topo_metrics.topology ===================== .. py:module:: topo_metrics.topology Classes ------- .. autoapisummary:: topo_metrics.topology.RingsResults topo_metrics.topology.Topology topo_metrics.topology.Node Functions --------- .. autoapisummary:: topo_metrics.topology.get_all_node_frac_coords Module Contents --------------- .. py:class:: RingsResults Bases: :py:obj:`NamedTuple` .. py:attribute:: depth :type: int The depth to which the rings were searcher for. .. py:attribute:: rings_are_strong :type: bool Whether the rings were filtered to strong rings only. .. py:attribute:: ring_size_count :type: topo_metrics.rings.RingSizeCounts The number of rings of a given size, of shape ``(**, 2)`` where the first column indicates the ring size, and the second indicates the number of rings of that size. .. py:attribute:: clusters :type: list[topo_metrics.clusters.Cluster] Each node can be characterised in terms of the rings in which it participates. This can be summarised using common metrics such as Vertex Symbols. .. py:class:: Topology A class detailing the topology of a network, based on nodes and edges. .. py:attribute:: nodes :type: list[Node] .. py:attribute:: edges :type: numpy.typing.NDArray[numpy.int_] .. py:attribute:: lattice :type: pymatgen.core.lattice.Lattice | None :value: None .. py:attribute:: properties :type: dict[Hashable, Any] .. py:method:: from_ase(ase_atoms: ase.Atoms, cutoff: float = 0.0, pair_cutoffs: dict[tuple[str, str], float] | None = None, remove_types: Iterable[Any] | None = None, remove_degree2: bool = False) -> Topology :classmethod: Creates a Topology object from an ASE Atoms object. :param ase_atoms: The ASE Atoms object representing the structure. :rtype: A Topology object representing the network as nodes and edges. .. py:method:: from_cgd(filename: pathlib.Path | str) -> Topology :classmethod: Parses and loads a CGD file with an adjacency matrix. :param filename: The path to the CGD file. :rtype: A Topology object representing the network as nodes and edges. .. py:method:: from_conflink(filename: str, node_type: str = 'Si', index: int | None = None) -> Topology :classmethod: Parses and loads a conflink file. :param filename: The path to the conflink file. :param node_type: The type to assign to all nodes in the topology. :rtype: A Topology object representing the network as nodes and edges. .. py:method:: from_lammps_data(filename: pathlib.Path | str, *, atom_style: str = 'atomic', units: str = 'metal', sort_by_id: bool = True, prefer_bonds: bool = True, cutoff: float = 0.0, pair_cutoffs: dict[tuple[str, str], float] | None = None, contract_neighborlist: bool = False, remove_types: Iterable[Any] | None = None, remove_degree2: bool = False, omit_node_types: bool = False) -> Topology :classmethod: Create a Topology from a LAMMPS data file. If the file contains a `Bonds` section, bonds are used as the edge list, and periodic image shifts are inferred assuming MIC. Otherwise edges are inferred by cutoff. .. py:method:: get_rings(depth: int = 12) -> list[topo_metrics.ring_geometry.RingGeometry] Computes or retrieves unique rings in the network. :param depth: The maximum depth to search for rings. .. rubric:: Notes - In the previous implementation, this method returned the clusters of rings at each node. This is obtained instead via the `get_clusters` method. This method now returns all unique rings in the network as RingGeometry objects. .. py:method:: get_clusters(depth: int = 12, strong: bool = False) -> RingsResults Computes or retrieves ring statistics for the network. :param depth: The maximum depth to search for rings. :param strong: Whether to filter the rings to strong rings only. :rtype: A dictionary containing the ring statistics. .. py:method:: get_topological_genome() -> str Returns a the topology code for the framework. .. rubric:: Notes - The topological genome is a finite series of numbers that is provably unique for each net. - It can be comptued in polynomial time with respect to the size of the net. .. py:method:: get_coordination_sequences(max_shell: int = 10, node_ids: Iterable[int] | int | None = None) -> numpy.typing.NDArray[numpy.int_] Return coordination sequences for specified nodes. :param max_shell: The maximum shell to compute coordination sequences to. :param node_ids: The node IDs for which to compute coordination sequences. If None, coordination sequences for all nodes are returned. .. py:property:: cartesian_coordinates :type: numpy.typing.NDArray[numpy.floating] Return the Cartesian positions of all nodes in the network. .. py:property:: fractional_coordinates :type: numpy.typing.NDArray[numpy.floating] Return the fractional positions of all nodes in the network. .. py:class:: Node A representation of a node in a network. .. py:attribute:: node_id :type: int .. py:attribute:: node_type :type: str | None :value: 'Si' .. py:attribute:: frac_coord :type: numpy.typing.NDArray[numpy.floating] | None :value: None .. py:attribute:: cart_coord :type: numpy.typing.NDArray[numpy.floating] | None :value: None .. py:attribute:: is_shifted :type: bool :value: False .. py:method:: apply_image_shift(lattice: pymatgen.core.lattice.Lattice, image_shift: numpy.typing.NDArray[numpy.int_]) -> Node Apply the image shift to this node and return a new Node object. :param lattice: The lattice object for the network. :param image_shift: The shift vector to apply to the node coordinates. :rtype: A new Node object with the shifted coordinates. .. py:function:: get_all_node_frac_coords(nodes: list[Node]) -> numpy.typing.NDArray[numpy.floating] Return the fractional coordinates of all nodes in the network.