Exemple #1
0
func Decompose(f []float64, maxImf int) int {

	h := make([]float64, len(f))
	residual := make([]float64, len(f))
	copy(h, f)
	copy(residual, f)
	const eps = 0.05
	imfCount := 0
	loopCount := 0
	rmin := 0.0
	rmax := 0.0
	monotonic := false

	n := len(f)

	imfs := algebra.NewMat(n, maxImf)

	for {
		fmt.Printf("loop %d\n", loopCount)
		loopCount = loopCount + 1
		util.DumpSlice("current h", h)
		fmt.Printf("Sifting...\n")
		minMean, zeroCrossings, minCount, maxCount := Sift(h)
		extrema := minCount + maxCount
		fmt.Printf("found minMean of %f\n", minMean)
		fmt.Printf("min mean %f zc %d ex %d %d\n", minMean, zeroCrossings, minCount, maxCount)
		pointMatch := ((zeroCrossings-extrema < 2) || (extrema-zeroCrossings < 2))
		if (minMean < eps) && pointMatch {
			fmt.Printf("storing imf at index %d\n", imfCount)
			for i := 0; i < n; i++ {
				imfs[i][imfCount] = h[i]
			}
			imfCount = imfCount + 1
			fmt.Printf("found imf number %d\n", imfCount)
			util.SliceSub(residual, h, residual)
			copy(h, residual)
			if imfCount >= maxImf {
				break
			}
			rmin, rmax, monotonic = util.SliceStats(residual)
			if monotonic {
				fmt.Printf("terminating with monotonic residual\n")
			}
			if (rmax - rmin) < eps {
				fmt.Printf("terminating with small residual %f\n", rmax-rmin)
			}
		}

	}

	algebra.MatInfo(imfs)

	return imfCount
}
Exemple #2
0
func TestSolver(n int) {
	fmt.Printf("Testing TDMA Solver\n")

	now := time.Now()
	seed := now.Unix()
	rand.Seed(seed)

	A := algebra.NewMat(n, n)
	x := make([]float64, n)
	b := make([]float64, n)

	for i := 0; i < n; i++ {
		x[i] = rand.Float64()
		A[i][i] = rand.Float64()
		if i < (n - 1) {
			A[i+1][i] = rand.Float64()
			A[i][i+1] = rand.Float64()
		}
	}

	algebra.MatMul(A, x, b)
	algebra.MatInfo(A)
	util.DumpSlice("x", x)
	util.DumpSlice("b", b)

	diag := make([]float64, n)
	unk := make([]float64, n)
	od_l := make([]float64, n)
	od_u := make([]float64, n)

	for i := 0; i < n; i++ {
		diag[i] = A[i][i]
		if i > 0 {
			od_l[i] = A[i][i-1]
		}
		if i < (n - 1) {
			od_u[i] = A[i][i+1]
		}
	}

	cp := make([]float64, n)
	dp := make([]float64, n)

	//util.DumpSlice("diag",diag)
	//util.DumpSlice("od_lower",od_l)
	//util.DumpSlice("od_upper",od_u)

	solver.Tdma(od_l, diag, od_u, b, unk, cp, dp)
	util.DumpSlice("result", unk)

}
Exemple #3
0
func TestMatMul() {

	a := algebra.NewMat(3, 4)
	x := make([]float64, 4)
	b := make([]float64, 3)

	for i := 0; i < len(x); i++ {
		x[i] = float64(i + 1)
	}

	v := 1.0

	for r, row := range a {
		for c, _ := range row {
			a[r][c] = v
			v = v + 1.0
		}
	}

	util.DumpSlice("x", x)
	algebra.MatInfo(a)
	algebra.MatMul(a, x, b)
	util.DumpSlice("b", b)
}
Exemple #4
0
func Sift(h []float64) (float64, int, int, int) {

	inEnergy := util.Energy(h)
	n := len(h)

	minVals := make([]float64, n)
	minLocs := make([]float64, n)
	maxVals := make([]float64, n)
	maxLocs := make([]float64, n)
	upperEnvelope := make([]float64, n)
	lowerEnvelope := make([]float64, n)
	var mean float64
	var smallestMean float64
	var zeroCrossings int

	detail := algebra.NewMat(n, 5)

	minVals, minLocs, maxVals, maxLocs, zeroCrossings = peaks.Detect(h,
		minVals, minLocs,
		maxVals, maxLocs,
		0.1, true)

	fmt.Printf("found %d minima and %d maxima and %d zero crossings\n",
		len(minVals), len(maxVals), zeroCrossings)

	util.DumpSlice("minima", minVals)
	util.DumpSlice("minlocs", minLocs)
	util.DumpSlice("maxima", maxVals)
	util.DumpSlice("maxlocs", maxLocs)

	fmt.Printf("getting upper envelope\n")
	upperEnvelope = resample.Resamp(maxLocs, maxVals, upperEnvelope)
	//util.DumpSlice("upper",upperEnvelope)
	fmt.Printf("getting lower envelope\n")
	lowerEnvelope = resample.Resamp(minLocs, minVals, lowerEnvelope)
	//util.DumpSlice("lower",lowerEnvelope)

	for i := 0; i < n; i++ {
		detail[i][0] = h[i]
		detail[i][1] = upperEnvelope[i]
		detail[i][2] = lowerEnvelope[i]
	}

	fmt.Printf("subtracting the mean\n")
	for i := 0; i < n; i++ {
		mean = 0.5 * (upperEnvelope[i] + lowerEnvelope[i])
		h[i] = h[i] - mean
		detail[i][3] = mean
		detail[i][4] = h[i]
		if i == 0 {
			smallestMean = math.Abs(mean)
		} else {
			smallestMean = math.Min(math.Abs(mean), smallestMean)
		}
	}

	algebra.MatInfo(detail)

	outEnergy := util.Energy(h)

	fmt.Printf("... reduced energy from %f to %f\n", inEnergy, outEnergy)

	return smallestMean, zeroCrossings, len(minVals), len(maxVals)
}