dacapo.experiments.datasplits.datasets.arrays.crop_array

Classes

CropArray

Used to crop a larger array to a smaller array. This is useful when you

Module Contents

class dacapo.experiments.datasplits.datasets.arrays.crop_array.CropArray(array_config)

Used to crop a larger array to a smaller array. This is useful when you want to work with a subset of a larger array, but don’t want to copy the data. The crop is done on demand, so the data is not copied until you actually access it.

name

The name of the array.

source_array

The array to crop.

crop_roi

The region of interest to crop to.

attrs()

Returns the attributes of the source array.

axes()

Returns the axes of the source array.

dims()

Returns the number of dimensions of the source array.

voxel_size()

Returns the voxel size of the source array.

roi()

Returns the region of interest of the source array.

writable()

Returns whether the array is writable.

dtype()

Returns the data type of the source array.

num_channels()

Returns the number of channels of the source array.

data()

Returns the data of the source array.

channels()

Returns the channels of the source array.

__getitem__(roi)

Returns the data of the source array within the region of interest.

_can_neuroglance()

Returns whether the source array can be viewed in Neuroglancer.

_neuroglancer_source()

Returns the source of the source array for Neuroglancer.

_neuroglancer_layer()

Returns the layer of the source array for Neuroglancer.

_source_name()

Returns the name of the source array.

Note

This class is a subclass of Array.

name

crop_roi

property attrs

Returns the attributes of the source array.

Returns:

The attributes of the source array.

Raises:

ValueError – If the region of interest to crop to is not within the

Examples

>>> from dacapo.experiments.datasplits.datasets.arrays import ArrayConfig
>>> from dacapo.experiments.datasplits.datasets.arrays import CropArray
>>> from funlib.geometry import Roi
>>> import numpy as np
>>> array_config = ArrayConfig(
...     name='array',
...     source_array_config=source_array_config,
...     roi=Roi((0, 0, 0), (10, 10, 10))
... )
>>> crop_array = CropArray(array_config)
>>> crop_array.attrs
{}

Note

The attributes are empty because the source array is not modified.

property axes

Returns the axes of the source array.

Returns:

The axes of the source array.

Raises:

ValueError – If the region of interest to crop to is not within the

Examples

>>> from dacapo.experiments.datasplits.datasets.arrays import ArrayConfig
>>> from dacapo.experiments.datasplits.datasets.arrays import CropArray
>>> from funlib.geometry import Roi
>>> import numpy as np
>>> array_config = ArrayConfig(
...     name='array',
...     source_array_config=source_array_config,
...     roi=Roi((0, 0, 0), (10, 10, 10))
... )
>>> crop_array = CropArray(array_config)
>>> crop_array.axes
'zyx'

Note

The axes are ‘zyx’ because the source array is not modified.

property dims: int

Returns the number of dimensions of the source array.

Returns:

The number of dimensions of the source array.

Raises:

ValueError – If the region of interest to crop to is not within the region of interest of the source array.

Examples

>>> from dacapo.experiments.datasplits.datasets.arrays import ArrayConfig
>>> from dacapo.experiments.datasplits.datasets.arrays import CropArray
>>> from funlib.geometry import Roi
>>> import numpy as np
>>> array_config = ArrayConfig(
...     name='array',
...     source_array_config=source_array_config,
...     roi=Roi((0, 0, 0), (10, 10, 10))
... )
>>> crop_array = CropArray(array_config)
>>> crop_array.dims
3

Note

The number of dimensions is 3 because the source array is not modified.

property voxel_size: funlib.geometry.Coordinate

Returns the voxel size of the source array.

Returns:

The voxel size of the source array.

Raises:

ValueError – If the region of interest to crop to is not within the region of interest of the source array.

Examples

>>> from dacapo.experiments.datasplits.datasets.arrays import ArrayConfig
>>> from dacapo.experiments.datasplits.datasets.arrays import CropArray
>>> from funlib.geometry import Roi
>>> import numpy as np
>>> array_config = ArrayConfig(
...     name='array',
...     source_array_config=source_array_config,
...     roi=Roi((0, 0, 0), (10, 10, 10))
... )
>>> crop_array = CropArray(array_config)
>>> crop_array.voxel_size
Coordinate(x=1.0, y=1.0, z=1.0)

Note

The voxel size is (1.0, 1.0, 1.0) because the source array is not modified.

property roi: funlib.geometry.Roi

Returns the region of interest of the source array.

Returns:

The region of interest of the source array.

Raises:

ValueError – If the region of interest to crop to is not within the region of interest of the source array.

Examples

>>> from dacapo.experiments.datasplits.datasets.arrays import ArrayConfig
>>> from dacapo.experiments.datasplits.datasets.arrays import CropArray
>>> from funlib.geometry import Roi
>>> import numpy as np
>>> array_config = ArrayConfig(
...     name='array',
...     source_array_config=source_array_config,
...     roi=Roi((0, 0, 0), (10, 10, 10))
... )
>>> crop_array = CropArray(array_config)
>>> crop_array.roi
Roi(offset=(0, 0, 0), shape=(10, 10, 10))

Note

The region of interest is (0, 0, 0) with shape (10, 10, 10) because the source array is not modified.

property writable: bool

Returns whether the array is writable.

Returns:

False

Raises:

ValueError – If the region of interest to crop to is not within the region of interest of the source array.

Examples

>>> from dacapo.experiments.datasplits.datasets.arrays import ArrayConfig
>>> from dacapo.experiments.datasplits.datasets.arrays import CropArray
>>> from funlib.geometry import Roi
>>> import numpy as np
>>> array_config = ArrayConfig(
...     name='array',
...     source_array_config=source_array_config,
...     roi=Roi((0, 0, 0), (10, 10, 10))
... )
>>> crop_array = CropArray(array_config)
>>> crop_array.writable
False

Note

The array is not writable because it is a virtual array created by modifying another array on demand.

property dtype

Returns the data type of the source array.

Returns:

The data type of the source array.

Raises:

ValueError – If the region of interest to crop to is not within the region of interest of the source array.

Examples

>>> from dacapo.experiments.datasplits.datasets.arrays import ArrayConfig
>>> from dacapo.experiments.datasplits.datasets.arrays import CropArray
>>> from funlib.geometry import Roi
>>> import numpy as np
>>> array_config = ArrayConfig(
...     name='array',
...     source_array_config=source_array_config,
...     roi=Roi((0, 0, 0), (10, 10, 10))
... )
>>> crop_array = CropArray(array_config)
>>> crop_array.dtype
numpy.dtype('uint8')

Note

The data type is uint8 because the source array is not modified.

property num_channels: int

Returns the number of channels of the source array.

Returns:

The number of channels of the source array.

Raises:

ValueError – If the region of interest to crop to is not within the region of interest of the source array.

Examples

>>> from dacapo.experiments.datasplits.datasets.arrays import ArrayConfig
>>> from dacapo.experiments.datasplits.datasets.arrays import CropArray
>>> from funlib.geometry import Roi
>>> import numpy as np
>>> array_config = ArrayConfig(
...     name='array',
...     source_array_config=source_array_config,
...     roi=Roi((0, 0, 0), (10, 10, 10))
... )
>>> crop_array = CropArray(array_config)
>>> crop_array.num_channels
1

Note

The number of channels is 1 because the source array is not modified.

property data

Returns the data of the source array.

Returns:

The data of the source array.

Raises:

ValueError – If the region of interest to crop to is not within the region of interest of the source array.

Examples

>>> from dacapo.experiments.datasplits.datasets.arrays import ArrayConfig
>>> from dacapo.experiments.datasplits.datasets.arrays import CropArray
>>> from funlib.geometry import Roi
>>> import numpy as np
>>> array_config = ArrayConfig(
...     name='array',
...     source_array_config=source_array_config,
...     roi=Roi((0, 0, 0), (10, 10, 10))
... )
>>> crop_array = CropArray(array_config)
>>> crop_array.data
array([[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]],
       [[0, 0, 0, 0, 0, 0, 0, 0, 0

property channels

Returns the channels of the source array.

Returns:

The channels of the source array.

Raises:

ValueError – If the region of interest to crop to is not within the region of interest of the source array.

Examples

>>> from dacapo.experiments.datasplits.datasets.arrays import ArrayConfig
>>> from dacapo.experiments.datasplits.datasets.arrays import CropArray
>>> from funlib.geometry import Roi
>>> import numpy as np
>>> array_config = ArrayConfig(
...     name='array',
...     source_array_config=source_array_config,
...     roi=Roi((0, 0, 0), (10, 10, 10))
... )
>>> crop_array = CropArray(array_config)
>>> crop_array.channels
1

Note

The channels is 1 because the source array is not modified.