CustomScan#

class abtem.scan.CustomScan(positions=(0.0, 0.0), squeeze=False)[source]#

Bases: abtem.scan.BaseScan

Custom scan based on explicit 2D probe positions.

Parameters: positions (np.ndarray, optional) – Scan positions [Å]. Anything that can be converted to an ndarray of shape (n, 3) is accepted. Default is (0., 0.).

__init__(positions=(0.0, 0.0), squeeze=False)[source]#

Methods

`__init__`([positions, squeeze])
`apply`(waves)	Apply the transform to the given waves.
`copy`()	Make a copy.
`ensemble_blocks`([chunks])	Split the ensemble into an array of smaller ensembles.
`generate_blocks`([chunks])	Generate chunks of the ensemble.
`get_positions`()	Get the scan positions as numpy array.
`match_probe`(probe)	Sets the positions to a single position in the center of the probe extent.
`select_block`(index, chunks)	Select a block from the ensemble.

Attributes

`axes_metadata`	List of AxisMetadata.
`base_axes_metadata`	List of AxisMetadata of the base axes.
`base_shape`	Shape of the base axes.
`distributions`
`ensemble_axes_metadata`	Axes metadata describing the ensemble axes added to the waves when applying the transform.
`ensemble_shape`	The shape of the ensemble axes added to the waves when applying the transform.
`in_place`	The array representing the waves may be modified in-place.
`limits`	Lower left and upper right corner of the bounding box containing all positions in the scan.
`metadata`	Metadata added to the waves when applying the transform.
`num_positions`	Number of probe positions in the scan.
`positions`	Scan positions [Å].
`shape`	The shape the scan.

apply(waves)#

Apply the transform to the given waves.

Parameters: array_object (ArrayObject) – The array object to transform.
Returns: transformed_array_object
Return type: ArrayObject

property axes_metadata: abtem.core.axes.AxesMetadataList#

List of AxisMetadata.

Return type: AxesMetadataList

property base_axes_metadata: list[abtem.core.axes.AxisMetadata]#

List of AxisMetadata of the base axes.

Return type: list[AxisMetadata]

property base_shape: tuple[int, ...]#

Shape of the base axes.

Return type: tuple[int, ...]

copy()#: Make a copy.

property ensemble_axes_metadata#: Axes metadata describing the ensemble axes added to the waves when applying the transform.

ensemble_blocks(chunks=None)#

Split the ensemble into an array of smaller ensembles.

Parameters: chunks (iterable of tuples) – Block sizes along each dimension.
Return type: Array

property ensemble_shape: tuple[int, ...]#

The shape of the ensemble axes added to the waves when applying the transform.

Return type: tuple[int, ...]

generate_blocks(chunks=1)#

Generate chunks of the ensemble.

Parameters: chunks (iterable of tuples) – Block sizes along each dimension.

get_positions()[source]#

Get the scan positions as numpy array.

Return type: ndarray

property in_place: bool#

The array representing the waves may be modified in-place.

Return type: bool

property limits#: Lower left and upper right corner of the bounding box containing all positions in the scan.

match_probe(probe)[source]#

Sets the positions to a single position in the center of the probe extent.

Parameters: probe (Probe or BaseSMatrix) – The matched probe or s-matrix.

property metadata: dict#

Metadata added to the waves when applying the transform.

Return type: dict

property num_positions: int#

Number of probe positions in the scan.

Return type: int

property positions#: Scan positions [Å].

select_block(index, chunks)#

Select a block from the ensemble.

Parameters

index (tuple of ints) – Index of selected block.
chunks (iterable of tuples) – Block sizes along each dimension.

property shape#: The shape the scan.