def test_generated_operator_several_output_types(plate_msup):
inpt = core.Field(nentities=3)
inpt.data = [1, 2, 3, 4, 5, 6, 7, 8, 9]
inpt.scoping.ids = [1, 2, 3]
inpt.unit = "m"
uc = op.math.unit_convert()
uc.inputs.entity_to_convert(inpt)
uc.inputs.unit_name("mm")
f = uc.outputs.converted_entity_as_field()
assert f.unit == "mm"
assert np.allclose(
f.data.flatten("C"), np.array([1, 2, 3, 4, 5, 6, 7, 8, 9]) * 1000
)
model = core.Model(plate_msup)
din = model.metadata.meshed_region.nodes.coordinates_field.data
assert model.metadata.meshed_region.nodes.coordinates_field.unit == "m"
uc.inputs.entity_to_convert(model.metadata.meshed_region)
uc.inputs.unit_name("mm")
m = uc.outputs.converted_entity_as_meshed_region()
assert m.nodes.coordinates_field.unit == "mm"
assert np.allclose(m.nodes.coordinates_field.data, np.array(din) * 1000)
def create_mesh_and_field_mapped(multishells):
# get metadata
model = core.Model(multishells)
mesh = model.metadata.meshed_region
disp_fc = model.results.displacement().outputs.fields_container()
field = disp_fc[0]
# coordinates field to map
coordinates = [[-0.02, 0.006, 0.014], [-0.02, 0.006, 0.012],
[-0.018, 0.006, 0.012], [-0.018, 0.006, 0.014]]
field_coord = core.Field()
field_coord.location = core.locations.nodal
field_coord.data = coordinates
scoping = core.Scoping()
scoping.location = core.locations.nodal
scoping.ids = list(range(1, len(coordinates) + 1))
field_coord.scoping = scoping
# mapping operator
mapping_operator = core.Operator("mapping")
mapping_operator.inputs.fields_container.connect(disp_fc)
mapping_operator.inputs.coordinates.connect(field_coord)
mapping_operator.inputs.mesh.connect(mesh)
mapping_operator.inputs.create_support.connect(True)
fields_mapped = mapping_operator.outputs.fields_container()
# mesh path
assert len(fields_mapped) == 1
field_m = fields_mapped[0]
mesh_m = field_m.meshed_region
return field, field_m, mesh, mesh_m
def test_set_get_data_property_field():
field = core.Field(nentities=20, nature=dpf.core.natures.scalar)
scoping = core.Scoping()
ids = []
data = []
for i in range(0, 20):
ids.append(i + 1)
data.append(i + 0.001)
scoping.ids = ids
field.scoping = scoping
field.data = data
assert np.allclose(field.data, data)
def test_generated_operator_several_output_types2():
inpt = core.Field(nentities=3)
inpt.data = [1, 2, 3, 4, 5, 6, 7, 8, 9]
inpt.scoping.ids = [1, 2, 3]
inpt.unit = "m"
uc = op.scoping.rescope(inpt, core.Scoping(ids=[1, 2]))
f = uc.outputs.fields_as_field()
assert np.allclose(f.data.flatten("C"), [1, 2, 3, 4, 5, 6])
fc = core.FieldsContainer()
fc.labels = ["time"]
fc.add_field({"time": 1}, inpt)
uc = op.scoping.rescope(fc, core.Scoping(ids=[1, 2]))
fc2 = uc.outputs.fields_as_fields_container()
assert np.allclose(fc2[0].data.flatten("C"), [1, 2, 3, 4, 5, 6])
def _set_harmonic_indices_at_stage(self, stage_num, step_harmonic_indices,
step_id):
"""Set values for harmonic indices for a specific stage number.
Parameters
----------
stage_num: int
Stage number.
harmonic_indices: list of int or float
List of values for harmonic indices.
"""
harmonic_indices = self.get_harmonic_indices(stage_num)
if harmonic_indices is None:
harmonic_indices = core.Field(
server=self._server,
nature=core.natures.scalar,
location=core.locations.time_freq,
)
harmonic_indices.scoping.location = core.locations.time_freq_step
harmonic_indices.append(step_harmonic_indices, step_id)
self.set_harmonic_indices(harmonic_indices, stage_num)
def test_generated_operator_set_config():
inpt = core.Field(nentities=3)
inpt.data = [1, 2, 3, 4, 5, 6, 7, 8, 9]
inpt.scoping.ids = [1, 2, 3]
inpt.unit = "m"
inpt2 = core.Field(nentities=3)
inpt2.data = [1, 2, 3, 4, 5, 6, 7, 8, 9]
inpt2.scoping.ids = [3, 4, 5]
inpt2.unit = "m"
conf = op.math.add.default_config()
print(conf)
conf.set_work_by_index_option(True)
op1 = op.math.add(config=conf)
op1.inputs.fieldA.connect(inpt)
op1.inputs.fieldB.connect(inpt2)
out = op1.outputs.field()
assert np.allclose(out.scoping.ids, [1, 2, 3]) or np.allclose(out.scoping.ids, [3, 4, 5])
assert np.allclose(
out.data, np.array([[2.0, 4.0, 6.0], [8.0, 10.0, 12.0], [14.0, 16.0, 18.0]])
)
conf.set_work_by_index_option(False)
op1 = op.math.add(config=conf)
op1.inputs.fieldA.connect(inpt)
op1.inputs.fieldB.connect(inpt2)
out = op1.outputs.field()
assert np.allclose(out.scoping.ids, [1, 2, 3, 4, 5])
assert np.allclose(
out.data,
np.array(
[
[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[8.0, 10.0, 12.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0],
]
),
)
inpt2.unit = "Pa"
conf = op.math.add.default_config()
conf.set_permissive_option(True)
op1.config = conf
op1.inputs.fieldB.connect(inpt2)
out = op1.outputs.field()
assert np.allclose(out.scoping.ids, [1, 2, 3, 4, 5])
assert np.allclose(
out.data,
np.array(
[
[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[8.0, 10.0, 12.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0],
]
),
)
assert conf.get_mutex_option() == "false"
assert conf.config_option_default_value("mutex") == "false"
assert conf.config_option_accepted_types("mutex") == ["bool"]
assert conf.options["mutex"] == "false"
assert "multiple threads" in conf.config_option_documentation("mutex")
def create_mesh_and_field_mapped_2(multishells):
# get metadata
model = core.Model(multishells)
mesh = model.metadata.meshed_region
disp_fc = model.results.displacement().outputs.fields_container()
field = disp_fc[0]
# coordinates field to map
coordinates = [[-0.0195, 0.006, -0.0025]]
for i in range(1, 101):
coord_copy = []
coord_copy.append(coordinates[0][0])
coord_copy.append(coordinates[0][1])
coord_copy.append(coordinates[0][2])
coord_copy[0] = coord_copy[0] + i * 0.0003
coordinates.append(coord_copy)
ref = [-0.0155, 0.00600634, -0.0025]
coordinates.append(ref)
for i in range(1, 101):
coord_copy = []
coord_copy.append(ref[0])
coord_copy.append(ref[1])
coord_copy.append(ref[2])
coord_copy[0] = coord_copy[0] + i * 0.0003
coordinates.append(coord_copy)
ref = [-0.0125, 0.00600507, -0.0025]
coordinates.append(ref)
for i in range(1, 101):
coord_copy = []
coord_copy.append(ref[0])
coord_copy.append(ref[1])
coord_copy.append(ref[2])
coord_copy[0] = coord_copy[0] + i * 0.0003
coordinates.append(coord_copy)
ref = [-0.0125, 0.00600444, -0.0025]
coordinates.append(ref)
for i in range(1, 101):
coord_copy = []
coord_copy.append(ref[0])
coord_copy.append(ref[1])
coord_copy.append(ref[2])
coord_copy[0] = coord_copy[0] + i * 0.0003
coordinates.append(coord_copy)
field_coord = core.Field()
field_coord.location = core.locations.nodal
field_coord.data = coordinates
scoping = core.Scoping()
scoping.location = core.locations.nodal
scoping.ids = list(range(1, len(coordinates) + 1))
field_coord.scoping = scoping
# mapping operator
mapping_operator = core.Operator("mapping")
mapping_operator.inputs.fields_container.connect(disp_fc)
mapping_operator.inputs.coordinates.connect(field_coord)
mapping_operator.inputs.mesh.connect(mesh)
mapping_operator.inputs.create_support.connect(True)
fields_mapped = mapping_operator.outputs.fields_container()
# mesh path
assert len(fields_mapped) == 1
field_m = fields_mapped[0]
mesh_m = field_m.meshed_region
return field, field_m, mesh, mesh_m
def append_step(
self,
step_id,
step_time_frequencies,
step_complex_frequencies=None,
rpm_value=None,
step_harmonic_indices=None,
):
"""Append a step with all its field values in the time frequencies support.
The RPM value is a step (or load step)-based value.
The values for time frequencies, complex frequencies, and harmonic indices are set-based.
There is one set value for each step/substep combination.
It is necessary that each call of my_time_freq_support.append_step(kwargs**) contains
the same arguments.
It is necessary that time_frequencies/complex_frequencies/harmonic_indices lists have
the same size if specified in the same my_time_freq_support.append_step(kwargs**) call.
Parameters
----------
step_id: int
ID of the step to add.
step_time_frequencies: list of int/float
Values for time frequencies related to the specified step.
step_complex_frequencies: list of int/float, optional
Values for complex frequencies related to the specified step.
rpm_value: int/float, optional
Value for RPM value for the specified step.
step_harmonic_indices: optional, dictionary or list
Dictionary of ``{ int : list of int/float } = { stage_num : harmonic_indices }``
or a list of int/float. In this case, stage_num default value is 0.
Harmonic indices are values related to the specified step.
Example
-------
>>> from ansys.dpf.core import TimeFreqSupport
>>> tfq = TimeFreqSupport()
>>> tfq.append_step(1, [0.1, 0.21, 1.0], rpm_value = 2.0)
>>> tfq.append_step(2, [1.1, 2.0], rpm_value = 2.3)
>>> tfq2 = TimeFreqSupport()
>>> tfq2.append_step(1, [0.1, 0.21, 1.0], rpm_value = 2.0, step_harmonic_indices = [1.0, 2.0, 3.0])
>>> tfq2.append_step(2, [1.1, 2.0], rpm_value = 2.3, step_harmonic_indices = [1.0, 2.0])
>>> tfq2.append_step(3, [0.23, 0.25], rpm_value = 3.0, step_harmonic_indices = [1.0, 2.0])
>>> tfq3 = TimeFreqSupport()
>>> tfq3.append_step(1, [0.1, 0.21, 1.0], rpm_value = 2.0, step_harmonic_indices = {1: [1.0, 2.0, 3.0], 2: [1.0, 2.0, 2.5]})
""" # noqa: E501
time_frequencies = self.time_frequencies
if time_frequencies is None:
time_frequencies = core.Field(
server=self._server,
nature=core.natures.scalar,
location=core.locations.time_freq,
)
time_frequencies.scoping.location = core.locations.time_freq_step
time_frequencies.append(step_time_frequencies, step_id)
self.time_frequencies = time_frequencies
if step_complex_frequencies is not None:
complex_frequencies = self.complex_frequencies
if complex_frequencies is None:
complex_frequencies = core.Field(
server=self._server,
nature=core.natures.scalar,
location=core.locations.time_freq,
)
complex_frequencies.scoping.location = core.locations.time_freq_step
complex_frequencies.append(step_complex_frequencies, step_id)
self.complex_frequencies = complex_frequencies
if rpm_value is not None:
rpms = self.rpms
if rpms is None:
rpms = core.Field(
server=self._server,
nature=core.natures.scalar,
location=core.locations.time_freq_step,
)
rpms.append([rpm_value], step_id)
self.rpms = rpms
if step_harmonic_indices is not None:
if isinstance(step_harmonic_indices, list):
self._set_harmonic_indices_at_stage(0, step_harmonic_indices,
step_id)
elif isinstance(step_harmonic_indices, dict):
for key in step_harmonic_indices:
self._set_harmonic_indices_at_stage(
key, step_harmonic_indices[key], step_id)
else:
raise dpf_errors.InvalidTypeError("list/dict",
"step_harmonic_indices")