Updates affine transformation

    log.debug(f'Number of GCPs for affine estimation: {len(dst_gcps)}')

    affine = tf.estimate_transform('affine', np.array([*base_gcps]), np.array([*dst_gcps]))

    affine = tf.estimate_transform('projective', np.array([*base_gcps]), np.array([*dst_gcps]))

    #affine = tf.estimate_transform('affine', np.array([*base_gcps]), np.array([*dst_gcps]))

    log.debug(f'Computed afffine: {affine}')

    t2 = time.time()

    log.debug(f'Estimation of local affine took {t2-t1} seconds.')

                                                    size_x=size_x, 

                                                    size_y=size_y)

    log.debug(f'Affine shear: {affine_transform.shear}')

    if abs(affine_transform.shear) > 1e-2:

        # Matching LROC NAC high slew images to nadir images demonstrated that affine transformations

        # with high shear match poorly. The search templates also have reflection (ROI object, x/y_read_length)

        # because a high shear affine requires  alot of data to be read in. 

        # TODO: Consider handling this differently in the future should nadir to high slew image matching be required.

        raise Exception(f'Affine shear: {affine_transform.shear} is greater than 1e-2. It is highly unlikely that these images will match, so skipping.')

    #log.debug(f'Affine shear: {affine_transform.shear}')

    # if abs(affine_transform.shear) > 1e-2:

    #     # Matching LROC NAC high slew images to nadir images demonstrated that affine transformations

    #     # with high shear match poorly. The search templates also have reflection (ROI object, x/y_read_length)

    #     # because a high shear affine requires  alot of data to be read in. 

    #     # TODO: Consider handling this differently in the future should nadir to high slew image matching be required.

    #     raise Exception(f'Affine shear: {affine_transform.shear} is greater than 1e-2. It is highly unlikely that these images will match, so skipping.')

    # The above coordinate transformation to get the center of the ROI handles translation. 

    # So, we only need to rotate/shear/scale the ROI. Omitting scale, which should be 1 (?) results

    # in an affine transoformation that does not match the full image affine

    tf_rotate = tf.AffineTransform(rotation=affine_transform.rotation, 

                                   shear=affine_transform.shear,

                                   scale=affine_transform.scale)

    # tf_rotate = tf.AffineTransform(rotation=affine_transform.rotation, 

    #                                shear=affine_transform.shear,

    #                                scale=affine_transform.scale)

    matrix = affine_transform.params

    matrix[0][-1] = 0

    matrix[1][-1] = 0

    affine_transform = tf.AffineTransform(matrix)

    # This rotates about the center of the image

    shift_x, shift_y = moving_roi.clip_center

    # Define the full chain multiplying the transformations (read right to left),

    # this is 'shift to the center', apply the rotation, shift back

    # to the origin.

    trans = tf_shift_inv + tf_rotate + tf_shift

    trans = tf_shift_inv + affine_transform + tf_shift

    return trans