util

Documentation

Overview

Package util is a set of utility functions that are used throughout the matrixprofile package.

Index

• func ApplyExclusionZone(profile []float64, idx, zoneSize int)
• func BinarySplit(lb, ub int) []int
• func E2P(mp []float64, w int)
• func MovMeanStd(ts []float64, m int) ([]float64, []float64, error)
• func MuInvN(a []float64, w int) ([]float64, []float64)
• func P2E(mp []float64, w int)
• func Sum2s(a []float64, w int) []float64
• func ZNormalize(ts []float64) ([]float64, error)
• type Batch
  • func DiagBatchingScheme(l, p int) []Batch

Functions

func ApplyExclusionZone

func ApplyExclusionZone(profile []float64, idx, zoneSize int)

ApplyExclusionZone performs an in place operation on a given matrix profile setting distances around an index to +Inf

func BinarySplit

func BinarySplit(lb, ub int) []int

func E2P

func E2P(mp []float64, w int)

E2P converts a slice of euclidean distances to pearson correlation values. This is only valid for z-normalized time series. Negative pearson correlation values will not be discovered

func MovMeanStd

func MovMeanStd(ts []float64, m int) ([]float64, []float64, error)

MovMeanStd computes the mean and standard deviation of each sliding window of m over a slice of floats. This is done by one pass through the data and keeping track of the cumulative sum and cumulative sum squared. s between these at intervals of m provide a total of O(n) calculations for the standard deviation of each window of size m for the time series ts.

func MuInvN

func MuInvN(a []float64, w int) ([]float64, []float64)

func P2E

func P2E(mp []float64, w int)

P2E converts a slice of pearson correlation values to euclidean distances. This is only valid for z-normalized time series.

func Sum2s

func Sum2s(a []float64, w int) []float64

func ZNormalize

func ZNormalize(ts []float64) ([]float64, error)

ZNormalize computes a z-normalized version of a slice of floats. This is represented by y[i] = (x[i] - mean(x))/std(x)

Types

type Batch

type Batch struct {
	Idx  int
	Size int
}

Batch indicates which index to start at and how many to process from that index.

func DiagBatchingScheme

func DiagBatchingScheme(l, p int) []Batch

DiagBatchingScheme computes a more balanced batching scheme based on the diagonal nature of computing matrix profiles. Later batches get more to work on since those operate on less data in the matrix.