update

.CondaPkg/env/Lib/site-packages/skimage/util/compare.py

@@ -0,0 +1,132 @@
+import functools
+import warnings
+from itertools import product
+
+import numpy as np
+
+from .dtype import img_as_float
+
+
+def _rename_image_params(func):
+    wm_images = (
+        "Since version 0.24, the two input images are named `image0` and "
+        "`image1` (instead of `image1` and `image2`, respectively). Please use "
+        "`image0, image1` to avoid this warning for now, and avoid an error "
+        "from version 0.26 onwards."
+    )
+
+    wm_method = (
+        "Starting in version 0.24, all arguments following `image0, image1` "
+        "(including `method`) will be keyword-only. Please pass `method=` "
+        "in the function call to avoid this warning for now, and avoid an error "
+        "from version 0.26 onwards."
+    )
+
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        # Turn all args into kwargs
+        for i, (value, param) in enumerate(
+            zip(args, ["image0", "image1", "method", "n_tiles"])
+        ):
+            if i >= 2:
+                warnings.warn(wm_method, category=FutureWarning, stacklevel=2)
+            if param in kwargs:
+                raise ValueError(
+                    f"{param} passed both as positional and keyword argument."
+                )
+            else:
+                kwargs[param] = value
+        args = tuple()
+
+        # Account for `image2` if given
+        if "image2" in kwargs.keys():
+            warnings.warn(wm_images, category=FutureWarning, stacklevel=2)
+
+            # Safely move `image2` to `image1` if that's empty
+            if "image1" in kwargs.keys():
+                # Safely move `image1` to `image0`
+                if "image0" in kwargs.keys():
+                    raise ValueError(
+                        "Three input images given; please use only `image0` "
+                        "and `image1`."
+                    )
+                kwargs["image0"] = kwargs.pop("image1")
+            kwargs["image1"] = kwargs.pop("image2")
+
+        return func(*args, **kwargs)
+
+    return wrapper
+
+
+@_rename_image_params
+def compare_images(image0, image1, *, method='diff', n_tiles=(8, 8)):
+    """
+    Return an image showing the differences between two images.
+
+    .. versionadded:: 0.16
+
+    Parameters
+    ----------
+    image0, image1 : ndarray, shape (M, N)
+        Images to process, must be of the same shape.
+
+        .. versionchanged:: 0.24
+            `image1` and `image2` were renamed into `image0` and `image1`
+            respectively.
+    method : string, optional
+        Method used for the comparison.
+        Valid values are {'diff', 'blend', 'checkerboard'}.
+        Details are provided in the note section.
+
+        .. versionchanged:: 0.24
+            This parameter and following ones are keyword-only.
+    n_tiles : tuple, optional
+        Used only for the `checkerboard` method. Specifies the number
+        of tiles (row, column) to divide the image.
+
+    Returns
+    -------
+    comparison : ndarray, shape (M, N)
+        Image showing the differences.
+
+    Notes
+    -----
+    ``'diff'`` computes the absolute difference between the two images.
+    ``'blend'`` computes the mean value.
+    ``'checkerboard'`` makes tiles of dimension `n_tiles` that display
+    alternatively the first and the second image. Note that images must be
+    2-dimensional to be compared with the checkerboard method.
+    """
+
+    if image1.shape != image0.shape:
+        raise ValueError('Images must have the same shape.')
+
+    img1 = img_as_float(image0)
+    img2 = img_as_float(image1)
+
+    if method == 'diff':
+        comparison = np.abs(img2 - img1)
+    elif method == 'blend':
+        comparison = 0.5 * (img2 + img1)
+    elif method == 'checkerboard':
+        if img1.ndim != 2:
+            raise ValueError(
+                'Images must be 2-dimensional to be compared with the '
+                'checkerboard method.'
+            )
+        shapex, shapey = img1.shape
+        mask = np.full((shapex, shapey), False)
+        stepx = int(shapex / n_tiles[0])
+        stepy = int(shapey / n_tiles[1])
+        for i, j in product(range(n_tiles[0]), range(n_tiles[1])):
+            if (i + j) % 2 == 0:
+                mask[i * stepx : (i + 1) * stepx, j * stepy : (j + 1) * stepy] = True
+        comparison = np.zeros_like(img1)
+        comparison[mask] = img1[mask]
+        comparison[~mask] = img2[~mask]
+    else:
+        raise ValueError(
+            'Wrong value for `method`. '
+            'Must be either "diff", "blend" or "checkerboard".'
+        )
+    return comparison