medipt.utils package

Submodules

medipt.utils.image_input_output_space module

medipt.utils.image_input_output_space.resolve_input_output_space(dim=3, input_image=None, reference_image=None, input_size=None, output_size=None, input_spacing=None, output_spacing=None, input_direction=None, output_direction=None, input_origin=None, output_origin=None, *args, **kwargs)

Parameters:

• dim (int) –

• input_image (Image | None) –

• reference_image (Image | None) –

• input_size (List[int | float] | Tuple[int | float, ...] | None) –

• output_size (List[int | float] | Tuple[int | float, ...] | None) –

• input_spacing (List[int | float] | Tuple[int | float, ...] | None) –

• output_spacing (List[int | float] | Tuple[int | float, ...] | None) –

• input_direction (List[int | float] | Tuple[int | float, ...] | None) –

• output_direction (List[int | float] | Tuple[int | float, ...] | None) –

• input_origin (List[int | float] | Tuple[int | float, ...] | None) –

• output_origin (List[int | float] | Tuple[int | float, ...] | None) –

medipt.utils.random_float module

medipt.utils.random_float.initialize_rand_state(seed=None, legacy_random_state=True)

Return type:

Union[ModuleType, Generator, BitGenerator]

Parameters:

• seed (RandomState | Generator | BitGenerator | int | None) –

• legacy_random_state (bool) –

medipt.utils.random_float.random_binomial(n, p, output_size=None, ignore_axis=None, seed=None, legacy_random_state=True, rand_init=None)

Parameters:

• n (Union[int, float, integer, floating]) –

• p (Union[int, float, integer, floating]) –

• output_size (Union[List[Union[int, float]], Tuple[Union[int, float]], int, float, integer, floating, None]) –

• ignore_axis (Union[None, List[int], Tuple[int], int]) – Ignores the axis specified. If None, then no axis is ignored. Works only for 1D right now.

• seed (Union[RandomState, Generator, BitGenerator, int, None]) –

• legacy_random_state (bool) –

• rand_init (module | Generator | BitGenerator | None) –

Return type:

Union[ndarray, int]

Returns:

medipt.utils.random_float.random_uniform_float(low_value, high_value, output_size=None, dim=None, seed=None, legacy_random_state=True, rand_init=None)

Return type:

Union[float, List[float], ndarray]

Parameters:

• low_value (float | int | List[int | float] | Tuple[int | float, ...] | integer | floating | ndarray) –

• high_value (float | int | List[int | float] | Tuple[int | float, ...] | integer | floating | ndarray) –

• output_size (List[int | float] | Tuple[int | float, ...] | int | float | integer | floating | ndarray | None) –

• dim (int | None) –

• seed (RandomState | Generator | BitGenerator | int | None) –

• legacy_random_state (bool) –

• rand_init (module | Generator | BitGenerator | None) –

medipt.utils.spatial_utils module

medipt.utils.spatial_utils.get_output_size_from_spacing(dim, input_size, input_spacing, input_direction, output_spacing, output_direction=None, *args, **kwargs)

Parameters:

• dim (int) –

• input_size (List[int] | Tuple[int, ...]) –

• input_spacing (List[int] | Tuple[int, ...]) –

• input_direction (List[int] | Tuple[int, ...]) –

• output_spacing (List[int] | Tuple[int, ...]) –

• output_direction (List[int] | Tuple[int, ...] | None) –

medipt.utils.spatial_utils.get_output_spacing_from_size(dim, input_size, input_spacing, input_direction, output_size, output_direction=None, *args, **kwargs)

Parameters:

• dim (int) –

• input_size (List[int] | Tuple[int, ...]) –

• input_spacing (List[int] | Tuple[int, ...]) –

• input_direction (List[int] | Tuple[int, ...]) –

• output_size (List[int] | Tuple[int, ...]) –

• output_direction (List[int] | Tuple[int, ...] | None) –

medipt.utils.spatial_utils.image_center(input_size, *args, **kwargs)

Parameters:

input_size (Tuple[int, ...]) –

medipt.utils.spatial_utils.image_index_to_phys(dim, index_coords, image=None, size=None, origin=None, spacing=None, direction=None, *args, **kwargs)

Return type:

List[float]

Parameters:

• dim (int) –

• index_coords (List[int | float] | Tuple[int | float, ...]) –

• image (Image | None) –

• size (Tuple[int, ...] | None) –

• origin (List[int | float] | Tuple[int | float, ...] | None) –

• spacing (List[int | float] | Tuple[int | float, ...] | None) –

• direction (List[int | float] | Tuple[int | float, ...] | None) –

medipt.utils.spatial_utils.physical_image_size(dim, size, spacing, direction, origin, *args, **kwargs)

Return type:

List[float]

Parameters:

• dim (int) –

• size (Tuple[int, ...]) –

• spacing (Tuple[float, ...]) –

• direction (Tuple[float, ...]) –

• origin (Tuple[float, ...]) –

medipt.utils.spatial_utils.physical_image_size_no_origin(dim, size, spacing, direction, *args, **kwargs)

Return type:

List[float]

Parameters:

• dim (int) –

• size (Tuple[int, ...]) –

• spacing (Tuple[float, ...]) –

• direction (Tuple[float, ...]) –

Module contents

medipt.utils.set_num_workers(n_threads)