Ensure extraction_dir is absolutely converted to a Path type

src/maldi_tools/extraction.py

@@ -260,17 +260,19 @@ def coordinate_integration(peak_df: pd.DataFrame, imz_data: ImzMLParser, extract
 
     image_shape: Tuple[int, int] = (x_size, y_size)
 
-    os.makedirs(extraction_dir / "float")
-    os.makedirs(extraction_dir / "int")
+    float_peak_dir: Path = Path(extraction_dir) / "float"
+    int_peak_dir: Path = Path(extraction_dir) / "int"
+    os.makedirs(float_peak_dir)
+    os.makedirs(int_peak_dir)
 
     for idx, (x, y, _) in tqdm(enumerate(imz_data.coordinates), total=len(imz_data.coordinates)):
         mzs, intensities = imz_data.getspectrum(idx)
         intensity: np.ndarray = intensities[np.isin(mzs, peak_df["m/z"])]
 
         for i_idx, peak in peak_df.loc[peak_df["m/z"].isin(mzs), "peak"].reset_index(drop=True).items():
             img_name: str = f"{peak:.4f}".replace(".", "_")
-            float_peak_path: Path = extraction_dir / "float" / f"{img_name}.tiff"
-            int_peak_path: Path = extraction_dir / "int" / f"{img_name}.tiff"
+            float_peak_path: Path = float_peak_dir / f"{img_name}.tiff"
+            int_peak_path: Path = int_peak_dir / f"{img_name}.tiff"
             peak_exists: bool = os.path.exists(float_peak_path)
             peak_img: np.ndarray = imread(float_peak_path).T if peak_exists else np.zeros(image_shape)
 

src/maldi_tools/plotting.py

@@ -184,8 +184,8 @@ def save_matched_peak_images(
         extraction_dir (Path): The directory to save extracted data in.
     """
     # Create image directories if they do not exist
-    float_dir: Path = extraction_dir / "library_matched" / "float"
-    int_dir: Path = extraction_dir / "library_matched" / "int"
+    float_dir: Path = Path(extraction_dir) / "library_matched" / "float"
+    int_dir: Path = Path(extraction_dir) / "library_matched" / "int"
     for img_dir in [float_dir, int_dir]:
         if not os.path.exists(img_dir):
             img_dir.mkdir(parents=True, exist_ok=True)
@@ -196,8 +196,8 @@ def save_matched_peak_images(
         if row.matched is True:
             peak_file_name: str = f"{row.lib_mz:.4f}".replace(".", "_") + ".tiff"
             # load in the corresponding float and integer images
-            float_img: np.ndarray = io.imread(extraction_dir / "float" / peak_file_name)
-            integer_img: np.ndarray = io.imread(extraction_dir / "int" / peak_file_name)
+            float_img: np.ndarray = io.imread(Path(extraction_dir) / "float" / peak_file_name)
+            integer_img: np.ndarray = io.imread(Path(extraction_dir) / "int" / peak_file_name)
 
             img_name: str = row.composition