from imagekit.lib import *


class _Resize(object):
    
    width = None
    height = None
    
    def __init__(self, width=None, height=None):
        if width is not None:
            self.width = width
        if height is not None:
            self.height = height

    def process(self, img):
        raise NotImplementedError('process must be overridden by subclasses.')


class Crop(_Resize):
    """Resizes an image , cropping it to the specified width and height.

    """

    TOP_LEFT = 'tl'
    TOP = 't'
    TOP_RIGHT = 'tr'
    BOTTOM_LEFT = 'bl'
    BOTTOM = 'b'
    BOTTOM_RIGHT = 'br'
    CENTER = 'c'
    LEFT = 'l'
    RIGHT = 'r'

    _ANCHOR_PTS = {
        TOP_LEFT: (0, 0),
        TOP: (0.5, 0),
        TOP_RIGHT: (1, 0),
        LEFT: (0, 0.5),
        CENTER: (0.5, 0.5),
        RIGHT: (1, 0.5),
        BOTTOM_LEFT: (0, 1),
        BOTTOM: (0.5, 1),
        BOTTOM_RIGHT: (1, 1),
    }

    def __init__(self, width=None, height=None, anchor=None):
        """
        :param width: The target width, in pixels.
        :param height: The target height, in pixels.
        :param anchor: Specifies which part of the image should be retained when
            cropping. Valid values are:

            - Crop.TOP_LEFT
            - Crop.TOP
            - Crop.TOP_RIGHT
            - Crop.LEFT
            - Crop.CENTER
            - Crop.RIGHT
            - Crop.BOTTOM_LEFT
            - Crop.BOTTOM
            - Crop.BOTTOM_RIGHT

        """
        super(Crop, self).__init__(width, height)
        self.anchor = anchor

    def process(self, img):
        cur_width, cur_height = img.size
        horizontal_anchor, vertical_anchor = Crop._ANCHOR_PTS[self.anchor or \
                Crop.CENTER]
        ratio = max(float(self.width)/cur_width, float(self.height)/cur_height)
        resize_x, resize_y = ((cur_width * ratio), (cur_height * ratio))
        crop_x, crop_y = (abs(self.width - resize_x), abs(self.height - resize_y))
        x_diff, y_diff = (int(crop_x / 2), int(crop_y / 2))
        box_left, box_right = {
            0:   (0, self.width),
            0.5: (int(x_diff), int(x_diff + self.width)),
            1:   (int(crop_x), int(resize_x)),
        }[horizontal_anchor]
        box_upper, box_lower = {
            0:   (0, self.height),
            0.5: (int(y_diff), int(y_diff + self.height)),
            1:   (int(crop_y), int(resize_y)),
        }[vertical_anchor]
        box = (box_left, box_upper, box_right, box_lower)
        img = img.resize((int(resize_x), int(resize_y)), Image.ANTIALIAS).crop(box)
        return img


class Fit(_Resize):
    """Resizes an image to fit within the specified dimensions.

    """
    
    def __init__(self, width=None, height=None, upscale=None):
        """
        :param width: The maximum width of the desired image.
        :param height: The maximum height of the desired image.
        :param upscale: A boolean value specifying whether the image should be
                enlarged if its dimensions are smaller than the target
                dimensions.

        """
        super(Fit, self).__init__(width, height)
        self.upscale = upscale

    def process(self, img):
        cur_width, cur_height = img.size
        if not self.width is None and not self.height is None:
            ratio = min(float(self.width)/cur_width,
                        float(self.height)/cur_height)
        else:
            if self.width is None:
                ratio = float(self.height)/cur_height
            else:
                ratio = float(self.width)/cur_width
        new_dimensions = (int(round(cur_width*ratio)),
                          int(round(cur_height*ratio)))
        if new_dimensions[0] > cur_width or \
           new_dimensions[1] > cur_height:
            if not self.upscale:
                return img
        img = img.resize(new_dimensions, Image.ANTIALIAS)
        return img