function splitRow(line) {
    return line.split(/[;,\t]/).map((value) => value.trim());
}

function isNumeric(value) {
    return value !== '' && Number.isFinite(Number(value));
}

function detectHeader(rows) {
    if (rows.length === 0) {
        return { hasHeader: false, headers: [] };
    }

    const [firstRow] = rows;
    const hasHeader = firstRow.some((value) => !isNumeric(value));
    return {
        hasHeader,
        headers: hasHeader ? firstRow.map((value) => value.toLowerCase()) : [],
    };
}

function detectTimeScale(headers) {
    const timeHeader = headers.find((header) => header.includes('time') || header.includes('timestamp'));
    if (!timeHeader) {
        return 1;
    }

    if (timeHeader.includes('sec') && !timeHeader.includes('msec') && !timeHeader.includes('ms')) {
        return 1000;
    }

    return 1;
}

function detectColumnIndexes(headers, columnCount) {
    if (headers.length === 0) {
        return {
            timeIndex: columnCount > 1 ? 0 : -1,
            valueIndex: columnCount > 1 ? 1 : 0,
        };
    }

    const timeIndex = headers.findIndex((header) => header.includes('time') || header.includes('timestamp'));
    const valueIndex = headers.findIndex((header) => header.includes('value') || header.includes('signal') || header.includes('y'));

    return {
        timeIndex,
        valueIndex: valueIndex >= 0 ? valueIndex : (headers.length > 1 ? 1 : 0),
    };
}

export function parseReplayCsv(text, { sampleRateHz = 60 } = {}) {
    const rows = text
        .split(/\r?\n/)
        .map((line) => line.trim())
        .filter((line) => line && !line.startsWith('#'))
        .map(splitRow)
        .filter((row) => row.some((value) => value !== ''));

    if (rows.length === 0) {
        throw new Error('CSV file is empty');
    }

    const { hasHeader, headers } = detectHeader(rows);
    const dataRows = hasHeader ? rows.slice(1) : rows;
    const columnCount = rows[0].length;
    const { timeIndex, valueIndex } = detectColumnIndexes(headers, columnCount);
    const timeScale = detectTimeScale(headers);
    const intervalMs = 1000 / Math.max(1, sampleRateHz);

    const points = dataRows
        .map((row, index) => {
            const rawValue = row[valueIndex];
            if (!isNumeric(rawValue)) {
                return null;
            }

            const parsedValue = Number(rawValue);
            const parsedTime = timeIndex >= 0 && isNumeric(row[timeIndex])
                ? Number(row[timeIndex]) * timeScale
                : index * intervalMs;

            return {
                timeMs: parsedTime,
                value: parsedValue,
            };
        })
        .filter(Boolean)
        .sort((left, right) => left.timeMs - right.timeMs);

    if (points.length === 0) {
        throw new Error('CSV file did not contain any numeric data points');
    }

    const firstTime = points[0].timeMs;
    const normalizedPoints = points.map((point) => ({
        timeMs: point.timeMs - firstTime,
        value: point.value,
    }));

    return {
        points: normalizedPoints,
        metadata: {
            pointCount: normalizedPoints.length,
            durationMs: normalizedPoints.at(-1)?.timeMs ?? 0,
        },
    };
}