| __call__(self, np.ndarray image, tuple[int, int] center) | lsst.scarlet.lite.operators.Monotonicity | |
| __copy__(self) | lsst.scarlet.lite.operators.Monotonicity | |
| __deepcopy__(self, dict[int, Any]|None memo=None) | lsst.scarlet.lite.operators.Monotonicity | |
| __init__(self, tuple[int, int] shape, npt.DTypeLike dtype=float, bool auto_update=True, int fit_radius=1) (defined in lsst.scarlet.lite.operators.Monotonicity) | lsst.scarlet.lite.operators.Monotonicity | |
| auto_update (defined in lsst.scarlet.lite.operators.Monotonicity) | lsst.scarlet.lite.operators.Monotonicity | |
| center(self) | lsst.scarlet.lite.operators.Monotonicity | |
| check_size(self, tuple[int, int] shape, tuple[int, int] center, bool update=True) | lsst.scarlet.lite.operators.Monotonicity | |
| distance (defined in lsst.scarlet.lite.operators.Monotonicity) | lsst.scarlet.lite.operators.Monotonicity | |
| dtype (defined in lsst.scarlet.lite.operators.Monotonicity) | lsst.scarlet.lite.operators.Monotonicity | |
| fit_radius (defined in lsst.scarlet.lite.operators.Monotonicity) | lsst.scarlet.lite.operators.Monotonicity | |
| shape(self) | lsst.scarlet.lite.operators.Monotonicity | |
| sizes (defined in lsst.scarlet.lite.operators.Monotonicity) | lsst.scarlet.lite.operators.Monotonicity | |
| update(self, tuple[int, int] shape) | lsst.scarlet.lite.operators.Monotonicity | |
| weights (defined in lsst.scarlet.lite.operators.Monotonicity) | lsst.scarlet.lite.operators.Monotonicity | |