releso.shape_parameterization.VariableLocation

class releso.shape_parameterization.VariableLocation(*, save_location: Path, logger_name: str | None = None, current_position: float, min_value: float | None = None, max_value: float | None = None, n_steps: ConstrainedIntValue | None = 10, step: float | None = None)

Bases: BaseModel

Variable location class.

Object of this class defines the position and movement possibilities for a single dimensions of a single control point of the geometry.

__init__(**data: Any) → None: Constructor for VariableLocation.

Methods

`apply_continuous_action`(value)	Apply a continuous action the variable.
`apply_discrete_action`(increasing)	Apply a discrete action to the variable.
`convert_to_pathlib_add_datetime`(v)	Add timestamp to save_location, of applicable.
`define_step`(values)	Validator for class.
`get_logger`()	Gets the currently defined environment logger.
`is_action`()	Boolean if variable defines an action.
`reset`()	Resets the current_location to the initial position.
`set_logger_name_recursively`(logger_name)	Set the logger_name variable for all child elements.
`set_variable_to_current_position_if_not_given`(v, ...)	Validator for min_value and max_value.

Attributes

`current_position`	coordinate of the current position of the current control point in the dimension
`min_value`	lower bound of possible values which can be reached by this variable
`max_value`	upper bound of possible values which can be reached by this variable
`n_steps`	number of steps the value range is divided into used to define the step if not given.
`step`	If discrete actions are used the step is used to define the new current position by adding/subtracting it from the current position.
`save_location`	Definition of the save location of the logs and validation results.
`logger_name`	name of the logger.

apply_continuous_action(value: float) → float

Apply a continuous action the variable.

Apply the zero-mean normalized value as the new current position. Needs to descale the value first. Also applies clipping.

Parameters:

value (float) – Scaled value [-1,1] that needs to be descaled and
position. (applied as the new current)

Returns:

New clipped value.

Return type:

float

apply_discrete_action(increasing: bool) → float

Apply a discrete action to the variable.

Apply the a discrete action to the current value. If resulting value would be outside of the min and max value range no step is taken.

Parameters:

increasing (bool) – Toggle whether or not the value should increase
not. (or)

Returns:

Value of the position that the current position is now at.

Return type:

float

current_position: float: coordinate of the current position of the current control point in the dimension

classmethod define_step(values: Dict[str, Any]) → Dict[str, Any]

Validator for class.

Validation function that defines the step taken if the action would be discrete. If nothing is given for the calculation a n_steps default value of 10 is used.

Parameters:: values (Dict[str, Any]) – Validated variables of the object.
Returns:: Validated variables but if steps was not given before now it has a value.
Return type:: Dict[str, Any]

is_action() → bool

Boolean if variable defines an action.

Checks if the variable has variability. Meaning is there optimization between the min_value and the max_value.

Returns:: True if (self.max_value > self.current_position) or (self.min_value < self.current_position)
Return type:: bool

max_value: float | None: upper bound of possible values which can be reached by this variable

min_value: float | None: lower bound of possible values which can be reached by this variable

n_steps: ConstrainedIntValue | None: number of steps the value range is divided into used to define the step if not given.

reset() → None: Resets the current_location to the initial position.

classmethod set_variable_to_current_position_if_not_given(v, values, field) → float

Validator for min_value and max_value.

Validation of the min and max values for the current VariableLocation. If non are set no variability is assumed min = max = current_position

Parameters:

v ([type]) – Value to validate.
values ([type]) – Already validated values.
field ([type]) – Name of the field that is currently validated.

Raises:

ParserException – Parser error if current_position is not already
validated. –

Returns:

value of the validated value.

Return type:

float

step: float | None: If discrete actions are used the step is used to define the new current position by adding/subtracting it from the current position.