import { keepSignificantDigits } from "./formatters";

export const NO_TAG = "NO TAG";

export type BitBucketSize = 8 | 16 | 32 | 64 | "packed";

export interface HistogramSummary {
  p50: number;
  p75: number;
  p90: number;
  p97_5: number;
  p99: number;
  p99_9: number;
  p99_99: number;
  p99_999: number;
  max: number;
  totalCount: number;
}

export default interface Histogram {
  /**
   * Flag to enable automatic resizing of the underlying array
   */
  autoResize: boolean;

  /**
   * The current highest trackable value. May change if autoresize flag is set to true
   */
  readonly highestTrackableValue: number;

  /**
   * Total count of all recorded values in the histogram
   */
  readonly totalCount: number;

  /**
   * The computed standard deviation of all recorded values in the histogram
   */
  readonly stdDeviation: number;

  /**
   * The computed mean value of all recorded values in the histogram
   */
  readonly mean: number;

  /**
   * Main percentiles, max value and total number of recorded values
   */
  readonly summary: HistogramSummary;

  /**
   * A (conservatively high) estimate of the Histogram's total footprint in bytes
   */
  readonly estimatedFootprintInBytes: number;

  readonly maxValue: number;

  readonly minNonZeroValue: number;

  readonly numberOfSignificantValueDigits: number;

  startTimeStampMsec: number;
  endTimeStampMsec: number;
  tag: string;

  /**
   * 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;

  /**
   * 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;

  /**
   * 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.
   * <p>
   * 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;

  /**
   * 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
   * <i>dumpTicksPerHalf</i> percentile reporting tick points.
   *
   * @param printStream    Stream into which the distribution will be output
   * <p>
   * @param percentileTicksPerHalfDistance  The number of reporting points per exponentially decreasing half-distance
   * <p>
   * @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?: false
  ): string;

  toJSON(): HistogramSummary;

  /**
   * Record a value in the histogram.
   * <p>
   * 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.
   * <p>
   * 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.
   * <p>
   * 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;

  /**
   * Add the contents of another histogram to this one, while correcting the incoming data for coordinated omission.
   * <p>
   * 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
   * <p>
   * 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: Histogram,
    expectedIntervalBetweenValueSamples: number
  ): void;

  /**
   * Get a copy of this histogram, corrected for coordinated omission.
   * <p>
   * 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
   * <p>
   * 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.
   */
  copyCorrectedForCoordinatedOmission(
    expectedIntervalBetweenValueSamples: number
  ): Histogram;

  /**
   * Add the contents of another histogram to this one.
   * <p>
   * 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: Histogram): void;

  /**
   * Subtract the contents of another histogram from this one.
   * <p>
   * 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: Histogram): void;

  reset(): void;

  /**
   * Clean up memory associated to this histogram. Useful for WebAssembly implementations
   */
  destroy(): void;
}

export interface HistogramConstructor {
  new (
    lowestDiscernibleValue: number,
    highestTrackableValue: number,
    numberOfSignificantValueDigits: number
  ): Histogram;
}

export const toSummary = (histogram: Histogram): HistogramSummary => {
  const { totalCount, maxValue, numberOfSignificantValueDigits } = histogram;
  const round = keepSignificantDigits(numberOfSignificantValueDigits);
  return {
    p50: round(histogram.getValueAtPercentile(50)),
    p75: round(histogram.getValueAtPercentile(75)),
    p90: round(histogram.getValueAtPercentile(90)),
    p97_5: round(histogram.getValueAtPercentile(97.5)),
    p99: round(histogram.getValueAtPercentile(99)),
    p99_9: round(histogram.getValueAtPercentile(99.9)),
    p99_99: round(histogram.getValueAtPercentile(99.99)),
    p99_999: round(histogram.getValueAtPercentile(99.999)),
    max: maxValue,
    totalCount,
  };
};