from __future__ import division
import numpy as np

from ._warp import warp


def _swirl_mapping(xy, center, rotation, strength, radius):
    x, y = xy.T
    x0, y0 = center
    rho = np.sqrt((x - x0)**2 + (y - y0)**2)

    # Ensure that the transformation decays to approximately 1/1000-th
    # within the specified radius.
    radius = radius / 5 * np.log(2)

    theta = rotation + strength * \
            np.exp(-rho / radius) + \
            np.arctan2(y - y0, x - x0)

    xy[..., 0] = x0 + rho * np.cos(theta)
    xy[..., 1] = y0 + rho * np.sin(theta)

    return xy

def swirl(image, center=None, strength=1, radius=100, rotation=0,
          output_shape=None, order=1, mode='constant', cval=0):
    """Perform a swirl transformation.

    Parameters
    ----------
    image : ndarray
        Input image.
    center : (x,y) tuple or (2,) ndarray
        Center coordinate of transformation.
    strength : float
        The amount of swirling applied.
    radius : float
        The extent of the swirl in pixels.  The effect dies out
        rapidly beyond `radius`.
    rotation : float
        Additional rotation applied to the image.

    Returns
    -------
    swirled : ndarray
        Swirled version of the input.

    Other parameters
    ----------------
    output_shape : tuple or ndarray
        Size of the generated output image.
    order : int
        Order of splines used in interpolation.  See
        `scipy.ndimage.map_coordinates` for detail.
    mode : string
        How to handle values outside the image borders.  See
        `scipy.ndimage.map_coordinates` for detail.
    cval : string
        Used in conjunction with mode 'constant', the value outside
        the image boundaries.

    """

    if center is None:
        center = np.array(image.shape)[:2] / 2

    warp_args = {'center': center,
                 'rotation': rotation,
                 'strength': strength,
                 'radius': radius}

    return warp(image, _swirl_mapping, map_args=warp_args,
                output_shape=output_shape,
                order=order, mode=mode, cval=cval)