def _not_equal_nodes_build_tree(nodes_xyz, xyz_compare, tol, neq_max=4, msg=''):
# type: (np.ndarray, np.ndarray, float, int, str) -> (Any, np.ndarray, np.ndarray)
"""
helper function for `bdf_equivalence_nodes`
Parameters
----------
nodes_xyz : (Nnodes, 3) float ndarray
the source points
xyz_compare : (Ncompare, 3) float ndarray
the xyz points to compare to
tol : float
the max spherical tolerance
neq_max : int; default=4
the number of close nodes
msg : str; default=''
error message
Returns
-------
kdt : cKDTree()
the kdtree object
ieq : int ndarray
The indices of nodes_xyz where the nodes in xyz_compare are close???
neq_max = 1:
(N, ) int ndarray
neq_max > 1:
(N, N) int ndarray
slots : int ndarray
The indices of nodes_xyz where the nodes in xyz_compare are close???
neq_max = 1:
(N, ) int ndarray
neq_max > 1:
(N, N) int ndarray
msg : str; default=''
error message
"""
assert isinstance(xyz_compare, np.ndarray), type(xyz_compare)
if nodes_xyz.shape[1] != xyz_compare.shape[1]:
msgi = 'nodes_xyz.shape=%s xyz_compare.shape=%s%s' % (
str(nodes_xyz.shape), str(xyz_compare.shape), msg)
raise RuntimeError(msgi)
kdt = _get_tree(nodes_xyz, msg=msg)
# check the closest 10 nodes for equality
deq, ieq = kdt.query(xyz_compare, k=neq_max, distance_upper_bound=tol)
#print(deq)
#print('ieq =', ieq)
#print('neq_max = %s' % neq_max)
# get the ids of the duplicate nodes
nnodes = nodes_xyz.shape[0]
if neq_max == 1:
assert len(deq.shape) == 1, deq.shape
slots = np.where(ieq < nnodes)
else:
assert len(deq.shape) == 2, deq.shape
slots = np.where(ieq[:, :] < nnodes)
#print('slots =', slots)
return kdt, ieq, slots
def _not_equal_nodes_build_tree(nodes_xyz, xyz_compare, tol, neq_max=4):
"""
helper function for `bdf_equivalence_nodes`
Parameters
----------
nodes_xyz : (N, 3) float ndarray
the source points
xyz_compare : (N, 3) float ndarray
the xyz points to compare to
tol : float
the max spherical tolerance
neq_max : int; default=4
the number of close nodes
Returns
-------
kdt : cKDTree() or KDTree()
the kdtree object
ieq : int ndarray
The indices of nodes_xyz where the nodes in xyz_compare are close???
neq_max = 1:
(N, ) int ndarray
neq_max > 1:
(N, N) int ndarray
slots : int ndarray
The indices of nodes_xyz where the nodes in xyz_compare are close???
neq_max = 1:
(N, ) int ndarray
neq_max > 1:
(N, N) int ndarray
"""
assert isinstance(xyz_compare, np.ndarray), type(xyz_compare)
if nodes_xyz.shape[1] != xyz_compare.shape[1]:
msg = 'nodes_xyz.shape=%s xyz_compare.shape=%s' % (
str(nodes_xyz.shape), str(xyz_compare.shape))
raise RuntimeError(msg)
kdt = _get_tree(nodes_xyz)
# check the closest 10 nodes for equality
deq, ieq = kdt.query(xyz_compare, k=neq_max, distance_upper_bound=tol)
#print(deq)
#print('ieq =', ieq)
#print('neq_max = %s' % neq_max)
# get the ids of the duplicate nodes
nnodes = nodes_xyz.shape[0]
if neq_max == 1:
assert len(deq.shape) == 1, deq.shape
slots = where(ieq < nnodes)
else:
assert len(deq.shape) == 2, deq.shape
slots = where(ieq[:, :] < nnodes)
#print('slots =', slots)
return kdt, ieq, slots
def pierce_shell_model(bdf_filename, xyz_points, tol=1.0):
# type: (Union[BDF, str], Any, float) -> List[int], np.ndarray, List[List[int]]
"""
Pierces a shell model with a <0., 0., 1.> vector. In other words,
models are pierced in the xy plane.
Parameters
----------
bdf_filename : str / BDF()
the model to run
xyz_points : (npoints, 3) float ndarray
the xyz_points to pierce
tol : float; default=1.0
the pierce tolerance
pick a value that is ~3x the max local element edge length
Returns
-------
eids_pierce : List[int]
int : The element ids that were pierced.
If multiple elements are pierced, the one with the largest
pierced z value will be returned.
None : invalid pierce
xyz_pierces_max : List[float ndarray, None]
ndarray : pierce location
None : invalid pierce
node_ids : List[int ndarray, None]
ndarray : pierced element's nodes
None : invalid pierce
"""
xyz_points = np.asarray(xyz_points)
assert xyz_points.shape[1] == 3, xyz_points.shape
xy_points = xyz_points[:, :2]
assert xy_points.shape[1] == 2, xy_points.shape
if isinstance(bdf_filename, BDF):
model = bdf_filename
else:
model = read_bdf(bdf_filename)
eids = []
centroids = []
etypes_to_skip = [
'CHEXA',
'CPENTA',
'CTETRA',
'CPYRAM',
'CBUSH',
'CBUSH1D',
'CBUSH2D',
'CBEAM',
'CROD',
'CONROD',
'CELAS1',
'CELAS2',
'CELAS3',
'CELAS4',
'CDAMP1',
'CDAMP2',
'CDAMP3',
'CDAMP4',
'CDAMP5',
]
for eid, elem in iteritems(model.elements):
if elem.type in ['CQUAD4', 'CTRIA3']:
centroid = elem.Centroid()
elif elem.type in etypes_to_skip:
continue
else:
print(elem.type)
#raise NotImplementedError(elem)
continue
eids.append(eid)
centroids.append(centroid)
eids = np.array(eids, dtype='int32')
assert len(eids) > 0, 'eids=%s\n' % eids
centroids_xy = np.array(centroids, dtype='float64')[:, :2]
#print('centroids:\n%s\n' % str(centroids_xy))
assert centroids_xy.shape[1] == 2, centroids_xy.shape
msg = 'which is required by pierce_shell_model'
kdt = _get_tree(centroids_xy, msg=msg)
results = kdt.query_ball_point(xy_points, tol)
nresults = len(results)
iresults = np.arange(nresults)
#print(results)
#print(iresults)
direction = np.array([0., 0., 1.])
ipoints = []
eids_pierce = []
xyz_pierces_max = []
node_ids = []
for i, xyz_point, eidsi in zip(count(), xyz_points, results):
model.log.debug('eidsi = [%s]' %
', '.join([str(eidii).rstrip('L') for eidii in eidsi]))
if not eidsi:
ipoints.append(i)
eids_pierce.append(None)
xyz_pierces_max.append(None)
node_ids.append(None)
model.log.warning(
'skipping %s because it failed tolerancing (tol=%s)' %
(xyz_point, tol))
continue
model.log.debug('xyz_point = %s' % xyz_point)
eidsi2 = eids[eidsi]
eids_newi = []
piercesi = []
zpiercesi = []
for eid in eidsi2:
elem = model.elements[eid]
if elem.type == 'CQUAD4':
v0 = elem.nodes_ref[0].get_position()
v1 = elem.nodes_ref[1].get_position()
v2 = elem.nodes_ref[2].get_position()
v3 = elem.nodes_ref[3].get_position()
xyz_pierce = quad_intersection(xyz_point, direction, v0, v1,
v2, v3)
elif elem.type == 'CTRIA3':
v0 = elem.nodes_ref[0].get_position()
v1 = elem.nodes_ref[1].get_position()
v2 = elem.nodes_ref[2].get_position()
xyz_pierce = triangle_intersection(xyz_point, direction, v0,
v1, v2)
else:
raise NotImplementedError(elem)
if xyz_pierce is None:
#model.log.warning('failed to pierce eid=%s' % eid)
continue
zpierce = xyz_pierce[2]
model.log.debug(' eid=%s xyz_pierce=%s zpierce=%s' %
(eid, xyz_pierce, zpierce))
eids_newi.append(eid)
piercesi.append(xyz_pierce)
zpiercesi.append(zpierce)
if len(zpiercesi) == 0:
ipoints.append(i)
eids_pierce.append(None)
xyz_pierces_max.append(None)
node_ids.append(None)
model.log.warning('skipping %s because no pierces found (tol=%s)' %
(xyz_point, tol))
continue
#print('zpiercesi = %s' % zpiercesi)
zpiercesi_max = max(zpiercesi)
ipierce_max = zpiercesi.index(zpiercesi_max)
eid_max = eids_newi[ipierce_max]
xyz_piercei_max = piercesi[ipierce_max]
model.log.debug(
'i=%s xyz_point=%s xyz_piercei_max=%s zpiercesi=%s zmax=%s eid_max=%s'
%
(i, xyz_point, xyz_piercei_max, zpiercesi, zpiercesi_max, eid_max))
ipoints.append(i)
eids_pierce.append(eid_max)
xyz_pierces_max.append(xyz_piercei_max)
#print(model.elements[eid_max])
node_ids.append(model.elements[eid_max].node_ids)
xyz_pierces_max = np.array(xyz_pierces_max)
model.log.debug('ipoints=%s' % ipoints)
model.log.info('eids_pierce=%s' % eids_pierce)
model.log.info('xyz_pierces_max:\n%s' % xyz_pierces_max)
model.log.info('node_ids=%s' % node_ids)
return eids_pierce, xyz_pierces_max, node_ids
