Documentation for Policy Evaluation Metrics

src.pcgym.evaluation_metrics.reproducibility_metric

Bases: metric_base

Class for calculating reproducibility metrics.

__init__(dispersion, performance, scalarised_weight)

Initialize the reproducibility metric.

Parameters:

Name	Type	Description	Default
dispersion	str	The dispersion metric to use ('std' or 'mad').	required
performance	str	The performance metric to use ('mean' or 'median').	required
scalarised_weight	float	The weight for scalarised performance.	required

evaluate(policy_evaluator, component=None)

Evaluate the given policy using the specified environment.

Parameters:

Name	Type	Description	Default
policy_evaluator	Any	The policy evaluator to generate data for a number of policy rollouts.	required
component	Optional[str]	The specific component to evaluate (optional).	None

Returns:

Type	Description
Dict[str, Dict[str, ndarray]]	The evaluation metric value.

policy_dispersion_metric(data, component)

Evaluate the dispersion of the policy.

Parameters:

Name	Type	Description	Default
data	Dict[str, Dict[str, ndarray]]	Nested dictionary containing policy data.	required
component	Optional[str]	The specific component to evaluate.	required

Returns:

Type	Description
Dict[str, Dict[str, ndarray]]	The policy dispersion metric value.

policy_performance_metric(data, component)

Evaluate the performance of the policy.

Parameters:

Name	Type	Description	Default
data	Dict[str, Dict[str, ndarray]]	Nested dictionary containing policy data.	required
component	Optional[str]	The specific component to evaluate.	required

Returns:

Type	Description
Dict[str, Dict[str, ndarray]]	The policy performance metric value.

scalarised_performance(data, component)

Evaluate the scalarised performance of the policy.

Parameters:

Name	Type	Description	Default
data	Dict[str, Dict[str, ndarray]]	Nested dictionary containing policy data.	required
component	Optional[str]	The specific component to evaluate (set to None to scalarise over all components).	required

Returns:

Type	Description
Dict[str, Dict[str, ndarray]]	The scalarised policy performance metric value.

determine_op(component)

Determine the operation to be applied based on the component.

Parameters:

Name	Type	Description	Default
component	str	The component to determine the operation for.	required

Returns:

Type	Description
Callable[[ndarray], ndarray]	A lambda function representing the operation to be applied.

src.pcgym.evaluation_metrics.metric_base

Bases: ABC

Abstract base class for policy evaluation metrics.

__init__(scalarised_weight)

Initialize the metric base.

Parameters:

Name	Type	Description	Default
scalarised_weight	float	The weight for scalarised performance.	required

evaluate(policy_evaluator)

Evaluate the given policy using the specified environment.

Parameters:

Name	Type	Description	Default
policy_evaluator	Any	The policy evaluator to generate data for a number of policy rollouts.	required

Returns:

Type	Description
Any	The evaluation metric value.

policy_dispersion_metric(data)

Evaluate the dispersion of the policy.

Parameters:

Name	Type	Description	Default
data	Dict[str, Any]	Nested dictionary containing policy data.	required

Returns:

Type	Description
Any	The policy dispersion metric value.

policy_performance_metric(data)

Evaluate the performance of the policy.

Parameters:

Name	Type	Description	Default
data	Dict[str, Any]	Nested dictionary containing policy data.	required

Returns:

Type	Description
Any	The policy performance metric value.

scalarised_performance(data)

Evaluate the scalarised performance of the policy.

Parameters:

Name	Type	Description	Default
data	Dict[str, Any]	Nested dictionary containing policy data.	required

Returns:

Type	Description
Any	The scalarised policy performance metric value.

src.pcgym.evaluation_metrics.standard_deviation

Class for calculating standard deviation.

__init__(data)

Initialize the standard deviation calculator.

Parameters:

Name	Type	Description	Default
data	ndarray	Input data for standard deviation calculation.	required

get_value()

Calculate the standard deviation of the data.

Returns:

Type	Description
ndarray	The standard deviation value.

src.pcgym.evaluation_metrics.median_absolute_deviation

Class for calculating median absolute deviation.

__init__(data)

Initialize the median absolute deviation calculator.

Parameters:

Name	Type	Description	Default
data	ndarray	Input data for median absolute deviation calculation.	required

get_value()

Calculate the median absolute deviation of the data.

Returns:

Type	Description
ndarray	The median absolute deviation value.

src.pcgym.evaluation_metrics.mean_performance

Class for calculating mean performance.

__init__(data)

Initialize the mean performance calculator.

Parameters:

Name	Type	Description	Default
data	ndarray	Input data for mean performance calculation.	required

get_value()

Calculate the mean performance of the data.

Returns:

Type	Description
ndarray	The mean performance value.

src.pcgym.evaluation_metrics.median_performance

Class for calculating median performance.

__init__(data)

Initialize the median performance calculator.

Parameters:

Name	Type	Description	Default
data	ndarray	Input data for median performance calculation.	required

get_value()

Calculate the median performance of the data.

Returns:

Type	Description
ndarray	The median performance value.