astroalign.py 文件源码

def apply_transform(transform, source, target):
    """Applies the transformation ``transform`` to ``source``.

    The output image will have the same shape as ``target``.

    Args:
        transform: A scikit-image ``SimilarityTransform`` object.
        source (numpy array): A 2D numpy array of the source image to be
            transformed.
        target (numpy array): A 2D numpy array of the target image. Only used
            to set the output image shape.

    Return:
        A numpy 2D array of the transformed source. If source is a masked array
        the returned image will also be a masked array with outside pixels set
        to True.
    """

    from skimage.transform import warp
    aligned_image = warp(source, inverse_map=transform.inverse,
                         output_shape=target.shape, order=3, mode='constant',
                         cval=_np.median(source), clip=False,
                         preserve_range=False)

    if isinstance(source, _np.ma.MaskedArray):
        # it could be that source's mask is just set to False
        if isinstance(source.mask, _np.ndarray):
            aligned_image_mask = warp(source.mask.astype('float32'),
                                      inverse_map=transform.inverse,
                                      output_shape=target.shape,
                                      cval=1.0)
            aligned_image_mask = aligned_image_mask > 0.4
            aligned_image = _np.ma.array(aligned_image,
                                         mask=aligned_image_mask)
        else:
            # If source is masked array with mask set to false, we
            # return the same
            aligned_image = _np.ma.array(aligned_image)
    return aligned_image