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ChangeLog.md

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Version 1.1.0

Change models

  • Compose all methods with same parameters into a single class
    • front: Evaluating all possible of all fronts (No need Reference front)
      • Ratio: Metrics Assessing the Number of Pareto Optimal Solutions in the Set
        • RNI: ratio_of_non_dominated_individuals
        • PDI: pareto_dominance_indicator (not implemented yet)
    • pfront (Pareto front): Evaluating single Pareto front (No need Reference front)
      • Distribution: Metrics Focusing on Distribution of the Solutions
        • UD = uniform_distribution
        • NDC = number_of_distinct_choices (not implemented yet)
    • tpfront (True Pareto front): Evaluating Pareto front vs Reference front
      • Ratio: Metrics Assessing the Number of Pareto Optimal Solutions in the Set
        • ER: error_ratio
        • ONVG: overall_non_dominated_vector_generation
      • Spread : Metrics Concerning Spread of the Solutions
        • MS = maximum_spread
      • Closeness: Metrics Measuring the Closeness of the Solutions to the True Pareto Front
        • GD: generational_distance
        • IGD: inverted_generational_distance
        • MPFE: maximum_pareto_front_error
      • Distribution: Metrics Focusing on Distribution of the Solutions
        • S: spacing
        • STE: spacing_to_extend
    • volume (need both Obtained front and Reference front): I kept this file since it using other library
      • HV
      • HAR

Change others

  • Examples:
    • Add all examples for all metrics
    • Add example for multiple metrics called at the same time
  • Add Change Log file
  • Add README.md file
  • Add support-data folder for test case

Version 1.0.0 (First version)

Models

root.py file: contains all need functions such as

  1. find non-dominated list function
  2. print_messages
  3. get_pareto_front_reference_front
  4. find_reference_front
  5. get_metrics_by_name
  6. get_metrics_by_list
  7. All Metric class will inherit this Root class.

Closeness: Metrics Measuring the Closeness of the Solutions to the True Pareto Front

  1. GD: generational_distance
  2. IGD: inverted_generational_distance
  3. MPFE: maximum_pareto_front_error

Closeness_diversity: Metrics Measuring the Closeness of the Solutions to the True Pareto Front

  1. HV: hyper_volume (using different library)
  2. HAR: hyper_area_ratio (using different library)

Distribution: Metrics Focusing on Distribution of the Solutions

  1. UD: uniform_distribution
  2. S: spacing
  3. STE: spacing_to_extend
  4. NDC: number_of_distinct_choices (not implemented yet)

Ratio: Metrics Assessing the Number of Pareto Optimal Solutions in the Set

  1. RNI: ratio_of_non_dominated_individuals
  2. ER: error_ratio
  3. ONVG: overall_non_dominated_vector_generation
  4. PDI: pareto_dominance_indicator (not implemented yet)

Spread: Metrics Concerning Spread of the Solutions

  1. MS: maximum_spread