StringField#

class ansys.dpf.core.string_field.StringField(nentities=0, string_field=None, server=None)#

Describes string data scoped on entities such as names.

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

Parameters:

nentities (int) – Number of entities that the string field is to contain (reserved). The default is 0.
string_field (Field, ansys.grpc.dpf.field_pb2.Field, ctypes.c_void_p, optional) – 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.

Examples

>>> from ansys.dpf import core as dpf
>>> pfield = dpf.StringField()
>>> list_ids = [1, 2, 4, 6, 7]
>>> scop = dpf.Scoping(ids = list_ids, location = dpf.locations.nodal)
>>> pfield.scoping = scop
>>> list_data = ["water", "oil", "gaz", "paint", "air"]
>>> pfield.data = list_data

Notes

Class available with server’s version starting at 5.0 (Ansys 2023R1).

property location#

Location of the string 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 dpf.locations: ie. dpf.locations.nodal or dpf.locations.elemental.
Return type:: str

Examples

Create a string field and request the location.

>>> from ansys.dpf import core as dpf
>>> pfield = dpf.StringField()
>>> 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: List[str], scopingid: int)#

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]...

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)