PropertyField#

class ansys.dpf.core.property_field.PropertyField(nentities=0, nature=natures.scalar, location='Nodal', property_field=None, server=None)#

Describes field properties such as connectivity.

This class is a field with integer values instead of double values.

Parameters:
  • nentities (int) – Number of entities that the property field is to contain. The default is 0.

  • nature (core.natures) – Nature of the property field, such as scalar or vector.

  • location (str, optional) – Location of the property field. Options are in ansys.dpf.core.locations. The default is ansys.dpf.core.locations.nodal.

  • field (property) – Field message generated from a gRPC stub, or returned by DPF’s C clients.

  • server (server.DPFServer, optional) – Server with the channel connected to the remote or local instance. The default is None, in which case an attempt is made to use the global server.

Returns:

property_field

Return type:

PropertyField

Examples

>>> from ansys.dpf import core as dpf
>>> pfield = dpf.PropertyField()
>>> list_ids = [1, 2, 4, 6, 7]
>>> scop = dpf.Scoping(ids = list_ids, location = dpf.locations.nodal)
>>> pfield.scoping = scop
>>> list_data = [20, 30, 50, 70, 80]
>>> pfield.data = list_data
property location#

Location of the property field.

A property field contains a scoping, which is the location that is read. To update location, directly update the scoping location.

Returns:

location – Location string, can be found in ansys.dpf.core.locations: ie. dpf.locations.nodal or dpf.locations.elemental.

Return type:

str

Examples

Create a property field and request the location.

>>> from ansys.dpf import core as dpf
>>> pfield = dpf.PropertyField()
>>> list_ids = [1, 2, 4, 6, 7]
>>> scop = dpf.Scoping(ids = list_ids, location = dpf.locations.nodal)
>>> pfield.scoping = scop
>>> pfield.scoping.location = dpf.locations.nodal
>>> pfield.location
'Nodal'
property component_count#

Number of components in each elementary data of the field.

Returns:

Number of components in each elementary data of the field.

Return type:

int

property elementary_data_count#

Number of elementary data in the field.

Returns:

Number of elementary data in the field.

Return type:

int

property size#

Length of the data vector.

The length is equal to the number of elementary data times the number of components.

Returns:

Length of the data vector.

Return type:

int

get_entity_data(index)#

Retrieves the elementary data of the scoping’s index in an array.

Return type:

numpy.ndarray

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> transient = examples.download_transient_result()
>>> model = dpf.Model(transient)
>>> stress_op = model.results.stress()
>>> fields_container = stress_op.outputs.fields_container()
>>> fields_container[0].get_entity_data(0)
DPFArray([[-3.27795062e+05,  1.36012200e+06,  1.49090608e+08,
        -4.88688900e+06,  1.43038560e+07,  1.65455040e+07],
       [-4.63817550e+06,  1.29312225e+06,  1.20411832e+08,
        -6.06617800e+06,  2.34829700e+07,  1.77231120e+07],
       [-2.35684860e+07, -3.53474400e+07,  2.01501168e+08,
        -5.23361700e+06, -2.88789280e+07, -6.16478200e+06],
       [-3.92756960e+07, -2.72369280e+07,  1.81454016e+08,
        -3.75441450e+06, -3.62480300e+06, -3.26075620e+07],
       [ 1.63554530e+07,  2.83190520e+07,  1.05084256e+08,
        -1.30219020e+07,  5.19906719e+05,  8.82430200e+06],
       [ 1.80755620e+07,  5.25578750e+06,  7.76211600e+07,
        -7.53063750e+06,  2.44717000e+06,  2.92675125e+06],
       [ 9.25567760e+07,  8.15244320e+07,  2.77157632e+08,
        -1.48489875e+06,  5.89250600e+07,  2.05608920e+07],
       [ 6.70443680e+07,  8.70343440e+07,  2.73050464e+08,
        -2.48670150e+06,  1.52268930e+07,  6.09583280e+07]]...
get_entity_data_by_id(id)#

Retrieve the data of the scoping’s ID in the parameter of the field in an array.

Returns:

Data based on the scoping ID.

Return type:

numpy.ndarray

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> transient = examples.download_transient_result()
>>> model = dpf.Model(transient)
>>> stress_op = model.results.stress()
>>> fields_container = stress_op.outputs.fields_container()
>>> fields_container[0].get_entity_data_by_id(391)
DPFArray([[-3.27795062e+05,  1.36012200e+06,  1.49090608e+08,
        -4.88688900e+06,  1.43038560e+07,  1.65455040e+07],
       [-4.63817550e+06,  1.29312225e+06,  1.20411832e+08,
        -6.06617800e+06,  2.34829700e+07,  1.77231120e+07],
       [-2.35684860e+07, -3.53474400e+07,  2.01501168e+08,
        -5.23361700e+06, -2.88789280e+07, -6.16478200e+06],
       [-3.92756960e+07, -2.72369280e+07,  1.81454016e+08,
        -3.75441450e+06, -3.62480300e+06, -3.26075620e+07],
       [ 1.63554530e+07,  2.83190520e+07,  1.05084256e+08,
        -1.30219020e+07,  5.19906719e+05,  8.82430200e+06],
       [ 1.80755620e+07,  5.25578750e+06,  7.76211600e+07,
        -7.53063750e+06,  2.44717000e+06,  2.92675125e+06],
       [ 9.25567760e+07,  8.15244320e+07,  2.77157632e+08,
        -1.48489875e+06,  5.89250600e+07,  2.05608920e+07],
       [ 6.70443680e+07,  8.70343440e+07,  2.73050464e+08,
        -2.48670150e+06,  1.52268930e+07,  6.09583280e+07]]...
append(data, scopingid)#

Add an entity data to the existing data.

Parameters:
  • data (list of int, double, or array) – Data in the entity.

  • scopingid (int) – ID of the scoping.

Examples

>>> from ansys.dpf.core import fields_factory
>>> field = fields_factory.create_3d_vector_field(2)
>>> field.append([1.,2.,3.],1)
>>> field.append([1.,2.,3.],2)
>>> field.data
DPFArray([[1., 2., 3.],
       [1., 2., 3.]]...
>>> field.scoping.ids

...[1, 2]...
as_local_field()#

Create a deep copy of the field locally.

This copy can then be accessed and modified locally, without a request being sent to the server. This method should be used in a with statement so that the local field is released and the data is sent to the server in one action. If it’s not used in a with statement, the method release_data() should be used to actually update the field.

Warning

If this as_local_field method is not used as a context manager in a with statement or if the method release_data() is not called, the data will not actually be updated.

Returns:

local_field

Return type:

PropertyField

Examples

>>> from ansys.dpf import core as dpf
>>> num_entities = 5
>>> field_to_local = dpf.PropertyField(num_entities, dpf.natures.scalar)
>>> with field_to_local.as_local_field() as f:
...     for i in range(1,num_entities+1):
...         f.append(list(range(i,i+3)),i)
...         print(f.get_entity_data(i-1))
[1 2 3]
[2 3 4]
[3 4 5]
[4 5 6]
[5 6 7]
property name#

Name of the property field.

..note:

Available starting with DPF 2024.2.pre1.

property data#

Data in the field as an array.

Returns:

Data in the field.

Return type:

numpy.ndarray

Notes

Print a progress bar.

property data_as_list#

Data in the field as a Python list.

Returns:

List of the data in the field.

Return type:

List

Notes

Print a progress bar.

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> transient = examples.download_transient_result()
>>> model = dpf.Model(transient)
>>> disp = model.results.displacement()
>>> fields_container = disp.outputs.fields_container()
>>> field = fields_container[0]
>>> # field.data_as_list
property elementary_data_shape#

Numpy-like shape of the field.

property scoping#

Scoping specifying where the data is.

Each entity data is on a given scoping ID.

Returns:

scoping

Return type:

ansys.dpf.core.scoping.Scoping

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> transient = examples.download_transient_result()
>>> model = dpf.Model(transient)
>>> stress_op = model.results.stress()
>>> fields_container = stress_op.outputs.fields_container()
>>> scoping = fields_container[0].scoping
>>> scoping.location
'Elemental'
>>> scoping.id(3)
586
>>> #The fourth elementary data of the field corresponds to
>>> #the element id number 586 in the mesh
property shape#

Numpy-like shape of the field.

Return type:

tuple

Examples

Shape of a stress field.

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_transient_result())
>>> s_op =model.results.stress()
>>> s_fc = s_op.outputs.fields_container()
>>> field = s_fc[0]
>>> field.shape
(5720, 6)