interfaces

class NumpyCase[source]

In-memory numpy array

interface

alias of NumpyInterface

classmethod make_array(shape: ~typing.Tuple[int, ...] = (10, 10), dtype: str | type | ~typing.Any | ~numpy.generic = <class 'float'>, path: ~pathlib.Path | None = None, array: ~numpydantic.types.NDArrayType | None = None) → ndarray[source]

Make an array from a shape and dtype, and a path if needed

Parameters:

  • shape – shape of the array

  • dtype – dtype of the array

  • path – Path, if needed to generate on disk

  • array – Rather than passing shape and dtype, pass a literal arraylike thing

class HDF5Case[source]

HDF5 Array

classmethod make_array(shape: ~typing.Tuple[int, ...] = (10, 10), dtype: str | type | ~typing.Any | ~numpy.generic = <class 'float'>, path: ~pathlib.Path | None = None, array: ~numpydantic.types.NDArrayType | None = None) → H5ArrayPath | None[source]

Make an array from a shape and dtype, and a path if needed

Parameters:

  • shape – shape of the array

  • dtype – dtype of the array

  • path – Path, if needed to generate on disk

  • array – Rather than passing shape and dtype, pass a literal arraylike thing

class HDF5CompoundCase[source]

HDF5 Array with a fake compound dtype

classmethod make_array(shape: ~typing.Tuple[int, ...] = (10, 10), dtype: str | type | ~typing.Any | ~numpy.generic = <class 'float'>, path: ~pathlib.Path | None = None, array: ~numpydantic.types.NDArrayType | None = None) → H5ArrayPath | None[source]

Make an array from a shape and dtype, and a path if needed

Parameters:

  • shape – shape of the array

  • dtype – dtype of the array

  • path – Path, if needed to generate on disk

  • array – Rather than passing shape and dtype, pass a literal arraylike thing

class DaskCase[source]

In-memory dask array

interface

alias of DaskInterface

classmethod make_array(shape: ~typing.Tuple[int, ...] = (10, 10), dtype: str | type | ~typing.Any | ~numpy.generic = <class 'float'>, path: ~pathlib.Path | None = None, array: ~numpydantic.types.NDArrayType | None = None) → Array[source]

Make an array from a shape and dtype, and a path if needed

Parameters:

  • shape – shape of the array

  • dtype – dtype of the array

  • path – Path, if needed to generate on disk

  • array – Rather than passing shape and dtype, pass a literal arraylike thing

class ZarrCase[source]

In-memory zarr array

classmethod make_array(shape: ~typing.Tuple[int, ...] = (10, 10), dtype: str | type | ~typing.Any | ~numpy.generic = <class 'float'>, path: ~pathlib.Path | None = None, array: ~numpydantic.types.NDArrayType | None = None) → Array | None[source]

Make an array from a shape and dtype, and a path if needed

Parameters:

  • shape – shape of the array

  • dtype – dtype of the array

  • path – Path, if needed to generate on disk

  • array – Rather than passing shape and dtype, pass a literal arraylike thing

class ZarrDirCase[source]

On-disk zarr array

classmethod make_array(shape: ~typing.Tuple[int, ...] = (10, 10), dtype: str | type | ~typing.Any | ~numpy.generic = <class 'float'>, path: ~pathlib.Path | None = None, array: ~numpydantic.types.NDArrayType | None = None) → Array | None[source]

Make an array from a shape and dtype, and a path if needed

Parameters:

  • shape – shape of the array

  • dtype – dtype of the array

  • path – Path, if needed to generate on disk

  • array – Rather than passing shape and dtype, pass a literal arraylike thing

class ZarrZipCase[source]

Zarr zip store

classmethod make_array(shape: ~typing.Tuple[int, ...] = (10, 10), dtype: str | type | ~typing.Any | ~numpy.generic = <class 'float'>, path: ~pathlib.Path | None = None, array: ~numpydantic.types.NDArrayType | None = None) → Array | None[source]

Make an array from a shape and dtype, and a path if needed

Parameters:

  • shape – shape of the array

  • dtype – dtype of the array

  • path – Path, if needed to generate on disk

  • array – Rather than passing shape and dtype, pass a literal arraylike thing

class ZarrNestedCase[source]

Nested zarr array

classmethod make_array(shape: ~typing.Tuple[int, ...] = (10, 10), dtype: str | type | ~typing.Any | ~numpy.generic = <class 'float'>, path: ~pathlib.Path | None = None, array: ~numpydantic.types.NDArrayType | None = None) → ZarrArrayPath[source]

Make an array from a shape and dtype, and a path if needed

Parameters:

  • shape – shape of the array

  • dtype – dtype of the array

  • path – Path, if needed to generate on disk

  • array – Rather than passing shape and dtype, pass a literal arraylike thing

class VideoCase[source]

AVI video

interface

alias of VideoInterface

classmethod make_array(shape: ~typing.Tuple[int, ...] = (10, 10, 10, 3), dtype: str | type | ~typing.Any | ~numpy.generic = <class 'numpy.uint8'>, path: ~pathlib.Path | None = None, array: ~numpydantic.types.NDArrayType | None = None) → Path | None[source]

Make an array from a shape and dtype, and a path if needed

Parameters:

  • shape – shape of the array

  • dtype – dtype of the array

  • path – Path, if needed to generate on disk

  • array – Rather than passing shape and dtype, pass a literal arraylike thing

classmethod skip(shape: Tuple[int, ...], dtype: str | type | Any | generic) → bool[source]

We really can only handle 4 dimensional cases in 8-bit rn lol

Todo

Fix shape/writing for grayscale videos