import warnings
import numpy as np
from skimage import img_as_float
from skimage.util.dtype import dtype_range, dtype_limits
from skimage._shared.utils import deprecated
__all__ = ['histogram', 'cumulative_distribution', 'equalize',
'rescale_intensity', 'adjust_gamma', 'adjust_log', 'adjust_sigmoid']
DTYPE_RANGE = dtype_range.copy()
DTYPE_RANGE.update((d.__name__, limits) for d, limits in dtype_range.items())
DTYPE_RANGE.update({'uint10': (0, 2**10 - 1),
'uint12': (0, 2**12 - 1),
'uint14': (0, 2**14 - 1),
'bool': dtype_range[np.bool_],
'float': dtype_range[np.float64]})
def histogram(image, nbins=256):
"""Return histogram of image.
Unlike `numpy.histogram`, this function returns the centers of bins and
does not rebin integer arrays. For integer arrays, each integer value has
its own bin, which improves speed and intensity-resolution.
The histogram is computed on the flattened image: for color images, the
function should be used separately on each channel to obtain a histogram
for each color channel.
import warnings
import numpy as np
from skimage import img_as_float
from skimage.util.dtype import dtype_range, dtype_limits
__all__ = [
'histogram', 'cumulative_distribution', 'equalize', 'rescale_intensity',
'adjust_gamma', 'adjust_log', 'adjust_sigmoid'
]
DTYPE_RANGE = dtype_range.copy()
DTYPE_RANGE.update((d.__name__, limits) for d, limits in dtype_range.items())
DTYPE_RANGE.update({
'uint10': (0, 2**10 - 1),
'uint12': (0, 2**12 - 1),
'uint14': (0, 2**14 - 1),
'bool': dtype_range[np.bool_],
'float': dtype_range[np.float64]
})
def histogram(image, nbins=256):
"""Return histogram of image.
Unlike `numpy.histogram`, this function returns the centers of bins and
does not rebin integer arrays. For integer arrays, each integer value has
its own bin, which improves speed and intensity-resolution.
The histogram is computed on the flattened image: for color images, the
function should be used separately on each channel to obtain a histogram
def test_invert_roundtrip():
for t, limits in dtype_range.items():
image = np.array(limits, dtype=t)
expected = invert(invert(image))
assert_array_equal(image, expected)