# 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)