hpcflow.sdk.core.parameters.InputValue

class hpcflow.sdk.core.parameters.InputValue(parameter, value=None, label=None, value_class_method=None, path=None, _check_obj=True)

Bases: AbstractInputValue, ValuesMixin

An input value to a task.

Parameters:

• parameter (Parameter | SchemaInput | str) – Parameter whose value is to be specified.

• label (str) – Optional identifier to be used where the associated SchemaInput accepts multiple parameters of the specified type. This will be cast to a string.

• value (Any) – The input parameter value.

• value_class_method (How to obtain the real value.) – A class method that can be invoked with the value attribute as keyword arguments.

• path (str) – Dot-delimited path within the parameter’s nested data structure for which value should be set.

• _check_obj (bool)

Methods

from_file	Generate a value from a NumPy range.
from_geometric_space	Generate a value from a NumPy geometric space.
from_json_like	Make an instance of this class from JSON (or YAML) data.
from_linear_space	Generate a value from a NumPy linear space.
from_log_normal	Generate a value from a log-normal random number generator.
from_log_space	Generate a value from a NumPy geometric space.
from_normal	Generate a value from a normal (Gaussian) random number generator.
from_random_uniform	Generate a value from a uniform random number generator.
from_range	Generate a value from a NumPy range.
from_rectangle	Generate a value from a sequence of coordinates to cover the perimeter of a rectangle.
from_uniform	Generate a value from a uniform random number generator.
make_persistent	Save value to a persistent workflow.
to_dict	Serialize this object as a dictionary.
to_json_like	Serialize this object as an object structure that can be trivially converted to JSON.

Attributes

is_sub_value	True if the value is for a sub part of the parameter (i.e. if path is set).
labelled_type	The labelled type of this input value.
normalised_inputs_path	The normalised input path without the inputs. prefix.
normalised_path	The full normalised input path.
value	The value itself.
workflow	The workflow containing this input value.
parameter	Parameter whose value is to be specified.
label	Identifier to be used where the associated SchemaInput accepts multiple parameters of the specified type.
path	Dot-delimited path within the parameter's nested data structure for which value should be set.
value_class_method	A class method that can be invoked with the value attribute as keyword arguments.

classmethod from_file(parameter, file_path, path=None, label=None, **kwargs)

Generate a value from a NumPy range.

Parameters:

• parameter (Parameter | SchemaInput | str)

• file_path (str | Path)

• path (str | None)

• label (str | int | None)

Return type:

Self

classmethod from_geometric_space(parameter, start, stop, num, endpoint=True, path=None, label=None, **kwargs)

Generate a value from a NumPy geometric space.

Parameters:

• parameter (Parameter | SchemaInput | str)

• start (float)

• stop (float)

• num (int)

• path (str | None)

• label (str | int | None)

Return type:

Self

classmethod from_json_like(json_like, shared_data=None)

Make an instance of this class from JSON (or YAML) data.

Parameters:

• json_like – The data to deserialise.

• shared_data – Shared context data.

Return type:

The deserialised object.

classmethod from_linear_space(parameter, start, stop, num, path=None, label=None, **kwargs)

Generate a value from a NumPy linear space.

Parameters:

• parameter (Parameter | SchemaInput | str)

• start (float)

• stop (float)

• num (int)

• path (str | None)

• label (str | int | None)

Return type:

Self

classmethod from_log_normal(parameter, mean=0.0, sigma=1.0, shape=None, seed=None, path=None, label=None, **kwargs)

Generate a value from a log-normal random number generator.

Parameters:

• parameter (Parameter | SchemaInput | str)

• mean (float)

• sigma (float)

• shape (int | Sequence[int] | None)

• seed (int | list[int] | None)

• path (str | None)

• label (str | int | None)

Return type:

Self

classmethod from_log_space(parameter, start, stop, num, base=10.0, endpoint=True, path=None, label=None, **kwargs)

Generate a value from a NumPy geometric space.

Parameters:

• parameter (Parameter | SchemaInput | str)

• start (float)

• stop (float)

• num (int)

• path (str | None)

• label (str | int | None)

Return type:

Self

classmethod from_normal(parameter, loc=0.0, scale=1.0, shape=None, seed=None, path=None, label=None, **kwargs)

Generate a value from a normal (Gaussian) random number generator.

Parameters:

• parameter (Parameter | SchemaInput | str)

• loc (float)

• scale (float)

• shape (int | Sequence[int] | None)

• seed (int | list[int] | None)

• path (str | None)

• label (str | int | None)

Return type:

Self

classmethod from_random_uniform(parameter, num, low=0.0, high=1.0, seed=None, path=None, label=None, **kwargs)

Generate a value from a uniform random number generator.

Parameters:

• parameter (Parameter | SchemaInput | str)

• num (int)

• low (float)

• high (float)

• seed (int | list[int] | None)

• path (str | None)

• label (str | int | None)

Return type:

Self

classmethod from_range(parameter, start, stop, step=1, path=None, label=None, **kwargs)

Generate a value from a NumPy range.

Parameters:

• parameter (Parameter | SchemaInput | str)

• start (float)

• stop (float)

• step (int | float)

• path (str | None)

• label (str | int | None)

Return type:

Self

classmethod from_rectangle(parameter, start, stop, num, coord=None, include=None, path=None, label=None, **kwargs)

Generate a value from a sequence of coordinates to cover the perimeter of a rectangle.

Parameters:

• coord (int | None) – Which coordinate to use. Either 0, 1, or None, meaning each value will be both coordinates.

• include (list[str] | None) – If specified, include only the specified edges. Choose from “top”, “right”, “bottom”, “left”.

• parameter (Parameter | SchemaInput | str)

• start (Sequence[float])

• stop (Sequence[float])

• num (Sequence[int])

• path (str | None)

• label (str | int | None)

Return type:

Self

classmethod from_uniform(parameter, low=0.0, high=1.0, shape=None, seed=None, path=None, label=None, **kwargs)

Generate a value from a uniform random number generator.

Parameters:

• parameter (Parameter | SchemaInput | str)

• low (float)

• high (float)

• shape (int | Sequence[int] | None)

• seed (int | list[int] | None)

• path (str | None)

• label (str | int | None)

Return type:

Self

property is_sub_value: bool

True if the value is for a sub part of the parameter (i.e. if path is set). Sub-values are not added to the base parameter data, but are interpreted as single-value sequences.

label

Identifier to be used where the associated SchemaInput accepts multiple parameters of the specified type.

property labelled_type: str

The labelled type of this input value.

make_persistent(workflow, source)

Save value to a persistent workflow.

Returns:

• str – Normalised path for this task input.

• list[int | list[int]] – The index of the parameter data Zarr group where the data is stored.

• bool – Whether this is newly persistent.

Parameters:

• workflow (Workflow)

• source (ParamSource)

Return type:

tuple[str, list[int | list[int]], bool]

property normalised_inputs_path: str

The normalised input path without the inputs. prefix.

property normalised_path: str

The full normalised input path.

parameter

Parameter whose value is to be specified.

path

Dot-delimited path within the parameter’s nested data structure for which value should be set.

to_dict()

Serialize this object as a dictionary.

Return type:

dict[str, Any]

to_json_like(dct=None, shared_data=None, exclude=(), path=None)

Serialize this object as an object structure that can be trivially converted to JSON. Note that YAML can also be produced from the result of this method; it just requires a different final serialization step.

Parameters:

• dct (dict[str, JSONable] | None)

• shared_data (_JSONDeserState)

• exclude (Container[str | None])

• path (list | None)

Return type:

tuple[JSONDocument, _JSONDeserState]

property value: Any

The value itself.

value_class_method

A class method that can be invoked with the value attribute as keyword arguments.

property workflow: Workflow | None

The workflow containing this input value.