Refactor tests for processing and adapt it to new library structure, plus fix...

Refactor tests for processing and adapt it to new library structure, plus fix unit tests for processing

qim3d/filters/_common_filter_methods.py

@@ -27,10 +27,7 @@ __all__ = [
 
 
 class FilterBase:
-    def __init__(self, 
-                 dask: bool = False, 
-                 chunks: str = "auto", 
-                 *args, **kwargs):
+    def __init__(self, *args, dask: bool = False, chunks: str = "auto", **kwargs):
         """
         Base class for image filters.
 
@@ -43,6 +40,7 @@ class FilterBase:
         self.chunks = chunks
         self.kwargs = kwargs
 
+
 class Gaussian(FilterBase):
     def __call__(self, input: np.ndarray) -> np.ndarray:
         """
@@ -54,7 +52,9 @@ class Gaussian(FilterBase):
         Returns:
             The filtered image or volume.
         """
-        return gaussian(input, dask=self.dask, chunks=self.chunks, *self.args, **self.kwargs)
+        return gaussian(
+            input, dask=self.dask, chunks=self.chunks, *self.args, **self.kwargs
+        )
 
 
 class Median(FilterBase):
@@ -98,6 +98,7 @@ class Minimum(FilterBase):
         """
         return minimum(input, dask=self.dask, chunks=self.chunks, **self.kwargs)
 
+
 class Tophat(FilterBase):
     def __call__(self, input: np.ndarray) -> np.ndarray:
         """
@@ -142,8 +143,9 @@ class Pipeline:
         ```
         ![original volume](assets/screenshots/filter_original.png)
         ![filtered volume](assets/screenshots/filter_processed.png)
-            
-        """
+
+    """
+
     def __init__(self, *args: Type[FilterBase]):
         """
         Represents a sequence of image filters.
@@ -182,7 +184,7 @@ class Pipeline:
 
         Args:
             fn: An instance of a FilterBase subclass to be appended.
-        
+
         Example:
             ```python
             import qim3d
@@ -214,10 +216,9 @@ class Pipeline:
         return input
 
 
-def gaussian(vol: np.ndarray, 
-             dask: bool = False, 
-             chunks: str = 'auto',
-             *args, **kwargs) -> np.ndarray:
+def gaussian(
+    vol: np.ndarray, dask: bool = False, chunks: str = "auto", *args, **kwargs
+) -> np.ndarray:
     """
     Applies a Gaussian filter to the input volume using scipy.ndimage.gaussian_filter or dask_image.ndfilters.gaussian_filter.
 
@@ -231,7 +232,7 @@ def gaussian(vol: np.ndarray,
     Returns:
         The filtered image or volume.
     """
-    
+
     if dask:
         if not isinstance(vol, da.Array):
             vol = da.from_array(vol, chunks=chunks)
@@ -243,10 +244,9 @@ def gaussian(vol: np.ndarray,
         return res
 
 
-def median(vol: np.ndarray, 
-           dask: bool = False, 
-           chunks: str ='auto', 
-           **kwargs) -> np.ndarray:
+def median(
+    vol: np.ndarray, dask: bool = False, chunks: str = "auto", **kwargs
+) -> np.ndarray:
     """
     Applies a median filter to the input volume using scipy.ndimage.median_filter or dask_image.ndfilters.median_filter.
 
@@ -270,10 +270,9 @@ def median(vol: np.ndarray,
         return res
 
 
-def maximum(vol: np.ndarray, 
-            dask: bool = False, 
-            chunks: str = 'auto', 
-            **kwargs) -> np.ndarray:
+def maximum(
+    vol: np.ndarray, dask: bool = False, chunks: str = "auto", **kwargs
+) -> np.ndarray:
     """
     Applies a maximum filter to the input volume using scipy.ndimage.maximum_filter or dask_image.ndfilters.maximum_filter.
 
@@ -297,10 +296,9 @@ def maximum(vol: np.ndarray,
         return res
 
 
-def minimum(vol: np.ndarray, 
-            dask: bool = False, 
-            chunks: str = 'auto', 
-            **kwargs) -> np.ndarray:
+def minimum(
+    vol: np.ndarray, dask: bool = False, chunks: str = "auto", **kwargs
+) -> np.ndarray:
     """
     Applies a minimum filter to the input volume using scipy.ndimage.minimum_filter or dask_image.ndfilters.minimum_filter.
 
@@ -323,10 +321,10 @@ def minimum(vol: np.ndarray,
         res = ndimage.minimum_filter(vol, **kwargs)
         return res
 
-def tophat(vol: np.ndarray, 
-           dask: bool = False, 
-           chunks: str = 'auto', 
-           **kwargs) -> np.ndarray:
+
+def tophat(
+    vol: np.ndarray, dask: bool = False, chunks: str = "auto", **kwargs
+) -> np.ndarray:
     """
     Remove background from the volume.
 
@@ -347,15 +345,17 @@ def tophat(vol: np.ndarray,
 
     if dask:
         log.info("Dask not supported for tophat filter, switching to scipy.")
-    
+
     if background == "bright":
-        log.info("Bright background selected, volume will be temporarily inverted when applying white_tophat")
+        log.info(
+            "Bright background selected, volume will be temporarily inverted when applying white_tophat"
+        )
         vol = np.invert(vol)
-    
+
     selem = morphology.ball(radius)
     vol = vol - morphology.white_tophat(vol, selem)
 
     if background == "bright":
         vol = np.invert(vol)
-    
-    return vol
\ No newline at end of file
+
+    return vol