monte_carlo_analysis.strategies package¶

Submodules¶

monte_carlo_analysis.strategies.AverageSingleDistributionStrategy module¶

Author : Robin Camarasa

Institution : Erasmus Medical Center

Position : PhD student

Contact : r.camarasa@erasmusmc.nl

Date : 2020-10-16

Project : monte_carlo_analysis

Implement AverageSingleDistributionStrategy class

class monte_carlo_analysis.strategies.AverageSingleDistributionStrategy.AverageSingleDistributionStrategy(uncertainty_metric: monte_carlo_analysis.uncertainty_metrics.UncertaintyMetric.UncertaintyMetric)[source]¶

Bases: monte_carlo_analysis.strategies.Strategy.Strategy

static transformation(uncertainty_metric_transformation: callable, ensemble_output: numpy.array, counter: list) → numpy.array[source]¶

monte_carlo_analysis.strategies.ClassWiseDistributionStrategy module¶

Author : Robin Camarasa

Institution : Erasmus Medical Center

Position : PhD student

Contact : r.camarasa@erasmusmc.nl

Date : 2020-10-29

Project : monte_carlo_analysis

Implement ClassWiseDistributionStrategy class

class monte_carlo_analysis.strategies.ClassWiseDistributionStrategy.ClassWiseDistributionStrategy(uncertainty_metric: monte_carlo_analysis.uncertainty_metrics.UncertaintyMetric.UncertaintyMetric)[source]¶

Bases: monte_carlo_analysis.strategies.Strategy.Strategy

static transformation(uncertainty_metric_transformation: callable, ensemble_output: numpy.array, counter: list) → numpy.array[source]¶

Compute the strategy

Parameters

ensemble_output – Ensemble error

monte_carlo_analysis.strategies.ClassWiseStrategy module¶

Author : Robin Camarasa

Institution : Erasmus Medical Center

Position : PhD student

Contact : r.camarasa@erasmusmc.nl

Date : 2020-10-29

Project : monte_carlo_analysis

Implement ClassWiseStrategy class

class monte_carlo_analysis.strategies.ClassWiseStrategy.ClassWiseStrategy(uncertainty_metric: monte_carlo_analysis.uncertainty_metrics.UncertaintyMetric.UncertaintyMetric)[source]¶

Bases: monte_carlo_analysis.strategies.Strategy.Strategy

static transformation(uncertainty_metric_transformation: callable, ensemble_output: numpy.array, counter: list) → numpy.array[source]¶

monte_carlo_analysis.strategies.MultipleDistributionsStrategy module¶

Author : Robin Camarasa

Institution : Erasmus Medical Center

Position : PhD student

Contact : r.camarasa@erasmusmc.nl

Date : 2020-10-16

Project : monte_carlo_analysis

Implement MultipleDistributionsStrategy class

class monte_carlo_analysis.strategies.MultipleDistributionsStrategy.MultipleDistributionsStrategy(uncertainty_metric: monte_carlo_analysis.uncertainty_metrics.UncertaintyMetric.UncertaintyMetric)[source]¶

Bases: monte_carlo_analysis.strategies.Strategy.Strategy

static transformation(uncertainty_metric_transformation: callable, ensemble_output: numpy.array, counter: list) → numpy.array[source]¶

Compute the strategy

Parameters

ensemble_output – Ensemble error

monte_carlo_analysis.strategies.OneVersusAllStrategy module¶

Author : Robin Camarasa

Institution : Erasmus Medical Center

Position : PhD student

Contact : r.camarasa@erasmusmc.nl

Date : 2020-10-29

Project : monte_carlo_analysis

Implement OneVersusAllStrategy class

class monte_carlo_analysis.strategies.OneVersusAllStrategy.OneVersusAllStrategy(uncertainty_metric: monte_carlo_analysis.uncertainty_metrics.UncertaintyMetric.UncertaintyMetric)[source]¶

Bases: monte_carlo_analysis.strategies.Strategy.Strategy

static transformation(uncertainty_metric_transformation: callable, ensemble_output: numpy.array, counter: list) → numpy.array[source]¶

monte_carlo_analysis.strategies.Strategy module¶

Author : Robin Camarasa

Institution : Erasmus Medical Center

Position : PhD student

Contact : r.camarasa@erasmusmc.nl

Date : 2020-09-29

Project : monte_carlo_analysis

Implement abstract class Strategy

class monte_carlo_analysis.strategies.Strategy.Strategy(uncertainty_metric: monte_carlo_analysis.uncertainty_metrics.UncertaintyMetric.UncertaintyMetric)[source]¶

Bases: object

Abstract class that implement the uncertainty_metric

Parameters

name – Name of the strategy

static transformation(uncertainty_metric, ensemble_output, counter)[source]¶

monte_carlo_analysis.strategies.TopDistributionsSimilarityStrategy module¶

Author : Robin Camarasa

Institution : Erasmus Medical Center

Position : PhD student

Contact : r.camarasa@erasmusmc.nl

Date : 2020-10-16

Project : monte_carlo_analysis

Implement TopDistributionsSimilarityStrategy class

class monte_carlo_analysis.strategies.TopDistributionsSimilarityStrategy.TopDistributionsSimilarityStrategy(uncertainty_metric: monte_carlo_analysis.uncertainty_metrics.UncertaintyMetric.UncertaintyMetric)[source]¶

Bases: monte_carlo_analysis.strategies.Strategy.Strategy

static transformation(uncertainty_metric_transformation: callable, ensemble_output: numpy.array, counter: list) → numpy.array[source]¶

Compute the strategy

Parameters

ensemble_output – Ensemble error

monte_carlo_analysis.strategies.TopSingleDistributionStrategy module¶

Author : Robin Camarasa

Institution : Erasmus Medical Center

Position : PhD student

Contact : r.camarasa@erasmusmc.nl

Date : 2020-10-15

Project : monte_carlo_analysis

Implement TopSingleDistributionStrategy class

class monte_carlo_analysis.strategies.TopSingleDistributionStrategy.TopSingleDistributionStrategy(uncertainty_metric: monte_carlo_analysis.uncertainty_metrics.UncertaintyMetric.UncertaintyMetric)[source]¶

Bases: monte_carlo_analysis.strategies.Strategy.Strategy

static transformation(uncertainty_metric_transformation: callable, ensemble_output: numpy.array, counter: list) → numpy.array[source]¶

Compute the strategy

Parameters

ensemble_output – Ensemble error

Module contents¶

Author : Robin Camarasa

Institution : Erasmus Medical Center

Position : PhD student

Contact : r.camarasa@erasmusmc.nl

Date : 2020-09-29

Project : monte_carlo_analysis

Module that contains the strategies