__all__ = ['imread', 'imsave']

import numpy as np

try:
    from PIL import Image
except ImportError:
    raise ImportError("The Python Image Library could not be found. "
                      "Please refer to "
                      "https://pypi.python.org/pypi/Pillow/ (or "
                      "http://pypi.python.org/pypi/PIL/) "
                      "for further instructions.")

from skimage.util import img_as_ubyte, img_as_uint

from six import string_types
from skimage.external.tifffile import imread as tif_imread, imsave as tif_imsave


def imread(fname, dtype=None):
    """Load an image from file.

    Parameters
    ----------
    fname : str
       File name.
    dtype : numpy dtype object or string specifier
       Specifies data type of array elements.

    Notes
    -----
    Tiff files are handled by Christophe Golhke's tifffile.py [1]_, and support many
    advanced image types including multi-page and floating point.

    All other files are read using the Python Imaging Libary.
    See PIL docs [2]_ for a list of supported formats.

    References
    ----------
    .. [1] http://www.lfd.uci.edu/~gohlke/code/tifffile.py.html
    .. [2] http://pillow.readthedocs.org/en/latest/handbook/image-file-formats.html

    """
    if hasattr(fname, 'lower') and dtype is None:
        if fname.lower().endswith(('.tiff', '.tif')):
            return tif_imread(fname)

    im = Image.open(fname)
    try:
        # this will raise an IOError if the file is not readable
        im.getdata()[0]
    except IOError:
        site = "http://pillow.readthedocs.org/en/latest/installation.html#external-libraries"
        raise ValueError('Could not load "%s"\nPlease see documentation at: %s' % (fname, site))
    else:
        return pil_to_ndarray(im, dtype)


def pil_to_ndarray(im, dtype=None):
    """Import a PIL Image object to an ndarray, in memory.

    Parameters
    ----------
    Refer to ``imread``.

    """
    fp = im.fp if hasattr(im, 'fp') else None
    if im.mode == 'P':
        if _palette_is_grayscale(im):
            im = im.convert('L')
        else:
            im = im.convert('RGB')
    elif im.mode == '1':
        im = im.convert('L')
    elif im.mode.startswith('I;16'):
        shape = im.size
        dtype = '>u2' if im.mode.endswith('B') else '<u2'
        if 'S' in im.mode:
            dtype = dtype.replace('u', 'i')
        im = np.fromstring(im.tostring(), dtype)
        im.shape = shape[::-1]
    elif 'A' in im.mode:
        im = im.convert('RGBA')
    im = np.array(im, dtype=dtype)
    if fp is not None:
        fp.close()
    return im


def _palette_is_grayscale(pil_image):
    """Return True if PIL image in palette mode is grayscale.

    Parameters
    ----------
    pil_image : PIL image
        PIL Image that is in Palette mode.

    Returns
    -------
    is_grayscale : bool
        True if all colors in image palette are gray.
    """
    assert pil_image.mode == 'P'
    # get palette as an array with R, G, B columns
    palette = np.asarray(pil_image.getpalette()).reshape((256, 3))
    # Not all palette colors are used; unused colors have junk values.
    start, stop = pil_image.getextrema()
    valid_palette = palette[start:stop]
    # Image is grayscale if channel differences (R - G and G - B)
    # are all zero.
    return np.allclose(np.diff(valid_palette), 0)


def ndarray_to_pil(arr, format_str=None):
    """Export an ndarray to a PIL object.

    Parameters
    ----------
    Refer to ``imsave``.

    """
    if arr.ndim == 3:
        arr = img_as_ubyte(arr)
        mode = {3: 'RGB', 4: 'RGBA'}[arr.shape[2]]

    elif format_str in ['png', 'PNG']:
        mode = 'I;16'
        mode_base = 'I'

        if arr.dtype.kind == 'f':
            arr = img_as_uint(arr)

        elif arr.max() < 256 and arr.min() >= 0:
            arr = arr.astype(np.uint8)
            mode = mode_base = 'L'

        else:
            arr = img_as_uint(arr)

    else:
        arr = img_as_ubyte(arr)
        mode = 'L'
        mode_base = 'L'

    if arr.ndim == 2:
        im = Image.new(mode_base, arr.T.shape)
        im.fromstring(arr.tostring(), 'raw', mode)

    else:
        try:
            im = Image.frombytes(mode, (arr.shape[1], arr.shape[0]),
                                 arr.tostring())
        except AttributeError:
            im = Image.fromstring(mode, (arr.shape[1], arr.shape[0]),
                                  arr.tostring())
    return im


def imsave(fname, arr, format_str=None):
    """Save an image to disk.

    Parameters
    ----------
    fname : str or file-like object
        Name of destination file.
    arr : ndarray of uint8 or float
        Array (image) to save.  Arrays of data-type uint8 should have
        values in [0, 255], whereas floating-point arrays must be
        in [0, 1].
    format_str: str
        Format to save as, this is defaulted to PNG if using a file-like
        object; this will be derived from the extension if fname is a string

    Notes
    -----
    Tiff files are handled by Christophe Golhke's tifffile.py [1]_,
    and support many advanced image types including multi-page and
    floating point.

    All other image formats use the Python Imaging Libary.
    See PIL docs [2]_ for a list of other supported formats.
    All images besides single channel PNGs are converted using `img_as_uint8`.
    Single Channel PNGs have the following behavior:
    - Integer values in [0, 255] and Boolean types -> img_as_uint8
    - Floating point and other integers -> img_as_uint16

    References
    ----------
    .. [1] http://www.lfd.uci.edu/~gohlke/code/tifffile.py.html
    .. [2] http://pillow.readthedocs.org/en/latest/handbook/image-file-formats.html
    """
    # default to PNG if file-like object
    if not isinstance(fname, string_types) and format_str is None:
        format_str = "PNG"
    # Check for png in filename
    if (isinstance(fname, string_types)
            and fname.lower().endswith(".png")):
        format_str = "PNG"

    arr = np.asanyarray(arr).squeeze()

    if arr.dtype.kind == 'b':
        arr = arr.astype(np.uint8)

    use_tif = False
    if hasattr(fname, 'lower'):
        if fname.lower().endswith(('.tiff', '.tif')):
            use_tif = True
    if not format_str is None:
        if format_str.lower() in ['tiff', 'tif']:
            use_tif = True

    if use_tif:
        tif_imsave(fname, arr)
        return

    if arr.ndim not in (2, 3):
        raise ValueError("Invalid shape for image array: %s" % arr.shape)

    if arr.ndim == 3:
        if arr.shape[2] not in (3, 4):
            raise ValueError("Invalid number of channels in image array.")

    img = ndarray_to_pil(arr, format_str=format_str)
    img.save(fname, format=format_str)


def imshow(arr):
    """Display an image, using PIL's default display command.

    Parameters
    ----------
    arr : ndarray
       Image to display.  Images of dtype float are assumed to be in
       [0, 1].  Images of dtype uint8 are in [0, 255].

    """
    Image.fromarray(img_as_ubyte(arr)).show()


def _app_show():
    pass