj_to_remove : list of str, optional
         The list of subject IDs to remove.
 
-    participants_df : pd.DataFrame, optional
-        A pandas dataframe that contains the participants data (required for OASIS3 only).
-
     Returns
     -------
     dict :
         Session dict.
     """
 
     subj_to_remove = subj_to_remove or []
-    location = f"{study_name.value} location"
+    location = f"{StudyName.OASIS.value} location"
     sessions = pd.read_csv(clinical_specifications_folder / "sessions.tsv", sep="\t")
-    sessions_fields = sessions[study_name.value]
+    sessions_fields = sessions[StudyName.OASIS.value]
     field_location = sessions[location]
     sessions_fields_bids = sessions["BIDS CLINICA"]
     fields_dataset = []
@@ -94,7 +82,7 @@ def create_sessions_dict(
 
             for r in range(0, len(file_to_read.values)):
                 # Extracts the subject ids columns from the dataframe
-                subj_id = file_to_read.iloc[r][name_column_ids]
+                subj_id = file_to_read.iloc[r]["ID"]
                 if hasattr(subj_id, "dtype"):
                     if subj_id.dtype == np.int64:
                         subj_id = str(subj_id)
@@ -116,34 +104,14 @@ def create_sessions_dict(
                     session_names = get_bids_sess_list(subj_dir)
                     for s in session_names:
                         s_name = s.replace("ses-", "")
-                        if study_name == StudyName.OASIS3:
-                            row = file_to_read[
-                                file_to_read["MR ID"].str.startswith(subj_id)
-                                & file_to_read["MR ID"].str.endswith(s_name)
-                            ].iloc[0]
-                        else:
-                            row = file_to_read.iloc[r]
+                        row = file_to_read.iloc[r]
                         if subj_bids not in sessions_dict:
                             sessions_dict.update({subj_bids: {}})
                         if s_name not in sessions_dict[subj_bids].keys():
                             sessions_dict[subj_bids].update({s_name: {"session_id": s}})
                         (sessions_dict[subj_bids][s_name]).update(
                             {sessions_fields_bids[i]: row[sessions_fields[i]]}
                         )
-                        # Calculate the difference in months for OASIS3 only
-                        if (
-                            study_name == StudyName.OASIS3
-                            and sessions_fields_bids[i] == "age"
-                        ):
-                            diff_years = (
-                                float(sessions_dict[subj_bids][s_name]["age"])
-                                - participants_df[
-                                    participants_df["participant_id"] == subj_bids
-                                ]["age_bl"]
-                            )
-                            (sessions_dict[subj_bids][s_name]).update(
-                                {"diff_months": round(float(diff_years) * 12)}
-                            )
 
     return sessions_dict
 

test/unittests/iotools/converters/oasis_to_bids/test_oasis_to_bids_utils.py

@@ -1,10 +1,43 @@
+from pathlib import Path
+
+import pandas as pd
 import pytest
 
 from clinica.iotools.converters.oasis_to_bids.oasis_to_bids_utils import (
     create_sessions_dict,
+    write_sessions_tsv,
 )
 
 
+def build_clinical_data(tmp_path: Path) -> None:
+    df = pd.DataFrame(
+        {
+            "ID": ["OAS1_0001_MR1", "OAS1_0002_MR1"],
+            "M/F": ["F", "M"],
+            "Hand": ["R", "L"],
+            "Age": [74, 67],
+            "Educ": [2, 2],
+            "SES": [3, 3],
+            "MMSE": [29, 29],
+            "CDR": [0, 0],
+            "eTIV": [1344, 1344],
+            "nWBV": [0.704, 0.645],
+            "ASF": [1.306, 1.100],
+            "Delay": [float("nan"), float("nan")],
+        }
+    )
+    df.to_csv(tmp_path / "oasis_cross-sectional.csv", index=False)
+
+    # todo : do excel for future
+    bids_ids = ["sub-OASIS10001", "sub-OASIS10002"]
+
+
 def test_create_sessions_dict():
+    # todo
+    clinical_specifications_folder = Path("clinica/iotools/converters/specifications")
+    pass
+
+
+def test_write_sessions_tsv():
     # todo
     pass