dacapo.experiments.datasplits.datasets.arrays.concat_array

Attributes

logger

Classes

ConcatArray

This is a wrapper around other source_arrays that concatenates

Module Contents

dacapo.experiments.datasplits.datasets.arrays.concat_array.logger

class dacapo.experiments.datasplits.datasets.arrays.concat_array.ConcatArray(array_config)

This is a wrapper around other source_arrays that concatenates them along the channel dimension. The source_arrays are expected to have the same shape and ROI, but can have different data types.

name: The name of the array.

channels: The list of channel names.

source_arrays: A dictionary mapping channel names to source arrays.

default_array: An optional default array to use for channels that are not present in source_arrays.

from_toml(cls, toml_path: str) -> ConcatArrayConfig: Load the ConcatArrayConfig from a TOML file

to_toml(self, toml_path: str) -> None: Save the ConcatArrayConfig to a TOML file

create_array(self) → ConcatArray: Create the ConcatArray from the config

Note

This class is a subclass of Array and inherits all its attributes and methods. The only difference is that the array_type is ConcatArray.

name

channels

property source_arrays: Dict[str, dacapo.experiments.datasplits.datasets.arrays.array.Array]

Return the source arrays of the ConcatArray.

Returns:: The source arrays of the ConcatArray.
Return type:: Dict[str, Array]
Raises:: AssertionError – If the source arrays are empty.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.source_arrays
{'A': Array(...), 'B': Array(...)}

Note

The source_arrays are expected to have the same shape and ROI.

default_array

property attrs

Return the attributes of the ConcatArray as a dictionary.

Returns:: The attributes of the ConcatArray.
Return type:: Dict[str, Any]
Raises:: AssertionError – If the source arrays have different attributes.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.attrs
{'axes': 'cxyz', 'roi': Roi(...), 'voxel_size': (1, 1, 1)}

Note

The source_arrays are expected to have the same attributes.

property source_array: dacapo.experiments.datasplits.datasets.arrays.array.Array

Return the source array of the ConcatArray.

Returns:: The source array of the ConcatArray.
Return type:: Array
Raises:: AssertionError – If the source array is None.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.source_array
Array(...)

Note

The source_array is expected to have the same shape and ROI.

property axes

Return the axes of the ConcatArray.

Returns:: The axes of the ConcatArray.
Return type:: str
Raises:: AssertionError – If the source arrays have different axes.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.axes
'cxyz'

Note

The source_arrays are expected to have the same axes.

property dims

Return the dimensions of the ConcatArray.

Returns:: The dimensions of the ConcatArray.
Return type:: Tuple[int]
Raises:: AssertionError – If the source arrays have different dimensions.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.dims
(2, 100, 100, 100)

Note

The source_arrays are expected to have the same dimensions.

property voxel_size

Return the voxel size of the ConcatArray.

Returns:: The voxel size of the ConcatArray.
Return type:: Tuple[float]
Raises:: AssertionError – If the source arrays have different voxel sizes.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.voxel_size
(1, 1, 1)

Note

The source_arrays are expected to have the same voxel size.

property roi

Return the ROI of the ConcatArray.

Returns:: The ROI of the ConcatArray.
Return type:: Roi
Raises:: AssertionError – If the source arrays have different ROIs.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.roi
Roi(...)

Note

The source_arrays are expected to have the same ROI.

property writable: bool

Return whether the ConcatArray is writable.

Returns:: Whether the ConcatArray is writable.
Return type:: bool
Raises:: AssertionError – If the ConcatArray is writable.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.writable
False

Note

The ConcatArray is not writable.

property data

Return the data of the ConcatArray.

Returns:: The data of the ConcatArray.
Return type:: np.ndarray
Raises:: RuntimeError – If the ConcatArray is not writable.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.data
np.ndarray(...)

Note

The ConcatArray is not writable.

property dtype

Return the data type of the ConcatArray.

Returns:: The data type of the ConcatArray.
Return type:: np.dtype
Raises:: AssertionError – If the source arrays have different data types.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.dtype
np.float32

Note

The source_arrays are expected to have the same data type.

property num_channels

Return the number of channels of the ConcatArray.

Returns:: The number of channels of the ConcatArray.
Return type:: int
Raises:: AssertionError – If the source arrays have different numbers of channels.

Examples

>>> config = ConcatArrayConfig(
...     name="my_concat_array",
...     channels=["A", "B"],
...     source_array_configs={
...         "A": ArrayConfig(...),
...         "B": ArrayConfig(...),
...     },
...     default_config=ArrayConfig(...),
... )
>>> array = ConcatArray(config)
>>> array.num_channels
2

Note

The source_arrays are expected to have the same number of channels.