cyrxnopt_analysis.metrics namespace

Submodules

cyrxnopt_analysis.metrics.Average module

class cyrxnopt_analysis.metrics.Average.Average[source]

Bases: Metric

property average_value: float

Averaged optimization iterations needed to reach a successful optimization.

Returns:: Average optimization iteration count.
Return type:: float

calculate(results: List[OptimizerResult])[source]

Calculate the metric.

Parameters:: results (List[Results]) – Results to use when calculating the metric

property total_cycles: int

Number of optimization cycle results used for calculating this metric.

Returns:: Total cycle count.
Return type:: int

property total_value: int

Total summed value of all optimization cycles’ best values.

Returns:: Sum of best values of cycles.
Return type:: int

cyrxnopt_analysis.metrics.Clearance module

class cyrxnopt_analysis.metrics.Clearance.Clearance(optimum: float, threshold: float = 0.01)[source]

Bases: Metric

calculate(results: List[OptimizerResult])[source]

Calculates the clearance rate of the collection of results.

Parameters:: results (List[Results]) – Results to use when calculating the metric

property clearance_rate: float

Success rate of the optimizer.

Returns:: Successful cycle rate out of the number of total cycles.
Return type:: float

property fail_count: int

Number of failed cycles counted.

Returns:: Number of failed cycles
Return type:: int

property failed_results: List[OptimizerResult]

List of only results that failed.

Returns:: List of failed result objects.
Return type:: List[OptimizerResult]

property success_count: int

Number of successful cycles counted.

Returns:: Number of successful cycles
Return type:: int

property successful_results: List[OptimizerResult]

List of only results that were successful.

Returns:: List of successful result objects.
Return type:: List[OptimizerResult]

cyrxnopt_analysis.metrics.FeatureVariance module

class cyrxnopt_analysis.metrics.FeatureVariance.FeatureVariance(optimum: float, threshold: float = 0.01)[source]

Bases: Metric

calculate(results: List[OptimizerResult])[source]

Calculates the clearance rate of the collection of results.

Parameters:: results (List[Results]) – Results to use when calculating the metric

property clearance_rate: float

Success rate of the optimizer.

Returns:: Successful cycle rate out of the number of total cycles.
Return type:: float

property fail_count: int

Number of failed cycles counted.

Returns:: Number of failed cycles
Return type:: int

property failed_results: List[OptimizerResult]

List of only results that failed.

Returns:: List of failed result objects.
Return type:: List[OptimizerResult]

property success_count: int

Number of successful cycles counted.

Returns:: Number of successful cycles
Return type:: int

property successful_results: List[OptimizerResult]

List of only results that were successful.

Returns:: List of successful result objects.
Return type:: List[OptimizerResult]

cyrxnopt_analysis.metrics.Metric module

class cyrxnopt_analysis.metrics.Metric.Metric[source]

Bases: ABC

calculate(results: List[OptimizerResult])[source]

Calculate the metric.

Parameters:: results (List[Results]) – Results to use when calculating the metric
Raises:: RuntimeError – This function must be overridden by chilren.

property result: Any

cyrxnopt_analysis.metrics.SolveTime module

class cyrxnopt_analysis.metrics.SolveTime.SolveTime[source]

Bases: Metric

calculate(results: List[OptimizerResult])[source]

Calculate the metric.

Parameters:: results (List[Results]) – Results to use when calculating the metric
Raises:: RuntimeError – This function must be overridden by chilren.

property solve_time: float

Averaged optimization iterations needed to reach a successful optimization.

Returns:: Average optimization iteration count.
Return type:: float

property solve_time_CI95: int

CI 95% of average optimization iterations needed to reach a successful optimization.

Returns:: CI
Return type:: float

property solve_time_std: int

Standard deviation of average optimization iterations needed to reach a successful optimization.

Returns:: Std.
Return type:: float

property total_cycles: int

Number of optimization cycle results used for calculating this metric.

Returns:: Total cycle count.
Return type:: int

property total_iterations: int

Total number of optimization iterations through all of the results used to reach the best result.

Returns:: Total iteration count.
Return type:: int

cyrxnopt_analysis.metrics.StdDev module

class cyrxnopt_analysis.metrics.StdDev.StdDev[source]

Bases: Metric

calculate(results: List[OptimizerResult])[source]

Calculate the metric.

Parameters:: results (List[Results]) – Results to use when calculating the metric

property sample_set: int

Sample set of best values to calculate Std. Dev. on.

Returns:: Sample set of best values.
Return type:: int

property stddev: float

Standard deviation of optimization iterations’ best values.

Returns:: Standard deviation of best values.
Return type:: float

property total_cycles: int

Number of optimization cycle results used for calculating this metric.

Returns:: Total cycle count.
Return type:: int