Custom Fields Containers

Contains the inherited classes from the FieldsContainer class. These new classes offer helpers to access data for specific usage, such as results split by body or split by material.

class ansys.dpf.core.custom_fields_container.ElShapeFieldsContainer(fields_container=None, server=None)

Represents a fields container with fields split by an element shape.

Instances of this class are created when a model result is split by an element shape, such as a solid, shell, or beam.

Parameters:

• fields_container (ansys.grpc.dpf.collection_pb2.Collection or FieldsContainer, optional) – Fields container created from either a collection message or by copying an existing fields container. The default is None.

• 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
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_all_kinds_of_complexity_modal())
>>> fc = model.results.displacement.on_all_time_freqs.split_by_shape.eval()
>>> len(fc.solid_fields())
45
>>> solid_f_time_2 = fc.solid_field(2)

solid_fields(timeid=None, complexid=None)

Retrieve a list of all fields with solid element shapes.

You can filter the list of fields with solid element shapes based on a given time, complex type, or both.

Parameters:

• timeid (int, optional) – Time ID for filtering fields with solid element shapes.

• complexid (int, optional) – Complex type ID for filtering fields with solid element shapes. 0 is for real numbers, and 1 is for imaginary numbers.

Returns:

List of fields corresponding to the request.

Return type:

list

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_all_kinds_of_complexity_modal())
>>> fc = model.results.displacement.split_by_shape.eval()
>>> len(fc.solid_fields())
1
>>> len(fc.solid_fields(timeid=1))
1

shell_fields(timeid=None, complexid=None)

Retrieve a list of all fields with shell element shapes.

You can filter the list of fields with shell element shapes based on a given time, complex type, or both.

Parameters:

• timeid (int, optional) – Time ID for filtering fields with shell element shapes.

• complexid (int, optional) – Complex type ID for filtering fields with shell element shapes. 0 is for real numbers, and 1 is for imaginary numbers.

Returns:

List of fields corresponding to the request.

Return type:

list

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_all_kinds_of_complexity_modal())
>>> fc = model.results.displacement.on_all_time_freqs.split_by_shape.eval()
>>> len(fc.shell_fields())
45
>>> len(fc.shell_fields(timeid=3))
1

beam_fields(timeid=None, complexid=None)

Retrieve a list of all fields with beam element shapes.

You can filter the list of fields with beam element shapes based on a given time, complex type, or both.

Parameters:

• timeid (int, optional) – Time ID for filtering fields with beam element shapes.

• complexid (int, optional) – Complex type ID for filtering fields with beam element shapes. 0 is for real numbers, and 1 is for imaginary numbers.

Returns:

List of fields corresponding to the request.

Return type:

list

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_all_kinds_of_complexity_modal())
>>> fc = model.results.displacement.on_all_time_freqs.split_by_shape.eval()
>>> len(fc.beam_fields())
45
>>> len(fc.beam_fields(timeid=3))
1

solid_field(timeid=None, complexid=None)

Retrieve a field with a solid element shape.

You can give a time, complex type, or both. If the number of fields matching the request is higher than one, an exception is raised.

Parameters:

• timeid (int, optional) – Time ID for filtering fields with solid element shapes.

• complexid (int, optional) – Complex type ID for filtering fields with solid element shapes. 0 is for real numbers, and 1 is for imaginary numbers.

Returns:

Field corresponding to the request.

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_all_kinds_of_complexity_modal())
>>> fc = model.results.displacement.on_all_time_freqs.split_by_shape.eval()
>>> field = fc.solid_field(timeid=3)

shell_field(timeid=None, complexid=None)

Retrieve a field with a shell element shape.

You can give a time, complex type, or both. If the number of fields matching the request is higher than one, an exception is raised.

Parameters:

• timeid (int, optional) – Time ID for filtering fields with shell element shapes.

• complexid (int, optional) – Complex type ID for filtering fields with shell element shapes. 0 is for real numbers, and 1 is for imaginary numbers.

Returns:

Field corresponding to the request.

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_all_kinds_of_complexity_modal())
>>> fc = model.results.displacement.on_all_time_freqs.split_by_shape.eval()
>>> field = fc.shell_field(timeid=3)

beam_field(timeid=None, complexid=None)

Retrieve a field with a beam element shape.

You can give a time, complex type, or both. If the number of fields matching the request is higher than one, an exception is raised.

Parameters:

• timeid (int, optional) – Time ID for filtering fields with solid element shapes.

• complexid (int, optional) – Complex type ID for filtering fields with solid element shapes. 0 is for real numbers, and 1 is for imaginary numbers.

Returns:

Field corresponding to the request.

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_all_kinds_of_complexity_modal())
>>> fc = model.results.displacement.on_all_time_freqs.split_by_shape.eval()
>>> field = fc.beam_field(timeid=3)

add_field(label_space, field)

Add or update a field at a requested label space.

Parameters:

• label_space (dict[str,int]) – Label space of the requested field. For example, {“time”:1, “complex”:0}.

• field (Field) – DPF field to add or update.

Examples

>>> from ansys.dpf import core as dpf
>>> fc= dpf.FieldsContainer()
>>> fc.labels =['time','complex']
>>> for i in range(0,20): #real fields
...     mscop = {"time":i+1,"complex":0}
...     fc.add_field(mscop,dpf.Field(nentities=i+10))
>>> for i in range(0,20): #imaginary fields
...     mscop = {"time":i+1,"complex":1}
...     fc.add_field(mscop,dpf.Field(nentities=i+10))

add_field_by_time_id(field, timeid=1)

Add or update a field at a requested time ID.

Parameters:

• field (Field) – DPF field to add or update.

• timeid (int, optional) – Time ID for the requested time set. The default is 1.

add_imaginary_field(field, timeid=1)

Add or update an imaginary field at a requested time ID.

Parameters:

• field (Field) – DPF field to add or update.

• timeid (int, optional) – Time ID for the requested time set. The default is 1.

add_label(label, default_value=None)

Add the requested label to scope the collection.

Parameters:

• label (str) – Labels to scope the entries to. For example, "time".

• default_value (int, optional) – Default value for existing fields in the collection. The default is None.

Examples

>>> from ansys.dpf import core as dpf
>>> coll = dpf.FieldsContainer()
>>> coll.add_label('time')

animate(save_as=None, deform_by=None, scale_factor=1.0, **kwargs)

Creates an animation based on the Fields contained in the FieldsContainer.

This method creates a movie or a gif based on the time ids of a FieldsContainer. For kwargs see pyvista.Plotter.open_movie/add_text/show.

Parameters:

• save_as (Path of file to save the animation to. Defaults to None. Can be of any format) – supported by pyvista.Plotter.write_frame (.gif, .mp4, …).

• deform_by (FieldsContainer, Result, Operator, optional) – Used to deform the plotted mesh. Must return a FieldsContainer of the same length as self, containing 3D vector Fields of distances. Defaults to None, which takes self if possible. Set as False to force static animation.

• scale_factor (float, list, optional) – Scale factor to apply when warping the mesh. Defaults to 1.0. Can be a list to make scaling frequency-dependent.

deep_copy(server=None)

Create a deep copy of the fields container’s data (and its fields) on a given server.

This method is useful for passing data from one server instance to another.

Parameters:

server (ansys.dpf.core.server, 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:

fields_container_copy

Return type:

FieldsContainer

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()
>>> disp.inputs.time_scoping.connect([1,5])
>>> fields_container = disp.outputs.fields_container()
>>> other_server = dpf.start_local_server(as_global=False)
>>> deep_copy = fields_container.deep_copy(server=other_server)

entries_type

alias of Field

get_available_ids_for_label(label='time')

Retrieve the IDs assigned to an input label.

Parameters:

label (str) – Name of the input label. The default is "time".

Returns:

ids – List of IDs assigned to the input label.

Return type:

list[int]

get_entries_indices(label_space)

Retrieve the indices of the entries corresponding a requested label space .

Notes

Available starting with DPF 2025R1.

Parameters:

label_space (dict[str,int]) – Label space or index. For example, {"time": 1, "complex": 0} or the index of the field.

Returns:

indices – Indices of the entries corresponding to the request.

Return type:

list[int], list[Field], list[MeshedRegion]

get_field(label_space_or_index)

Retrieves the field at a requested index or label space.

An exception is raised if the number of fields matching the request is greater than one.

Parameters:

label_space_or_index (dict[str,int], int) – Scoping of the requested fields. For example, {"time": 1, "complex": 0} or the index of the field.

Returns:

field – Field corresponding to the request.

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> fc = dpf.fields_container_factory.over_time_freq_fields_container(
...     [dpf.Field(nentities=10)]
... )
>>> field = fc.get_field({"time":1})

get_field_by_time_complex_ids(timeid=None, complexid=None)

Retrieve a field at a requested time ID or complex ID.

An exception is raised if the number of fields matching the request is greater than one.

Parameters:

• timeid (int, optional) – Time ID or frequency ID, which is the one-based index of the result set.

• complexid (int, optional) – Complex ID, where 1 is for imaginary and 0 is for real.

Returns:

fields – Field corresponding to the request

Return type:

Field

Examples

Extract the fifth time set of a transient analysis.

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> transient = examples.download_transient_result()
>>> model = dpf.Model(transient)
>>> len(model.metadata.time_freq_support.time_frequencies)
35
>>> disp = model.results.displacement()
>>> disp.inputs.time_scoping.connect([1,5])
>>> fields_container = disp.outputs.fields_container()
>>> field_set_5 =fields_container.get_fields_by_time_complex_ids(5)

get_field_by_time_id(timeid=None)

Retrieves the complex field at a requested time.

Parameters:

timeid (int, optional) – Time ID, which is the one-based index of the result set.

Returns:

fields – Fields corresponding to the request.

Return type:

Field

get_fields(label_space)

Retrieve the fields at a requested index or label space.

Parameters:

label_space (dict[str,int]) – Scoping of the requested fields. For example, {"time": 1, "complex": 0}.

Returns:

fields – Fields corresponding to the request.

Return type:

list[Field]

Examples

>>> from ansys.dpf import core as dpf
>>> fc= dpf.FieldsContainer()
>>> fc.labels =['time','complex']
>>> #real fields
>>> for i in range(0,20):
...     mscop = {"time":i+1,"complex":0}
...     fc.add_field(mscop,dpf.Field(nentities=i+10))
>>> #imaginary fields
>>> for i in range(0,20):
...     mscop = {"time":i+1,"complex":1}
...     fc.add_field(mscop,dpf.Field(nentities=i+10))

>>> fields = fc.get_fields({"time":2})
>>> # imaginary and real fields of time 2
>>> len(fields)
2

get_fields_by_time_complex_ids(timeid=None, complexid=None)

Retrieve fields at a requested time ID or complex ID.

Parameters:

• timeid (int, optional) – Time ID or frequency ID, which is the one-based index of the result set.

• complexid (int, optional) – Complex ID, where 1 is for imaginary and 0 is for real.

Returns:

fields – Fields corresponding to the request.

Return type:

list[Field]

Examples

Extract the fifth time set of a transient analysis.

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> transient = examples.download_transient_result()
>>> model = dpf.Model(transient)
>>> len(model.metadata.time_freq_support.time_frequencies)
35
>>> disp = model.results.displacement()
>>> disp.inputs.time_scoping.connect([1,5])
>>> fields_container = disp.outputs.fields_container()
>>> field_set_5 =fields_container.get_fields_by_time_complex_ids(5)

get_imaginary_field(timeid=None)

Retrieve the complex field at a requested time.

Parameters:

timeid (int, optional) – Time ID, which is the one-based index of the result set.

Returns:

fields – Field corresponding to the request.

Return type:

Field

get_imaginary_fields(timeid=None)

Retrieve the complex fields at a requested time.

Parameters:

timeid (int, optional) – Time ID, which is the one-based index of the result set.

Returns:

fields – Fields corresponding to the request.

Return type:

list[Field]

get_label_scoping(label='time')

Retrieve the scoping for an input label.

This method allows you to retrieve a list of IDs for a given input label in the collection. For example, if the label el_type exists in the collection, you can use the get_lable_scoping method to retrieve a list of IDS with this label. You can then use these IDs to request a given entity inside the collection.

Parameters:

label (str) – Name of the input label.

Returns:

scoping – IDs scoped to the input label.

Return type:

Scoping

get_label_space(index)

Retrieve the label space of an entry at a requested index.

Parameters:

index (int) – Index of the entry.

Returns:

label_space – Scoping of the requested entry. For example, {"time": 1, "complex": 0}.

Return type:

dict(str:int)

get_support(label: str)

Get the support of the collection for a given label.

Return type:

Support

Notes

Available starting with DPF 2023 R1.

get_time_scoping()

Retrieves the time scoping containing the time sets.

Returns:

scoping – Scoping containing the time set IDs available in the fields container.

Return type:

Scoping

has_label(label)

Check if a collection has a specified label.

Parameters:

label (str) – Label to search for. For example, "time".

Returns:

True when successful, False when failed.

Return type:

bool

Examples

>>> from ansys.dpf import core as dpf
>>> coll = dpf.FieldsContainer()
>>> coll.add_label('time')
>>> coll.has_label('time')
True

>>> coll.has_label('complex')
False

static integral_collection(inpt, server: ansys.dpf.core.server_types.BaseServer | None = None)

Creates a collection of integral type with a list.

The collection of integral is the equivalent of an array of data sent server side. It can be used to efficiently stream large data to the server.

Parameters:

inpt (list[float], list[int], numpy.array) – list to transfer server side

Return type:

IntegralCollection

Notes

Used by default by the 'Operator' and the``’Workflow’`` when a list is connected or returned.

property name

Name of the Collection.

Notes

Available starting with DPF 2024 R2 pre0.

Return type:

str

plot(label_space: dict | None = None, **kwargs)

Plots the fields in the FieldsContainer for the given LabelSpace. Check the labels available for the FieldsContainer with labels().

Parameters:

• label_space (Optional[dict], default: None) – A dictionary (LabelSpace) of labels of the FieldsContainer with associated values to select for plotting. This is used to filter the data to plot, for example: - if label_space={'time': 10}: a single time step (mandatory for transient) - if label_space={'complex': 0, 'part': 12}: real part of complex data for a part See get_fields(). If None is given, it renders all fields available, which may not make sense.

• **kwargs – For more information on accepted keyword arguments, see plot() and DpfPlotter.

select_component(index)

Select fields containing only the component index.

Fields can be selected only by component index as multiple fields may contain a different number of components.

Parameters:

index (int) – Index of the component.

Returns:

fields – Fields container with one component selected in each field.

Return type:

FieldsContainer

Examples

Select using a component index.

>>> 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()
>>> disp.inputs.time_scoping.connect([1,5])
>>> fields_container = disp.outputs.fields_container()
>>> disp_x_fields = fields_container.select_component(0)
>>> my_field = disp_x_fields[0]

set_labels(labels)

Set labels for scoping the collection.

Parameters:

labels (list[str], optional) – Labels to scope entries to. For example, ["time", "complex"].

set_support(label: str, support: ansys.dpf.core.support.Support)

Set the support of the collection for a given label.

Return type:

None

Notes

Available starting with DPF 2023 R1.

property time_freq_support

Time frequency support.

class ansys.dpf.core.custom_fields_container.BodyFieldsContainer(fields_container=None, server=None)

Represents a fields container with fields split by a body.

Instances of this class are created when a model result is split by a body, which is an MAPDL material property.

Parameters:

• fields_container (ansys.grpc.dpf.collection_pb2.Collection or FieldsContainer, optional) – Fields container created from either a collection message or by copying an existing fields container. The default is None.

• 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
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_all_kinds_of_complexity_modal())
>>> fc = model.results.displacement.on_all_time_freqs.split_by_body.eval()
>>> fc.get_mat_scoping().ids[3]
np.int32(45)
>>> len(fc.get_fields_by_mat_id(45))
45
>>> f_time_2 = fc.get_field_by_mat_id(45, timeid=2)

get_fields_by_mat_id(matid, timeid=None, complexid=None)

Retrieve a list of all fields for a material ID. You can filter the list of fields for a material ID based on a given time, complex type, or both.

Parameters:

• matid (int, optional) – Material ID. To request available material IDs, you can use the get_mat_scoping method.

• timeid (int, optional) – Time ID for filtering fields with the given material ID.

• complexid (int, optional) – Complex type ID for filtering fields with the given material ID. 0 is for real numbers, and 1 is for imaginary numbers.

Returns:

List of fields corresponding to the request.

Return type:

List

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_all_kinds_of_complexity_modal())
>>> fc = model.results.displacement.on_all_time_freqs.split_by_body.eval()
>>> len(fc.get_fields_by_mat_id(1))
45
>>> len(fc.get_fields_by_mat_id(1, timeid=3))
1

get_field_by_mat_id(matid, timeid=None, complexid=None)

Retrieve a field with a given material ID. You can filter the field based on a given time, complex type, or both.

Parameters:

• matid (int, optional) – Material ID. To request available material IDs, you can use the get_mat_scoping method.

• timeid (int, optional) – Time ID for filtering fields with the given material ID.

• complexid (int, optional) – Complex type ID for filtering fields with the given material ID. 0 is for real numbers, and 1 is for imaginary numbers.

Returns:

Field corresponding to the request.

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> model = dpf.Model(examples.download_all_kinds_of_complexity_modal())
>>> fc = model.results.displacement.on_all_time_freqs.split_by_body.eval()
>>> f_time_2 = fc.get_field_by_mat_id(45, timeid=2)

get_mat_scoping()

Retrieves the material or body scoping containing material IDs.

Returns:

Field corresponding to the request. Scoping containing the material IDs available in the fields container.

Return type:

Scoping

add_field(label_space, field)

Add or update a field at a requested label space.

Parameters:

• label_space (dict[str,int]) – Label space of the requested field. For example, {“time”:1, “complex”:0}.

• field (Field) – DPF field to add or update.

Examples

>>> from ansys.dpf import core as dpf
>>> fc= dpf.FieldsContainer()
>>> fc.labels =['time','complex']
>>> for i in range(0,20): #real fields
...     mscop = {"time":i+1,"complex":0}
...     fc.add_field(mscop,dpf.Field(nentities=i+10))
>>> for i in range(0,20): #imaginary fields
...     mscop = {"time":i+1,"complex":1}
...     fc.add_field(mscop,dpf.Field(nentities=i+10))

add_field_by_time_id(field, timeid=1)

Add or update a field at a requested time ID.

Parameters:

• field (Field) – DPF field to add or update.

• timeid (int, optional) – Time ID for the requested time set. The default is 1.

add_imaginary_field(field, timeid=1)

Add or update an imaginary field at a requested time ID.

Parameters:

• field (Field) – DPF field to add or update.

• timeid (int, optional) – Time ID for the requested time set. The default is 1.

add_label(label, default_value=None)

Add the requested label to scope the collection.

Parameters:

• label (str) – Labels to scope the entries to. For example, "time".

• default_value (int, optional) – Default value for existing fields in the collection. The default is None.

Examples

>>> from ansys.dpf import core as dpf
>>> coll = dpf.FieldsContainer()
>>> coll.add_label('time')

animate(save_as=None, deform_by=None, scale_factor=1.0, **kwargs)

Creates an animation based on the Fields contained in the FieldsContainer.

This method creates a movie or a gif based on the time ids of a FieldsContainer. For kwargs see pyvista.Plotter.open_movie/add_text/show.

Parameters:

• save_as (Path of file to save the animation to. Defaults to None. Can be of any format) – supported by pyvista.Plotter.write_frame (.gif, .mp4, …).

• deform_by (FieldsContainer, Result, Operator, optional) – Used to deform the plotted mesh. Must return a FieldsContainer of the same length as self, containing 3D vector Fields of distances. Defaults to None, which takes self if possible. Set as False to force static animation.

• scale_factor (float, list, optional) – Scale factor to apply when warping the mesh. Defaults to 1.0. Can be a list to make scaling frequency-dependent.

deep_copy(server=None)

Create a deep copy of the fields container’s data (and its fields) on a given server.

This method is useful for passing data from one server instance to another.

Parameters:

server (ansys.dpf.core.server, 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:

fields_container_copy

Return type:

FieldsContainer

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()
>>> disp.inputs.time_scoping.connect([1,5])
>>> fields_container = disp.outputs.fields_container()
>>> other_server = dpf.start_local_server(as_global=False)
>>> deep_copy = fields_container.deep_copy(server=other_server)

entries_type

alias of Field

get_available_ids_for_label(label='time')

Retrieve the IDs assigned to an input label.

Parameters:

label (str) – Name of the input label. The default is "time".

Returns:

ids – List of IDs assigned to the input label.

Return type:

list[int]

get_entries_indices(label_space)

Retrieve the indices of the entries corresponding a requested label space .

Notes

Available starting with DPF 2025R1.

Parameters:

label_space (dict[str,int]) – Label space or index. For example, {"time": 1, "complex": 0} or the index of the field.

Returns:

indices – Indices of the entries corresponding to the request.

Return type:

list[int], list[Field], list[MeshedRegion]

get_field(label_space_or_index)

Retrieves the field at a requested index or label space.

An exception is raised if the number of fields matching the request is greater than one.

Parameters:

label_space_or_index (dict[str,int], int) – Scoping of the requested fields. For example, {"time": 1, "complex": 0} or the index of the field.

Returns:

field – Field corresponding to the request.

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> fc = dpf.fields_container_factory.over_time_freq_fields_container(
...     [dpf.Field(nentities=10)]
... )
>>> field = fc.get_field({"time":1})

get_field_by_time_complex_ids(timeid=None, complexid=None)

Retrieve a field at a requested time ID or complex ID.

An exception is raised if the number of fields matching the request is greater than one.

Parameters:

• timeid (int, optional) – Time ID or frequency ID, which is the one-based index of the result set.

• complexid (int, optional) – Complex ID, where 1 is for imaginary and 0 is for real.

Returns:

fields – Field corresponding to the request

Return type:

Field

Examples

Extract the fifth time set of a transient analysis.

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> transient = examples.download_transient_result()
>>> model = dpf.Model(transient)
>>> len(model.metadata.time_freq_support.time_frequencies)
35
>>> disp = model.results.displacement()
>>> disp.inputs.time_scoping.connect([1,5])
>>> fields_container = disp.outputs.fields_container()
>>> field_set_5 =fields_container.get_fields_by_time_complex_ids(5)

get_field_by_time_id(timeid=None)

Retrieves the complex field at a requested time.

Parameters:

timeid (int, optional) – Time ID, which is the one-based index of the result set.

Returns:

fields – Fields corresponding to the request.

Return type:

Field

get_fields(label_space)

Retrieve the fields at a requested index or label space.

Parameters:

label_space (dict[str,int]) – Scoping of the requested fields. For example, {"time": 1, "complex": 0}.

Returns:

fields – Fields corresponding to the request.

Return type:

list[Field]

Examples

>>> from ansys.dpf import core as dpf
>>> fc= dpf.FieldsContainer()
>>> fc.labels =['time','complex']
>>> #real fields
>>> for i in range(0,20):
...     mscop = {"time":i+1,"complex":0}
...     fc.add_field(mscop,dpf.Field(nentities=i+10))
>>> #imaginary fields
>>> for i in range(0,20):
...     mscop = {"time":i+1,"complex":1}
...     fc.add_field(mscop,dpf.Field(nentities=i+10))

>>> fields = fc.get_fields({"time":2})
>>> # imaginary and real fields of time 2
>>> len(fields)
2

get_fields_by_time_complex_ids(timeid=None, complexid=None)

Retrieve fields at a requested time ID or complex ID.

Parameters:

• timeid (int, optional) – Time ID or frequency ID, which is the one-based index of the result set.

• complexid (int, optional) – Complex ID, where 1 is for imaginary and 0 is for real.

Returns:

fields – Fields corresponding to the request.

Return type:

list[Field]

Examples

Extract the fifth time set of a transient analysis.

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> transient = examples.download_transient_result()
>>> model = dpf.Model(transient)
>>> len(model.metadata.time_freq_support.time_frequencies)
35
>>> disp = model.results.displacement()
>>> disp.inputs.time_scoping.connect([1,5])
>>> fields_container = disp.outputs.fields_container()
>>> field_set_5 =fields_container.get_fields_by_time_complex_ids(5)

get_imaginary_field(timeid=None)

Retrieve the complex field at a requested time.

Parameters:

timeid (int, optional) – Time ID, which is the one-based index of the result set.

Returns:

fields – Field corresponding to the request.

Return type:

Field

get_imaginary_fields(timeid=None)

Retrieve the complex fields at a requested time.

Parameters:

timeid (int, optional) – Time ID, which is the one-based index of the result set.

Returns:

fields – Fields corresponding to the request.

Return type:

list[Field]

get_label_scoping(label='time')

Retrieve the scoping for an input label.

This method allows you to retrieve a list of IDs for a given input label in the collection. For example, if the label el_type exists in the collection, you can use the get_lable_scoping method to retrieve a list of IDS with this label. You can then use these IDs to request a given entity inside the collection.

Parameters:

label (str) – Name of the input label.

Returns:

scoping – IDs scoped to the input label.

Return type:

Scoping

get_label_space(index)

Retrieve the label space of an entry at a requested index.

Parameters:

index (int) – Index of the entry.

Returns:

label_space – Scoping of the requested entry. For example, {"time": 1, "complex": 0}.

Return type:

dict(str:int)

get_support(label: str)

Get the support of the collection for a given label.

Return type:

Support

Notes

Available starting with DPF 2023 R1.

get_time_scoping()

Retrieves the time scoping containing the time sets.

Returns:

scoping – Scoping containing the time set IDs available in the fields container.

Return type:

Scoping

has_label(label)

Check if a collection has a specified label.

Parameters:

label (str) – Label to search for. For example, "time".

Returns:

True when successful, False when failed.

Return type:

bool

Examples

>>> from ansys.dpf import core as dpf
>>> coll = dpf.FieldsContainer()
>>> coll.add_label('time')
>>> coll.has_label('time')
True

>>> coll.has_label('complex')
False

static integral_collection(inpt, server: ansys.dpf.core.server_types.BaseServer | None = None)

Creates a collection of integral type with a list.

The collection of integral is the equivalent of an array of data sent server side. It can be used to efficiently stream large data to the server.

Parameters:

inpt (list[float], list[int], numpy.array) – list to transfer server side

Return type:

IntegralCollection

Notes

Used by default by the 'Operator' and the``’Workflow’`` when a list is connected or returned.

property name

Name of the Collection.

Notes

Available starting with DPF 2024 R2 pre0.

Return type:

str

plot(label_space: dict | None = None, **kwargs)

Plots the fields in the FieldsContainer for the given LabelSpace. Check the labels available for the FieldsContainer with labels().

Parameters:

• label_space (Optional[dict], default: None) – A dictionary (LabelSpace) of labels of the FieldsContainer with associated values to select for plotting. This is used to filter the data to plot, for example: - if label_space={'time': 10}: a single time step (mandatory for transient) - if label_space={'complex': 0, 'part': 12}: real part of complex data for a part See get_fields(). If None is given, it renders all fields available, which may not make sense.

• **kwargs – For more information on accepted keyword arguments, see plot() and DpfPlotter.

select_component(index)

Select fields containing only the component index.

Fields can be selected only by component index as multiple fields may contain a different number of components.

Parameters:

index (int) – Index of the component.

Returns:

fields – Fields container with one component selected in each field.

Return type:

FieldsContainer

Examples

Select using a component index.

>>> 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()
>>> disp.inputs.time_scoping.connect([1,5])
>>> fields_container = disp.outputs.fields_container()
>>> disp_x_fields = fields_container.select_component(0)
>>> my_field = disp_x_fields[0]

set_labels(labels)

Set labels for scoping the collection.

Parameters:

labels (list[str], optional) – Labels to scope entries to. For example, ["time", "complex"].

set_support(label: str, support: ansys.dpf.core.support.Support)

Set the support of the collection for a given label.

Return type:

None

Notes

Available starting with DPF 2023 R1.

property time_freq_support

Time frequency support.