scale

class ansys.dpf.core.operators.math.scale.scale(field=None, weights=None, boolean=None, algorithm=None, config=None, server=None, ponderation=None)

Bases: ansys.dpf.core.dpf_operator.Operator

Scales a field by a constant factor. This factor can be a scalar or a vector, where each value of the vector represents a scaler per component. Number of the components are corresponding to the input field dimensionality

Parameters:

• field (Field or FieldsContainer) – field or fields container with only one field is expected

• weights (float or Field) – Double/Field/Vector of doubles. When scoped on overall, same value(s) applied on all the data, when scoped elsewhere, corresponding values will be multiplied due to the scoping

• boolean (bool, optional) – Default is false. If set to true, output of scale is made dimensionless

• algorithm (int, optional) – Default is 0 use mkl. If set to 1, don’t

Returns:

field

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf

>>> # Instantiate operator
>>> op = dpf.operators.math.scale()

>>> # Make input connections
>>> my_field = dpf.Field()
>>> op.inputs.field.connect(my_field)
>>> my_weights = float()
>>> op.inputs.weights.connect(my_weights)
>>> my_boolean = bool()
>>> op.inputs.boolean.connect(my_boolean)
>>> my_algorithm = int()
>>> op.inputs.algorithm.connect(my_algorithm)

>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.math.scale(
...     field=my_field,
...     weights=my_weights,
...     boolean=my_boolean,
...     algorithm=my_algorithm,
... )

>>> # Get output data
>>> result_field = op.outputs.field()

Overview

Methods

connect	Connect an input on the operator using a pin number.
connect_operator_as_input	Connect an operator as an input on a pin.
get_output	Retrieve the output of the operator on the pin number.
run	Evaluate this operator.
eval	Evaluate this operator.

Properties

inputs	Enables to connect inputs to the operator
outputs	Enables to get outputs of the operator by evaluating it
progress_bar	Enable or disable progress bar display when requesting the operator’s output.
config	Copy of the operator’s current configuration.
id	Retrieve the unique identifier of the operator.
specification	Returns the Specification (or documentation) of this Operator.

Attributes

name

Static methods

default_config	Returns the default config of the operator.
operator_specification	Documents an Operator with its description (what the Operator does),its inputs and outputs and some properties.

Special methods

__del__	Delete this instance.
__str__	Describe the entity.
__add__	Add two fields or two fields containers.
__sub__	Subtract two fields or two fields containers.
__pow__	Raise each element of a field or a fields container to power 2.
__mul__	Multiply two fields or two fields containers.
__truediv__	Perform division with another operator or a scalar.

Import detail

from ansys.dpf.core.operators.math.scale import scale

Property detail

property scale.inputs: InputsScale

Enables to connect inputs to the operator

Returns:

An instance of InputsScale.

Return type:

inputs

property scale.outputs: OutputsScale

Enables to get outputs of the operator by evaluating it

Returns:

An instance of OutputsScale.

Return type:

outputs

property scale.progress_bar: bool

Enable or disable progress bar display when requesting the operator’s output.

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

property scale.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

property scale.id: int

Retrieve the unique identifier of the operator.

This property returns the unique ID associated with the operator. This property is lazily initialized.

Returns:

The unique identifier of the operator.

Return type:

int

Notes

Property available with server’s version starting at 10.0.

property scale.specification

Returns the Specification (or documentation) of this Operator.

Return type:

Specification

Attribute detail

scale.name = None

Method detail

static scale.default_config(server: ansys.dpf.core.server_types.AnyServerType = None) → ansys.dpf.core.config.Config

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 with channel connected to the remote or local instance. When None, attempts to use the global server.

Returns:

A new Config instance equivalent to the default config for this operator.

Return type:

config

scale.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 ]]...

scale.connect_operator_as_input(pin, op)

Connect an operator as an input on a pin.

Parameters:

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

• op (ansys.dpf.core.dpf_operator.Operator) – Requested type of the output. The default is None.

scale.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

scale.__del__()

Delete this instance.

scale.__str__()

Describe the entity.

Returns:

Description of the entity.

Return type:

str

scale.run()

Evaluate this operator.

scale.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()

scale.__add__(fields_b)

Add two fields or two fields containers.

Returns:

add

Return type:

operators.math.add_fc

scale.__sub__(fields_b)

Subtract two fields or two fields containers.

Returns:

minus

Return type:

operators.math.minus_fc

scale.__pow__(value)

Raise each element of a field or a fields container to power 2.

scale.__mul__(value)

Multiply two fields or two fields containers.

Returns:

mul

Return type:

operators.math.generalized_inner_product_fc

static scale.operator_specification(op_name, server=None)

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

scale.__truediv__(inpt)

Perform division with another operator or a scalar.

This method allows the use of the division operator (/) between an Operator instance and either another Operator or a scalar value (float).