matflow.param_classes.orientations.Orientations#

class matflow.param_classes.orientations.Orientations(data, unit_cell_alignment, representation)#

Bases: ParameterValue

A description of the orientations of some data.

Parameters:

data (numpy.ndarray[tuple[int, ...], numpy.dtype[numpy._typing._array_like._ScalarType_co]]) – The orientation data.
unit_cell_alignment (matflow.param_classes.orientations.UnitCellAlignment) – The alignment of the unit cell.
representation (matflow.param_classes.orientations.OrientationRepresentation) – The orientation representation descriptor.

Methods

`dump_element_group_to_HDF5_group`	Write a list (from an element group) of parameter values to an HDF5 group.
`dump_to_HDF5_group`	Write this parameter value to an HDF5 group.
`from_JSON_like`	For custom initialisation via YAML or JSON.
`from_file`	Load orientation data from a text file.
`from_random`	Generate random orientation data.
`prepare_JSON_dump`	Prepare this parameter value for serialisation as JSON.
`quat_sample_random`	Generate random uniformly distributed unit quaternions.
`save_from_HDF5_group`	Save orientation data from an HDF5 group to a persistent workflow.
`save_from_JSON`	Extract a parameter value from JSON data.
`to_dict`	Serialise this parameter value as a dictionary.

Attributes

`data`	Orientation data
`unit_cell_alignment`	Alignment of the unit cell.
`representation`	How the orientation data is represented.

data: ndarray[tuple[int, ...], dtype[_ScalarType_co]]#: Orientation data

classmethod dump_element_group_to_HDF5_group(objs, group)#

Write a list (from an element group) of parameter values to an HDF5 group.

Parameters:: objs (list[matflow.param_classes.orientations.Orientations]) –

dump_to_HDF5_group(group)#: Write this parameter value to an HDF5 group.

classmethod from_JSON_like(data, ori_format)#

For custom initialisation via YAML or JSON.

Parameters:

data (Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes]) –
ori_format (str) –

Return type:

Self

classmethod from_file(path, representation, unit_cell_alignment, *, number=None, start_index=0, delimiter=' ')#

Load orientation data from a text file.

Parameters:

path (str) – Path to the file to load from.
representation (dict) – Description of how the orientation data is arranged.
unit_cell_alignment (UnitCellAlignment) – How the unit cell is aligned.
number (int | None) – Number of orientations to read from the file.
start_index (int) – The line number of the file that the orientations start at. Allows skipping headers.
delimiter (str) – The delimiter separating values in the file. Defaults to space, but commas and tabs are also sensible (and correspond to CSV and TSV files respectively).

Return type:

Self

classmethod from_random(number)#

Generate random orientation data.

Parameters:: number (int) – The number of orientations to generate.
Return type:: Self

prepare_JSON_dump()#

Prepare this parameter value for serialisation as JSON.

Return type:: dict[str, Any]

static quat_sample_random(number)#

Generate random uniformly distributed unit quaternions.

Parameters:: number (int) – How many quaternions to generate.
Returns:: quats
Return type:: ndarray, shape (number, 4)

References

https://stackoverflow.com/a/44031492/5042280 http://planning.cs.uiuc.edu/node198.html

representation: OrientationRepresentation#: How the orientation data is represented.

classmethod save_from_HDF5_group(group, param_id, workflow)#

Save orientation data from an HDF5 group to a persistent workflow.

Note

We avoid loading the data into memory all at once by firstly generating an Orientations object with a small data array, and then copying from the HDF5 group directly into the newly created Zarr group.

We assume that the workflow is using a Zarr datastore. This is not checked!

Parameters:: param_id (int) –

classmethod save_from_JSON(data, param_id, workflow)#

Extract a parameter value from JSON data.

Parameters:

param_id (int | list[int]) –
workflow (Workflow) –

to_dict()#

Serialise this parameter value as a dictionary.

Return type:: dict[str, Any]

unit_cell_alignment: UnitCellAlignment#: Alignment of the unit cell.