- implement sliced views, including min, max, sum and mean operations

tests/test_open.py

@@ -6,16 +6,20 @@ import pytest
 from ndbioimage import Imread
 
 
-@pytest.mark.parametrize('file',
-                         [file for file in (Path(__file__).parent / 'files').iterdir() if not file.suffix == '.pzl'])
+@pytest.mark.parametrize(
+    "file",
+    [
+        file
+        for file in (Path(__file__).parent / "files").iterdir()
+        if not file.suffix == ".pzl"
+    ],
+)
 def test_open(file):
-    with Imread(file) as im:
-        mean = im[dict(c=0, z=0, t=0)].mean()
+    with Imread(file, axes="cztyx") as im:
+        mean = im[0, 0, 0].mean()
         b = pickle.dumps(im)
         jm = pickle.loads(b)
-        assert jm[dict(c=0, z=0, t=0)].mean() == mean
-        v = im.view()
-        assert v[dict(c=0, z=0, t=0)].mean() == mean
-        b = pickle.dumps(v)
-        w = pickle.loads(b)
-        assert w[dict(c=0, z=0, t=0)].mean() == mean
+        assert jm.get_frame(0, 0, 0).mean() == mean
+        b = pickle.dumps(im)
+        jm = pickle.loads(b)
+        assert jm[0, 0, 0].mean() == mean

tests/test_slicing.py

@@ -12,19 +12,24 @@ from ndbioimage import Imread
 
 @pytest.fixture
 def array():
-    return np.random.randint(0, 255, (64, 64, 2, 3, 4), 'uint8')
+    return np.random.randint(0, 255, (64, 64, 2, 3, 4), "uint8")
+
 
 @pytest.fixture()
 def image(array):
     with tempfile.TemporaryDirectory() as folder:
         file = Path(folder) / "test.tif"
-        tiffwrite(file, array, 'yxczt')
-        with Imread(file, axes='yxczt') as im:
+        tiffwrite(file, array, "yxczt")
+        with Imread(file, axes="yxczt") as im:
             yield im
 
 
-@pytest.mark.parametrize('s', combinations_with_replacement(
-    (0, -1, 1, slice(None), slice(0, 1), slice(-1, 0), slice(1, 1)), 5))
+@pytest.mark.parametrize(
+    "s",
+    combinations_with_replacement(
+        (0, -1, 1, slice(None), slice(0, 1), slice(-1, 0), slice(1, 1)), 5
+    ),
+)
 def test_slicing(s, image, array):
     s_im, s_a = image[s], array[s]
     if isinstance(s_a, Number):

tests/test_ufuncs.py

@@ -11,21 +11,42 @@ from ndbioimage import Imread
 
 @pytest.fixture
 def array():
-    return np.random.randint(0, 255, (64, 64, 2, 3, 4), 'uint16')
+    return np.random.randint(0, 255, (64, 64, 2, 3, 4), "uint16")
+
 
 @pytest.fixture()
 def image(array):
     with tempfile.TemporaryDirectory() as folder:
         file = Path(folder) / "test.tif"
-        tiffwrite(file, array, 'yxczt')
-        with Imread(file, axes='yxczt') as im:
+        tiffwrite(file, array, "yxczt")
+        with Imread(file, axes="yxczt") as im:
             yield im
 
 
-@pytest.mark.parametrize('fun_and_axis', product(
-    (np.sum, np.nansum, np.min, np.nanmin, np.max, np.nanmax, np.argmin, np.argmax,
-     np.mean, np.nanmean, np.var, np.nanvar, np.std, np.nanstd), (None, 0, 1, 2, 3, 4)))
+@pytest.mark.parametrize(
+    "fun_and_axis",
+    product(
+        (
+            np.sum,
+            np.nansum,
+            np.min,
+            np.nanmin,
+            np.max,
+            np.nanmax,
+            np.argmin,
+            np.argmax,
+            np.mean,
+            np.nanmean,
+            np.var,
+            np.nanvar,
+            np.std,
+            np.nanstd,
+        ),
+        (None, 0, 1, 2, 3, 4),
+    ),
+)
 def test_ufuncs(fun_and_axis, image, array):
     fun, axis = fun_and_axis
-    assert np.all(np.isclose(fun(image, axis), fun(array, axis))), \
-        f'function {fun.__name__} over axis {axis} does not give the correct result'
+    assert np.all(np.isclose(np.asarray(fun(image, axis)), fun(array, axis))), (
+        f"function {fun.__name__} over axis {axis} does not give the correct result"
+    )