stk.cage.M24L48

class stk.cage.M24L48(building_blocks, vertex_alignments=None, vertex_positions=None, reaction_factory=GenericReactionFactory(), num_processes=1, optimizer=<stk._internal.optimizers.null.NullOptimizer object>, scale_multiplier=1.0)

Bases: Cage

Represents a cage topology graph.

Metal building blocks with four functional groups are required for this topology.

Ligand building blocks with two functional groups are required for this topology.

When using a dict for the building_blocks parameter, as in Examples: Multi-Building Block Cage Construction, a BuildingBlock, with the following number of functional groups, needs to be assigned to each of the following vertex ids:

4-functional groups: 0 to 23

2-functional groups: 24 to 71

See Cage for more details and examples.

Parameters:

• building_blocks (Iterable[BuildingBlock] | dict[BuildingBlock, tuple[int, ...]]) –

  Can be a iterable of BuildingBlock instances, which should be placed on the topology graph.

  Can also be a dict which maps the BuildingBlock instances to the ids of the vertices it should be placed on. A dict is required when there are multiple building blocks with the same number of functional groups, because in this case the desired placement is ambiguous.

• vertex_alignments (dict[int, int] | None) – A mapping from the id of a Vertex to an Edge connected to it. The Edge is used to align the first FunctionalGroup of a BuildingBlock placed on that vertex. Only vertices which need to have their default edge changed need to be present in the dict. If None then the default edge is used for each vertex. Changing which Edge is used will mean that the topology graph represents different structural isomers. The edge is referred to by a number between 0 (inclusive) and the number of edges the vertex is connected to (exclusive).

• vertex_positions (dict[int, ndarray] | None) – A mapping from the id of a Vertex to a custom BuildingBlock position. The default vertex alignment algorithm is still applied. Only vertices which need to have their default position changed need to be present in the dict. Note that any vertices with modified positions will not be scaled like the rest of the building block positions and will not use neighbor placements in its positioning if requested by the default topology. If None then the default placement algorithm is used for each vertex.

• reaction_factory (ReactionFactory) – The reaction factory to use for creating bonds between building blocks.

• num_processes (int) – The number of parallel processes to create during construct().

• optimizer (Optimizer) – Used to optimize the structure of the constructed molecule.

• scale_multiplier (float) – Scales the positions of the vertices.

Raises:

• AssertionError – If the any building block does not have a valid number of functional groups.

• ValueError – If the there are multiple building blocks with the same number of functional_groups in building_blocks, and they are not explicitly assigned to vertices. The desired placement of building blocks is ambiguous in this case.

• UnoccupiedVertexError – If a vertex of the cage topology graph does not have a building block placed on it.

• OverlyOccupiedVertexError – If a vertex of the cage topology graph has more than one building block placed on it.

Methods

clone	Return a clone.
construct	Construct a ConstructedMolecule.
get_building_blocks	Yield the building blocks.
get_num_building_block	Get the number of times building_block is present.
get_vertex_alignments	Get the vertex alignments.
with_building_blocks	Return a clone holding different building blocks.

clone()

Return a clone.

Returns:

The clone.

Return type:

Self

construct()

Construct a ConstructedMolecule.

Returns:

The data describing the ConstructedMolecule.

Return type:

ConstructionResult

get_building_blocks()

Yield the building blocks.

Building blocks are yielded in an order based on their position in the topology graph. For two equivalent topology graphs, but with different building blocks, equivalently positioned building blocks will be yielded at the same time.

Yields:

A building block of the topology graph.

Return type:

Iterator[BuildingBlock]

get_num_building_block(building_block)

Get the number of times building_block is present.

Parameters:

building_block (BuildingBlock) – The building block whose frequency in the topology graph is desired.

Returns:

The number of times building_block is present in the topology graph.

Return type:

int

get_vertex_alignments()

Get the vertex alignments.

Returns:

The vertex alignments.

Return type:

dict[int, int]

with_building_blocks(building_block_map)

Return a clone holding different building blocks.

Parameters:

building_block_map (dict[BuildingBlock, BuildingBlock]) – Maps a building block in the current topology graph to the building block which should replace it in the clone. If a building block should be not replaced in the clone, it can be omitted from the map.

Returns:

The clone.

Return type:

Self