/**
 * LiXX Cell Pack Matcher - Web Worker
 * 
 * Runs matching algorithms in a background thread to keep the UI responsive.
 * Communicates with the main thread via postMessage.
 */

// =============================================================================
// Utility Functions
// =============================================================================

/**
 * Calculate the coefficient of variation (CV) as a percentage.
 */
function coefficientOfVariation(values) {
    if (!values || values.length === 0) return 0;
    const mean = values.reduce((a, b) => a + b, 0) / values.length;
    if (mean === 0) return 0;
    const variance = values.reduce((acc, val) => acc + Math.pow(val - mean, 2), 0) / values.length;
    return (Math.sqrt(variance) / mean) * 100;
}

/**
 * Shuffle array in place using Fisher-Yates algorithm.
 */
function shuffleArray(array) {
    for (let i = array.length - 1; i > 0; i--) {
        const j = Math.floor(Math.random() * (i + 1));
        [array[i], array[j]] = [array[j], array[i]];
    }
    return array;
}

/**
 * Deep clone an array of arrays.
 */
function cloneConfiguration(arr) {
    return arr.map(group => [...group]);
}

/**
 * Shuffle cells based on random
 */
function shuffleCells(cells) {
    const shuffled = [...cells];

    for (let i = shuffled.length - 1; i > 0; i--) {
        const j = Math.floor(Math.random() * (i + 1));
        [shuffled[i], shuffled[j]] = [shuffled[j], shuffled[i]];
    }

    return shuffled;
}

// =============================================================================
// Scoring Functions
// =============================================================================

/**
 * Calculate the match score for a pack configuration.
 * Lower score = better match.
 */
function calculateScore(configuration, capacityWeight = 0.7, irWeight = 0.3) {
    const groupCapacities = configuration.map(group =>
        group.reduce((sum, cell) => sum + cell.capacity, 0)
    );

    const groupIRs = configuration.map(group => {
        const irsWithValues = group.filter(cell => cell.ir !== null && cell.ir !== undefined);
        if (irsWithValues.length === 0) return null;
        return irsWithValues.reduce((sum, cell) => sum + cell.ir, 0) / irsWithValues.length;
    }).filter(ir => ir !== null);

    const withinGroupIRVariances = configuration.map(group => {
        const irsWithValues = group.filter(cell => cell.ir !== null && cell.ir !== undefined);
        if (irsWithValues.length < 2) return 0;
        const irs = irsWithValues.map(cell => cell.ir);
        return coefficientOfVariation(irs);
    });

    const capacityCV = coefficientOfVariation(groupCapacities);
    const avgWithinGroupIRCV = withinGroupIRVariances.length > 0
        ? withinGroupIRVariances.reduce((a, b) => a + b, 0) / withinGroupIRVariances.length
        : 0;

    const score = (capacityWeight * capacityCV) + (irWeight * avgWithinGroupIRCV);

    return {
        score,
        capacityCV,
        irCV: avgWithinGroupIRCV,
        groupCapacities,
        groupIRs,
        withinGroupIRVariances
    };
}

// =============================================================================
// Statistics Tracker
// =============================================================================

class StatsTracker {
    constructor() {
        this.startTime = Date.now();
        this.lastProgressTime = this.startTime;
        this.lastProgressIteration = 0;
        this.speedHistory = [];
        this.windowSize = 5; // Rolling window for speed averaging
        this.lastEta = null;
        this.lastEtaUpdate = 0;
    }

    getStats(currentIteration, maxIterations) {
        const now = Date.now();
        const elapsedTime = now - this.startTime;

        // Calculate speed based on iterations since last progress update
        const iterationsDelta = currentIteration - this.lastProgressIteration;
        const timeDelta = now - this.lastProgressTime;

        if (timeDelta > 0 && iterationsDelta > 0) {
            const currentSpeed = (iterationsDelta / timeDelta) * 1000; // iterations per second
            this.speedHistory.push(currentSpeed);
            if (this.speedHistory.length > this.windowSize) {
                this.speedHistory.shift();
            }
        }

        this.lastProgressTime = now;
        this.lastProgressIteration = currentIteration;

        // Average speed from history
        const avgSpeed = this.speedHistory.length > 0
            ? this.speedHistory.reduce((a, b) => a + b, 0) / this.speedHistory.length
            : 0;

        const remainingIterations = maxIterations - currentIteration;
        const eta = avgSpeed > 0 ? (remainingIterations / avgSpeed) * 1000 : 0;

        // Only update ETA every 500ms to avoid flickering
        if (now - this.lastEtaUpdate > 500 || this.lastEta === null) {
            this.lastEta = eta;
            this.lastEtaUpdate = now;
        }

        return {
            elapsedTime,
            eta: this.lastEta,
            iterationsPerSecond: avgSpeed
        };
    }
}

// =============================================================================
// Exhaustive Search
// =============================================================================

class ExhaustiveSearch {
    constructor(cells, serial, parallel, options = {}) {
        this.cells = shuffleCells(cells);
        this.serial = serial;
        this.parallel = parallel;
        this.totalCellsNeeded = serial * parallel;

        this.capacityWeight = options.capacityWeight ?? 0.7;
        this.irWeight = options.irWeight ?? 0.3;
        this.maxIterations = options.maxIterations || 100000;

        this.stopped = false;
        this.bestSolution = null;
        this.bestScore = Infinity;
        this.stats = new StatsTracker();
    }

    stop() {
        console.log("ExhaustiveSearch: stop requested")
        this.stopped = true;
    }

    *combinations(array, k) {
        if (k === 0) {
            yield [];
            return;
        }
        if (array.length < k) return;

        const [first, ...rest] = array;
        for (const combo of this.combinations(rest, k - 1)) {
            yield [first, ...combo];
        }
        yield* this.combinations(rest, k);
    }

    *generatePartitions(cells, groupSize, numGroups) {
        if (numGroups === 0) {
            yield [];
            return;
        }

        if (cells.length < groupSize * numGroups) return;

        for (const group of this.combinations(cells, groupSize)) {
            const remaining = cells.filter(c => !group.includes(c));
            for (const rest of this.generatePartitions(remaining, groupSize, numGroups - 1)) {
                yield [group, ...rest];
            }
        }
    }

    calculateTotalCombinations() {
        // Formula: C(n, k) * C(n-k, k) * ... / numGroups! for identical groups
        const n = this.cells.length;
        const k = this.parallel;
        const numGroups = this.serial;

        let total = 1;
        let remaining = n;

        for (let i = 0; i < numGroups; i++) {
            total *= this.binomial(remaining, k);
            remaining -= k;
        }

        // Divide by numGroups! if groups are interchangeable
        // (but for battery packs, position matters, so we don't divide)

        return total;
    }

    binomial(n, k) {
        if (k > n) return 0;
        if (k === 0 || k === n) return 1;

        let result = 1;
        for (let i = 0; i < k; i++) {
            result = result * (n - i) / (i + 1);
        }
        return Math.round(result);
    }

    run() {
        let iteration = 0;
        const totalCombinations = this.calculateTotalCombinations();

        const cellCombos = this.cells.length > this.totalCellsNeeded
            ? this.combinations(this.cells, this.totalCellsNeeded)
            : [[...this.cells]];

        for (const cellSubset of cellCombos) {
            if (this.stopped) {
                return this.returnBestResult(iteration, totalCombinations);
            }

            for (const partition of this.generatePartitions(cellSubset, this.parallel, this.serial)) {
                if (this.stopped) {
                    return this.returnBestResult(iteration, totalCombinations);
                }

                const scoreResult = calculateScore(partition, this.capacityWeight, this.irWeight);

                if (scoreResult.score < this.bestScore) {
                    this.bestScore = scoreResult.score;
                    this.bestSolution = { config: partition, ...scoreResult };
                }

                iteration++;

                // Check for stop every 100 iterations, but only send progress updates every 200ms
                if (iteration % 100 === 0) {
                    const now = Date.now();
                    const timeSinceLastProgress = now - this.stats.lastProgressTime;

                    if (timeSinceLastProgress >= 200) {
                        const stats = this.stats.getStats(iteration, Math.min(totalCombinations, this.maxIterations));

                        self.postMessage({
                            type: 'progress',
                            data: {
                                iteration,
                                maxIterations: Math.min(totalCombinations, this.maxIterations),
                                bestScore: this.bestScore,
                                currentBest: this.bestSolution,
                                totalCombinations,
                                evaluatedCombinations: iteration,
                                ...stats
                            }
                        });
                    }
                }

                if (iteration >= this.maxIterations) {
                    return this.returnBestResult(iteration, totalCombinations);
                }
            }
        }

        return this.returnBestResult(iteration, totalCombinations);
    }

    returnBestResult(iteration, totalCombinations) {
        if (!this.bestSolution) {
            // No solution found yet, create one from first cells
            const config = [];
            for (let i = 0; i < this.serial; i++) {
                config.push(this.cells.slice(i * this.parallel, (i + 1) * this.parallel));
            }
            const scoreResult = calculateScore(config, this.capacityWeight, this.irWeight);
            this.bestSolution = { config, ...scoreResult };
            this.bestScore = scoreResult.score;
        }

        const usedLabels = new Set(this.bestSolution.config.flat().map(c => c.label));
        const excludedCells = this.cells.filter(c => !usedLabels.has(c.label));

        // Final progress update
        const stats = this.stats.getStats(iteration, Math.min(totalCombinations, this.maxIterations));
        self.postMessage({
            type: 'progress',
            data: {
                iteration,
                maxIterations: Math.min(totalCombinations, this.maxIterations),
                bestScore: this.bestScore,
                currentBest: this.bestSolution,
                totalCombinations,
                evaluatedCombinations: iteration,
                ...stats
            }
        });

        return {
            configuration: this.bestSolution.config,
            score: this.bestScore,
            capacityCV: this.bestSolution.capacityCV,
            irCV: this.bestSolution.irCV,
            groupCapacities: this.bestSolution.groupCapacities,
            excludedCells,
            iterations: iteration,
            elapsedTime: Date.now() - this.stats.startTime
        };
    }
}

// =============================================================================
// Worker Message Handler
// =============================================================================

let currentAlgorithm = null;

self.onmessage = function (e) {
    const { type, data } = e.data;

    switch (type) {
        case 'start':
            const { cells, serial, parallel, algorithm, options } = data;

            switch (algorithm) {
                case 'exhaustive':
                    currentAlgorithm = new ExhaustiveSearch(cells, serial, parallel, options);
                    break;
            }

            try {
                const result = currentAlgorithm.run();
                self.postMessage({ type: 'complete', data: result });
            } catch (error) {
                self.postMessage({ type: 'error', data: error.message });
            }

            currentAlgorithm = null;
            break;

        case 'stop':
            console.log("Algo: Stop requested")
            if (currentAlgorithm) {
                currentAlgorithm.stop();
            }
            break;
    }
};