webknossos.dataset.downsampling_utils

# class SamplingModes:

# SamplingModes()

# ANISOTROPIC = 'anisotropic'

# ISOTROPIC = 'isotropic'

# CONSTANT_Z = 'constant_z'

# class InterpolationModes(enum.Enum):

An enumeration.

# def determine_buffer_shape( array_info: webknossos.dataset._array.ArrayInfo ) -> webknossos.geometry.vec3_int.Vec3Int:

# def calculate_mags_to_downsample( from_mag: webknossos.geometry.mag.Mag, max_mag: webknossos.geometry.mag.Mag, scale: Union[Tuple[float, float, float], NoneType] ) -> List[webknossos.geometry.mag.Mag]:

# def calculate_mags_to_upsample( from_mag: webknossos.geometry.mag.Mag, min_mag: webknossos.geometry.mag.Mag, scale: Union[Tuple[float, float, float], NoneType] ) -> List[webknossos.geometry.mag.Mag]:

# def calculate_default_max_mag( dataset_size: Union[webknossos.geometry.vec3_int.Vec3Int, Tuple[int, int, int], numpy.ndarray, Iterable[int]] ) -> webknossos.geometry.mag.Mag:

# def parse_interpolation_mode( interpolation_mode: str, layer_category: Literal['color', 'segmentation'] ) -> webknossos.dataset.downsampling_utils.InterpolationModes:

# def linear_filter_3d(data: numpy.ndarray, factors: List[int], order: int) -> numpy.ndarray:

# def non_linear_filter_3d( data: numpy.ndarray, factors: List[int], func: Callable[[numpy.ndarray], numpy.ndarray] ) -> numpy.ndarray:

# def downsample_unpadded_data( buffer: numpy.ndarray, target_mag: webknossos.geometry.mag.Mag, interpolation_mode: webknossos.dataset.downsampling_utils.InterpolationModes ) -> numpy.ndarray:

# def downsample_cube( cube_buffer: numpy.ndarray, factors: List[int], interpolation_mode: webknossos.dataset.downsampling_utils.InterpolationModes ) -> numpy.ndarray: