'use strict'; System.register(['lodash', './utils'], function (_export, _context) { "use strict"; var _, utils, POINT_VALUE, POINT_TIMESTAMP, exportedFunctions; /** * Downsample time series by using given function (avg, min, max). */ function downsample(datapoints, time_to, ms_interval, func) { var downsampledSeries = []; var timeWindow = { from: time_to * 1000 - ms_interval, to: time_to * 1000 }; var points_sum = 0; var points_num = 0; var value_avg = 0; var frame = []; for (var i = datapoints.length - 1; i >= 0; i -= 1) { if (timeWindow.from < datapoints[i][1] && datapoints[i][1] <= timeWindow.to) { points_sum += datapoints[i][0]; points_num++; frame.push(datapoints[i][0]); } else { value_avg = points_num ? points_sum / points_num : 0; if (func === "max") { downsampledSeries.push([_.max(frame), timeWindow.to]); } else if (func === "min") { downsampledSeries.push([_.min(frame), timeWindow.to]); } // avg by default else { downsampledSeries.push([value_avg, timeWindow.to]); } // Shift time window timeWindow.to = timeWindow.from; timeWindow.from -= ms_interval; points_sum = 0; points_num = 0; frame = []; // Process point again i++; } } return downsampledSeries.reverse(); } /** * Group points by given time interval * datapoints: [[, ], ...] */ function groupBy(datapoints, interval, groupByCallback) { var ms_interval = utils.parseInterval(interval); // Calculate frame timestamps var frames = _.groupBy(datapoints, function (point) { // Calculate time for group of points return Math.floor(point[1] / ms_interval) * ms_interval; }); // frame: { '': [[, ], ...] } // return [{ '': }, { '': }, ...] var grouped = _.mapValues(frames, function (frame) { var points = _.map(frame, function (point) { return point[0]; }); return groupByCallback(points); }); // Convert points to Grafana format return sortByTime(_.map(grouped, function (value, timestamp) { return [Number(value), Number(timestamp)]; })); } function groupBy_perf(datapoints, interval, groupByCallback) { if (datapoints.length === 0) { return []; } var ms_interval = utils.parseInterval(interval); var grouped_series = []; var frame_values = []; var frame_value = void 0; var frame_ts = datapoints.length ? getPointTimeFrame(datapoints[0][POINT_TIMESTAMP], ms_interval) : 0; var point_frame_ts = frame_ts; var point = void 0; for (var i = 0; i < datapoints.length; i++) { point = datapoints[i]; point_frame_ts = getPointTimeFrame(point[POINT_TIMESTAMP], ms_interval); if (point_frame_ts === frame_ts) { frame_values.push(point[POINT_VALUE]); } else if (point_frame_ts > frame_ts) { frame_value = groupByCallback(frame_values); grouped_series.push([frame_value, frame_ts]); // Move frame window to next non-empty interval and fill empty by null frame_ts += ms_interval; while (frame_ts < point_frame_ts) { grouped_series.push([null, frame_ts]); frame_ts += ms_interval; } frame_values = [point[POINT_VALUE]]; } } frame_value = groupByCallback(frame_values); grouped_series.push([frame_value, frame_ts]); return grouped_series; } /** * Summarize set of time series into one. * @param {datapoints[]} timeseries array of time series */ function sumSeries(timeseries) { // Calculate new points for interpolation var new_timestamps = _.uniq(_.map(_.flatten(timeseries, true), function (point) { return point[1]; })); new_timestamps = _.sortBy(new_timestamps); var interpolated_timeseries = _.map(timeseries, function (series) { series = fillZeroes(series, new_timestamps); var timestamps = _.map(series, function (point) { return point[1]; }); var new_points = _.map(_.difference(new_timestamps, timestamps), function (timestamp) { return [null, timestamp]; }); var new_series = series.concat(new_points); return sortByTime(new_series); }); _.each(interpolated_timeseries, interpolateSeries); var new_timeseries = []; var sum; for (var i = new_timestamps.length - 1; i >= 0; i--) { sum = 0; for (var j = interpolated_timeseries.length - 1; j >= 0; j--) { sum += interpolated_timeseries[j][i][0]; } new_timeseries.push([sum, new_timestamps[i]]); } return sortByTime(new_timeseries); } function scale(datapoints, factor) { return _.map(datapoints, function (point) { return [point[0] * factor, point[1]]; }); } function scale_perf(datapoints, factor) { for (var i = 0; i < datapoints.length; i++) { datapoints[i] = [datapoints[i][POINT_VALUE] * factor, datapoints[i][POINT_TIMESTAMP]]; } return datapoints; } /** * Simple delta. Calculate value delta between points. * @param {*} datapoints */ function delta(datapoints) { var newSeries = []; var deltaValue = void 0; for (var i = 1; i < datapoints.length; i++) { deltaValue = datapoints[i][0] - datapoints[i - 1][0]; newSeries.push([deltaValue, datapoints[i][1]]); } return newSeries; } /** * Calculates rate per second. Resistant to counter reset. * @param {*} datapoints */ function rate(datapoints) { var newSeries = []; var point = void 0, point_prev = void 0; var valueDelta = 0; var timeDelta = 0; for (var i = 1; i < datapoints.length; i++) { point = datapoints[i]; point_prev = datapoints[i - 1]; // Convert ms to seconds timeDelta = (point[POINT_TIMESTAMP] - point_prev[POINT_TIMESTAMP]) / 1000; // Handle counter reset - use previous value if (point[POINT_VALUE] >= point_prev[POINT_VALUE]) { valueDelta = (point[POINT_VALUE] - point_prev[POINT_VALUE]) / timeDelta; } newSeries.push([valueDelta, point[POINT_TIMESTAMP]]); } return newSeries; } function simpleMovingAverage(datapoints, n) { var sma = []; var w_sum = void 0; var w_avg = null; var w_count = 0; // Initial window for (var j = n; j > 0; j--) { if (datapoints[n - j][POINT_VALUE] !== null) { w_avg += datapoints[n - j][POINT_VALUE]; w_count++; } } if (w_count > 0) { w_avg = w_avg / w_count; } else { w_avg = null; } sma.push([w_avg, datapoints[n - 1][POINT_TIMESTAMP]]); for (var i = n; i < datapoints.length; i++) { // Insert next value if (datapoints[i][POINT_VALUE] !== null) { w_sum = w_avg * w_count; w_avg = (w_sum + datapoints[i][POINT_VALUE]) / (w_count + 1); w_count++; } // Remove left side point if (datapoints[i - n][POINT_VALUE] !== null) { w_sum = w_avg * w_count; if (w_count > 1) { w_avg = (w_sum - datapoints[i - n][POINT_VALUE]) / (w_count - 1); w_count--; } else { w_avg = null; w_count = 0; } } sma.push([w_avg, datapoints[i][POINT_TIMESTAMP]]); } return sma; } function expMovingAverage(datapoints, n) { var ema = [datapoints[0]]; var ema_prev = datapoints[0][POINT_VALUE]; var ema_cur = void 0; var a = void 0; if (n > 1) { // Calculate a from window size a = 2 / (n + 1); // Initial window, use simple moving average var w_avg = null; var w_count = 0; for (var j = n; j > 0; j--) { if (datapoints[n - j][POINT_VALUE] !== null) { w_avg += datapoints[n - j][POINT_VALUE]; w_count++; } } if (w_count > 0) { w_avg = w_avg / w_count; // Actually, we should set timestamp from datapoints[n-1] and start calculation of EMA from n. // But in order to start EMA from first point (not from Nth) we should expand time range and request N additional // points outside left side of range. We can't do that, so this trick is used for pretty view of first N points. // We calculate AVG for first N points, but then start from 2nd point, not from Nth. In general, it means we // assume that previous N values (0-N, 0-(N-1), ..., 0-1) have the same average value as a first N values. ema = [[w_avg, datapoints[0][POINT_TIMESTAMP]]]; ema_prev = w_avg; n = 1; } } else { // Use predefined a and start from 1st point (use it as initial EMA value) a = n; n = 1; } for (var i = n; i < datapoints.length; i++) { if (datapoints[i][POINT_VALUE] !== null) { ema_cur = a * datapoints[i][POINT_VALUE] + (1 - a) * ema_prev; ema_prev = ema_cur; ema.push([ema_cur, datapoints[i][POINT_TIMESTAMP]]); } else { ema.push([null, datapoints[i][POINT_TIMESTAMP]]); } } return ema; } function PERCENTIL(n, values) { var sorted = _.sortBy(values); return sorted[Math.floor(sorted.length * n / 100)]; } function COUNT(values) { return values.length; } function SUM(values) { var sum = null; for (var i = 0; i < values.length; i++) { if (values[i] !== null) { sum += values[i]; } } return sum; } function AVERAGE(values) { var values_non_null = getNonNullValues(values); if (values_non_null.length === 0) { return null; } return SUM(values_non_null) / values_non_null.length; } function getNonNullValues(values) { var values_non_null = []; for (var i = 0; i < values.length; i++) { if (values[i] !== null) { values_non_null.push(values[i]); } } return values_non_null; } function MIN(values) { return _.min(values); } function MAX(values) { return _.max(values); } function MEDIAN(values) { var sorted = _.sortBy(values); return sorted[Math.floor(sorted.length / 2)]; } /////////////////////// // Utility functions // /////////////////////// /** * For given point calculate corresponding time frame. * * |__*_|_*__|___*| -> |*___|*___|*___| * * @param {*} timestamp * @param {*} ms_interval */ function getPointTimeFrame(timestamp, ms_interval) { return Math.floor(timestamp / ms_interval) * ms_interval; } function sortByTime(series) { return _.sortBy(series, function (point) { return point[1]; }); } /** * Fill empty front and end of series by zeroes. * * | *** | | *** | * |___ ___| -> |*** ***| * @param {*} series * @param {*} timestamps */ function fillZeroes(series, timestamps) { var prepend = []; var append = []; var new_point = void 0; for (var i = 0; i < timestamps.length; i++) { if (timestamps[i] < series[0][POINT_TIMESTAMP]) { new_point = [0, timestamps[i]]; prepend.push(new_point); } else if (timestamps[i] > series[series.length - 1][POINT_TIMESTAMP]) { new_point = [0, timestamps[i]]; append.push(new_point); } } return _.concat(_.concat(prepend, series), append); } /** * Interpolate series with gaps */ function interpolateSeries(series) { var left, right; // Interpolate series for (var i = series.length - 1; i >= 0; i--) { if (!series[i][0]) { left = findNearestLeft(series, i); right = findNearestRight(series, i); if (!left) { left = right; } if (!right) { right = left; } series[i][0] = linearInterpolation(series[i][1], left, right); } } return series; } function linearInterpolation(timestamp, left, right) { if (left[1] === right[1]) { return (left[0] + right[0]) / 2; } else { return left[0] + (right[0] - left[0]) / (right[1] - left[1]) * (timestamp - left[1]); } } function findNearestRight(series, pointIndex) { for (var i = pointIndex; i < series.length; i++) { if (series[i][0] !== null) { return series[i]; } } return null; } function findNearestLeft(series, pointIndex) { for (var i = pointIndex; i > 0; i--) { if (series[i][0] !== null) { return series[i]; } } return null; } //////////// // Export // //////////// return { setters: [function (_lodash) { _ = _lodash.default; }, function (_utils) { utils = _utils; }], execute: function () { POINT_VALUE = 0; POINT_TIMESTAMP = 1; exportedFunctions = { downsample: downsample, groupBy: groupBy, groupBy_perf: groupBy_perf, sumSeries: sumSeries, scale: scale, scale_perf: scale_perf, delta: delta, rate: rate, simpleMovingAverage: simpleMovingAverage, expMovingAverage: expMovingAverage, SUM: SUM, COUNT: COUNT, AVERAGE: AVERAGE, MIN: MIN, MAX: MAX, MEDIAN: MEDIAN, PERCENTIL: PERCENTIL }; _export('default', exportedFunctions); } }; }); //# sourceMappingURL=timeseries.js.map