import RecordedValuesIterator from "./RecordedValuesIterator"; import PercentileIterator from "./PercentileIterator"; import Histogram, { HistogramSummary } from "./Histogram"; export declare abstract class JsHistogram implements Histogram { static identityBuilder: number; identity: number; autoResize: boolean; highestTrackableValue: number; lowestDiscernibleValue: number; numberOfSignificantValueDigits: number; bucketCount: number; /** * Power-of-two length of linearly scaled array slots in the counts array. Long enough to hold the first sequence of * entries that must be distinguished by a single unit (determined by configured precision). */ subBucketCount: number; countsArrayLength: number; wordSizeInBytes: number; startTimeStampMsec: number; endTimeStampMsec: number; tag: string; percentileIterator: PercentileIterator; recordedValuesIterator: RecordedValuesIterator; /** * Number of leading zeros in the largest value that can fit in bucket 0. */ leadingZeroCountBase: number; subBucketHalfCountMagnitude: number; /** * Largest k such that 2^k <= lowestDiscernibleValue */ unitMagnitude: number; subBucketHalfCount: number; lowestDiscernibleValueRounded: number; /** * Biggest value that can fit in bucket 0 */ subBucketMask: number; /** * Lowest unitMagnitude bits are set */ unitMagnitudeMask: number; maxValue: number; minNonZeroValue: number; _totalCount: number; incrementTotalCount(): void; addToTotalCount(value: number): void; setTotalCount(value: number): void; /** * Get the total count of all recorded values in the histogram * @return the total count of all recorded values in the histogram */ get totalCount(): number; abstract getCountAtIndex(index: number): number; abstract incrementCountAtIndex(index: number): void; abstract addToCountAtIndex(index: number, value: number): void; abstract setCountAtIndex(index: number, value: number): void; abstract clearCounts(): void; protected abstract _getEstimatedFootprintInBytes(): number; abstract resize(newHighestTrackableValue: number): void; private updatedMaxValue; private updateMinNonZeroValue; constructor(lowestDiscernibleValue: number, highestTrackableValue: number, numberOfSignificantValueDigits: number); init(lowestDiscernibleValue: number, highestTrackableValue: number, numberOfSignificantValueDigits: number): void; /** * The buckets (each of which has subBucketCount sub-buckets, here assumed to be 2048 as an example) overlap: * *
     * The 0'th bucket covers from 0...2047 in multiples of 1, using all 2048 sub-buckets
     * The 1'th bucket covers from 2048..4097 in multiples of 2, using only the top 1024 sub-buckets
     * The 2'th bucket covers from 4096..8191 in multiple of 4, using only the top 1024 sub-buckets
     * ...
     * 
* * Bucket 0 is "special" here. It is the only one that has 2048 entries. All the rest have 1024 entries (because * their bottom half overlaps with and is already covered by the all of the previous buckets put together). In other * words, the k'th bucket could represent 0 * 2^k to 2048 * 2^k in 2048 buckets with 2^k precision, but the midpoint * of 1024 * 2^k = 2048 * 2^(k-1) = the k-1'th bucket's end, so we would use the previous bucket for those lower * values as it has better precision. */ establishSize(newHighestTrackableValue: number): void; determineArrayLengthNeeded(highestTrackableValue: number): number; /** * If we have N such that subBucketCount * 2^N > max value, we need storage for N+1 buckets, each with enough * slots to hold the top half of the subBucketCount (the lower half is covered by previous buckets), and the +1 * being used for the lower half of the 0'th bucket. Or, equivalently, we need 1 more bucket to capture the max * value if we consider the sub-bucket length to be halved. */ getLengthForNumberOfBuckets(numberOfBuckets: number): number; getBucketsNeededToCoverValue(value: number): number; /** * Record a value in the histogram * * @param value The value to be recorded * @throws may throw Error if value is exceeds highestTrackableValue */ recordValue(value: number): void; recordSingleValue(value: number): void; handleRecordException(count: number, value: number): void; countsArrayIndex(value: number): number; private computeCountsArrayIndex; /** * @return the lowest (and therefore highest precision) bucket index that can represent the value */ getBucketIndex(value: number): number; getSubBucketIndex(value: number, bucketIndex: number): number; updateMinAndMax(value: number): void; /** * Get the value at a given percentile. * When the given percentile is > 0.0, the value returned is the value that the given * percentage of the overall recorded value entries in the histogram are either smaller than * or equivalent to. When the given percentile is 0.0, the value returned is the value that all value * entries in the histogram are either larger than or equivalent to. *

* Note that two values are "equivalent" in this statement if * {@link org.HdrHistogram.JsHistogram#valuesAreEquivalent} would return true. * * @param percentile The percentile for which to return the associated value * @return The value that the given percentage of the overall recorded value entries in the * histogram are either smaller than or equivalent to. When the percentile is 0.0, returns the * value that all value entries in the histogram are either larger than or equivalent to. */ getValueAtPercentile(percentile: number): number; valueFromIndexes(bucketIndex: number, subBucketIndex: number): number; valueFromIndex(index: number): number; /** * Get the lowest value that is equivalent to the given value within the histogram's resolution. * Where "equivalent" means that value samples recorded for any two * equivalent values are counted in a common total count. * * @param value The given value * @return The lowest value that is equivalent to the given value within the histogram's resolution. */ lowestEquivalentValue(value: number): number; /** * Get the highest value that is equivalent to the given value within the histogram's resolution. * Where "equivalent" means that value samples recorded for any two * equivalent values are counted in a common total count. * * @param value The given value * @return The highest value that is equivalent to the given value within the histogram's resolution. */ highestEquivalentValue(value: number): number; /** * Get the next value that is not equivalent to the given value within the histogram's resolution. * Where "equivalent" means that value samples recorded for any two * equivalent values are counted in a common total count. * * @param value The given value * @return The next value that is not equivalent to the given value within the histogram's resolution. */ nextNonEquivalentValue(value: number): number; /** * Get the size (in value units) of the range of values that are equivalent to the given value within the * histogram's resolution. Where "equivalent" means that value samples recorded for any two * equivalent values are counted in a common total count. * * @param value The given value * @return The size of the range of values equivalent to the given value. */ sizeOfEquivalentValueRange(value: number): number; /** * Get a value that lies in the middle (rounded up) of the range of values equivalent the given value. * Where "equivalent" means that value samples recorded for any two * equivalent values are counted in a common total count. * * @param value The given value * @return The value lies in the middle (rounded up) of the range of values equivalent the given value. */ medianEquivalentValue(value: number): number; /** * Get the computed mean value of all recorded values in the histogram * * @return the mean value (in value units) of the histogram data */ get mean(): number; private getStdDeviation; /** * Get the computed standard deviation of all recorded values in the histogram * * @return the standard deviation (in value units) of the histogram data */ get stdDeviation(): number; /** * Produce textual representation of the value distribution of histogram data by percentile. The distribution is * output with exponentially increasing resolution, with each exponentially decreasing half-distance containing * dumpTicksPerHalf percentile reporting tick points. * * @param printStream Stream into which the distribution will be output *

* @param percentileTicksPerHalfDistance The number of reporting points per exponentially decreasing half-distance *

* @param outputValueUnitScalingRatio The scaling factor by which to divide histogram recorded values units in * output * @param useCsvFormat Output in CSV format if true. Otherwise use plain text form. */ outputPercentileDistribution(percentileTicksPerHalfDistance?: number, outputValueUnitScalingRatio?: number, useCsvFormat?: boolean): string; get summary(): HistogramSummary; toJSON(): HistogramSummary; inspect(): string; /** * Provide a (conservatively high) estimate of the Histogram's total footprint in bytes * * @return a (conservatively high) estimate of the Histogram's total footprint in bytes */ get estimatedFootprintInBytes(): number; recordSingleValueWithExpectedInterval(value: number, expectedIntervalBetweenValueSamples: number): void; private recordCountAtValue; /** * Record a value in the histogram (adding to the value's current count) * * @param value The value to be recorded * @param count The number of occurrences of this value to record * @throws ArrayIndexOutOfBoundsException (may throw) if value is exceeds highestTrackableValue */ recordValueWithCount(value: number, count: number): void; /** * Record a value in the histogram. *

* To compensate for the loss of sampled values when a recorded value is larger than the expected * interval between value samples, Histogram will auto-generate an additional series of decreasingly-smaller * (down to the expectedIntervalBetweenValueSamples) value records. *

* Note: This is a at-recording correction method, as opposed to the post-recording correction method provided * by {@link #copyCorrectedForCoordinatedOmission(long)}. * The two methods are mutually exclusive, and only one of the two should be be used on a given data set to correct * for the same coordinated omission issue. *

* See notes in the description of the Histogram calls for an illustration of why this corrective behavior is * important. * * @param value The value to record * @param expectedIntervalBetweenValueSamples If expectedIntervalBetweenValueSamples is larger than 0, add * auto-generated value records as appropriate if value is larger * than expectedIntervalBetweenValueSamples * @throws ArrayIndexOutOfBoundsException (may throw) if value is exceeds highestTrackableValue */ recordValueWithExpectedInterval(value: number, expectedIntervalBetweenValueSamples: number): void; private recordValueWithCountAndExpectedInterval; /** * Add the contents of another histogram to this one, while correcting the incoming data for coordinated omission. *

* To compensate for the loss of sampled values when a recorded value is larger than the expected * interval between value samples, the values added will include an auto-generated additional series of * decreasingly-smaller (down to the expectedIntervalBetweenValueSamples) value records for each count found * in the current histogram that is larger than the expectedIntervalBetweenValueSamples. * * Note: This is a post-recording correction method, as opposed to the at-recording correction method provided * by {@link #recordValueWithExpectedInterval(long, long) recordValueWithExpectedInterval}. The two * methods are mutually exclusive, and only one of the two should be be used on a given data set to correct * for the same coordinated omission issue. * by *

* See notes in the description of the Histogram calls for an illustration of why this corrective behavior is * important. * * @param otherHistogram The other histogram. highestTrackableValue and largestValueWithSingleUnitResolution must match. * @param expectedIntervalBetweenValueSamples If expectedIntervalBetweenValueSamples is larger than 0, add * auto-generated value records as appropriate if value is larger * than expectedIntervalBetweenValueSamples * @throws ArrayIndexOutOfBoundsException (may throw) if values exceed highestTrackableValue */ addWhileCorrectingForCoordinatedOmission(otherHistogram: JsHistogram, expectedIntervalBetweenValueSamples: number): void; /** * Get a copy of this histogram, corrected for coordinated omission. *

* To compensate for the loss of sampled values when a recorded value is larger than the expected * interval between value samples, the new histogram will include an auto-generated additional series of * decreasingly-smaller (down to the expectedIntervalBetweenValueSamples) value records for each count found * in the current histogram that is larger than the expectedIntervalBetweenValueSamples. * * Note: This is a post-correction method, as opposed to the at-recording correction method provided * by {@link #recordValueWithExpectedInterval(long, long) recordValueWithExpectedInterval}. The two * methods are mutually exclusive, and only one of the two should be be used on a given data set to correct * for the same coordinated omission issue. * by *

* See notes in the description of the Histogram calls for an illustration of why this corrective behavior is * important. * * @param expectedIntervalBetweenValueSamples If expectedIntervalBetweenValueSamples is larger than 0, add * auto-generated value records as appropriate if value is larger * than expectedIntervalBetweenValueSamples * @return a copy of this histogram, corrected for coordinated omission. */ abstract copyCorrectedForCoordinatedOmission(expectedIntervalBetweenValueSamples: number): JsHistogram; /** * Add the contents of another histogram to this one. *

* As part of adding the contents, the start/end timestamp range of this histogram will be * extended to include the start/end timestamp range of the other histogram. * * @param otherHistogram The other histogram. * @throws (may throw) if values in fromHistogram's are * higher than highestTrackableValue. */ add(otherHistogram: JsHistogram): void; /** * Get the count of recorded values at a specific value (to within the histogram resolution at the value level). * * @param value The value for which to provide the recorded count * @return The total count of values recorded in the histogram within the value range that is * {@literal >=} lowestEquivalentValue(value) and {@literal <=} highestEquivalentValue(value) */ private getCountAtValue; /** * Subtract the contents of another histogram from this one. *

* The start/end timestamps of this histogram will remain unchanged. * * @param otherHistogram The other histogram. * @throws ArrayIndexOutOfBoundsException (may throw) if values in otherHistogram's are higher than highestTrackableValue. * */ subtract(otherHistogram: JsHistogram): void; establishInternalTackingValues(lengthToCover?: number): void; reset(): void; destroy(): void; } export { JsHistogram as default };