modeci_mdf.execution_engine.EvaluableParameter

class modeci_mdf.execution_engine.EvaluableParameter(parameter: Parameter, verbose: bool = False)[source]

Bases: object

Evaluates the current value of a Parameter during the MDF graph execution.

Parameters:

parameter – The parameter to evaluate during execution.
verbose – Whether to print output of parameter calculations.

Methods

`evaluate`(parameters[, time_increment, ...])	Evaluate the parameter and store the result in the `curr_value` attribute.
`get_current_value`(parameters[, array_format])	Get the current value of the parameter; evaluates the expression if the current value has not yet been set.

get_current_value(parameters: Dict[str, Any], array_format: str = 'numpy') → Any[source]

Get the current value of the parameter; evaluates the expression if the current value has not yet been set. Note: this is different from 'evaluate', as calling that method multiple times can change the state of the parameter, but calling this should not reevaluate the parameter if it has a current value.

Parameters:

parameters – a dictionary of parameters and their values that may or may not be needed to evaluate this parameter.
array_format – The array format to use (either 'numpy' or tensorflow').

Returns:

The evaluated value of the parameter.

evaluate(parameters: Dict[str, Any], time_increment: float | None = None, array_format: str = 'numpy') → Any[source]

Evaluate the parameter and store the result in the curr_value attribute.

Parameters:

parameters – a dictionary of parameters and their values that may or may not be needed to evaluate this parameter.
time_increment – a floating point value specifying the timestep size, only used for time_derivative parameters
array_format – The array format to use (either 'numpy' or tensorflow').

Returns:

The current value of the parameter.