Function _create_shear

monai/transforms/utils.py:986–1012

(spatial_dims: int, coefs: Sequence[float] | float, eye_func=np.eye)

def _create_shear(spatial_dims: int, coefs: Sequence[float] | float, eye_func=np.eye) -> NdarrayOrTensor:
    if spatial_dims == 2:
        coefs = ensure_tuple_size(coefs, dim=2, pad_val=0.0)
        rank = 3
        shear_indices = [(0, 1, coefs[0]), (1, 0, coefs[1])]
    elif spatial_dims == 3:
        coefs = ensure_tuple_size(coefs, dim=6, pad_val=0.0)
        rank = 4
        shear_indices = [
            (0, 1, coefs[0]),
            (0, 2, coefs[1]),
            (1, 0, coefs[2]),
            (1, 2, coefs[3]),
            (2, 0, coefs[4]),
            (2, 1, coefs[5]),
        ]
    else:
        raise NotImplementedError("Currently only spatial_dims in [2, 3] are supported.")
    # Compose individual single-axis shear matrices so that the result is a
    # proper (area/volume-preserving) shear with determinant 1.  Each elementary
    # shear is pre-multiplied, so the first coefficient is applied first.
    out = eye_func(rank)
    for i, j, c in shear_indices:
        s = eye_func(rank)
        s[i, j] = c
        out = s @ out
    return out  # type: ignore


def create_scale(