def _run_loads(model, nelements: int, run_loads=True):
"""helper method"""
if not run_loads:
return
assert isinstance(nelements, int), nelements
#node_ids = None
#nnodes = model.nnodes
#node_ids = [None] * nnodes
try:
out = model.get_displacement_index_xyz_cp_cd(
fdtype='float64', idtype='int32', sort_ids=True)
except ValueError:
return
unused_icd_transformi, unused_icp_transformi, unused_xyz_cpi, nid_cp_cd = out
node_ids = nid_cp_cd[:, 0]
normals, eids, eid_map = _normals_eid_map(model, nelements, fdtype='float64')
nsubcases = len(model.subcases)
if nsubcases == 0:
load_ids = list(set(list(model.load_combinations) + list(model.loads)))
for load_id in sorted(load_ids):
unused_subcase = model.case_control_deck.add_subcase(load_id)
get_pressure_array(model, load_id, eids, stop_on_failure=True,
fdtype='float32')
load_ids = list(set(list(model.load_combinations) + list(model.loads)))
for subcase_id in model.subcases:
get_load_arrays(model, subcase_id, eid_map, node_ids, normals, nid_map=None,
fdtype='float32')
if nsubcases == 0:
del model.case_control_deck
def _run_loads(model, nelements, run_loads=True):
"""helper method"""
if not run_loads:
return
eid_map = {}
normals = np.zeros((nelements, 3), dtype='float64')
ieid = 0
#node_ids = None
#nnodes = model.nnodes
#node_ids = [None] * nnodes
try:
out = model.get_displacement_index_xyz_cp_cd(fdtype='float64',
idtype='int32',
sort_ids=True)
except ValueError:
return
unused_icd_transformi, unused_icp_transformi, unused_xyz_cpi, nid_cp_cd = out
node_ids = nid_cp_cd[:, 0]
eids = []
for eid, elem in model.elements.items():
if hasattr(elem, 'Normal'):
normals[ieid, :] = elem.Normal()
eid_map[eid] = ieid
eids.append(eid)
ieid += 1
nsubcases = len(model.subcases)
if nsubcases == 0:
load_ids = list(set(list(model.load_combinations) + list(model.loads)))
for load_id in sorted(load_ids):
unused_subcase = model.case_control_deck.add_subcase(load_id)
get_pressure_array(model, load_id, eids, stop_on_failure=True)
load_ids = list(set(list(model.load_combinations) + list(model.loads)))
for subcase_id in model.subcases:
get_load_arrays(model,
subcase_id,
eid_map,
node_ids,
normals,
nid_map=None)
if nsubcases == 0:
del model.case_control_deck
def test_loads(self):
"""tests the ``get_load_arrays`` and ``_reduce_dload_case`` methods"""
model = BDF(debug=True, log=None, mode='msc')
subcase_id = 10
eid_map = None
node_ids = []
normals = None
lines = []
cc = CaseControlDeck(lines, log=None)
#print(model.case_control_deck)
model.case_control_deck = cc
subcase = cc.create_new_subcase(subcase_id)
out = get_load_arrays(model,
subcase_id,
eid_map,
node_ids,
normals,
nid_map=None)
is_loads, is_temperatures, temperature_data, load_data = out
assert is_loads is False, is_loads
assert is_temperatures is False, is_temperatures
assert temperature_data == (None, None), temperature_data
assert load_data == (None, None, None), load_data
key = 'LOAD'
value = 10
options = []
param_type = '???'
with self.assertRaises(TypeError):
subcase.add(key, value, options, param_type)
param_type = 'STRESS-type'
subcase.add(key, value, options, param_type)
with self.assertRaises(KeyError):
get_load_arrays(model,
subcase_id,
eid_map,
node_ids,
normals,
nid_map=None,
stop_on_failure=True)
#is_loads, is_temperatures, temperature_data, load_data = out
#assert is_loads is False, is_loads
#assert is_temperatures is False, is_temperatures
#assert temperature_data == (None, None), temperature_data
#assert load_data == (None, None, None), load_data
dload_case = []
dloads, scale_factors = model._reduce_dload_case(
dload_case,
scale=1.,
unallowed_dload_ids=None,
skip_scale_factor0=False,
msg='')
assert dloads == [], dloads
assert scale_factors == [], scale_factors
del dloads, scale_factors
# ----------------------------------------------------------------------
dload_id = 5
scale = 1.
scale_factors = [2]
load_ids = [3]
dload = model.add_dload(dload_id, scale, scale_factors, load_ids)
dload_case = [dload]
with self.assertRaises(KeyError):
model._reduce_dload_case(dload_case,
scale=1.,
unallowed_dload_ids=None,
skip_scale_factor0=False,
msg='')
excite_id = 100
tid = 2
model.add_tload1(dload_id,
excite_id,
tid,
delay=0,
Type='LOAD',
us0=0.0,
vs0=0.0,
comment='')
with self.assertRaises(KeyError):
model._reduce_dload_case(dload_case,
scale=1.,
unallowed_dload_ids=None,
skip_scale_factor0=False,
msg='')