bdf_equivalence Module

defines:

model = bdf_equivalence_nodes(bdf_filename, bdf_filename_out, tol,

renumber_nodes=False, neq_max=4, xref=True, node_set=None, size=8, is_double=False, remove_collapsed_elements=False, avoid_collapsed_elements=False, crash_on_collapse=False, log=None, debug=True)

pyNastran.bdf.mesh_utils.bdf_equivalence._bdf_equivalence_nodes(bdf_filename: str, tol: float, renumber_nodes: bool = False, neq_max: int = 4, xref: bool = True, node_set: list[NDArrayNint] | None = None, log: SimpleLogger | None = None, debug: bool = True, method: str = 'new', idtype: str = 'int32', fdtype: str = 'float64') → tuple[BDF, list[tuple[int, int]]]

helper for bdf_equivalence_nodes

pyNastran.bdf.mesh_utils.bdf_equivalence._check_for_referenced_nodes(model: BDF, node_set: ndarray[Any, dtype[int64]] | None, nids: ndarray[Any, dtype[int64]], all_nids: ndarray[Any, dtype[int64]], nodes_xyz: ndarray[Any, dtype[float64]]) → ndarray[Any, dtype[int64]] | None

helper function for _eq_nodes_setup

Parameters:

nodes_xyz(nnode, 3) float array

the xyz for nids

pyNastran.bdf.mesh_utils.bdf_equivalence._eq_nodes_build_tree_new(kdt: KDTree, nodes_xyz: NDArrayN3float, nids: NDArrayNint, all_node_set: NDArrayNint, nnodes: int, is_not_node_set: bool, tol: float, log: SimpleLogger, inew=None, node_set=None, neq_max: int = 4, msg: str = '', debug: float = False) → list[tuple[int, int]]

pyNastran.bdf.mesh_utils.bdf_equivalence._eq_nodes_final(nid_pairs: list[tuple[int, int]], model: BDF, tol: float, all_node_set: ndarray[Any, dtype[int64]], debug: bool = False) → None

apply nodal equivalencing to model

pyNastran.bdf.mesh_utils.bdf_equivalence._eq_nodes_setup_node(model: BDF, renumber_nodes: bool = False, idtype: str = 'int32') → tuple[ndarray[Any, dtype[int64]], ndarray[Any, dtype[int64]]]

helper function for _eq_nodes_setup that doesn’t handle node sets

Returns:

nids(nnode,) int array

???

all_nids(nnode,) int array

all the GRID ids

pyNastran.bdf.mesh_utils.bdf_equivalence._eq_nodes_setup_node_set(model: BDF, node_set: list[ndarray[Any, dtype[int64]]], all_node_set: ndarray[Any, dtype[int64]], renumber_nodes: bool = False, idtype: str = 'int32') → tuple[ndarray[Any, dtype[int64]], ndarray[Any, dtype[int64]]]

helper function for _eq_nodes_setup that handles node_sets

pyNastran.bdf.mesh_utils.bdf_equivalence._get_tree(nodes_xyz: ndarray[Any, dtype[float64]], msg: str = '') → KDTree

gets the kdtree

pyNastran.bdf.mesh_utils.bdf_equivalence._get_xyz_cid0(model: BDF, nids: ndarray[Any, dtype[int64]], fdtype: str = 'float32') → ndarray[Any, dtype[float64]]

gets xyz_cid0

pyNastran.bdf.mesh_utils.bdf_equivalence._nodes_xyz_nids_to_nid_pairs(nodes_xyz: NDArrayN3float, nids: NDArrayNint, all_node_set: NDArrayNint, tol: float, log: SimpleLogger, inew: NDArrayNint, node_set: NDArrayNint | None = None, neq_max: int = 4, method: str = 'new', debug: bool = False) → list[tuple[int, int]]

Helper for equivalencing

Returns:

nid_pairslist[tuple[int, int]]

a series of (nid1, nid2) pairs

pyNastran.bdf.mesh_utils.bdf_equivalence._nodes_xyz_nids_to_nid_pairs_new(kdt: KDTree, nids: NDArrayNint, all_node_set: NDArrayNint, node_set: NDArrayNint | None, tol: float, log: SimpleLogger) → list[tuple[int, int]]

helper function for bdf_equivalence_nodes

pyNastran.bdf.mesh_utils.bdf_equivalence._simplify_node_set(node_set: list[int] | set[int] | list[ndarray[Any, dtype[int64]]] | None, idtype: str = 'int32') → list[ndarray[Any, dtype[int64]]] | None

accepts multiple forms of the node_set parameter

• list[int]

• set[int]

• int ndarray

• list[int ndarray]

pyNastran.bdf.mesh_utils.bdf_equivalence._update_grid(node1: GRID, node2: GRID) → None

helper method for _eq_nodes_final

pyNastran.bdf.mesh_utils.bdf_equivalence.bdf_equivalence_nodes(bdf_filename: str, bdf_filename_out: str | None, tol: float, renumber_nodes: bool = False, neq_max: int = 4, xref: bool = True, node_set: list[int] | NDArrayNint | None = None, size: int = 8, is_double: bool = False, remove_collapsed_elements: bool = False, avoid_collapsed_elements: bool = False, crash_on_collapse: bool = False, log: SimpleLogger | None = None, debug: bool = True, method: str = 'new') → BDF

Equivalences nodes; keeps the lower node id; creates two nodes with the same

Parameters:

bdf_filenamestr / BDF

str : bdf file path BDF : a BDF model that is fully valid (see xref)

bdf_filename_outstr

str: a bdf_filename to write None: don’t write the deck

tolfloat

the spherical tolerance

renumber_nodesbool

should the nodes be renumbered (default=False)

neq_maxint

the number of “close” points (default=4)

xrefbool

does the model need to be cross_referenced (default=True; only applies to model option)

node_setlist[int] / (n, ) ndarray; default=None

the list/array of nodes to consider (not supported with renumber_nodes=True)

sizeint; {8, 16}; default=8

the bdf write precision

is_doublebool; default=False

the field precision to write

remove_collapsed_elementsbool; default=False (unsupported)

True1D/2D/3D elements will not be collapsed;

CELASx/CDAMP/MPC/etc. are not considered

False : no elements will be removed

avoid_collapsed_elementsbool; default=False (unsupported)

Trueonly collapses that don’t break 1D/2D/3D elements will be considered;

CELASx/CDAMP/MPC/etc. are considered

False : element can be collapsed

crash_on_collapsebool; default=False

stop if nodes have been collapsed

False: blindly move on True: rereads the BDF which catches doubled nodes (temporary);

in the future collapse=True won’t need to double read; an alternative is to do Patran’s method of avoiding collapse)

debugbool

bdf debugging

method: str; default=’new’

‘new’: doesn’t require neq_max; new in v1.3 ‘old’: use neq_max; used in v1.2

loglogger(); default=None

bdf logging

Returns:

modelBDF()

The BDF model corresponding to bdf_filename_out

Warning

I doubt SPOINTs/EPOINTs work correctly ..

Warning

xref not fully implemented (assumes cid=0) ..

Todo

node_set still does work on the all the nodes in the big kdtree loop, which is very inefficient

Todo

remove_collapsed_elements is not supported ..

Todo

avoid_collapsed_elements is not supported ..

pyNastran.bdf.mesh_utils.bdf_equivalence.get_all_node_set(node_set: list[ndarray[Any, dtype[int64]]] | None) → ndarray[Any, dtype[int64]]