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# Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from .interval import (PercentileInterval, AsymmetricPercentileInterval,
ManualInterval, MinMaxInterval)
from .stretch import (LinearStretch, SqrtStretch, PowerStretch, LogStretch,
AsinhStretch)
from ..utils.decorators import deprecated
__all__ = ['scale_image']
@deprecated('1.3',
alternative='`~astropy.visualization.mpl_normalize.simple_norm`')
def scale_image(image, scale='linear', power=1.0, asinh_a=0.1, min_cut=None,
max_cut=None, min_percent=None, max_percent=None,
percent=None, clip=True):
"""
Perform scaling/stretching of an image between minimum and maximum
cut levels.
Parameters
----------
image : array-like
The array of values.
scale : {{'linear', 'sqrt', 'power', log', 'asinh'}}
The scaling/stretch function to apply to the image. The default
is 'linear'.
power : float, optional
The power index for ``scale='power'`` image scaling. The
default is 1.0.
asinh_a : float, optional
For ``scale='asinh'`` image scaling, the value where the asinh
curve transitions from linear to logarithmic behavior, expressed
as a fraction of the normalized image. Must be in the range
between 0 and 1.
min_cut : float, optional
The pixel value of the minimum cut level. Data values less than
``min_cut`` will set to ``min_cut`` before scaling the image.
The default is the image minimum. ``min_cut`` overrides
``min_percent``.
max_cut : float, optional
The pixel value of the maximum cut level. Data values greater
than ``min_cut`` will set to ``min_cut`` before scaling the
image. The default is the image maximum. ``max_cut`` overrides
``max_percent``.
min_percent : float, optional
The percentile value used to determine the pixel value of
minimum cut level. The default is 0.0. ``min_percent``
overrides ``percent``.
max_percent : float, optional
The percentile value used to determine the pixel value of
maximum cut level. The default is 100.0. ``max_percent``
overrides ``percent``.
percent : float, optional
The percentage of the image values used to determine the pixel
values of the minimum and maximum cut levels. The lower cut
level will set at the ``(100 - percent) / 2`` percentile, while
the upper cut level will be set at the ``(100 + percent) / 2``
percentile. The default is 100.0. ``percent`` is ignored if
either ``min_percent`` or ``max_percent`` is input.
clip : bool, optional
Whether to clip the result to the range [0:1].
Returns
-------
image : ndarray
The array of the scaled/stretched image with a minimum of 0.0
and a maximum of 1.0.
"""
if percent is not None:
interval = PercentileInterval(percent)
elif min_percent is not None or max_percent is not None:
interval = AsymmetricPercentileInterval(min_percent or 0.,
max_percent or 100.)
elif min_cut is not None or max_cut is not None:
interval = ManualInterval(min_cut or np.min(image),
max_cut or np.max(image))
else:
interval = MinMaxInterval()
if scale == 'linear':
stretch = LinearStretch()
elif scale == 'sqrt':
stretch = SqrtStretch()
elif scale == 'power':
stretch = PowerStretch(power)
elif scale == 'log':
stretch = LogStretch()
elif scale == 'asinh':
stretch = AsinhStretch(asinh_a)
else:
raise ValueError('Unknown scale: {0}'.format(scale))
return (stretch + interval)(image, clip=clip)
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