matflow.param_classes.seeds.MicrostructureSeeds

class matflow.param_classes.seeds.MicrostructureSeeds(position, box_size, phase_label, orientations=None, random_seed=None)

Bases: ParameterValue

The seeds for crystalline microstructure.

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 a microstructure definition from a text file.
from_random	Generate a random microstructure.
prepare_JSON_dump	Prepare this parameter value for serialisation as JSON.
save_from_HDF5_group	Extract a parameter value from an HDF5 group.
save_from_JSON	Extract a parameter value from JSON data.
show	Plot the microstructure.
to_dict	Serialise this parameter value as a dictionary.

Attributes

num_seeds	The number of seeds.
orientations	Orientation data.
random_seed	Seed for the random number generator, if used.
position	The positions of the seeds.
box_size	The size of box containing the seeds.
phase_label	Label for the phase.

Parameters:

• position (ndarray[Any, dtype[_ScalarType_co]]) –

• box_size (ndarray[Any, dtype[_ScalarType_co]]) –

• phase_label (str) –

• orientations (Orientations | None) –

• random_seed (int | None) –

box_size: NDArray

The size of box containing the seeds.

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[ParameterValue]) –

• group (Group) –

dump_to_HDF5_group(group)

Write this parameter value to an HDF5 group.

Parameters:

group (Group) –

classmethod from_JSON_like(position, orientations=None, **kwargs)

For custom initialisation via YAML or JSON.

Parameters:

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

• orientations (dict | None) –

Return type:

Self

classmethod from_file(path, box_size, phase_label, *, number=None, start_index=0, delimiter=' ')

Load a microstructure definition from a text file.

Parameters:

• path (str) – Path to the file to load from.

• box_size (ndarray[Any, dtype[_ScalarType_co]]) – The size of box containing the microstructure.

• phase_label (str) – Label for the microstructure.

• number (int | None) – Number of seeds to read from the file.

• start_index (int) – The line number of the file that the seeds 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(num_seeds, box_size, phase_label, *, random_seed=None, orientations=None)

Generate a random microstructure.

Parameters:

• num_seeds (int) – The number of seeds for the microstructure.

• box_size (ndarray[Any, dtype[_ScalarType_co]]) – The size of box containing the microstructure.

• phase_label (str) – Label for the microstructure.

• random_seed (int | None) – Seed for the random number generator.

• orientations (Orientations | dict[str, Any] | None) – Orientation information. If omitted, random.

Return type:

Self

property num_seeds: int

The number of seeds.

orientations: Orientations | None = None

Orientation data.

phase_label: str

Label for the phase.

position: NDArray

The positions of the seeds.

prepare_JSON_dump()

Prepare this parameter value for serialisation as JSON.

Return type:

dict[str, Any]

random_seed: int | None = None

Seed for the random number generator, if used.

classmethod save_from_HDF5_group(group, param_id, workflow)

Extract a parameter value from an HDF5 group.

Parameters:

• group (Group) –

• param_id (int) –

• workflow (Workflow) –

classmethod save_from_JSON(data, param_id, workflow)

Extract a parameter value from JSON data.

Parameters:

• param_id (int | list[int]) –

• workflow (Workflow) –

show()

Plot the microstructure.

Note

Requires matplotlib to be installed and configured.

Return type:

None

to_dict()

Serialise this parameter value as a dictionary.

Return type:

dict[str, Any]