all: use go tool embedmd

Signed-off-by: Sebastien Binet <[email protected]>

Author: sbinet

fit/README.md

@@ -17,7 +17,7 @@ func ExampleH1D_gaussian() {
 		mean  = 2.0
 		sigma = 4.0
 		// Values from gonum/optimize:
-		want = []float64{447.0483517081991, 2.02127773281178, 3.9965893891862687}
+		want = []float64{450.56454241860934, 2.0146898541006277, 3.9613086671267466}
 		// Values from ROOT:
 		// want  = []float64{4.53720e+02, 1.93218e+00, 3.93188e+00}
 	)
@@ -28,13 +28,13 @@ func ExampleH1D_gaussian() {
 	dist := distuv.Normal{
 		Mu:    mean,
 		Sigma: sigma,
-		Src:   rand.New(rand.NewSource(0)),
+		Src:   rand.New(rand.NewPCG(0, 0)),
 	}
 
 	// Draw some random values from the standard
 	// normal distribution.
 	hist := hbook.NewH1D(100, -20, +25)
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v := dist.Rand()
 		hist.Fill(v, 1)
 	}

fit/fit.go

@@ -10,8 +10,7 @@ import (
 	"gonum.org/v1/gonum/mat"
 )
 
-//go:generate go get github.com/campoy/embedmd
-//go:generate embedmd -w README.md
+//go:generate go tool github.com/campoy/embedmd -w README.md
 
 // Func1D describes a 1D function to fit some data.
 type Func1D struct {

go.mod

@@ -10,7 +10,6 @@ require (
 	codeberg.org/sbinet/npyio v0.11.0
 	git.sr.ht/~sbinet/epok v0.5.0
 	git.sr.ht/~sbinet/go-arrow v0.3.0
-	github.com/campoy/embedmd v1.0.0
 	github.com/google/go-cmp v0.7.0
 	github.com/hashicorp/go-uuid v1.0.3
 	github.com/jcmturner/gokrb5/v8 v8.4.4
@@ -37,6 +36,7 @@ require (
 	codeberg.org/go-pdf/fpdf v0.11.1 // indirect
 	git.sr.ht/~sbinet/gg v0.6.0 // indirect
 	github.com/ajstarks/svgo v0.0.0-20211024235047-1546f124cd8b // indirect
+	github.com/campoy/embedmd v1.0.0 // indirect
 	github.com/edsrzf/mmap-go v1.2.0 // indirect
 	github.com/golang/freetype v0.0.0-20170609003504-e2365dfdc4a0 // indirect
 	github.com/google/flatbuffers v25.2.10+incompatible // indirect

hbook/README.md

@@ -33,30 +33,30 @@ func ExampleH1D() {
 	dist := distuv.Normal{
 		Mu:    0,
 		Sigma: 1,
-		Src:   rand.New(rand.NewSource(0)),
+		Src:   rand.New(rand.NewPCG(0, 0)),
 	}
 
 	// Draw some random values from the standard
 	// normal distribution.
 	h := hbook.NewH1D(20, -4, +4)
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v := dist.Rand()
 		h.Fill(v, 1)
 	}
 	// fill h with a slice of values and their weights
 	h.FillN([]float64{1, 2, 3}, []float64{1, 1, 1})
 	h.FillN([]float64{1, 2, 3}, nil) // all weights are 1.
 
-	fmt.Printf("mean:    %v\n", h.XMean())
-	fmt.Printf("rms:     %v\n", h.XRMS())
-	fmt.Printf("std-dev: %v\n", h.XStdDev())
-	fmt.Printf("std-err: %v\n", h.XStdErr())
+	fmt.Printf("mean:    %.12f\n", h.XMean())
+	fmt.Printf("rms:     %.12f\n", h.XRMS())
+	fmt.Printf("std-dev: %.12f\n", h.XStdDev())
+	fmt.Printf("std-err: %.12f\n", h.XStdErr())
 
 	// Output:
-	// mean:    0.005589967511734562
-	// rms:     1.0062596231244403
-	// std-dev: 1.0062943821322063
-	// std-err: 0.010059926295994191
+	// mean:    0.002104228518
+	// rms:     1.000617135827
+	// std-dev: 1.000664927794
+	// std-err: 0.010003648633
 }
 ```
 
@@ -86,7 +86,7 @@ func ExampleAddH1D() {
 
 	hsum := hbook.AddH1D(h1, h2)
 	fmt.Printf("Under: %.1f +/- %.1f\n", hsum.Binning.Outflows[0].SumW(), math.Sqrt(hsum.Binning.Outflows[0].SumW2()))
-	for i := 0; i < hsum.Len(); i++ {
+	for i := range hsum.Len() {
 		fmt.Printf("Bin %v: %.1f +/- %.1f\n", i, hsum.Binning.Bins[i].SumW(), math.Sqrt(hsum.Binning.Bins[i].SumW2()))
 	}
 	fmt.Printf("Over : %.1f +/- %.1f\n", hsum.Binning.Outflows[1].SumW(), math.Sqrt(hsum.Binning.Outflows[1].SumW2()))
@@ -128,7 +128,7 @@ func ExampleAddScaledH1D() {
 
 	hsum := hbook.AddScaledH1D(h1, 10, h2)
 	fmt.Printf("Under: %.1f +/- %.1f\n", hsum.Binning.Outflows[0].SumW(), math.Sqrt(hsum.Binning.Outflows[0].SumW2()))
-	for i := 0; i < hsum.Len(); i++ {
+	for i := range hsum.Len() {
 		fmt.Printf("Bin %v: %.1f +/- %.1f\n", i, hsum.Binning.Bins[i].SumW(), math.Sqrt(hsum.Binning.Bins[i].SumW2()))
 	}
 	fmt.Printf("Over : %.1f +/- %.1f\n", hsum.Binning.Outflows[1].SumW(), math.Sqrt(hsum.Binning.Outflows[1].SumW2()))
@@ -201,7 +201,7 @@ func ExampleH2D() {
 	dist, ok := distmv.NewNormal(
 		[]float64{0, 1},
 		mat.NewSymDense(2, []float64{4, 0, 0, 2}),
-		rand.New(rand.NewSource(1234)),
+		rand.New(rand.NewPCG(1234, 1234)),
 	)
 	if !ok {
 		log.Fatalf("error creating distmv.Normal")
@@ -210,7 +210,7 @@ func ExampleH2D() {
 	v := make([]float64, 2)
 	// Draw some random values from the standard
 	// normal distribution.
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v = dist.Rand(v)
 		h.Fill(v[0], v[1], 1)
 	}

hbook/hbook.go

@@ -8,8 +8,7 @@ import (
 	"math"
 )
 
-//go:generate go get github.com/campoy/embedmd
-//go:generate embedmd -w README.md
+//go:generate go tool github.com/campoy/embedmd -w README.md
 
 //go:generate -command brio-gen go run go-hep.org/x/hep/brio/cmd/brio-gen
 //go:generate brio-gen -p go-hep.org/x/hep/hbook -t Dist0D,Dist1D,Dist2D -o dist_brio.go

hplot/README.md

@@ -34,13 +34,13 @@ func ExampleH1D() {
 	dist := distuv.Normal{
 		Mu:    0,
 		Sigma: 1,
-		Src:   rand.New(rand.NewSource(0)),
+		Src:   rand.New(rand.NewPCG(0, 0)),
 	}
 
 	// Draw some random values from the standard
 	// normal distribution.
 	hist := hbook.NewH1D(20, -4, +4)
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v := dist.Rand()
 		hist.Fill(v, 1)
 	}
@@ -93,13 +93,13 @@ func ExampleH1D_withYErrBars() {
 	dist := distuv.Normal{
 		Mu:    0,
 		Sigma: 1,
-		Src:   rand.New(rand.NewSource(0)),
+		Src:   rand.New(rand.NewPCG(0, 0)),
 	}
 
 	// Draw some random values from the standard
 	// normal distribution.
 	hist := hbook.NewH1D(20, -4, +4)
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v := dist.Rand()
 		hist.Fill(v, 1)
 	}
@@ -155,13 +155,13 @@ func ExampleH1D_withYErrBarsAndData() {
 	dist := distuv.Normal{
 		Mu:    0,
 		Sigma: 1,
-		Src:   rand.New(rand.NewSource(0)),
+		Src:   rand.New(rand.NewPCG(0, 0)),
 	}
 
 	// Draw some random values from the standard
 	// normal distribution.
 	hist := hbook.NewH1D(20, -4, +4)
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v := dist.Rand()
 		hist.Fill(v, 1)
 	}
@@ -229,13 +229,13 @@ func ExampleH1D_withYErrBars_withBand() {
 	dist := distuv.Normal{
 		Mu:    0,
 		Sigma: 1,
-		Src:   rand.New(rand.NewSource(0)),
+		Src:   rand.New(rand.NewPCG(0, 0)),
 	}
 
 	// Draw some random values from the standard
 	// normal distribution.
 	hist := hbook.NewH1D(20, -4, +4)
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v := dist.Rand()
 		hist.Fill(v, 1)
 	}
@@ -292,13 +292,13 @@ func ExampleTiledPlot() {
 	dist := distuv.Normal{
 		Mu:    0,
 		Sigma: 1,
-		Src:   rand.New(rand.NewSource(0)),
+		Src:   rand.New(rand.NewPCG(0, 0)),
 	}
 
 	newHist := func(p *hplot.Plot) {
 		const npoints = 10000
 		hist := hbook.NewH1D(20, -4, +4)
-		for i := 0; i < npoints; i++ {
+		for range npoints {
 			v := dist.Rand()
 			hist.Fill(v, 1)
 		}
@@ -307,8 +307,8 @@ func ExampleTiledPlot() {
 		p.Add(h)
 	}
 
-	for i := 0; i < tp.Tiles.Rows; i++ {
-		for j := 0; j < tp.Tiles.Cols; j++ {
+	for i := range tp.Tiles.Rows {
+		for j := range tp.Tiles.Cols {
 			p := tp.Plot(j, i)
 			p.X.Min = -5
 			p.X.Max = +5
@@ -344,7 +344,7 @@ func ExampleTiledPlot_align() {
 		j = int(math.Pow(10, float64(n)))
 
 		var pts []hbook.Point2D
-		for ii := 0; ii < 10; ii++ {
+		for ii := range 10 {
 			pts = append(pts, hbook.Point2D{
 				X: float64(i + ii),
 				Y: float64(j + ii + 1),
@@ -354,8 +354,8 @@ func ExampleTiledPlot_align() {
 
 	}
 
-	for i := 0; i < tp.Tiles.Rows; i++ {
-		for j := 0; j < tp.Tiles.Cols; j++ {
+	for i := range tp.Tiles.Rows {
+		for j := range tp.Tiles.Cols {
 			p := tp.Plot(j, i)
 			p.X.Min = -5
 			p.X.Max = +5
@@ -398,13 +398,13 @@ func ExampleRatioPlot() {
 	dist := distuv.Normal{
 		Mu:    0,
 		Sigma: 1,
-		Src:   rand.New(rand.NewSource(0)),
+		Src:   rand.New(rand.NewPCG(0, 0)),
 	}
 
 	hist1 := hbook.NewH1D(20, -4, +4)
 	hist2 := hbook.NewH1D(20, -4, +4)
 
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v1 := dist.Rand() - 0.5
 		v2 := dist.Rand() + 0.5
 		hist1.Fill(v1, 1)
@@ -431,7 +431,7 @@ func ExampleRatioPlot() {
 	rp.Top.Add(hplot.NewGrid())
 
 	hist3 := hbook.NewH1D(20, -4, +4)
-	for i := 0; i < hist3.Len(); i++ {
+	for i := range hist3.Len() {
 		v1 := hist1.Value(i)
 		v2 := hist2.Value(i)
 		x1, _ := hist1.XY(i)
@@ -475,7 +475,7 @@ func ExampleH2D() {
 	dist, ok := distmv.NewNormal(
 		[]float64{0, 1},
 		mat.NewSymDense(2, []float64{4, 0, 0, 2}),
-		rand.New(rand.NewSource(1234)),
+		rand.New(rand.NewPCG(1234, 1234)),
 	)
 	if !ok {
 		log.Fatalf("error creating distmv.Normal")
@@ -484,7 +484,7 @@ func ExampleH2D() {
 	v := make([]float64, 2)
 	// Draw some random values from the standard
 	// normal distribution.
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v = dist.Rand(v)
 		h.Fill(v[0], v[1], 1)
 	}
@@ -514,7 +514,7 @@ func ExampleS2D() {
 	dist, ok := distmv.NewNormal(
 		[]float64{0, 1},
 		mat.NewSymDense(2, []float64{4, 0, 0, 2}),
-		rand.New(rand.NewSource(1234)),
+		rand.New(rand.NewPCG(1234, 1234)),
 	)
 	if !ok {
 		log.Fatalf("error creating distmv.Normal")
@@ -525,7 +525,7 @@ func ExampleS2D() {
 	v := make([]float64, 2)
 	// Draw some random values from the standard
 	// normal distribution.
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v = dist.Rand(v)
 		s2d.Fill(hbook.Point2D{X: v[0], Y: v[1]})
 	}
@@ -630,15 +630,15 @@ func ExampleBand() {
 	dist := distuv.Normal{
 		Mu:    0,
 		Sigma: 1,
-		Src:   rand.New(rand.NewSource(0)),
+		Src:   rand.New(rand.NewPCG(0, 0)),
 	}
 
 	topData := make(plotter.XYs, npoints)
 	botData := make(plotter.XYs, npoints)
 
 	// Draw some random values from the standard
 	// normal distribution.
-	for i := 0; i < npoints; i++ {
+	for i := range npoints {
 		x := float64(i+1) / xmax
 
 		v1 := dist.Rand()
@@ -705,13 +705,13 @@ func ExampleH1D_withPlotBorders() {
 	dist := distuv.Normal{
 		Mu:    0,
 		Sigma: 1,
-		Src:   rand.New(rand.NewSource(0)),
+		Src:   rand.New(rand.NewPCG(0, 0)),
 	}
 
 	// Draw some random values from the standard
 	// normal distribution.
 	hist := hbook.NewH1D(20, -4, +4)
-	for i := 0; i < npoints; i++ {
+	for range npoints {
 		v := dist.Rand()
 		hist.Fill(v, 1)
 	}

hplot/hplot.go

@@ -6,7 +6,7 @@
 // Use of this source code is governed by an MIT-style license
 // that can be found in the LICENSE file.
 
-//go:generate go run github.com/campoy/embedmd -w README.md
+//go:generate go tool github.com/campoy/embedmd -w README.md
 
 package hplot // import "go-hep.org/x/hep/hplot"
 

lcio/README.md

@@ -93,7 +93,7 @@ func ExampleWriter() {
 	}
 
 	const NEVENTS = 1
-	for ievt := 0; ievt < NEVENTS; ievt++ {
+	for ievt := range NEVENTS {
 		evt := lcio.Event{
 			RunNumber:   run.RunNumber,
 			Detector:    run.Detector,

lcio/lcio.go

@@ -5,5 +5,4 @@
 // Package lcio provides read/write access to the LCIO data model.
 package lcio // import "go-hep.org/x/hep/lcio"
 
-//go:generate go get github.com/campoy/embedmd
-//go:generate embedmd -w README.md
+//go:generate go tool github.com/campoy/embedmd -w README.md