dacapo.experiments.datasplits.datasets.arrays.array

Classes

Array

An Array is a multi-dimensional array of data that can be read from and written to. It is

Module Contents

class dacapo.experiments.datasplits.datasets.arrays.array.Array

An Array is a multi-dimensional array of data that can be read from and written to. It is defined by a region of interest (ROI) in world units, a voxel size, and a number of spatial dimensions. The data is stored in a numpy array, and can be accessed using numpy-like slicing syntax.

The Array class is an abstract base class that defines the interface for all Array implementations. It provides a number of properties that must be implemented by subclasses, such as the ROI, voxel size, and data type of the array. It also provides a method for fetching data from the array, which is implemented by slicing the numpy array.

The Array class also provides a method for checking if the array can be visualized in Neuroglancer, and a method for generating a Neuroglancer layer for the array. These methods are implemented by subclasses that support visualization in Neuroglancer.

attrs

A dictionary of metadata attributes stored on this array.

Type:: Dict[str, Any]

axes

The axes of this dataset as a string of characters, as they are indexed. Permitted characters are:

zyx for spatial dimensions

c for channels

s for samples

Type:: List[str]

dims

The number of spatial dimensions.

Type:: int

voxel_size

The size of a voxel in physical units.

Type:: Coordinate

roi

The total ROI of this array, in world units.

Type:: Roi

dtype

The dtype of this array, in numpy dtypes

Type:: Any

num_channels

The number of channels provided by this dataset. Should return None if the channel dimension doesn’t exist.

Type:: Optional[int]

data

A numpy-like readable and writable view into this array.

Type:: np.ndarray

writable

Can we write to this Array?

Type:: bool

__getitem__(self, roi: Roi) -> np.ndarray: Get a numpy like readable and writable view into this array.

_can_neuroglance(self) → bool: Check if this array can be visualized in Neuroglancer.

_neuroglancer_layer(self): Generate a Neuroglancer layer for this array.

_slices(self, roi: Roi) -> Iterable[slice]: Generate a list of slices for the given ROI.

Note

This class is used to define the interface for all Array implementations. It provides a number of properties that must be implemented by subclasses, such as the ROI, voxel size, and data type of the array. It also provides a method for fetching data from the array, which is implemented by slicing the numpy array. The Array class also provides a method for checking if the array can be visualized in Neuroglancer, and a method for generating a Neuroglancer layer for the array. These methods are implemented by subclasses that support visualization in Neuroglancer.

property attrs: Dict[str, Any]

Abstractmethod:

Return a dictionary of metadata attributes stored on this array.

Returns:: A dictionary of metadata attributes stored on this array.
Return type:: Dict[str, Any]
Raises:: NotImplementedError – This method must be implemented by the subclass.

Examples

>>> array = Array()
>>> array.attrs
{}

Note

This method must be implemented by the subclass.

property axes: List[str]

Abstractmethod:

Returns the axes of this dataset as a string of charactes, as they are indexed. Permitted characters are:

zyx for spatial dimensions

c for channels

s for samples

Returns:: The axes of this dataset as a string of characters, as they are indexed.
Return type:: List[str]
Raises:: NotImplementedError – This method must be implemented by the subclass.

Examples

>>> array = Array()
>>> array.axes
['z', 'y', 'x']

Note

This method must be implemented by the subclass.

property dims: int

Abstractmethod:

Returns the number of spatial dimensions.

Returns:: The number of spatial dimensions.
Return type:: int
Raises:: NotImplementedError – This method must be implemented by the subclass.

Examples

>>> array = Array()
>>> array.dims
3

Note

This method must be implemented by the subclass.

property voxel_size: funlib.geometry.Coordinate

Abstractmethod:

The size of a voxel in physical units.

Returns:: The size of a voxel in physical units.
Return type:: Coordinate
Raises:: NotImplementedError – This method must be implemented by the subclass.

Examples

>>> array = Array()
>>> array.voxel_size
Coordinate((1, 1, 1))

Note

This method must be implemented by the subclass.

property roi: funlib.geometry.Roi

Abstractmethod:

The total ROI of this array, in world units.

Returns:: The total ROI of this array, in world units.
Return type:: Roi
Raises:: NotImplementedError – This method must be implemented by the subclass.

Examples

>>> array = Array()
>>> array.roi
Roi(offset=Coordinate((0, 0, 0)), shape=Coordinate((100, 100, 100)))

Note

This method must be implemented by the subclass.

property dtype: Any

Abstractmethod:

The dtype of this array, in numpy dtypes

Returns:: The dtype of this array, in numpy dtypes.
Return type:: Any
Raises:: NotImplementedError – This method must be implemented by the subclass.

Examples

>>> array = Array()
>>> array.dtype
np.dtype('uint8')

Note

This method must be implemented by the subclass.

property num_channels: int | None

Abstractmethod:

The number of channels provided by this dataset. Should return None if the channel dimension doesn’t exist.

Returns:: The number of channels provided by this dataset.
Return type:: Optional[int]
Raises:: NotImplementedError – This method must be implemented by the subclass.

Examples

>>> array = Array()
>>> array.num_channels
1

Note

This method must be implemented by the subclass.

property data: numpy.ndarray

Abstractmethod:

Get a numpy like readable and writable view into this array.

Returns:: A numpy like readable and writable view into this array.
Return type:: np.ndarray
Raises:: NotImplementedError – This method must be implemented by the subclass.

Examples

>>> array = Array()
>>> array.data
np.ndarray

Note

This method must be implemented by the subclass.

property writable: bool

Abstractmethod:

Can we write to this Array?

Returns:: Can we write to this Array?
Return type:: bool
Raises:: NotImplementedError – This method must be implemented by the subclass.

Examples

>>> array = Array()
>>> array.writable
False

Note

This method must be implemented by the subclass.