README
¶
hplot
hplot
is a WIP package relying on gonum/plot
to plot histograms,
n-tuples and functions.
Installation
$ go get go-hep.org/x/hep/hplot
Documentation
Is available on godoc
:
https://godoc.org/go-hep.org/x/hep/hplot
Examples
1D histogram
func ExampleH1D() {
const npoints = 10000
// Create a normal distribution.
dist := distuv.Normal{
Mu: 0,
Sigma: 1,
Src: rand.New(rand.NewSource(0)),
}
// Draw some random values from the standard
// normal distribution.
hist := hbook.NewH1D(20, -4, +4)
for i := 0; i < npoints; i++ {
v := dist.Rand()
hist.Fill(v, 1)
}
// normalize histogram
area := 0.0
for _, bin := range hist.Binning.Bins {
area += bin.SumW() * bin.XWidth()
}
hist.Scale(1 / area)
// Make a plot and set its title.
p := hplot.New()
p.Title.Text = "Histogram"
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
// Create a histogram of our values drawn
// from the standard normal.
h := hplot.NewH1D(hist)
h.Infos.Style = hplot.HInfoSummary
p.Add(h)
// The normal distribution function
norm := hplot.NewFunction(dist.Prob)
norm.Color = color.RGBA{R: 255, A: 255}
norm.Width = vg.Points(2)
p.Add(norm)
// draw a grid
p.Add(hplot.NewGrid())
// Save the plot to a PNG file.
if err := p.Save(6*vg.Inch, -1, "testdata/h1d_plot.png"); err != nil {
log.Fatalf("error saving plot: %v\n", err)
}
}
1D histogram with y-error bars
func ExampleH1D_withYErrBars() {
const npoints = 100
// Create a normal distribution.
dist := distuv.Normal{
Mu: 0,
Sigma: 1,
Src: rand.New(rand.NewSource(0)),
}
// Draw some random values from the standard
// normal distribution.
hist := hbook.NewH1D(20, -4, +4)
for i := 0; i < npoints; i++ {
v := dist.Rand()
hist.Fill(v, 1)
}
// normalize histogram
area := 0.0
for _, bin := range hist.Binning.Bins {
area += bin.SumW() * bin.XWidth()
}
hist.Scale(1 / area)
// Make a plot and set its title.
p := hplot.New()
p.Title.Text = "Histogram"
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
// Create a histogram of our values drawn
// from the standard normal.
h := hplot.NewH1D(hist,
hplot.WithHInfo(hplot.HInfoSummary),
hplot.WithYErrBars(true),
)
h.YErrs.LineStyle.Color = color.RGBA{R: 255, A: 255}
p.Add(h)
// The normal distribution function
norm := hplot.NewFunction(dist.Prob)
norm.Color = color.RGBA{R: 255, A: 255}
norm.Width = vg.Points(2)
p.Add(norm)
// draw a grid
p.Add(hplot.NewGrid())
// Save the plot to a PNG file.
if err := p.Save(6*vg.Inch, -1, "testdata/h1d_yerrs.png"); err != nil {
log.Fatalf("error saving plot: %v\n", err)
}
}
1D histogram with y-error bars, no lines
func ExampleH1D_withYErrBarsAndData() {
const npoints = 100
// Create a normal distribution.
dist := distuv.Normal{
Mu: 0,
Sigma: 1,
Src: rand.New(rand.NewSource(0)),
}
// Draw some random values from the standard
// normal distribution.
hist := hbook.NewH1D(20, -4, +4)
for i := 0; i < npoints; i++ {
v := dist.Rand()
hist.Fill(v, 1)
}
// normalize histogram
area := 0.0
for _, bin := range hist.Binning.Bins {
area += bin.SumW() * bin.XWidth()
}
hist.Scale(1 / area)
// Make a plot and set its title.
p := hplot.New()
p.Title.Text = "Histogram"
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
p.Legend.Top = true
p.Legend.Left = true
// Create a histogram of our values drawn
// from the standard normal.
h := hplot.NewH1D(hist,
hplot.WithHInfo(hplot.HInfoSummary),
hplot.WithYErrBars(true),
hplot.WithGlyphStyle(draw.GlyphStyle{
Shape: draw.CrossGlyph{},
Color: color.Black,
Radius: vg.Points(2),
}),
)
h.GlyphStyle.Shape = draw.CircleGlyph{}
h.YErrs.LineStyle.Color = color.Black
h.LineStyle.Width = 0 // disable histogram lines
p.Add(h)
p.Legend.Add("data", h)
// The normal distribution function
norm := hplot.NewFunction(dist.Prob)
norm.Color = color.RGBA{R: 255, A: 255}
norm.Width = vg.Points(2)
p.Add(norm)
p.Legend.Add("model", norm)
// draw a grid
p.Add(hplot.NewGrid())
// Save the plot to a PNG file.
if err := p.Save(6*vg.Inch, -1, "testdata/h1d_glyphs.png"); err != nil {
log.Fatalf("error saving plot: %v\n", err)
}
}
1D histogram with y-error bars and error bands
func ExampleH1D_withYErrBars_withBand() {
const npoints = 100
// Create a normal distribution.
dist := distuv.Normal{
Mu: 0,
Sigma: 1,
Src: rand.New(rand.NewSource(0)),
}
// Draw some random values from the standard
// normal distribution.
hist := hbook.NewH1D(20, -4, +4)
for i := 0; i < npoints; i++ {
v := dist.Rand()
hist.Fill(v, 1)
}
// normalize histogram
area := 0.0
for _, bin := range hist.Binning.Bins {
area += bin.SumW() * bin.XWidth()
}
hist.Scale(1 / area)
// Make a plot and set its title.
p := hplot.New()
p.Title.Text = "Histogram"
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
// Create a histogram of our values drawn
// from the standard normal.
h := hplot.NewH1D(hist,
hplot.WithHInfo(hplot.HInfoSummary),
hplot.WithYErrBars(true),
hplot.WithBand(true),
)
h.YErrs.LineStyle.Color = color.RGBA{R: 255, A: 255}
p.Add(h)
// The normal distribution function
norm := hplot.NewFunction(dist.Prob)
norm.Color = color.RGBA{R: 255, A: 255}
norm.Width = vg.Points(2)
p.Add(norm)
// draw a grid
p.Add(hplot.NewGrid())
// Save the plot to a PNG file.
if err := p.Save(6*vg.Inch, -1, "testdata/h1d_yerrs_band.png"); err != nil {
log.Fatalf("error saving plot: %v\n", err)
}
}
Tiles of 1D histograms
func ExampleTiledPlot() {
tp := hplot.NewTiledPlot(draw.Tiles{Cols: 3, Rows: 2})
// Create a normal distribution.
dist := distuv.Normal{
Mu: 0,
Sigma: 1,
Src: rand.New(rand.NewSource(0)),
}
newHist := func(p *hplot.Plot) {
const npoints = 10000
hist := hbook.NewH1D(20, -4, +4)
for i := 0; i < npoints; i++ {
v := dist.Rand()
hist.Fill(v, 1)
}
h := hplot.NewH1D(hist)
p.Add(h)
}
for i := 0; i < tp.Tiles.Rows; i++ {
for j := 0; j < tp.Tiles.Cols; j++ {
p := tp.Plot(j, i)
p.X.Min = -5
p.X.Max = +5
newHist(p)
p.Title.Text = fmt.Sprintf("hist - (%02d, %02d)", j, i)
}
}
// remove plot at (1,0)
tp.Plots[1] = nil
err := tp.Save(15*vg.Centimeter, -1, "testdata/tiled_plot_histogram.png")
if err != nil {
log.Fatalf("error: %+v\n", err)
}
}
func ExampleTiledPlot_align() {
tp := hplot.NewTiledPlot(draw.Tiles{
Cols: 3, Rows: 3,
PadX: 20, PadY: 20,
})
tp.Align = true
points := func(i, j int) []hbook.Point2D {
n := i*tp.Tiles.Cols + j + 1
i += 1
j = int(math.Pow(10, float64(n)))
var pts []hbook.Point2D
for ii := 0; ii < 10; ii++ {
pts = append(pts, hbook.Point2D{
X: float64(i + ii),
Y: float64(j + ii + 1),
})
}
return pts
}
for i := 0; i < tp.Tiles.Rows; i++ {
for j := 0; j < tp.Tiles.Cols; j++ {
p := tp.Plot(j, i)
p.X.Min = -5
p.X.Max = +5
s := hplot.NewS2D(hbook.NewS2D(points(i, j)...))
s.GlyphStyle.Color = color.RGBA{R: 255, A: 255}
s.GlyphStyle.Radius = vg.Points(4)
p.Add(s)
p.Title.Text = fmt.Sprintf("hist - (%02d, %02d)", j, i)
}
}
// remove plot at (1,1)
tp.Plots[4] = nil
err := tp.Save(15*vg.Centimeter, -1, "testdata/tiled_plot_aligned_histogram.png")
if err != nil {
log.Fatalf("error: %+v\n", err)
}
}
Subplots
https://godoc.org/go-hep.org/x/hep/hplot#example-package--Subplot
Ratio-plots
func ExampleRatioPlot() {
const npoints = 10000
// Create a normal distribution.
dist := distuv.Normal{
Mu: 0,
Sigma: 1,
Src: rand.New(rand.NewSource(0)),
}
hist1 := hbook.NewH1D(20, -4, +4)
hist2 := hbook.NewH1D(20, -4, +4)
for i := 0; i < npoints; i++ {
v1 := dist.Rand() - 0.5
v2 := dist.Rand() + 0.5
hist1.Fill(v1, 1)
hist2.Fill(v2, 1)
}
rp := hplot.NewRatioPlot()
rp.Ratio = 0.3
// Make a plot and set its title.
rp.Top.Title.Text = "Histos"
rp.Top.Y.Label.Text = "Y"
// Create a histogram of our values drawn
// from the standard normal.
h1 := hplot.NewH1D(hist1)
h1.FillColor = color.NRGBA{R: 255, A: 100}
rp.Top.Add(h1)
h2 := hplot.NewH1D(hist2)
h2.FillColor = color.NRGBA{B: 255, A: 100}
rp.Top.Add(h2)
rp.Top.Add(hplot.NewGrid())
hist3 := hbook.NewH1D(20, -4, +4)
for i := 0; i < hist3.Len(); i++ {
v1 := hist1.Value(i)
v2 := hist2.Value(i)
x1, _ := hist1.XY(i)
hist3.Fill(x1, v1-v2)
}
hdiff := hplot.NewH1D(hist3)
rp.Bottom.X.Label.Text = "X"
rp.Bottom.Y.Label.Text = "Delta-Y"
rp.Bottom.Add(hdiff)
rp.Bottom.Add(hplot.NewGrid())
const (
width = 15 * vg.Centimeter
height = width / math.Phi
)
err := hplot.Save(rp, width, height, "testdata/diff_plot.png")
if err != nil {
log.Fatalf("error: %v\n", err)
}
}
LaTeX-plots
https://godoc.org/go-hep.org/x/hep/hplot#example-package--Latexplot
2D histogram
func ExampleH2D() {
h := hbook.NewH2D(100, -10, 10, 100, -10, 10)
const npoints = 10000
dist, ok := distmv.NewNormal(
[]float64{0, 1},
mat.NewSymDense(2, []float64{4, 0, 0, 2}),
rand.New(rand.NewSource(1234)),
)
if !ok {
log.Fatalf("error creating distmv.Normal")
}
v := make([]float64, 2)
// Draw some random values from the standard
// normal distribution.
for i := 0; i < npoints; i++ {
v = dist.Rand(v)
h.Fill(v[0], v[1], 1)
}
p := hplot.New()
p.Title.Text = "Hist-2D"
p.X.Label.Text = "x"
p.Y.Label.Text = "y"
p.Add(hplot.NewH2D(h, nil))
p.Add(plotter.NewGrid())
err := p.Save(10*vg.Centimeter, 10*vg.Centimeter, "testdata/h2d_plot.png")
if err != nil {
log.Fatal(err)
}
}
Scatter2D
func ExampleS2D() {
const npoints = 1000
dist, ok := distmv.NewNormal(
[]float64{0, 1},
mat.NewSymDense(2, []float64{4, 0, 0, 2}),
rand.New(rand.NewSource(1234)),
)
if !ok {
log.Fatalf("error creating distmv.Normal")
}
s2d := hbook.NewS2D()
v := make([]float64, 2)
// Draw some random values from the standard
// normal distribution.
for i := 0; i < npoints; i++ {
v = dist.Rand(v)
s2d.Fill(hbook.Point2D{X: v[0], Y: v[1]})
}
p := hplot.New()
p.Title.Text = "Scatter-2D"
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
p.Add(plotter.NewGrid())
s := hplot.NewS2D(s2d)
s.GlyphStyle.Color = color.RGBA{R: 255, A: 255}
s.GlyphStyle.Radius = vg.Points(2)
p.Add(s)
err := p.Save(10*vg.Centimeter, 10*vg.Centimeter, "testdata/s2d.png")
if err != nil {
log.Fatal(err)
}
}
Vertical lines
func ExampleVLine() {
p := hplot.New()
p.Title.Text = "vlines"
p.X.Min = 0
p.X.Max = 10
p.Y.Min = 0
p.Y.Max = 10
var (
left = color.RGBA{B: 255, A: 255}
right = color.RGBA{R: 255, A: 255}
)
p.Add(
hplot.VLine(2.5, left, nil),
hplot.VLine(5, nil, nil),
hplot.VLine(7.5, nil, right),
)
err := p.Save(10*vg.Centimeter, -1, "testdata/vline.png")
if err != nil {
log.Fatalf("error: %+v", err)
}
}
Horizontal lines
func ExampleHLine() {
p := hplot.New()
p.Title.Text = "hlines"
p.X.Min = 0
p.X.Max = 10
p.Y.Min = 0
p.Y.Max = 10
var (
top = color.RGBA{B: 255, A: 255}
bottom = color.RGBA{R: 255, A: 255}
)
p.Add(
hplot.HLine(2.5, nil, bottom),
hplot.HLine(5, nil, nil),
hplot.HLine(7.5, top, nil),
)
err := p.Save(10*vg.Centimeter, -1, "testdata/hline.png")
if err != nil {
log.Fatalf("error: %+v", err)
}
}
Band between lines
func ExampleBand() {
const (
npoints = 100
xmax = 10
)
// Create a normal distribution.
dist := distuv.Normal{
Mu: 0,
Sigma: 1,
Src: rand.New(rand.NewSource(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++ {
x := float64(i+1) / xmax
v1 := dist.Rand()
v2 := dist.Rand()
topData[i].X = x
topData[i].Y = 1/x + v1 + 10
botData[i].X = x
botData[i].Y = math.Log(x) + v2
}
top, err := hplot.NewLine(topData)
if err != nil {
log.Fatalf("error: %+v", err)
}
top.LineStyle.Color = color.RGBA{R: 255, A: 255}
bot, err := hplot.NewLine(botData)
if err != nil {
log.Fatalf("error: %+v", err)
}
bot.LineStyle.Color = color.RGBA{B: 255, A: 255}
tp := hplot.NewTiledPlot(draw.Tiles{Cols: 1, Rows: 2})
tp.Plots[0].Title.Text = "Band"
tp.Plots[0].Add(
top,
bot,
hplot.NewBand(color.Gray{200}, topData, botData),
)
tp.Plots[1].Title.Text = "Band"
var (
blue = color.RGBA{B: 255, A: 255}
grey = color.Gray{200}
band = hplot.NewBand(grey, topData, botData)
)
band.LineStyle = plotter.DefaultLineStyle
band.LineStyle.Color = blue
tp.Plots[1].Add(band)
err = tp.Save(10*vg.Centimeter, -1, "testdata/band.png")
if err != nil {
log.Fatalf("error: %+v", err)
}
}
Plot with borders
One can specify extra-space between the image borders (the physical file canvas) and the actual plot data.
func ExampleH1D_withPlotBorders() {
const npoints = 10000
// Create a normal distribution.
dist := distuv.Normal{
Mu: 0,
Sigma: 1,
Src: rand.New(rand.NewSource(0)),
}
// Draw some random values from the standard
// normal distribution.
hist := hbook.NewH1D(20, -4, +4)
for i := 0; i < npoints; i++ {
v := dist.Rand()
hist.Fill(v, 1)
}
// normalize histogram
area := 0.0
for _, bin := range hist.Binning.Bins {
area += bin.SumW() * bin.XWidth()
}
hist.Scale(1 / area)
// Make a plot and set its title.
p := hplot.New()
p.Title.Text = "Histogram"
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
// Create a histogram of our values drawn
// from the standard normal.
h := hplot.NewH1D(hist)
h.Infos.Style = hplot.HInfoSummary
p.Add(h)
// The normal distribution function
norm := hplot.NewFunction(dist.Prob)
norm.Color = color.RGBA{R: 255, A: 255}
norm.Width = vg.Points(2)
p.Add(norm)
// draw a grid
p.Add(hplot.NewGrid())
fig := hplot.Figure(p,
hplot.WithDPI(96),
hplot.WithBorder(hplot.Border{
Right: 25,
Left: 20,
Top: 25,
Bottom: 20,
}),
)
// Save the plot to a PNG file.
if err := hplot.Save(fig, 6*vg.Inch, -1, "testdata/h1d_borders.png"); err != nil {
log.Fatalf("error saving plot: %v\n", err)
}
}
Stack of 1D histograms
func ExampleHStack() {
h1 := hbook.NewH1D(100, -10, 10)
h2 := hbook.NewH1D(100, -10, 10)
h3 := hbook.NewH1D(100, -10, 10)
const seed = 1234
fillH1(h1, 10000, -2, 1, seed)
fillH1(h2, 10000, +3, 3, seed)
fillH1(h3, 10000, +4, 1, seed)
colors := []color.Color{
color.NRGBA{122, 195, 106, 150},
color.NRGBA{90, 155, 212, 150},
color.NRGBA{250, 167, 91, 150},
}
hh1 := hplot.NewH1D(h1)
hh1.FillColor = colors[0]
hh1.LineStyle.Color = color.Black
hh2 := hplot.NewH1D(h2)
hh2.FillColor = colors[1]
hh2.LineStyle.Width = 0
hh3 := hplot.NewH1D(h3)
hh3.FillColor = colors[2]
hh3.LineStyle.Color = color.Black
hs := []*hplot.H1D{hh1, hh2, hh3}
tp := hplot.NewTiledPlot(draw.Tiles{Cols: 1, Rows: 3})
tp.Align = true
{
p := tp.Plots[0]
p.Title.Text = "Histograms"
p.Y.Label.Text = "Y"
p.Add(hh1, hh2, hh3, hplot.NewGrid())
p.Legend.Add("h1", hh1)
p.Legend.Add("h2", hh2)
p.Legend.Add("h3", hh3)
p.Legend.Top = true
p.Legend.Left = true
}
{
p := tp.Plot(0, 1)
p.Title.Text = "HStack - stack: OFF"
p.Y.Label.Text = "Y"
hstack := hplot.NewHStack(hs)
hstack.Stack = hplot.HStackOff
p.Add(hstack, hplot.NewGrid())
p.Legend.Add("h1", hs[0])
p.Legend.Add("h2", hs[1])
p.Legend.Add("h3", hs[2])
p.Legend.Top = true
p.Legend.Left = true
}
{
p := tp.Plot(0, 2)
p.Title.Text = "Hstack - stack: ON"
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
hstack := hplot.NewHStack(hs, hplot.WithLogY(false))
p.Add(hstack, hplot.NewGrid())
p.Legend.Add("h1", hs[0])
p.Legend.Add("h2", hs[1])
p.Legend.Add("h3", hs[2])
p.Legend.Top = true
p.Legend.Left = true
}
err := tp.Save(15*vg.Centimeter, 15*vg.Centimeter, "testdata/hstack.png")
if err != nil {
log.Fatalf("error: %+v", err)
}
}
Stack of 1D histograms with a band
func ExampleHStack_withBand() {
h1 := hbook.NewH1D(50, -8, 12)
h2 := hbook.NewH1D(50, -8, 12)
h3 := hbook.NewH1D(50, -8, 12)
const seed = 1234
fillH1(h1, 2000, -2, 1, seed)
fillH1(h2, 2000, +3, 3, seed)
fillH1(h3, 2000, +4, 1, seed)
colors := []color.Color{
color.NRGBA{122, 195, 106, 150},
color.NRGBA{90, 155, 212, 150},
color.NRGBA{250, 167, 91, 150},
}
hh1 := hplot.NewH1D(h1, hplot.WithBand(true))
hh1.FillColor = colors[0]
hh1.LineStyle.Color = color.Black
hh1.Band.FillColor = color.NRGBA{G: 210, A: 200}
hh2 := hplot.NewH1D(h2, hplot.WithBand(false))
hh2.FillColor = colors[1]
hh2.LineStyle.Width = 0
hh3 := hplot.NewH1D(h3, hplot.WithBand(true))
hh3.FillColor = colors[2]
hh3.LineStyle.Color = color.Black
hh3.Band.FillColor = color.NRGBA{R: 220, A: 200}
hs := []*hplot.H1D{hh1, hh2, hh3}
hh4 := hplot.NewH1D(h1)
hh4.FillColor = colors[0]
hh4.LineStyle.Color = color.Black
hh5 := hplot.NewH1D(h2)
hh5.FillColor = colors[1]
hh5.LineStyle.Width = 0
hh6 := hplot.NewH1D(h3)
hh6.FillColor = colors[2]
hh6.LineStyle.Color = color.Black
hsHistoNoBand := []*hplot.H1D{hh4, hh5, hh6}
tp := hplot.NewTiledPlot(draw.Tiles{Cols: 2, Rows: 2})
tp.Align = true
{
p := tp.Plot(0, 0)
p.Title.Text = "Histos With or Without Band, Stack: OFF"
p.Title.Padding = 10
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
hstack := hplot.NewHStack(hs, hplot.WithBand(true))
hstack.Stack = hplot.HStackOff
p.Add(hstack, hplot.NewGrid())
p.Legend.Add("h1", hs[0])
p.Legend.Add("h2", hs[1])
p.Legend.Add("h3", hs[2])
p.Legend.Top = true
p.Legend.Left = true
}
{
p := tp.Plot(1, 0)
p.Title.Text = "Histos Without Band, Stack: OFF"
p.Title.Padding = 10
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
hstack := hplot.NewHStack(hsHistoNoBand, hplot.WithBand(true))
hstack.Stack = hplot.HStackOff
hstack.Band.FillColor = color.NRGBA{R: 100, G: 100, B: 100, A: 200}
p.Add(hstack, hplot.NewGrid())
p.Legend.Add("h1", hs[0])
p.Legend.Add("h2", hs[1])
p.Legend.Add("h3", hs[2])
p.Legend.Top = true
p.Legend.Left = true
}
{
p := tp.Plot(0, 1)
p.Title.Text = "Histos With or Without Band, Stack: ON"
p.Title.Padding = 10
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
hstack := hplot.NewHStack(hs, hplot.WithBand(true))
hstack.Band.FillColor = color.NRGBA{R: 100, G: 100, B: 100, A: 200}
p.Add(hstack, hplot.NewGrid())
p.Legend.Add("h1", hs[0])
p.Legend.Add("h2", hs[1])
p.Legend.Add("h3", hs[2])
p.Legend.Top = true
p.Legend.Left = true
}
{
p := tp.Plot(1, 1)
p.Title.Text = "Histos Without Band, Stack: ON"
p.Title.Padding = 10
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
hstack := hplot.NewHStack(hsHistoNoBand, hplot.WithBand(true))
hstack.Band.FillColor = color.NRGBA{R: 100, G: 100, B: 100, A: 200}
p.Add(hstack, hplot.NewGrid())
p.Legend.Add("h1", hs[0])
p.Legend.Add("h2", hs[1])
p.Legend.Add("h3", hs[2])
p.Legend.Top = true
p.Legend.Left = true
}
err := tp.Save(25*vg.Centimeter, 15*vg.Centimeter, "testdata/hstack_band.png")
if err != nil {
log.Fatalf("error: %+v", err)
}
}
Stack of 1D histograms with a band, with a log-y scale
func ExampleHStack_withLogY() {
h1 := hbook.NewH1D(50, -8, 12)
h2 := hbook.NewH1D(50, -8, 12)
h3 := hbook.NewH1D(50, -8, 12)
const seed = 1234
fillH1(h1, 2000, -2, 1, seed)
fillH1(h2, 2000, +3, 3, seed)
fillH1(h3, 2000, +4, 1, seed)
colors := []color.Color{
color.NRGBA{122, 195, 106, 150},
color.NRGBA{90, 155, 212, 150},
color.NRGBA{250, 167, 91, 150},
}
logy := hplot.WithLogY(true)
hh1 := hplot.NewH1D(h1, hplot.WithBand(true), logy)
hh1.FillColor = colors[0]
hh1.LineStyle.Color = color.Black
hh1.Band.FillColor = color.NRGBA{G: 210, A: 200}
hh2 := hplot.NewH1D(h2, hplot.WithBand(false), logy)
hh2.FillColor = colors[1]
hh2.LineStyle.Width = 0
hh3 := hplot.NewH1D(h3, hplot.WithBand(true), logy)
hh3.FillColor = colors[2]
hh3.LineStyle.Color = color.Black
hh3.Band.FillColor = color.NRGBA{R: 220, A: 200}
hs := []*hplot.H1D{hh1, hh2, hh3}
hh4 := hplot.NewH1D(h1, logy)
hh4.FillColor = colors[0]
hh4.LineStyle.Color = color.Black
hh5 := hplot.NewH1D(h2, logy)
hh5.FillColor = colors[1]
hh5.LineStyle.Width = 0
hh6 := hplot.NewH1D(h3, logy)
hh6.FillColor = colors[2]
hh6.LineStyle.Color = color.Black
hsHistoNoBand := []*hplot.H1D{hh4, hh5, hh6}
tp := hplot.NewTiledPlot(draw.Tiles{Cols: 2, Rows: 2})
tp.Align = true
{
p := tp.Plot(0, 0)
p.Title.Text = "Histos With or Without Band, Stack: OFF"
p.Title.Padding = 10
p.Y.Scale = plot.LogScale{}
p.Y.Tick.Marker = plot.LogTicks{}
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
hstack := hplot.NewHStack(hs, hplot.WithBand(true), logy)
hstack.Stack = hplot.HStackOff
p.Add(hstack, hplot.NewGrid())
p.Legend.Add("h1", hs[0])
p.Legend.Add("h2", hs[1])
p.Legend.Add("h3", hs[2])
p.Legend.Top = true
p.Legend.Left = true
}
{
p := tp.Plot(1, 0)
p.Title.Text = "Histos Without Band, Stack: OFF"
p.Title.Padding = 10
p.Y.Scale = plot.LogScale{}
p.Y.Tick.Marker = plot.LogTicks{}
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
hstack := hplot.NewHStack(hsHistoNoBand, hplot.WithBand(true), logy)
hstack.Stack = hplot.HStackOff
hstack.Band.FillColor = color.NRGBA{R: 100, G: 100, B: 100, A: 200}
p.Add(hstack, hplot.NewGrid())
p.Legend.Add("h1", hs[0])
p.Legend.Add("h2", hs[1])
p.Legend.Add("h3", hs[2])
p.Legend.Top = true
p.Legend.Left = true
}
{
p := tp.Plot(0, 1)
p.Title.Text = "Histos With or Without Band, Stack: ON"
p.Title.Padding = 10
p.Y.Scale = plot.LogScale{}
p.Y.Tick.Marker = plot.LogTicks{}
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
hstack := hplot.NewHStack(hs, hplot.WithBand(true), logy)
hstack.Band.FillColor = color.NRGBA{R: 100, G: 100, B: 100, A: 200}
p.Add(hstack, hplot.NewGrid())
p.Legend.Add("h1", hs[0])
p.Legend.Add("h2", hs[1])
p.Legend.Add("h3", hs[2])
p.Legend.Top = true
p.Legend.Left = true
}
{
p := tp.Plot(1, 1)
p.Title.Text = "Histos Without Band, Stack: ON"
p.Title.Padding = 10
p.Y.Scale = plot.LogScale{}
p.Y.Tick.Marker = plot.LogTicks{}
p.X.Label.Text = "X"
p.Y.Label.Text = "Y"
hstack := hplot.NewHStack(hsHistoNoBand, hplot.WithBand(true), logy)
hstack.Band.FillColor = color.NRGBA{R: 100, G: 100, B: 100, A: 200}
p.Add(hstack, hplot.NewGrid())
p.Legend.Add("h1", hs[0])
p.Legend.Add("h2", hs[1])
p.Legend.Add("h3", hs[2])
p.Legend.Top = true
p.Legend.Left = true
}
err := tp.Save(25*vg.Centimeter, 15*vg.Centimeter, "testdata/hstack_logy.png")
if err != nil {
log.Fatalf("error: %+v", err)
}
}
Labels
func ExampleLabel() {
// Creating a new plot
p := hplot.New()
p.Title.Text = "Plot labels"
p.X.Min = -10
p.X.Max = +10
p.Y.Min = -10
p.Y.Max = +10
// Default labels
l1 := hplot.NewLabel(-8, 5, "(-8,5)\nDefault label")
p.Add(l1)
// Label with normalized coordinates.
l3 := hplot.NewLabel(
0.5, 0.5,
"(0.5,0.5)\nLabel with relative coords",
hplot.WithLabelNormalized(true),
)
p.Add(l3)
// Label with normalized coordinates and auto-adjustement.
l4 := hplot.NewLabel(
0.95, 0.95,
"(0.95,0.95)\nLabel at the canvas edge, with AutoAdjust",
hplot.WithLabelNormalized(true),
hplot.WithLabelAutoAdjust(true),
)
p.Add(l4)
// Label with a customed TextStyle
usrFont := font.Font{
Typeface: "Liberation",
Variant: "Mono",
Weight: xfnt.WeightBold,
Style: xfnt.StyleNormal,
Size: 12,
}
sty := text.Style{
Color: plotutil.Color(2),
Font: usrFont,
}
l5 := hplot.NewLabel(
0.0, 0.1,
"(0.0,0.1)\nLabel with a user-defined font",
hplot.WithLabelTextStyle(sty),
hplot.WithLabelNormalized(true),
)
p.Add(l5)
p.Add(plotter.NewGlyphBoxes())
p.Add(hplot.NewGrid())
// Save the plot to a PNG file.
err := p.Save(15*vg.Centimeter, -1, "testdata/label_plot.png")
if err != nil {
log.Fatalf("error saving plot: %v\n", err)
}
}
Time series
func ExampleTicks_monthly() {
cnv := epok.UTCUnixTimeConverter{}
p := hplot.New()
p.Title.Text = "Time series (monthly)"
p.Y.Label.Text = "Goroutines"
p.Y.Min = 0
p.Y.Max = 4
p.X.AutoRescale = true
p.X.Tick.Marker = epok.Ticks{
Ruler: epok.Rules{
Major: epok.Rule{
Freq: epok.Monthly,
Range: epok.RangeFrom(1, 13, 2),
},
},
Format: "2006\nJan-02\n15:04:05",
Converter: cnv,
}
xysFrom := func(vs ...float64) plotter.XYs {
o := make(plotter.XYs, len(vs))
for i := range o {
o[i].X = vs[i]
o[i].Y = float64(i + 1)
}
return o
}
data := xysFrom(
cnv.FromTime(parse("2010-01-02 01:02:03")),
cnv.FromTime(parse("2010-02-01 01:02:03")),
cnv.FromTime(parse("2010-02-04 11:22:33")),
cnv.FromTime(parse("2010-03-04 01:02:03")),
cnv.FromTime(parse("2010-04-05 01:02:03")),
cnv.FromTime(parse("2010-04-05 01:02:03")),
cnv.FromTime(parse("2010-05-01 00:02:03")),
cnv.FromTime(parse("2010-05-04 04:04:04")),
cnv.FromTime(parse("2010-05-08 11:12:13")),
cnv.FromTime(parse("2010-06-15 01:02:03")),
cnv.FromTime(parse("2010-07-04 04:04:43")),
cnv.FromTime(parse("2010-07-14 14:17:09")),
cnv.FromTime(parse("2010-08-04 21:22:23")),
cnv.FromTime(parse("2010-08-15 11:12:13")),
cnv.FromTime(parse("2010-09-01 21:52:53")),
cnv.FromTime(parse("2010-10-25 01:19:23")),
cnv.FromTime(parse("2010-11-30 11:32:53")),
cnv.FromTime(parse("2010-12-24 23:59:59")),
cnv.FromTime(parse("2010-12-31 23:59:59")),
cnv.FromTime(parse("2011-01-12 01:02:03")),
)
line, pnts, err := hplot.NewLinePoints(data)
if err != nil {
log.Fatalf("could not create plotter: %+v", err)
}
line.Color = color.RGBA{B: 255, A: 255}
pnts.Shape = draw.CircleGlyph{}
pnts.Color = color.RGBA{R: 255, A: 255}
p.Add(line, pnts, hplot.NewGrid())
err = p.Save(20*vg.Centimeter, 10*vg.Centimeter, "testdata/timeseries_monthly.png")
if err != nil {
log.Fatalf("could not save plot: %+v", err)
}
}
Documentation
¶
Overview ¶
Package hplot is a package to plot histograms, n-tuples and functions
Index ¶
- func Dims(width, height vg.Length) (w, h vg.Length)
- func NewGrid() *plotter.Grid
- func NewLine(xys plotter.XYer) (*plotter.Line, error)
- func NewLinePoints(xys plotter.XYer) (*plotter.Line, *plotter.Scatter, error)
- func NewScatter(xys plotter.XYer) (*plotter.Scatter, error)
- func Save(p Drawer, w, h vg.Length, fnames ...string) (err error)
- func Show(p Drawer, w, h vg.Length, format string) ([]byte, error)
- func WriterTo(p Drawer, w, h vg.Length, format string) (io.WriterTo, error)
- func ZipXY(x, y []float64) plotter.XYer
- type Band
- type BinnedErrBand
- type Border
- type Drawer
- type Fig
- type FigOption
- type FreqTicks
- type Function
- type H1D
- type H2D
- type HInfoStyle
- type HInfos
- type HStack
- type HStackKind
- type HorizLine
- type Label
- type LabelOption
- type Legend
- type NoTicks
- type Options
- type Plot
- type RatioPlot
- type S2D
- type StepsKind
- type Style
- type Ticks
- type TiledPlot
- type VertLine
Examples ¶
- Package (Latexplot)
- Package (Subplot)
- Band
- BinnedErrBand
- BinnedErrBand (FromH1D)
- Function
- Function (LogY)
- H1D
- H1D (LegendStyle)
- H1D (LogScaleY)
- H1D (ToPDF)
- H1D (WithPlotBorders)
- H1D (WithYErrBars)
- H1D (WithYErrBarsAndData)
- H1D (WithYErrBars_withBand)
- H2D
- H2D (WithLegend)
- HLine
- HStack
- HStack (WithBand)
- HStack (WithLogY)
- Label
- RatioPlot
- S2D
- S2D (WithBand)
- S2D (WithErrorBars)
- S2D (WithStepsKind)
- S2D (WithStepsKind_withBand)
- Save
- Ticks
- Ticks (Daily)
- Ticks (Monthly)
- Ticks (Yearly)
- TiledPlot
- TiledPlot (Align)
- VLine
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func NewGrid ¶
NewGrid returns a new grid with both vertical and horizontal lines using the default grid line style.
func NewLinePoints ¶ added in v0.34.0
NewLinePoints returns both a Line and a Points for the given point data.
func NewScatter ¶
NewScatter returns a Scatter that uses the default glyph style.
func Save ¶ added in v0.27.0
Save saves the plot to an image file. The file format is determined by the extension.
Supported extensions are:
.eps, .jpg, .jpeg, .json, .pdf, .png, .svg, .tex, .tif and .tiff.
If w or h are <= 0, the value is chosen such that it follows the Golden Ratio. If w and h are <= 0, the values are chosen such that they follow the Golden Ratio (the width is defaulted to vgimg.DefaultWidth).
func Show ¶
Show displays the plot according to format, returning the raw bytes and an error, if any.
If format is the empty string, then "png" is selected. The list of accepted format strings is the same one than from the gonum.org/v1/plot/vg/draw.NewFormattedCanvas function.
func WriterTo ¶ added in v0.27.0
WriterTo returns an io.WriterTo that will write the plots as the specified image format.
Supported formats are the same ones than hplot.Save.
If w or h are <= 0, the value is chosen such that it follows the Golden Ratio. If w and h are <= 0, the values are chosen such that they follow the Golden Ratio (the width is defaulted to vgimg.DefaultWidth).
Types ¶
type Band ¶ added in v0.20.0
type Band struct { // LineStyle is the style of the line contouring the band. // Use zero width to disable. draw.LineStyle // FillColor is the color to fill the area between // the top and bottom data points. // Use nil to disable the filling. FillColor color.Color // contains filtered or unexported fields }
Band implements the plot.Plotter interface, drawing a colored band made of two lines.
type BinnedErrBand ¶ added in v0.28.0
type BinnedErrBand struct { // Data for every bins. Counts []hbook.Count // LineStyle is the style of the line // contouring the band. // Use zero width to disable. draw.LineStyle // FillColor is the color to fill the area // between the top and bottom data points. // Use nil to disable the filling. FillColor color.Color // LogY allows rendering with a log-scaled Y axis. // When enabled, bins with negative or zero minimal value (val-err) // will be discarded from the error band. // The lowest Y value for the DataRange will be corrected to leave an // arbitrary amount of height for the smallest bin entry so it is visible // on the final plot. LogY bool }
BinnedErrBand implements the plot.Plotter interface, drawing a colored band for the error on any binned quantity.
func NewBinnedErrBand ¶ added in v0.28.0
func NewBinnedErrBand(cs []hbook.Count) *BinnedErrBand
NewBinnedErrBand creates a binned error band from a slice of count.
func (*BinnedErrBand) DataRange ¶ added in v0.28.0
func (b *BinnedErrBand) DataRange() (xmin, xmax, ymin, ymax float64)
DataRange returns the minimum and maximum x and y values, implementing the plot.DataRanger interface.
type Border ¶ added in v0.27.0
Border specifies the borders' sizes, the space between the end of the plot image (PDF, PNG, ...) and the actual plot.
type Fig ¶ added in v0.27.0
type Fig struct { // Plot is a gonum/plot.Plot like value. Plot Drawer // Legend displays a legend on the righthand-side of the plot. Legend *Legend // Border specifies the borders' sizes, the space between the // end of the plot image (PDF, PNG, ...) and the actual plot. Border Border // Latex handles the generation of PDFs from .tex files. // The default is to use htex.NoopHandler (a no-op). // To enable the automatic generation of PDFs, use DefaultHandler: // p := hplot.Wrap(plt) // p.Latex = htex.DefaultHandler Latex htex.Handler // DPI is the dot-per-inch for PNG,JPEG,... plots. DPI float64 }
Fig is a figure, holding a plot and figure-level customizations.
type FigOption ¶ added in v0.27.0
type FigOption func(fig *Fig)
FigOption allows to customize the creation of figures.
func WithBorder ¶ added in v0.27.0
WithBorder allows to specify the borders' sizes, the space between the end of the plot image (PDF, PNG, ...) and the actual plot.
func WithLatexHandler ¶ added in v0.27.0
WithLatexHandler allows to enable the automatic generation of PDFs from .tex files. To enable the automatic generation of PDFs, use DefaultHandler:
WithLatexHandler(htex.DefaultHandler)
func WithLegend ¶ added in v0.34.0
WithLegend enables the display of a legend on the righthand-side of a plot.
type FreqTicks ¶
FreqTicks implements a simple plot.Ticker scheme. FreqTicks will generate N ticks where 1 every Freq tick will be labeled.
type Function ¶ added in v0.21.0
type Function struct { F func(x float64) (y float64) // XMin and XMax specify the range // of x values to pass to F. XMin, XMax float64 Samples int draw.LineStyle // LogY allows rendering with a log-scaled Y axis. // When enabled, function values returning 0 will be discarded from // the final plot. LogY bool }
Function implements the Plotter interface, drawing a line for the given function.
func NewFunction ¶
NewFunction returns a Function that plots F using the default line style with 50 samples.
type H1D ¶
type H1D struct { // Hist is the histogramming data Hist *hbook.H1D // FillColor is the color used to fill each // bar of the histogram. If the color is nil // then the bars are not filled. FillColor color.Color // LineStyle is the style of the outline of each // bar of the histogram. draw.LineStyle // GlyphStyle is the style of the glyphs drawn // at the top of each histogram bar. GlyphStyle draw.GlyphStyle // LogY allows rendering with a log-scaled Y axis. // When enabled, histogram bins with no entries will be discarded from // the histogram's DataRange. // The lowest Y value for the DataRange will be corrected to leave an // arbitrary amount of height for the smallest bin entry so it is visible // on the final plot. LogY bool // InfoStyle is the style of infos displayed for // the histogram (entries, mean, rms). Infos HInfos // YErrs is the y error bars plotter. YErrs *plotter.YErrorBars // Band displays a colored band between the y-min and y-max error bars. // The band is shown in the legend thumbnail only if there is no filling. Band *BinnedErrBand }
H1D implements the plotter.Plotter interface, drawing a histogram of the data.
Example (WithYErrBarsAndData) ¶
An example of making a 1D-histogram with y-error bars and no histogram rectangle.
Output:
Example (WithYErrBars_withBand) ¶
An example of making a 1D-histogram with y-error bars and the associated band.
Output:
func NewH1D ¶
NewH1D returns a new histogram, as in NewH1DFromXYer, except that it accepts a hbook.H1D instead of a plotter.XYer
func NewH1FromValuer ¶
NewH1FromValuer returns a new histogram, as in NewH1FromXYer, except that it accepts a plotter.Valuer instead of an XYer.
func NewH1FromXYer ¶
NewH1FromXYer returns a new histogram that represents the distribution of values using the given number of bins.
Each y value is assumed to be the frequency count for the corresponding x.
It panics if the number of bins is non-positive.
func (*H1D) GlyphBoxes ¶
GlyphBoxes returns a slice of GlyphBoxes, one for each of the bins, implementing the plot.GlyphBoxer interface.
type H2D ¶
type H2D struct { // H is the histogramming data H *hbook.H2D // InfoStyle is the style of infos displayed for // the histogram (entries, mean, rms) Infos HInfos // HeatMap implements the Plotter interface, drawing // a heat map of the values in the 2-d histogram. HeatMap *plotter.HeatMap }
H2D implements the plotter.Plotter interface, drawing a 2-dim histogram of the data.
func (*H2D) GlyphBoxes ¶
GlyphBoxes returns a slice of GlyphBoxes, one for each of the bins, implementing the plot.GlyphBoxer interface.
type HInfoStyle ¶
type HInfoStyle uint32
const ( HInfoNone HInfoStyle = 0 HInfoEntries HInfoStyle = 1 << iota HInfoMean HInfoRMS HInfoStdDev HInfoSummary HInfoStyle = HInfoEntries | HInfoMean | HInfoStdDev )
type HInfos ¶
type HInfos struct {
Style HInfoStyle
}
type HStack ¶ added in v0.26.0
type HStack struct { // LogY allows rendering with a log-scaled Y axis. // When enabled, histogram bins with no entries will be discarded from // the histogram's DataRange. // The lowest Y value for the DataRange will be corrected to leave an // arbitrary amount of height for the smallest bin entry so it is visible // on the final plot. LogY bool // Stack specifies how histograms are displayed. // Default is to display histograms stacked on top of each other. // If not stacked, individual histogram uncertainty bands will be // displayed when defined. // If stacked, individual uncertainty bands will not be diplayed // but the total band can be displayed with the hplot.WithBand(true) // option. Stack HStackKind // Band displays a colored band between the y-min and y-max error bars. // Error bars are computed as the bin-by-bin quadratic sum of individual // histogram uncertainties. Band *BinnedErrBand // contains filtered or unexported fields }
HStack implements the plot.Plotter interface, drawing a stack of histograms.
func NewHStack ¶ added in v0.26.0
NewHStack creates a new histogram stack from the provided list of histograms. NewHStack panicks if the list of histograms is empty. NewHStack panicks if the histograms have different binning.
type HStackKind ¶ added in v0.26.0
type HStackKind int
HStackKind customizes how a HStack should behave.
const ( // HStackOn instructs HStack to display histograms // stacked on top of each other. HStackOn HStackKind = iota // HStackOff instructs HStack to display histograms // with the stack disabled. HStackOff )
type HorizLine ¶ added in v0.20.0
HorizLine draws a horizontal line at Y and colors the top and bottom portions of the plot with the provided colors.
type Label ¶ added in v0.28.4
type Label struct { Text string // Text of the label X, Y float64 // Position of the label TextStyle draw.TextStyle // Text style of the label // Normalized indicates whether the label position // is in data coordinates or normalized with regard // to the canvas space. // When normalized, the label position is assumed // to fall in the [0, 1] interval. If true, NewLabel // panics if x or y are outside [0, 1]. // // Normalized is false by default. Normalized bool // AutoAdjust enables auto adjustment of the label // position, when Normalized is true and when x // and/or y are close to 1 and the label is partly // outside the canvas. If false and the label doesn't // fit in the canvas, an error is returned. // // AutoAdjust is false by default. AutoAdjust bool // contains filtered or unexported fields }
Label displays a user-defined text string on a plot.
Fields of Label should not be modified once the Label has been added to an hplot.Plot.
func NewLabel ¶ added in v0.28.4
func NewLabel(x, y float64, txt string, opts ...LabelOption) *Label
NewLabel creates a new txt label at position (x, y).
func (*Label) DataRange ¶ added in v0.28.4
DataRange returns the minimum and maximum x and y values, implementing the plot.DataRanger interface.
func (*Label) GlyphBoxes ¶ added in v0.28.4
GlyphBoxes returns a GlyphBox, corresponding to the label. GlyphBoxes implements the plot.GlyphBoxer interface.
type LabelOption ¶ added in v0.28.4
type LabelOption func(cfg *labelConfig)
LabelOption handles various options to configure a Label.
func WithLabelAutoAdjust ¶ added in v0.28.4
func WithLabelAutoAdjust(auto bool) LabelOption
WithLabelAutoAdjust specifies whether the coordinates are automatically adjusted to the canvas size.
func WithLabelNormalized ¶ added in v0.28.4
func WithLabelNormalized(norm bool) LabelOption
WithLabelNormalized specifies whether the coordinates are normalized to the canvas size.
func WithLabelTextStyle ¶ added in v0.28.4
func WithLabelTextStyle(style draw.TextStyle) LabelOption
WithLabelTextStyle specifies the text style of the label.
type Legend ¶ added in v0.34.0
A Legend gives a description of the meaning of different data elements of the plot. Each legend entry has a name and a thumbnail, where the thumbnail shows a small sample of the display style of the corresponding data.
type Options ¶
type Options func(cfg *config)
Options encodes various options to pass to a plot.
func WithBand ¶ added in v0.20.0
WithBand enables or disables the display of a colored band between Y-error bars.
func WithGlyphStyle ¶ added in v0.26.0
func WithGlyphStyle(sty draw.GlyphStyle) Options
WithGlyphStyle sets the glyph style of a plotter.
func WithHInfo ¶ added in v0.25.0
func WithHInfo(v HInfoStyle) Options
WithHInfo sets a given histogram info style.
func WithStepsKind ¶ added in v0.27.0
WithStepsKind sets the style of the connecting line (NoSteps, HiSteps, etc...)
func WithXErrBars ¶
WithXErrBars enables or disables the display of X-error bars.
func WithYErrBars ¶
WithYErrBars enables or disables the display of Y-error bars.
type Plot ¶
Plot is the basic type representing a plot.
func (*Plot) Add ¶
Add adds a Plotters to the plot.
If the plotters implements DataRanger then the minimum and maximum values of the X and Y axes are changed if necessary to fit the range of the data.
When drawing the plot, Plotters are drawn in the order in which they were added to the plot.
func (*Plot) Draw ¶ added in v0.26.0
Draw draws a plot to a draw.Canvas.
Plotters are drawn in the order in which they were added to the plot. Plotters that implement the GlyphBoxer interface will have their GlyphBoxes taken into account when padding the plot so that none of their glyphs are clipped.
func (*Plot) Save ¶
Save saves the plot to an image file. The file format is determined by the extension.
Supported extensions are:
.eps, .jpg, .jpeg, .json, .pdf, .png, .svg, .tex, .tif and .tiff.
If w or h are <= 0, the value is chosen such that it follows the Golden Ratio. If w and h are <= 0, the values are chosen such that they follow the Golden Ratio (the width is defaulted to vgimg.DefaultWidth).
type RatioPlot ¶ added in v0.27.0
type RatioPlot struct { Top *Plot Bottom *Plot // Tiles controls the layout of the 2x1 ratio-plot grid. // Tiles can be used to customize the padding between plots. Tiles draw.Tiles // Ratio controls how the vertical space is partioned between // the top and bottom plots. // The top plot will take (1-ratio)*height. // Default is 0.3. Ratio float64 }
func NewRatioPlot ¶ added in v0.27.0
func NewRatioPlot() *RatioPlot
func (*RatioPlot) Draw ¶ added in v0.27.0
Draw draws a ratio plot to a draw.Canvas.
Plotters are drawn in the order in which they were added to the plot. Plotters that implement the GlyphBoxer interface will have their GlyphBoxes taken into account when padding the plot so that none of their glyphs are clipped.
type S2D ¶
type S2D struct { Data plotter.XYer // GlyphStyle is the style of the glyphs drawn // at each point. draw.GlyphStyle // LineStyle is the style of the line drawn // connecting each point. // Use zero width to disable. LineStyle draw.LineStyle // XErrs is the x error bars plotter. XErrs *plotter.XErrorBars // YErrs is the y error bars plotter. YErrs *plotter.YErrorBars // Band displays a colored band between the y-min and y-max error bars. Band *Band // Steps controls the style of the connecting // line (NoSteps, HiSteps, etc...) Steps StepsKind }
S2D plots a set of 2-dim points with error bars.
Example (WithBand) ¶
ExampleS2D_withBand draws some scatter points with their error bars and a band
Output:
Example (WithErrorBars) ¶
ExampleS2D_withErrorBars draws some scatter points with their error bars.
Output:
Example (WithStepsKind) ¶
ExampleS2D_withStepsKind draws some scatter points with their error bars, using a step-like style
Output:
Example (WithStepsKind_withBand) ¶
ExampleS2D_withSteps_withBand draws some scatter points with their error bars, using a step-like style together with a band
Output:
func (*S2D) DataRange ¶
DataRange returns the minimum and maximum x and y values, implementing the plot.DataRanger interface.
func (*S2D) GlyphBoxes ¶
GlyphBoxes returns a slice of plot.GlyphBoxes, implementing the plot.GlyphBoxer interface.
type Style ¶
type Style struct { Fonts struct { Name string // font name of this style Default font.Font // font used for the plot Title font.Font // font used for the plot title Label font.Font // font used for the plot labels Legend font.Font // font used for the plot legend Tick font.Font // font used for the plot's axes' ticks Cache *font.Cache // cache of fonts for this plot. } TextHandler text.Handler }
Style stores a given plot style.
var ( // DefaultStyle is the default style used for hplot plots. DefaultStyle Style )
type Ticks ¶ added in v0.25.0
type Ticks struct { N int // N is the suggested number of major ticks to display. // Format is an optional major-tick formatter. // If empty, a format will be automatically chosen. Format string }
Ticks implements plot.Ticker. Ticks allows to specify the maximum number of major ticks to display. The zero value of Ticks display a maximum number of 3 major ticks.
type TiledPlot ¶
type TiledPlot struct { Plots []*Plot Tiles draw.Tiles Align bool // whether to align all tiles axes }
TiledPlot is a regularly spaced set of plots, aranged as tiles.
func NewTiledPlot ¶
NewTiledPlot creates a new set of plots aranged as tiles. By default, NewTiledPlot will put a 1 vg.Length space between each plot.
func (*TiledPlot) Draw ¶
Draw draws the tiled plot to a draw.Canvas.
Each non-nil plot.Plot in the aranged set of tiled plots is drawn inside its dedicated sub-canvas, using hplot.Plot.Draw.
func (*TiledPlot) Plot ¶
Plot returns the plot at the i-th column and j-th row in the set of tiles. (0,0) is at the top-left of the set of tiles.
func (*TiledPlot) Save ¶
Save saves the plots to an image file. The file format is determined by the extension.
Supported extensions are the same ones than hplot.Save.
If w or h are <= 0, the value is chosen such that it follows the Golden Ratio. If w and h are <= 0, the values are chosen such that they follow the Golden Ratio (the width is defaulted to vgimg.DefaultWidth).
Source Files
¶
Directories
¶
Path | Synopsis |
---|---|
cmd
|
|
hplot
hplot is a simple gnuplot-like command to create plots
|
hplot is a simple gnuplot-like command to create plots |
internal
|
|
Package vgop provides tools to record a set of vector graphics operations.
|
Package vgop provides tools to record a set of vector graphics operations. |