fix unit-tests filters

qim3d/filters/_common_filter_methods.py

@@ -8,9 +8,10 @@ from skimage import morphology
 import dask.array as da
 import dask_image.ndfilters as dask_ndfilters
 
-from qim3d.utils._logger import log
+from qim3d.utils import log
 
 __all__ = [
+    "FilterBase",
     "Gaussian",
     "Median",
     "Maximum",
@@ -26,7 +27,7 @@ __all__ = [
 
 
 class FilterBase:
-    def __init__(self, dask=False, chunks="auto", *args, **kwargs):
+    def __init__(self, *args, dask=False, chunks="auto", **kwargs):
         """
         Base class for image filters.
 
@@ -210,7 +211,7 @@ class Pipeline:
         return input
 
 
-def gaussian(vol, dask=False, chunks='auto', *args, **kwargs):
+def gaussian(vol, *args, dask=False, chunks='auto', **kwargs):
     """
     Applies a Gaussian filter to the input volume using scipy.ndimage.gaussian_filter or dask_image.ndfilters.gaussian_filter.
 

qim3d/tests/filters/test_filters.py

 import qim3d
-from qim3d.filters import *
 import numpy as np
 import pytest
 import re
 
 def test_filter_base_initialization():
-    filter_base = qim3d.processing.filters.FilterBase(3,size=2)
+    filter_base = qim3d.filters.FilterBase(3,size=2)
     assert filter_base.args == (3,)
     assert filter_base.kwargs == {'size': 2}
 
@@ -13,10 +12,10 @@ def test_gaussian_filter():
     input_image = np.random.rand(50, 50)
 
     # Testing the function
-    filtered_image_fn = gaussian(input_image,sigma=1.5)
+    filtered_image_fn = qim3d.filters.gaussian(input_image,sigma=1.5)
 
     # Testing the class method
-    gaussian_filter_cls = Gaussian(sigma=1.5)
+    gaussian_filter_cls = qim3d.filters.Gaussian(sigma=1.5)
     filtered_image_cls = gaussian_filter_cls(input_image)
     
     # Assertions
@@ -28,10 +27,10 @@ def test_median_filter():
     input_image = np.random.rand(50, 50)
 
     # Testing the function
-    filtered_image_fn = median(input_image, size=3)
+    filtered_image_fn = qim3d.filters.median(input_image, size=3)
 
     # Testing the class method
-    median_filter_cls = Median(size=3)
+    median_filter_cls = qim3d.filters.Median(size=3)
     filtered_image_cls = median_filter_cls(input_image)
 
     # Assertions
@@ -43,10 +42,10 @@ def test_maximum_filter():
     input_image = np.random.rand(50, 50)
 
     # Testing the function
-    filtered_image_fn = maximum(input_image, size=3)
+    filtered_image_fn = qim3d.filters.maximum(input_image, size=3)
 
     # Testing the class method
-    maximum_filter_cls = Maximum(size=3)
+    maximum_filter_cls = qim3d.filters.Maximum(size=3)
     filtered_image_cls = maximum_filter_cls(input_image)
 
     # Assertions
@@ -58,10 +57,10 @@ def test_minimum_filter():
     input_image = np.random.rand(50, 50)
 
     # Testing the function
-    filtered_image_fn = minimum(input_image, size=3)
+    filtered_image_fn = qim3d.filters.minimum(input_image, size=3)
 
     # Testing the class method
-    minimum_filter_cls = Minimum(size=3)
+    minimum_filter_cls = qim3d.filters.Minimum(size=3)
     filtered_image_cls = minimum_filter_cls(input_image)
 
     # Assertions
@@ -73,16 +72,16 @@ def test_sequential_filter_pipeline():
     input_image = np.random.rand(50, 50)
 
     # Individual filters
-    gaussian_filter = Gaussian(sigma=1.5)
-    median_filter = Median(size=3)
-    maximum_filter = Maximum(size=3)
+    gaussian_filter = qim3d.filters.Gaussian(sigma=1.5)
+    median_filter = qim3d.filters.Median(size=3)
+    maximum_filter = qim3d.filters.Maximum(size=3)
 
     # Testing the sequential pipeline
-    sequential_pipeline = Pipeline(gaussian_filter, median_filter, maximum_filter)
+    sequential_pipeline = qim3d.filters.Pipeline(gaussian_filter, median_filter, maximum_filter)
     filtered_image_pipeline = sequential_pipeline(input_image)
 
     # Testing the equivalence to maximum(median(gaussian(input,**kwargs),**kwargs),**kwargs)
-    expected_output = maximum(median(gaussian(input_image, sigma=1.5), size=3), size=3)
+    expected_output = qim3d.filters.maximum(qim3d.filters.median(qim3d.filters.gaussian(input_image, sigma=1.5), size=3), size=3)
 
     # Assertions
     assert filtered_image_pipeline.shape == expected_output.shape == input_image.shape
@@ -93,16 +92,16 @@ def test_sequential_filter_appending():
     input_image = np.random.rand(50, 50)
 
     # Individual filters
-    gaussian_filter = Gaussian(sigma=1.5)
-    median_filter = Median(size=3)
-    maximum_filter = Maximum(size=3)
+    gaussian_filter = qim3d.filters.Gaussian(sigma=1.5)
+    median_filter = qim3d.filters.Median(size=3)
+    maximum_filter = qim3d.filters.Maximum(size=3)
 
     # Sequential pipeline with filter initialized at the beginning
-    sequential_pipeline_initial = Pipeline(gaussian_filter, median_filter, maximum_filter)
+    sequential_pipeline_initial = qim3d.filters.Pipeline(gaussian_filter, median_filter, maximum_filter)
     filtered_image_initial = sequential_pipeline_initial(input_image)
 
     # Sequential pipeline with filter appended
-    sequential_pipeline_appended = Pipeline(gaussian_filter, median_filter)
+    sequential_pipeline_appended = qim3d.filters.Pipeline(gaussian_filter, median_filter)
     sequential_pipeline_appended.append(maximum_filter)
     filtered_image_appended = sequential_pipeline_appended(input_image)
 
@@ -113,7 +112,7 @@ def test_sequential_filter_appending():
 
 def test_assertion_error_not_filterbase_subclass():
     # Get valid filter classes
-    valid_filters = [subclass.__name__ for subclass in qim3d.processing.filters.FilterBase.__subclasses__()]
+    valid_filters = [subclass.__name__ for subclass in qim3d.filters.FilterBase.__subclasses__()]
 
     # Create invalid object
     invalid_filter = object()  # An object that is not an instance of FilterBase
@@ -124,4 +123,4 @@ def test_assertion_error_not_filterbase_subclass():
 
     # Use pytest.raises to catch the AssertionError
     with pytest.raises(AssertionError, match=re.escape(message)):
-        sequential_pipeline = Pipeline(invalid_filter)
\ No newline at end of file
+        sequential_pipeline = qim3d.filters.Pipeline(invalid_filter)
\ No newline at end of file