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425 lines
11 KiB
TypeScript
425 lines
11 KiB
TypeScript
///<reference path="../../../headers/common.d.ts" />
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import _ from 'lodash';
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import TimeSeries from 'app/core/time_series2';
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let VALUE_INDEX = 0;
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let TIME_INDEX = 1;
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interface XBucket {
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x: number;
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buckets: any;
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}
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interface YBucket {
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y: number;
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values: number[];
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}
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function elasticHistogramToHeatmap(seriesList) {
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let heatmap = {};
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for (let series of seriesList) {
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let bound = Number(series.alias);
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if (isNaN(bound)) {
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return;
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}
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for (let point of series.datapoints) {
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let count = point[VALUE_INDEX];
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let time = point[TIME_INDEX];
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if (!_.isNumber(count)) {
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continue;
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}
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let bucket = heatmap[time];
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if (!bucket) {
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bucket = heatmap[time] = {x: time, buckets: {}};
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}
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bucket.buckets[bound] = {y: bound, count: count, values: [], points: []};
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}
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}
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return heatmap;
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}
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/**
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* Convert buckets into linear array of "cards" - objects, represented heatmap elements.
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* @param {Object} buckets
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* @return {Array} Array of "card" objects
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*/
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function convertToCards(buckets) {
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let cards = [];
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_.forEach(buckets, xBucket => {
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_.forEach(xBucket.buckets, yBucket=> {
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let card = {
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x: xBucket.x,
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y: yBucket.y,
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yBounds: yBucket.bounds,
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values: yBucket.values,
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count: yBucket.count,
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};
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cards.push(card);
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});
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});
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return cards;
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}
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/**
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* Special method for log scales. When series converted into buckets with log scale,
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* for simplification, 0 values are converted into 0, not into -Infinity. On the other hand, we mean
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* that all values less than series minimum, is 0 values, and we create special "minimum" bucket for
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* that values (actually, there're no values less than minimum, so this bucket is empty).
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* 8-16| | ** | | * | **|
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* 4-8| * |* *|* |** *| * |
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* 2-4| * *| | ***| |* |
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* 1-2|* | | | | | This bucket contains minimum series value
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* 0.5-1|____|____|____|____|____| This bucket should be displayed as 0 on graph
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* 0|____|____|____|____|____| This bucket is for 0 values (should actually be -Infinity)
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* So we should merge two bottom buckets into one (0-value bucket).
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*
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* @param {Object} buckets Heatmap buckets
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* @param {Number} minValue Minimum series value
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* @return {Object} Transformed buckets
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*/
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function mergeZeroBuckets(buckets, minValue) {
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_.forEach(buckets, xBucket => {
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let yBuckets = xBucket.buckets;
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let emptyBucket = {
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bounds: {bottom: 0, top: 0},
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values: [],
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points: [],
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count: 0,
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};
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let nullBucket = yBuckets[0] || emptyBucket;
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let minBucket = yBuckets[minValue] || emptyBucket;
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let newBucket = {
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y: 0,
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bounds: {bottom: minValue, top: minBucket.bounds.top || minValue},
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values: [],
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points: [],
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count: 0,
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};
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newBucket.points = nullBucket.points.concat(minBucket.points);
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newBucket.values = nullBucket.values.concat(minBucket.values);
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newBucket.count = newBucket.values.length;
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if (newBucket.count === 0) {
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return;
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}
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delete yBuckets[minValue];
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yBuckets[0] = newBucket;
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});
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return buckets;
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}
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/**
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* Convert set of time series into heatmap buckets
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* @return {Object} Heatmap object:
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* {
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* xBucketBound_1: {
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* x: xBucketBound_1,
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* buckets: {
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* yBucketBound_1: {
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* y: yBucketBound_1,
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* bounds: {bottom, top}
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* values: [val_1, val_2, ..., val_K],
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* points: [[val_Y, val_X, series_name], ..., [...]],
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* seriesStat: {seriesName_1: val_1, seriesName_2: val_2}
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* },
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* ...
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* yBucketBound_M: {}
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* },
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* values: [val_1, val_2, ..., val_K],
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* points: [
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* [val_Y, val_X, series_name], (point_1)
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* ...
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* [...] (point_K)
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* ]
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* },
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* xBucketBound_2: {},
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* ...
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* xBucketBound_N: {}
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* }
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*/
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function convertToHeatMap(seriesList, yBucketSize, xBucketSize, logBase = 1) {
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let heatmap = {};
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for (let series of seriesList) {
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let datapoints = series.datapoints;
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let seriesName = series.label;
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// Slice series into X axis buckets
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// | | ** | | * | **|
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// | * |* *|* |** *| * |
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// |** *| | ***| |* |
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// |____|____|____|____|____|_
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//
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_.forEach(datapoints, point => {
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let bucketBound = getBucketBound(point[TIME_INDEX], xBucketSize);
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pushToXBuckets(heatmap, point, bucketBound, seriesName);
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});
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}
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// Slice X axis buckets into Y (value) buckets
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// | **| |2|,
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// | * | --\ |1|,
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// |* | --/ |1|,
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// |____| |0|
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//
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_.forEach(heatmap, xBucket => {
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if (logBase !== 1) {
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xBucket.buckets = convertToLogScaleValueBuckets(xBucket, yBucketSize, logBase);
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} else {
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xBucket.buckets = convertToValueBuckets(xBucket, yBucketSize);
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}
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});
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return heatmap;
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}
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function pushToXBuckets(buckets, point, bucketNum, seriesName) {
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let value = point[VALUE_INDEX];
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if (value === null || value === undefined || isNaN(value)) { return; }
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// Add series name to point for future identification
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point.push(seriesName);
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if (buckets[bucketNum] && buckets[bucketNum].values) {
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buckets[bucketNum].values.push(value);
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buckets[bucketNum].points.push(point);
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} else {
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buckets[bucketNum] = {
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x: bucketNum,
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values: [value],
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points: [point]
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};
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}
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}
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function pushToYBuckets(buckets, bucketNum, value, point, bounds) {
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var count = 1;
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// Use the 3rd argument as scale/count
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if (point.length > 2) {
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count = parseInt(point[2]);
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}
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if (buckets[bucketNum]) {
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buckets[bucketNum].values.push(value);
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buckets[bucketNum].count += count;
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} else {
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buckets[bucketNum] = {
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y: bucketNum,
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bounds: bounds,
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values: [value],
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count: count,
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};
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}
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}
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function getValueBucketBound(value, yBucketSize, logBase) {
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if (logBase === 1) {
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return getBucketBound(value, yBucketSize);
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} else {
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return getLogScaleBucketBound(value, yBucketSize, logBase);
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}
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}
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/**
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* Find bucket for given value (for linear scale)
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*/
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function getBucketBounds(value, bucketSize) {
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let bottom, top;
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bottom = Math.floor(value / bucketSize) * bucketSize;
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top = (Math.floor(value / bucketSize) + 1) * bucketSize;
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return {bottom, top};
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}
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function getBucketBound(value, bucketSize) {
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let bounds = getBucketBounds(value, bucketSize);
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return bounds.bottom;
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}
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function convertToValueBuckets(xBucket, bucketSize) {
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let values = xBucket.values;
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let points = xBucket.points;
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let buckets = {};
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_.forEach(values, (val, index) => {
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let bounds = getBucketBounds(val, bucketSize);
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let bucketNum = bounds.bottom;
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pushToYBuckets(buckets, bucketNum, val, points[index], bounds);
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});
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return buckets;
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}
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/**
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* Find bucket for given value (for log scales)
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*/
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function getLogScaleBucketBounds(value, yBucketSplitFactor, logBase) {
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let top, bottom;
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if (value === 0) {
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return {bottom: 0, top: 0};
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}
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let value_log = logp(value, logBase);
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let pow, powTop;
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if (yBucketSplitFactor === 1 || !yBucketSplitFactor) {
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pow = Math.floor(value_log);
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powTop = pow + 1;
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} else {
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let additional_bucket_size = 1 / yBucketSplitFactor;
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let additional_log = value_log - Math.floor(value_log);
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additional_log = Math.floor(additional_log / additional_bucket_size) * additional_bucket_size;
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pow = Math.floor(value_log) + additional_log;
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powTop = pow + additional_bucket_size;
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}
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bottom = Math.pow(logBase, pow);
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top = Math.pow(logBase, powTop);
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return {bottom, top};
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}
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function getLogScaleBucketBound(value, yBucketSplitFactor, logBase) {
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let bounds = getLogScaleBucketBounds(value, yBucketSplitFactor, logBase);
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return bounds.bottom;
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}
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function convertToLogScaleValueBuckets(xBucket, yBucketSplitFactor, logBase) {
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let values = xBucket.values;
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let points = xBucket.points;
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let buckets = {};
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_.forEach(values, (val, index) => {
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let bounds = getLogScaleBucketBounds(val, yBucketSplitFactor, logBase);
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let bucketNum = bounds.bottom;
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pushToYBuckets(buckets, bucketNum, val, points[index], bounds);
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});
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return buckets;
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}
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// Get minimum non zero value.
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function getMinLog(series) {
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let values = _.compact(_.map(series.datapoints, p => p[0]));
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return _.min(values);
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}
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/**
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* Logarithm for custom base
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* @param value
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* @param base logarithm base
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*/
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function logp(value, base) {
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return Math.log(value) / Math.log(base);
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}
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/**
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* Calculate size of Y bucket from given buckets bounds.
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* @param bounds Array of Y buckets bounds
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* @param logBase Logarithm base
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*/
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function calculateBucketSize(bounds: number[], logBase = 1): number {
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let bucketSize = Infinity;
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if (bounds.length === 0) {
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return 0;
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} else if (bounds.length === 1) {
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return bounds[0];
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} else {
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bounds = _.sortBy(bounds);
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for (let i = 1; i < bounds.length; i++) {
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let distance = getDistance(bounds[i], bounds[i - 1], logBase);
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bucketSize = distance < bucketSize ? distance : bucketSize;
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}
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}
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return bucketSize;
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}
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/**
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* Calculate distance between two numbers in given scale (linear or logarithmic).
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* @param a
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* @param b
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* @param logBase
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*/
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function getDistance(a: number, b: number, logBase = 1): number {
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if (logBase === 1) {
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// Linear distance
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return Math.abs(b - a);
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} else {
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// logarithmic distance
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let ratio = Math.max(a, b) / Math.min(a, b);
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return logp(ratio, logBase);
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}
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}
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/**
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* Compare two heatmap data objects
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* @param objA
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* @param objB
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*/
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function isHeatmapDataEqual(objA: any, objB: any): boolean {
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let is_eql = !emptyXOR(objA, objB);
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_.forEach(objA, (xBucket: XBucket, x) => {
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if (objB[x]) {
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if (emptyXOR(xBucket.buckets, objB[x].buckets)) {
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is_eql = false;
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return false;
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}
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_.forEach(xBucket.buckets, (yBucket: YBucket, y) => {
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if (objB[x].buckets && objB[x].buckets[y]) {
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if (objB[x].buckets[y].values) {
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is_eql = _.isEqual(_.sortBy(yBucket.values), _.sortBy(objB[x].buckets[y].values));
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if (!is_eql) {
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return false;
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}
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} else {
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is_eql = false;
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return false;
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}
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} else {
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is_eql = false;
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return false;
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}
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});
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if (!is_eql) {
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return false;
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}
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} else {
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is_eql = false;
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return false;
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}
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});
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return is_eql;
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}
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function emptyXOR(foo: any, bar: any): boolean {
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return (_.isEmpty(foo) || _.isEmpty(bar)) && !(_.isEmpty(foo) && _.isEmpty(bar));
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}
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export {
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convertToHeatMap,
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elasticHistogramToHeatmap,
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convertToCards,
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mergeZeroBuckets,
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getMinLog,
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getValueBucketBound,
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isHeatmapDataEqual,
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calculateBucketSize
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};
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