rm CondaPkg environment

.CondaPkg/env/Lib/site-packages/skimage/exposure/histogram_matching.py

@@ -1,90 +0,0 @@
-import numpy as np
-
-from .._shared import utils
-
-
-def _match_cumulative_cdf(source, template):
-    """
-    Return modified source array so that the cumulative density function of
-    its values matches the cumulative density function of the template.
-    """
-    if source.dtype.kind == 'u':
-        src_lookup = source.reshape(-1)
-        src_counts = np.bincount(src_lookup)
-        tmpl_counts = np.bincount(template.reshape(-1))
-
-        # omit values where the count was 0
-        tmpl_values = np.nonzero(tmpl_counts)[0]
-        tmpl_counts = tmpl_counts[tmpl_values]
-    else:
-        src_values, src_lookup, src_counts = np.unique(source.reshape(-1),
-                                                       return_inverse=True,
-                                                       return_counts=True)
-        tmpl_values, tmpl_counts = np.unique(template.reshape(-1),
-                                             return_counts=True)
-
-    # calculate normalized quantiles for each array
-    src_quantiles = np.cumsum(src_counts) / source.size
-    tmpl_quantiles = np.cumsum(tmpl_counts) / template.size
-
-    interp_a_values = np.interp(src_quantiles, tmpl_quantiles, tmpl_values)
-    return interp_a_values[src_lookup].reshape(source.shape)
-
-
-@utils.channel_as_last_axis(channel_arg_positions=(0, 1))
-def match_histograms(image, reference, *, channel_axis=None):
-    """Adjust an image so that its cumulative histogram matches that of another.
-
-    The adjustment is applied separately for each channel.
-
-    Parameters
-    ----------
-    image : ndarray
-        Input image. Can be gray-scale or in color.
-    reference : ndarray
-        Image to match histogram of. Must have the same number of channels as
-        image.
-    channel_axis : int or None, optional
-        If None, the image is assumed to be a grayscale (single channel) image.
-        Otherwise, this parameter indicates which axis of the array corresponds
-        to channels.
-
-    Returns
-    -------
-    matched : ndarray
-        Transformed input image.
-
-    Raises
-    ------
-    ValueError
-        Thrown when the number of channels in the input image and the reference
-        differ.
-
-    References
-    ----------
-    .. [1] http://paulbourke.net/miscellaneous/equalisation/
-
-    """
-    if image.ndim != reference.ndim:
-        raise ValueError('Image and reference must have the same number '
-                         'of channels.')
-
-    if channel_axis is not None:
-        if image.shape[-1] != reference.shape[-1]:
-            raise ValueError('Number of channels in the input image and '
-                             'reference image must match!')
-
-        matched = np.empty(image.shape, dtype=image.dtype)
-        for channel in range(image.shape[-1]):
-            matched_channel = _match_cumulative_cdf(image[..., channel],
-                                                    reference[..., channel])
-            matched[..., channel] = matched_channel
-    else:
-        # _match_cumulative_cdf will always return float64 due to np.interp
-        matched = _match_cumulative_cdf(image, reference)
-
-    if matched.dtype.kind == 'f':
-        # output a float32 result when the input is float16 or float32
-        out_dtype = utils._supported_float_type(image.dtype)
-        matched = matched.astype(out_dtype, copy=False)
-    return matched