feature: Returns just dictionary when loading .topostats

AFMReader/topostats.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 from pathlib import Path
+from typing import Any
 
 import h5py
 
@@ -11,7 +12,7 @@
 logger.enable(__package__)
 
 
-def load_topostats(file_path: Path | str) -> tuple:
+def load_topostats(file_path: Path | str) -> dict[str, Any]:
     """
     Extract image and pixel to nm scaling from the .topostats (HDF5 format) file.
 
@@ -22,9 +23,9 @@ def load_topostats(file_path: Path | str) -> tuple:
 
     Returns
     -------
-    tuple(np.ndarray, float)
-        A tuple containing the image, its pixel to nm scaling factor and the data dictionary
-        containing all the extra image data and metadata in dictionary format.
+    dict[str, Any]
+        A dictionary containing the image, its pixel to nm scaling factor and nested Numpy arrays representing the
+        analyses performed on the data.
 
     Raises
     ------
@@ -45,12 +46,10 @@ def load_topostats(file_path: Path | str) -> tuple:
                 data["img_path"] = Path(data["img_path"])
             file_version = data["topostats_file_version"]
             logger.info(f"[{filename}] TopoStats file version : {file_version}")
-            image = data["image"]
-            pixel_to_nm_scaling = data["pixel_to_nm_scaling"]
 
     except OSError as e:
         if "Unable to open file" in str(e):
             logger.error(f"[{filename}] File not found : {file_path}")
         raise e
 
-    return (image, pixel_to_nm_scaling, data)
+    return data

tests/test_topostats.py

@@ -3,7 +3,6 @@
 from pathlib import Path
 import pytest
 
-import numpy as np
 
 from AFMReader import topostats
 
@@ -55,27 +54,22 @@
 def test_load_topostats(
     file_name: str,
     topostats_file_version: float,
-    image_shape: tuple[int, int],
+    image_shape: tuple,
     pixel_to_nm_scaling: float,
     data_keys: set[str],
     image_sum: float,
 ) -> None:
     """Test the normal operation of loading a .topostats (HDF5 format) file."""
-    result_image = np.ndarray
-    result_pixel_to_nm_scaling = float
-    result_data = dict
-
     file_path = RESOURCES / file_name
-    result_image, result_pixel_to_nm_scaling, result_data = topostats.load_topostats(file_path)
+    topostats_data = topostats.load_topostats(file_path)
 
-    assert result_pixel_to_nm_scaling == pixel_to_nm_scaling
-    assert isinstance(result_image, np.ndarray)
-    assert result_image.shape == image_shape
-    assert set(result_data.keys()) == data_keys  # type: ignore
-    assert result_data["topostats_file_version"] == topostats_file_version
-    assert result_image.sum() == image_sum
+    assert set(topostats_data.keys()) == data_keys  # type: ignore
+    assert topostats_data["topostats_file_version"] == topostats_file_version
+    assert topostats_data["pixel_to_nm_scaling"] == pixel_to_nm_scaling
+    assert topostats_data["image"].shape == image_shape
+    assert topostats_data["image"].sum() == image_sum
     if topostats_file_version >= 0.2:
-        assert isinstance(result_data["img_path"], Path)
+        assert isinstance(topostats_data["img_path"], Path)
 
 
 def test_load_topostats_file_not_found() -> None: