Adding support for .jpk-qi-data and .bin files and moving to dataclasses for the returned loaded data

.gitignore

@@ -3,6 +3,9 @@ __pycache__/
 *.py[cod]
 *$py.class
 
+AFMReader/data/*
+AFMReader/notebooks/*
+
 # C extensions
 *.so
 

AFMReader/asd.py

@@ -10,6 +10,7 @@
 import numpy.typing as npt
 from matplotlib import animation
 
+from AFMReader.data_classes import AFMLoad
 from AFMReader.io import (
     read_ascii,
     read_bool,
@@ -182,7 +183,7 @@ def calculate_scaling_factor(
     raise ValueError(f"channel {channel} not known for .asd file type.")
 
 
-def load_asd(file_path: str | Path, channel: str):
+def load_asd(file_path: str | Path, channel: str) -> AFMLoad:
     """
     Load a .asd file.
 
@@ -196,17 +197,16 @@ def load_asd(file_path: str | Path, channel: str):
 
     Returns
     -------
-    npt.NDArray
-        The .asd file frames data as a numpy 3D array N x W x H
-        (Number of frames x Width of each frame x height of each frame).
-    float
-        The number of nanometres per pixel for the .asd file. (AKA the resolution).
-        Enables converting between pixels and nanometres when working with the data, in order to use real-world length
-        scales.
-    dict
-        Metadata for the .asd file. The number of entries is too long to list here, and changes based on the file
-        version please either look into the `read_header_file_version_x` functions or print the keys too see what
-        metadata is available.
+    AFMLoad
+        An AFMLoad object containing:
+        - image : npt.NDArray
+            Shape (Number of frames x Width of each frame x height of each frame).
+        - px2nm : float
+            The number of nanometres per pixel for the .asd file.
+        - metadata : dict
+            Metadata for the .asd file. The number of entries is too long to list here, and changes based on the file
+            version please either look into the `read_header_file_version_x` functions or print the keys too see what
+            metadata is available.
     """
     # Ensure the file path is a Path object
     file_path = Path(file_path)
@@ -285,7 +285,39 @@ def load_asd(file_path: str | Path, channel: str):
         frames = np.array(frames)
 
         logger.info(f"[{filename}] : Extracted image.")
-        return frames, pixel_to_nanometre_scaling_factor, header_dict
+        return AFMLoad(image=frames, px2nm=pixel_to_nanometre_scaling_factor, metadata=header_dict)
+
+
+def get_asd_channels(file_path: Path):
+    """
+    Get the channels available in given .asd file.
+
+    Parameters
+    ----------
+    file_path : Path
+        Path to the .asd file.
+
+    Returns
+    -------
+    list
+        List of channels available in the .asd file.
+    """
+    with Path.open(file_path, "rb", encoding=None) as open_file:  # pylint: disable=unspecified-encoding
+        file_version = read_file_version(open_file)
+
+        if file_version == 0:
+            header_dict = read_header_file_version_0(open_file)
+
+        elif file_version == 1:
+            header_dict = read_header_file_version_1(open_file)
+
+        elif file_version == 2:
+            header_dict = read_header_file_version_2(open_file)
+        else:
+            raise ValueError(
+                f"File version {file_version} unknown. Please add support if you know how to decode this file version."
+            )
+        return [header_dict["channel1"], header_dict["channel2"]]
 
 
 def read_file_version(open_file: BinaryIO) -> int: