updated json naming for pmp, kmp, mp

Author: aouyang1

av/annotation_vector.go

@@ -11,13 +11,13 @@ import (
 	"github.com/matrix-profile-foundation/go-matrixprofile/util"
 )
 
-type AV int
+type AV string
 
 const (
-	Default    = iota // Default is the default annotation vector of all ones
-	Complexity        // Complexity is the annotation vector that focuses on areas of high "complexity"
-	MeanStd           // MeanStd is the annotation vector focusing on areas where the signal is within a standard deviation of the mean
-	Clipping          // Clipping is the annotation vector reducing the importance of areas showing clipping effects on the positive and negative regime
+	Default    AV = "default"    // Default is the default annotation vector of all ones
+	Complexity AV = "complexity" // Complexity is the annotation vector that focuses on areas of high "complexity"
+	MeanStd    AV = "mean_std"   // MeanStd is the annotation vector focusing on areas where the signal is within a standard deviation of the mean
+	Clipping   AV = "clipping"   // Clipping is the annotation vector reducing the importance of areas showing clipping effects on the positive and negative regime
 )
 
 // Create returns the annotation vector given an input time series and a window size m
@@ -33,7 +33,7 @@ func Create(av AV, ts []float64, m int) ([]float64, error) {
 	case Clipping:
 		avec = makeClipping(ts, m)
 	default:
-		return nil, fmt.Errorf("invalid annotation vector specified with matrix profile, %d", av)
+		return nil, fmt.Errorf("invalid annotation vector specified with matrix profile, %s", av)
 	}
 	return avec, nil
 }

kmp_test.go

@@ -200,7 +200,7 @@ func TestKMPSave(t *testing.T) {
 	m := 3
 	p, err := NewKMP(ts, m)
 	p.Compute()
-	filepath := "./mp.json"
+	filepath := "./kmp.json"
 	err = p.Save(filepath, "json")
 	if err != nil {
 		t.Errorf("Received error while saving matrix profile, %v", err)
@@ -215,7 +215,7 @@ func TestKMPLoad(t *testing.T) {
 	m := 3
 	p, err := NewKMP(ts, m)
 	p.Compute()
-	filepath := "./mp.json"
+	filepath := "./kmp.json"
 	if err = p.Save(filepath, "json"); err != nil {
 		t.Errorf("Received error while saving matrix profile, %v", err)
 	}

matrixprofile.go

@@ -26,22 +26,22 @@ import (
 // for a given timeseries of length N and subsequence length of M. The profile
 // and the profile index are stored here.
 type MatrixProfile struct {
-	A        []float64    // query time series
-	B        []float64    // timeseries to perform full join with
-	AMean    []float64    // sliding mean of a with a window of m each
-	AStd     []float64    // sliding standard deviation of a with a window of m each
-	BMean    []float64    // sliding mean of b with a window of m each
-	BStd     []float64    // sliding standard deviation of b with a window of m each
-	BF       []complex128 // holds an existing calculation of the FFT of b timeseries
-	N        int          // length of the timeseries
-	M        int          // length of a subsequence
-	SelfJoin bool         // indicates whether a self join is performed with an exclusion zone
-	MP       []float64    // matrix profile
-	Idx      []int        // matrix profile index
-	MPB      []float64    // matrix profile for the BA join
-	IdxB     []int        // matrix profile index for the BA join
-	AV       av.AV        // type of annotation vector which defaults to all ones
-	Opts     *MPOptions   // options used for the computation
+	A        []float64    `json:"a"`                 // query time series
+	B        []float64    `json:"b"`                 // timeseries to perform full join with
+	AMean    []float64    `json:"a_mean"`            // sliding mean of a with a window of m each
+	AStd     []float64    `json:"a_std"`             // sliding standard deviation of a with a window of m each
+	BMean    []float64    `json:"b_mean"`            // sliding mean of b with a window of m each
+	BStd     []float64    `json:"b_std"`             // sliding standard deviation of b with a window of m each
+	BF       []complex128 `json:"b_fft"`             // holds an existing calculation of the FFT of b timeseries
+	N        int          `json:"n"`                 // length of the timeseries
+	M        int          `json:"w"`                 // length of a subsequence
+	SelfJoin bool         `json:"self_join"`         // indicates whether a self join is performed with an exclusion zone
+	MP       []float64    `json:"mp"`                // matrix profile
+	Idx      []int        `json:"pi"`                // matrix profile index
+	MPB      []float64    `json:"mp_ba"`             // matrix profile for the BA join
+	IdxB     []int        `json:"pi_ba"`             // matrix profile index for the BA join
+	AV       av.AV        `json:"annotation_vector"` // type of annotation vector which defaults to all ones
+	Opts     *MPOptions   `json:"options"`           // options used for the computation
 }
 
 // New creates a matrix profile struct with a given timeseries length n and
@@ -283,19 +283,19 @@ func MPDist(a, b []float64, m int, o *MPOptions) (float64, error) {
 type Algo string
 
 const (
-	AlgoSTOMP Algo = "STOMP"
-	AlgoSTAMP Algo = "STAMP"
-	AlgoSTMP  Algo = "STMP"
-	AlgoMPX   Algo = "MPX"
+	AlgoSTOMP Algo = "stomp"
+	AlgoSTAMP Algo = "stamp"
+	AlgoSTMP  Algo = "stmp"
+	AlgoMPX   Algo = "mpx"
 )
 
 // MPOptions are parameters to vary the algorithm to compute the matrix profile.
 type MPOptions struct {
-	Algorithm    Algo    // choose which algorithm to compute the matrix profile
-	Sample       float64 // only applicable to algorithm STAMP
-	Parallelism  int
-	Euclidean    bool // defaults to using euclidean distance instead of pearson correlation for matrix profile
-	RemapNegCorr bool // defaults to no remapping. This is used so that highly negatively correlated sequences will show a low distance as well.
+	Algorithm    Algo    `json:"algorithm"`  // choose which algorithm to compute the matrix profile
+	Sample       float64 `json:"sample_pct"` // only applicable to algorithm STAMP
+	Parallelism  int     `json:"parallelism"`
+	Euclidean    bool    `json:"euclidean"`                  // defaults to using euclidean distance instead of pearson correlation for matrix profile
+	RemapNegCorr bool    `json:"remap_negative_correlation"` // defaults to no remapping. This is used so that highly negatively correlated sequences will show a low distance as well.
 }
 
 // NewMPOpts returns a default MPOptions

pmp.go

@@ -13,13 +13,13 @@ import (
 
 // PMP represents the pan matrix profile
 type PMP struct {
-	A        []float64   // query time series
-	B        []float64   // timeseries to perform full join with
-	SelfJoin bool        // indicates whether a self join is performed with an exclusion zone
-	PMP      [][]float64 // pan matrix profile
-	PIdx     [][]int     // pan matrix profile index
-	PWindows []int       // pan matrix windows used and is aligned with PMP and PIdx
-	Opts     *PMPOptions // options used for the computation
+	A        []float64   `json:"a"`         // query time series
+	B        []float64   `json:"b"`         // timeseries to perform full join with
+	SelfJoin bool        `json:"self_join"` // indicates whether a self join is performed with an exclusion zone
+	PMP      [][]float64 `json:"pmp"`       // pan matrix profile
+	PIdx     [][]int     `json:"ppi"`       // pan matrix profile index
+	PWindows []int       `json:"windows"`   // pan matrix windows used and is aligned with PMP and PIdx
+	Opts     *PMPOptions `json:"options"`   // options used for the computation
 }
 
 // NewPMP creates a new Pan matrix profile
@@ -90,9 +90,9 @@ func (p *PMP) Load(filepath, format string) error {
 
 // PMPOptions are parameters to vary the algorithm to compute the pan matrix profile.
 type PMPOptions struct {
-	LowerM int // used for pan matrix profile
-	UpperM int // used for pan matrix profile
-	MPOpts *MPOptions
+	LowerM int        `json:"lower_m"` // used for pan matrix profile
+	UpperM int        `json:"upper_m"` // used for pan matrix profile
+	MPOpts *MPOptions `json:"mp_options"`
 }
 
 // NewPMPOpts returns a default PMPOptions

pmp_test.go

@@ -10,7 +10,7 @@ func TestPMPSave(t *testing.T) {
 	ts := []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13}
 	p, err := NewPMP(ts, nil)
 	p.Compute(NewPMPOpts(3, 5))
-	filepath := "./mp.json"
+	filepath := "./pmp.json"
 	err = p.Save(filepath, "json")
 	if err != nil {
 		t.Errorf("Received error while saving matrix profile, %v", err)
@@ -24,7 +24,7 @@ func TestPMPLoad(t *testing.T) {
 	ts := []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13}
 	p, err := NewPMP(ts, nil)
 	p.Compute(NewPMPOpts(3, 5))
-	filepath := "./mp.json"
+	filepath := "./pmp.json"
 	if err = p.Save(filepath, "json"); err != nil {
 		t.Errorf("Received error while saving matrix profile, %v", err)
 	}