genetic-search/es/stats.js

Multiprocessing genetic algorithm implementation library

import { zip } from "./itertools";
import { arraySum, calcRangeStatSummary, calcStatSummary, createEmptyGroupedStatSummary, createEmptyRangeStatSummary, createEmptyStatSummary, fullCopyObject, roundGroupedStatSummary, roundRangeStatSummary, roundStatSummary, } from "./utils";
/**
 * A manager for the statistics of a population of genomes.
 *
 * This class implements the [[GenomeStatsManagerInterface]] interface.
 *
 * @category Statistics
 */
export class GenomeStatsManager {
    init(population, origin) {
        for (const genome of population) {
            this.initItem(genome, origin);
        }
    }
    update(population, phenomeMatrix, fitnessColumn) {
        for (const [genome, phenome, fitness] of zip(population, phenomeMatrix, fitnessColumn)) {
            this.updateItem(genome, phenome, fitness);
        }
    }
    initItem(genome, origin, parents = []) {
        if (genome.stats !== undefined) {
            return genome.stats;
        }
        genome.stats = {
            fitness: 0,
            age: 0,
            phenome: [],
            origin,
            originCounters: {
                crossover: arraySum(parents.map((p) => { var _a, _b, _c; return (_c = (_b = (_a = p.stats) === null || _a === void 0 ? void 0 : _a.originCounters) === null || _b === void 0 ? void 0 : _b.crossover) !== null && _c !== void 0 ? _c : 0; })) + Number(origin === 'crossover'),
                mutation: arraySum(parents.map((p) => { var _a, _b, _c; return (_c = (_b = (_a = p.stats) === null || _a === void 0 ? void 0 : _a.originCounters) === null || _b === void 0 ? void 0 : _b.mutation) !== null && _c !== void 0 ? _c : 0; })) + Number(origin === 'mutation'),
            },
            parentIds: parents.map((p) => p.id),
        };
        return genome.stats;
    }
    /**
     * Updates the statistics of a genome.
     *
     * @param genome The genome to update.
     * @param phenome The phenome of the genome.
     * @param fitness The fitness of the genome.
     *
     * @returns The updated genome statistics.
     */
    updateItem(genome, phenome, fitness) {
        const stats = this.initItem(genome, 'initial');
        stats.age++;
        stats.fitness = fitness;
        stats.phenome = phenome;
        return stats;
    }
}
/**
 * A manager for the population summary.
 *
 * This class implements the [[PopulationSummaryManagerInterface]] interface.
 * It is used to manage the population summary, which is a summary of the
 * statistics of a population of genomes.
 *
 * @category Statistics
 */
export class PopulationSummaryManager {
    /**
     * Constructs a new population summary manager.
     */
    constructor() {
        /**
         * The number of generations since the best genome has changed.
         */
        this.stagnationCounter = 0;
        this.fitnessSummary = createEmptyStatSummary();
        this.groupedFitnessSummary = createEmptyGroupedStatSummary();
        this.ageSummary = createEmptyRangeStatSummary();
    }
    get() {
        return {
            fitnessSummary: fullCopyObject(this.fitnessSummary),
            groupedFitnessSummary: fullCopyObject(this.groupedFitnessSummary),
            ageSummary: fullCopyObject(this.ageSummary),
            stagnationCounter: this.stagnationCounter,
        };
    }
    getRounded(precision) {
        return {
            fitnessSummary: roundStatSummary(this.fitnessSummary, precision),
            groupedFitnessSummary: roundGroupedStatSummary(this.groupedFitnessSummary, precision),
            ageSummary: roundRangeStatSummary(this.ageSummary, precision),
            stagnationCounter: this.stagnationCounter,
        };
    }
    update(sortedPopulation) {
        var _a;
        const bestGenomeId = (_a = sortedPopulation[0]) === null || _a === void 0 ? void 0 : _a.id;
        if (this.bestGenomeId !== bestGenomeId) {
            this.bestGenomeId = bestGenomeId;
            this.stagnationCounter = 0;
        }
        else {
            this.stagnationCounter++;
        }
        const statsCollection = sortedPopulation
            .filter((genome) => genome.stats !== undefined)
            .map((genome) => genome.stats);
        this.updateSummary(statsCollection);
        this.updateGroupedSummary(statsCollection);
        this.updateAgeSummary(statsCollection);
    }
    /**
     * Updates the summary of the population.
     *
     * @param sortedStatsCollection The sorted collection of genome statistics.
     */
    updateSummary(sortedStatsCollection) {
        this.fitnessSummary = calcStatSummary(sortedStatsCollection.map((stats) => stats.fitness));
    }
    /**
     * Updates the grouped summary of the population.
     *
     * @param sortedStatsCollection The sorted collection of genome statistics.
     */
    updateGroupedSummary(sortedStatsCollection) {
        const initialCollection = sortedStatsCollection.filter((stats) => stats.origin === 'initial');
        const crossoverCollection = sortedStatsCollection.filter((stats) => stats.origin === 'crossover');
        const mutationCollection = sortedStatsCollection.filter((stats) => stats.origin === 'mutation');
        this.groupedFitnessSummary = {
            initial: calcStatSummary(initialCollection.map((stats) => stats.fitness)),
            crossover: calcStatSummary(crossoverCollection.map((stats) => stats.fitness)),
            mutation: calcStatSummary(mutationCollection.map((stats) => stats.fitness)),
        };
    }
    /**
     * Updates the summary of the age of the population.
     *
     * @param sortedStatsCollection The sorted collection of genome statistics.
     */
    updateAgeSummary(sortedStatsCollection) {
        const ageCollection = sortedStatsCollection.map((stats) => stats.age);
        this.ageSummary = calcRangeStatSummary(ageCollection);
    }
}
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