move get_subject_metadata_from_rat_info_folder utility method to be a…

…ccessible from other projects

src/constantinople_lab_to_nwb/mah_2024/mah_2024_convert_session.py

@@ -1,75 +1,13 @@
 from pathlib import Path
 from typing import Union, Optional
-from warnings import warn
 
-import pandas as pd
 from dateutil import tz
 from neuroconv.utils import load_dict_from_file, dict_deep_update
-from pymatreader import read_mat
 
+from constantinople_lab_to_nwb.utils import get_subject_metadata_from_rat_info_folder
 from constantinople_lab_to_nwb.mah_2024 import Mah2024NWBConverter
 
 
-def get_subject_metadata_from_rat_info_folder(
-    folder_path: Union[str, Path],
-    subject_id: str,
-    date: str,
-) -> dict:
-    """
-    Load subject metadata from the rat info files.
-    The "registry.mat" file contains information about the subject such as date of birth, sex, and vendor.
-    The "Mass_registry.mat" file contains information about the weight of the subject.
-
-    Parameters
-    ----------
-    folder_path: Union[str, Path]
-        The folder path containing the rat info files.
-    subject_id: str
-        The subject ID.
-    date: str
-        The date of the session in the format "yyyy-mm-dd".
-    """
-
-    folder_path = Path(folder_path)
-    rat_registry_file_path = folder_path / "registry.mat"
-
-    subject_metadata = dict()
-    if rat_registry_file_path.exists():
-        rat_registry = read_mat(str(rat_registry_file_path))
-        rat_registry = pd.DataFrame(rat_registry["Registry"])
-
-        filtered_rat_registry = rat_registry[rat_registry["RatName"] == subject_id]
-        if not filtered_rat_registry.empty:
-            date_of_birth = filtered_rat_registry["DOB"].values[0]
-            if date_of_birth:
-                # convert date of birth to datetime with format "yyyy-mm-dd"
-                date_of_birth = pd.to_datetime(date_of_birth, format="%Y-%m-%d")
-                subject_metadata.update(date_of_birth=date_of_birth)
-            else:
-                # TODO: what to do if date of birth is missing?
-                warn("Date of birth is missing. We recommend adding this information to the rat info files.")
-                # Using age range specified in the manuscript
-                subject_metadata.update(age="P6M/P24M")
-            subject_metadata.update(sex=filtered_rat_registry["sex"].values[0])
-            vendor = filtered_rat_registry["vendor"].values[0]
-            if vendor:
-                subject_metadata.update(description=f"Vendor: {vendor}")
-
-    mass_registry_file_path = folder_path / "Mass_registry.mat"
-    if mass_registry_file_path.exists():
-        mass_registry = read_mat(str(mass_registry_file_path))
-        mass_registry = pd.DataFrame(mass_registry["Mass_registry"])
-
-        filtered_mass_registry = mass_registry[(mass_registry["rat"] == subject_id) & (mass_registry["date"] == date)]
-        if not filtered_mass_registry.empty:
-            weight_g = filtered_mass_registry["mass"].astype(int).values[0]  # in grams
-            # convert mass to kg
-            weight_kg = weight_g / 1000
-            subject_metadata.update(weight=str(weight_kg))
-
-    return subject_metadata
-
-
 def session_to_nwb(
     raw_behavior_file_path: Union[str, Path],
     processed_behavior_file_path: Union[str, Path],

src/constantinople_lab_to_nwb/utils/__init__.py

@@ -0,0 +1 @@
+from .get_subject_metadata import get_subject_metadata_from_rat_info_folder

src/constantinople_lab_to_nwb/utils/get_subject_metadata.py

@@ -0,0 +1,66 @@
+from pathlib import Path
+from typing import Union
+from warnings import warn
+
+import pandas as pd
+from pymatreader import read_mat
+
+
+def get_subject_metadata_from_rat_info_folder(
+    folder_path: Union[str, Path],
+    subject_id: str,
+    date: str,
+) -> dict:
+    """
+    Load subject metadata from the rat info files.
+    The "registry.mat" file contains information about the subject such as date of birth, sex, and vendor.
+    The "Mass_registry.mat" file contains information about the weight of the subject.
+
+    Parameters
+    ----------
+    folder_path: Union[str, Path]
+        The folder path containing the rat info files.
+    subject_id: str
+        The subject ID.
+    date: str
+        The date of the session in the format "yyyy-mm-dd".
+    """
+
+    folder_path = Path(folder_path)
+    rat_registry_file_path = folder_path / "registry.mat"
+
+    subject_metadata = dict()
+    if rat_registry_file_path.exists():
+        rat_registry = read_mat(str(rat_registry_file_path))
+        rat_registry = pd.DataFrame(rat_registry["Registry"])
+
+        filtered_rat_registry = rat_registry[rat_registry["RatName"] == subject_id]
+        if not filtered_rat_registry.empty:
+            date_of_birth = filtered_rat_registry["DOB"].values[0]
+            if date_of_birth:
+                # convert date of birth to datetime with format "yyyy-mm-dd"
+                date_of_birth = pd.to_datetime(date_of_birth, format="%Y-%m-%d")
+                subject_metadata.update(date_of_birth=date_of_birth)
+            else:
+                # TODO: what to do if date of birth is missing?
+                warn("Date of birth is missing. We recommend adding this information to the rat info files.")
+                # Using age range specified in the manuscript
+                subject_metadata.update(age="P6M/P24M")
+            subject_metadata.update(sex=filtered_rat_registry["sex"].values[0])
+            vendor = filtered_rat_registry["vendor"].values[0]
+            if vendor:
+                subject_metadata.update(description=f"Vendor: {vendor}")
+
+    mass_registry_file_path = folder_path / "Mass_registry.mat"
+    if mass_registry_file_path.exists():
+        mass_registry = read_mat(str(mass_registry_file_path))
+        mass_registry = pd.DataFrame(mass_registry["Mass_registry"])
+
+        filtered_mass_registry = mass_registry[(mass_registry["rat"] == subject_id) & (mass_registry["date"] == date)]
+        if not filtered_mass_registry.empty:
+            weight_g = filtered_mass_registry["mass"].astype(int).values[0]  # in grams
+            # convert mass to kg
+            weight_kg = weight_g / 1000
+            subject_metadata.update(weight=str(weight_kg))
+
+    return subject_metadata