apply_zfp

Autogenerated DPF operator classes.

class ansys.dpf.core.operators.compression.apply_zfp.apply_zfp(dataIn=None, mode=None, mode_parameter=None, dim=None, order=None, double_absthreshold=None, double_relthreshold=None, config=None, server=None)

Compressing input data using one of zfp compression algorithm modes.

Parameters:

• dataIn (Field or FieldsContainer) – Field or fields container to be compressed

• mode (str or Char) – Zfp mode: fixed-rate (‘r’), fixed-precision (‘p’), fixed-accuracy (‘a’)

• mode_parameter (int or float) – Mode-corresponding parameter: rate (double) / precision (int) / accuracy (double)

• dim (int, optional) – Dimension (1d/2d/3d) for data organization before the compression (int; default: 2)

• order (int, optional) – Xyz dimensions order, where x (row) corresponds to number of elementary data, y (col) - number of time steps, z - number of components (applicable only for 3d data) : 0=xyz, 1=yxz (int; default: 0)

• double_absthreshold (float, optional) – Double positive small value. all the values smaller than max(small value, max(vi) * relative threshold) are considered as zero values, (default value: 1.0e-18).

• double_relthreshold (float, optional) – Double relative threshold. values smaller than (v1 - v2) < max(small value, v1 * relativetol) are considered identical (default value: 1.0e-10).

Returns:

• compress_speed (float) – The output entity is a double, containing compression speed of the input data: for elementalnodal location - [elements/sec], for nodal location - [nodes/sec]

• compress_ratio (float) – The output entity is a double, containing compression rate = initial/compressed

• dataOut (CustomTypeFieldsContainer) – The output entity is a ‘custom type field container’; each output field containing compressed results corresponding to one component data (ie. input vector field/fc contains 3 components will give 3 output fields), this is not the case when input pin3 is set to 3, all components will be compressed into one field.

Examples

>>> from ansys.dpf import core as dpf

>>> # Instantiate operator
>>> op = dpf.operators.compression.apply_zfp()

>>> # Make input connections
>>> my_dataIn = dpf.Field()
>>> op.inputs.dataIn.connect(my_dataIn)
>>> my_mode = str()
>>> op.inputs.mode.connect(my_mode)
>>> my_mode_parameter = int()
>>> op.inputs.mode_parameter.connect(my_mode_parameter)
>>> my_dim = int()
>>> op.inputs.dim.connect(my_dim)
>>> my_order = int()
>>> op.inputs.order.connect(my_order)
>>> my_double_absthreshold = float()
>>> op.inputs.double_absthreshold.connect(my_double_absthreshold)
>>> my_double_relthreshold = float()
>>> op.inputs.double_relthreshold.connect(my_double_relthreshold)

>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.compression.apply_zfp(
...     dataIn=my_dataIn,
...     mode=my_mode,
...     mode_parameter=my_mode_parameter,
...     dim=my_dim,
...     order=my_order,
...     double_absthreshold=my_double_absthreshold,
...     double_relthreshold=my_double_relthreshold,
... )

>>> # Get output data
>>> result_compress_speed = op.outputs.compress_speed()
>>> result_compress_ratio = op.outputs.compress_ratio()
>>> result_dataOut = op.outputs.dataOut()

static default_config(server=None)

Returns the default config of the operator.

This config can then be changed to the user needs and be used to instantiate the operator. The Configuration allows to customize how the operation will be processed by the operator.

Parameters:

server (server.DPFServer, optional) – Server with channel connected to the remote or local instance. When None, attempts to use the global server.

property inputs

Enables to connect inputs to the operator

Returns:

inputs

Return type:

InputsApplyZfp

property outputs

Enables to get outputs of the operator by evaluating it

Returns:

outputs

Return type:

OutputsApplyZfp

property config

Copy of the operator’s current configuration.

You can modify the copy of the configuration and then use operator.config = new_config or instantiate an operator with the new configuration as a parameter.

For information on an operator’s options, see the documentation for that operator.

Returns:

Copy of the operator’s current configuration.

Return type:

ansys.dpf.core.config.Config

Examples

Modify the copy of an operator’s configuration and set it as current config of the operator.

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.add()
>>> config_add = op.config
>>> config_add.set_work_by_index_option(True)
>>> op.config = config_add

connect(pin, inpt, pin_out=0)

Connect an input on the operator using a pin number.

Parameters:

• pin (int) – Number of the input pin.

• inpt (str, int, double, bool, list[int], list[float], Field, FieldsContainer, Scoping,) –

• ScopingsContainer – Operator, os.PathLike Object to connect to.

• MeshedRegion – Operator, os.PathLike Object to connect to.

• MeshesContainer – Operator, os.PathLike Object to connect to.

• DataSources – Operator, os.PathLike Object to connect to.

• CyclicSupport – Operator, os.PathLike Object to connect to.

• dict – Operator, os.PathLike Object to connect to.

• Outputs – Operator, os.PathLike Object to connect to.

• pin_out (int, optional) – If the input is an operator, the output pin of the input operator. The default is 0.

Examples

Compute the minimum of displacement by chaining the "U" and "min_max_fc" operators.

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> data_src = dpf.DataSources(examples.find_multishells_rst())
>>> disp_op = dpf.operators.result.displacement()
>>> disp_op.inputs.data_sources(data_src)
>>> max_fc_op = dpf.operators.min_max.min_max_fc()
>>> max_fc_op.inputs.connect(disp_op.outputs)
>>> max_field = max_fc_op.outputs.field_max()
>>> max_field.data
DPFArray([[0.59428386, 0.00201751, 0.0006032 ]]...

connect_operator_as_input(pin, op)

Connects an operator as an input on a pin. :type pin: :param pin: Number of the output pin. The default is 0. :type pin: int :type op: :param op: Requested type of the output. The default is None. :type op: ansys.dpf.core.dpf_operator.Operator

eval(pin=None)

Evaluate this operator.

Parameters:

pin (int) – Number of the output pin. The default is None.

Returns:

output – Returns the first output of the operator by default and the output of a given pin when specified. Or, it only evaluates the operator without output.

Return type:

FieldsContainer, Field, MeshedRegion, Scoping

Examples

Use the eval method.

>>> from ansys.dpf import core as dpf
>>> import ansys.dpf.core.operators.math as math
>>> from ansys.dpf.core import examples
>>> data_src = dpf.DataSources(examples.find_multishells_rst())
>>> disp_op = dpf.operators.result.displacement()
>>> disp_op.inputs.data_sources(data_src)
>>> normfc = math.norm_fc(disp_op).eval()

get_output(pin=0, output_type=None)

Retrieve the output of the operator on the pin number.

To activate the progress bar for server version higher or equal to 3.0, use my_op.progress_bar=True

Parameters:

• pin (int, optional) – Number of the output pin. The default is 0.

• output_type (ansys.dpf.core.common.types, type, optional) – Requested type of the output. The default is None.

Returns:

Output of the operator.

Return type:

type

static operator_specification(op_name, server=None)

Documents an Operator with its description (what the Operator does), its inputs and outputs and some properties

property progress_bar: bool

With this property, the user can choose to print a progress bar when the operator’s output is requested, default is False

run()

Evaluate this operator.

property specification

Returns the Specification (or documentation) of this Operator

Return type:

Specification

class ansys.dpf.core.operators.compression.apply_zfp.InputsApplyZfp(op: ansys.dpf.core.dpf_operator.Operator)

Intermediate class used to connect user inputs to apply_zfp operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> my_dataIn = dpf.Field()
>>> op.inputs.dataIn.connect(my_dataIn)
>>> my_mode = str()
>>> op.inputs.mode.connect(my_mode)
>>> my_mode_parameter = int()
>>> op.inputs.mode_parameter.connect(my_mode_parameter)
>>> my_dim = int()
>>> op.inputs.dim.connect(my_dim)
>>> my_order = int()
>>> op.inputs.order.connect(my_order)
>>> my_double_absthreshold = float()
>>> op.inputs.double_absthreshold.connect(my_double_absthreshold)
>>> my_double_relthreshold = float()
>>> op.inputs.double_relthreshold.connect(my_double_relthreshold)

property dataIn

Allows to connect dataIn input to the operator.

Field or fields container to be compressed

Parameters:

my_dataIn (Field or FieldsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> op.inputs.dataIn.connect(my_dataIn)
>>> # or
>>> op.inputs.dataIn(my_dataIn)

property mode

Allows to connect mode input to the operator.

Zfp mode: fixed-rate (‘r’), fixed-precision (‘p’), fixed-accuracy (‘a’)

Parameters:

my_mode (str or Char) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> op.inputs.mode.connect(my_mode)
>>> # or
>>> op.inputs.mode(my_mode)

property mode_parameter

Allows to connect mode_parameter input to the operator.

Mode-corresponding parameter: rate (double) / precision (int) / accuracy (double)

Parameters:

my_mode_parameter (int or float) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> op.inputs.mode_parameter.connect(my_mode_parameter)
>>> # or
>>> op.inputs.mode_parameter(my_mode_parameter)

property dim

Allows to connect dim input to the operator.

Dimension (1d/2d/3d) for data organization before the compression (int; default: 2)

Parameters:

my_dim (int) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> op.inputs.dim.connect(my_dim)
>>> # or
>>> op.inputs.dim(my_dim)

property order

Allows to connect order input to the operator.

Xyz dimensions order, where x (row) corresponds to number of elementary data, y (col) - number of time steps, z - number of components (applicable only for 3d data) : 0=xyz, 1=yxz (int; default: 0)

Parameters:

my_order (int) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> op.inputs.order.connect(my_order)
>>> # or
>>> op.inputs.order(my_order)

property double_absthreshold

Allows to connect double_absthreshold input to the operator.

Double positive small value. all the values smaller than max(small value, max(vi) * relative threshold) are considered as zero values, (default value: 1.0e-18).

Parameters:

my_double_absthreshold (float) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> op.inputs.double_absthreshold.connect(my_double_absthreshold)
>>> # or
>>> op.inputs.double_absthreshold(my_double_absthreshold)

property double_relthreshold

Allows to connect double_relthreshold input to the operator.

Double relative threshold. values smaller than (v1 - v2) < max(small value, v1 * relativetol) are considered identical (default value: 1.0e-10).

Parameters:

my_double_relthreshold (float) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> op.inputs.double_relthreshold.connect(my_double_relthreshold)
>>> # or
>>> op.inputs.double_relthreshold(my_double_relthreshold)

connect(inpt)

Connect any input (an entity or an operator output) to any input pin of this operator. Searches for the input type corresponding to the output.

Parameters:

• inpt (str, int, double, bool, list[int], list[float], Field, FieldsContainer, Scoping,) –

• ScopingsContainer (E501) – Input of the operator.

• MeshedRegion (E501) – Input of the operator.

• MeshesContainer (E501) – Input of the operator.

• DataSources (E501) – Input of the operator.

• CyclicSupport (E501) – Input of the operator.

• Outputs (E501) – Input of the operator.

• noqa (os.PathLike #) – Input of the operator.

class ansys.dpf.core.operators.compression.apply_zfp.OutputsApplyZfp(op: ansys.dpf.core.dpf_operator.Operator)

Intermediate class used to get outputs from apply_zfp operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> # Connect inputs : op.inputs. ...
>>> result_compress_speed = op.outputs.compress_speed()
>>> result_compress_ratio = op.outputs.compress_ratio()
>>> result_dataOut = op.outputs.dataOut()

property compress_speed

Allows to get compress_speed output of the operator

Returns:

my_compress_speed

Return type:

float

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> # Connect inputs : op.inputs. ...
>>> result_compress_speed = op.outputs.compress_speed()

property compress_ratio

Allows to get compress_ratio output of the operator

Returns:

my_compress_ratio

Return type:

float

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> # Connect inputs : op.inputs. ...
>>> result_compress_ratio = op.outputs.compress_ratio()

property dataOut

Allows to get dataOut output of the operator

Returns:

my_dataOut

Return type:

CustomTypeFieldsContainer

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.compression.apply_zfp()
>>> # Connect inputs : op.inputs. ...
>>> result_dataOut = op.outputs.dataOut()