updated dependencies

Author: Anna Grim

pyproject.toml

@@ -25,7 +25,7 @@ dependencies = [
     'interrogate',
     'ome-zarr',
     'pandas',
-    's3fs',
+    's3fs==2025.7.0',
     'scikit-image',
     'scikit-learn',
     'scipy',
@@ -34,7 +34,7 @@ dependencies = [
     'torch',
     'torchvision',
     'tqdm',
-    'xarray_multiscale',
+    'xarray_multiscale==1.2.0',
     'zarr',
     "aind-exaspim-dataset-utils @ git+https://github.com/AllenNeuralDynamics/aind-exaspim-dataset-utils.git@main"
 ]

src/aind_exaspim_image_compression/machine_learning/data_handling.py

@@ -145,6 +145,28 @@ def load_swcs(self, swc_pointer):
 
     # --- Sample Image Patches ---
     def __getitem__(self, dummy_input):
+        """
+        Return a pair of noisy and BM4D-denoised image patches, normalized 
+        according to percentile-based scaling.
+
+        Parameters
+        ----------
+        dummy_input : Any
+            Dummy argument required by PyTorch's `Dataset` interface for indexing.
+            Not used in the patch sampling procedure.
+
+        Returns
+        -------
+        tuple
+            A tuple containing:
+            - noise : np.ndarray
+                Noisy image patch, normalized and clipped.
+            denoised : np.ndarray
+                Denoised image patch, normalized and clipped using the same
+                scale as the noisy patch.
+            (mn, mx) : Tuple[float]
+                Lower and upper percentiles used for normalization.
+        """
         # Get image patches
         brain_id = self.sample_brain()
         voxel = self.sample_voxel(brain_id)