Golang vg.Points函數代碼示例

// NewBoxPlot returns a new BoxPlot that represents
// the distribution of the given values.  The style of
// the box plot is that used for Tukey's schematic
// plots is ``Exploratory Data Analysis.''
//
// An error is returned if the boxplot is created with
// no values.
//
// The fence values are 1.5x the interquartile before
// the first quartile and after the third quartile.  Any
// value that is outside of the fences are drawn as
// Outside points.  The adjacent values (to which the
// whiskers stretch) are the minimum and maximum
// values that are not outside the fences.
func NewBoxPlot(w vg.Length, loc float64, values Valuer) (*BoxPlot, error) {
	if w < 0 {
		return nil, errors.New("Negative boxplot width")
	}

	b := new(BoxPlot)
	var err error
	if b.fiveStatPlot, err = newFiveStat(w, loc, values); err != nil {
		return nil, err
	}

	b.Width = w
	b.CapWidth = 3 * w / 4

	b.GlyphStyle = DefaultGlyphStyle
	b.BoxStyle = DefaultLineStyle
	b.MedianStyle = DefaultLineStyle
	b.WhiskerStyle = plot.LineStyle{
		Width:  vg.Points(0.5),
		Dashes: []vg.Length{vg.Points(4), vg.Points(2)},
	}

	if len(b.Values) == 0 {
		b.Width = 0
		b.GlyphStyle.Radius = 0
		b.BoxStyle.Width = 0
		b.MedianStyle.Width = 0
		b.WhiskerStyle.Width = 0
	}

	return b, nil
}

// Example_groupedBoxPlots draws vertical boxplots.
func Example_groupedBoxPlots() *plot.Plot {
	rand.Seed(int64(0))
	n := 100
	uniform := make(plotter.Values, n)
	normal := make(plotter.Values, n)
	expon := make(plotter.Values, n)
	for i := 0; i < n; i++ {
		uniform[i] = rand.Float64()
		normal[i] = rand.NormFloat64()
		expon[i] = rand.ExpFloat64()
	}

	p, err := plot.New()
	if err != nil {
		panic(err)
	}
	p.Title.Text = "Box Plot"
	p.Y.Label.Text = "plotter.Values"

	w := vg.Points(20)
	for x := 0.0; x < 3.0; x++ {
		b0 := must(plotter.NewBoxPlot(w, x, uniform)).(*plotter.BoxPlot)
		b0.Offset = -w - vg.Points(3)
		b1 := must(plotter.NewBoxPlot(w, x, normal)).(*plotter.BoxPlot)
		b2 := must(plotter.NewBoxPlot(w, x, expon)).(*plotter.BoxPlot)
		b2.Offset = w + vg.Points(3)
		p.Add(b0, b1, b2)
	}

	// Set the X axis of the plot to nominal with
	// the given names for x=0, x=1 and x=2.
	p.NominalX("Group 0", "Group 1", "Group 2")
	return p
}

// Example_groupedHorizontalBoxPlots draws vertical boxplots.
func Example_groupedHorizontalBoxPlots() *plot.Plot {
	rand.Seed(int64(0))
	n := 100
	uniform := make(plotter.Values, n)
	normal := make(plotter.Values, n)
	expon := make(plotter.Values, n)
	for i := 0; i < n; i++ {
		uniform[i] = rand.Float64()
		normal[i] = rand.NormFloat64()
		expon[i] = rand.ExpFloat64()
	}

	p, err := plot.New()
	if err != nil {
		panic(err)
	}
	p.Title.Text = "Box Plot"
	p.Y.Label.Text = "plotter.Values"

	w := vg.Points(20)
	for y := 0.0; y < 3.0; y++ {
		b0 := must(plotter.MakeHorizBoxPlot(w, y, uniform)).(plotter.HorizBoxPlot)
		b0.Offset = -w - vg.Points(3)
		b1 := must(plotter.MakeHorizBoxPlot(w, y, normal)).(plotter.HorizBoxPlot)
		b2 := must(plotter.MakeHorizBoxPlot(w, y, expon)).(plotter.HorizBoxPlot)
		b2.Offset = w + vg.Points(3)
		p.Add(b0, b1, b2)
	}
	p.NominalY("Group 0", "Group 1", "Group 2")
	return p
}

func test_point() {
	rand.Seed(int64(0))
	points_data := randomPoint(200)
	points_data2 := randomPoint(50)
	p, err := plot.New()
	if err != nil {
		panic(err)
	}

	p.Title.Text = "Points"
	p.X.Label.Text = "X"
	p.Y.Label.Text = "Y"

	bs, _ := plotter.NewBubbles(points_data, vg.Points(5), vg.Points(5))
	bs2, _ := plotter.NewBubbles(points_data2, vg.Points(5), vg.Points(5))

	bs.Color = color.RGBA{R: 255, G: 0, B: 0, A: 255}
	bs2.Color = color.RGBA{R: 0, G: 255, B: 0, A: 255}
	p.Add(bs)
	p.Add(bs2)

	if err := p.Save(10, 10, "points.png"); err != nil {
		panic(err)
	}
}

// Example_boxPlots draws vertical boxplots.
func Example_boxPlots() *plot.Plot {
	rand.Seed(int64(0))
	n := 100
	uniform := make(plotter.Values, n)
	normal := make(plotter.Values, n)
	expon := make(plotter.Values, n)
	for i := 0; i < n; i++ {
		uniform[i] = rand.Float64()
		normal[i] = rand.NormFloat64()
		expon[i] = rand.ExpFloat64()
	}

	p, err := plot.New()
	if err != nil {
		panic(err)
	}
	p.Title.Text = "Box Plot"
	p.Y.Label.Text = "plotter.Values"

	// Make boxes for our data and add them to the plot.
	p.Add(must(plotter.NewBoxPlot(vg.Points(20), 0, uniform)).(*plotter.BoxPlot),
		must(plotter.NewBoxPlot(vg.Points(20), 1, normal)).(*plotter.BoxPlot),
		must(plotter.NewBoxPlot(vg.Points(20), 2, expon)).(*plotter.BoxPlot))

	// Set the X axis of the plot to nominal with
	// the given names for x=0, x=1 and x=2.
	p.NominalX("Uniform\nDistribution", "Normal\nDistribution",
		"Exponential\nDistribution")
	return p
}

// Draw the plotinum logo.
func Example_logo() *plot.Plot {
	p, err := plot.New()
	if err != nil {
		panic(err)
	}

	plotter.DefaultLineStyle.Width = vg.Points(1)
	plotter.DefaultGlyphStyle.Radius = vg.Points(3)

	p.Y.Tick.Marker = plot.ConstantTicks([]plot.Tick{
		{0, "0"}, {0.25, ""}, {0.5, "0.5"}, {0.75, ""}, {1, "1"},
	})
	p.X.Tick.Marker = plot.ConstantTicks([]plot.Tick{
		{0, "0"}, {0.25, ""}, {0.5, "0.5"}, {0.75, ""}, {1, "1"},
	})

	pts := plotter.XYs{{0, 0}, {0, 1}, {0.5, 1}, {0.5, 0.6}, {0, 0.6}}
	line := must(plotter.NewLine(pts)).(*plotter.Line)
	scatter := must(plotter.NewScatter(pts)).(*plotter.Scatter)
	p.Add(line, scatter)

	pts = plotter.XYs{{1, 0}, {0.75, 0}, {0.75, 0.75}}
	line = must(plotter.NewLine(pts)).(*plotter.Line)
	scatter = must(plotter.NewScatter(pts)).(*plotter.Scatter)
	p.Add(line, scatter)

	pts = plotter.XYs{{0.5, 0.5}, {1, 0.5}}
	line = must(plotter.NewLine(pts)).(*plotter.Line)
	scatter = must(plotter.NewScatter(pts)).(*plotter.Scatter)
	p.Add(line, scatter)

	return p
}

// makeLegend returns a legend with the default
// parameter settings.
func makeLegend() (Legend, error) {
	font, err := vg.MakeFont(defaultFont, vg.Points(12))
	if err != nil {
		return Legend{}, err
	}
	return Legend{
		ThumbnailWidth: vg.Points(20),
		TextStyle:      TextStyle{Font: font},
	}, nil
}

func DataTableToPng(b *bytes.Buffer, dt *db.DataTable, title string, width, height float64, xLabel string) error {
	p, err := plot.New()
	if err != nil {
		return err
	}

	p.Title.Text = title
	p.X.Label.Text = xLabel
	p.Y.Label.Text = "msec" // TODO: Fix this.

	// TODO: need new ticker function to handle equalX (while keeping xLabel as selected)
	if xLabel == common.TimeName {
		p.X.Tick.Marker = TimeTicks
	}
	p.Legend.Top = true

	numColumns := len(dt.ColumnNames)
	lines := make([]plotter.XYs, numColumns-1) // Skip X column.

	for _, dRow := range dt.Data {
		xp := (*dRow)[0]
		if xp != nil {
			for col := 1; col < numColumns; col++ { // Skip X column.
				yp := (*dRow)[col]
				if yp != nil {
					lines[col-1] = append(lines[col-1], struct{ X, Y float64 }{X: *xp, Y: *yp})
				}
			}
		}
	}

	colorList := getColors(numColumns - 1) // Skip X column.

	for i, line := range lines {
		columnName := dt.ColumnNames[i+1]
		l, err := plotter.NewLine(line)
		if err != nil {
			return err
		}
		if strings.Index(columnName, common.RegressNamePrefix) == 0 { // If regression value.
			l.LineStyle.Color = color.RGBA{255, 0, 0, 255}
			l.LineStyle.Width = vg.Points(2.0)
		} else {
			l.LineStyle.Color = colorList[i]
			l.LineStyle.Width = vg.Points(1.5)
		}
		p.Add(l)
		p.Legend.Add(columnName, l)
	}

	tPng := time.Now()
	drawPng(b, p, width, height)
	glog.V(3).Infof("PERF: makePng time: %v", time.Now().Sub(tPng))
	return nil
}

// NewBoxPlot returns a new BoxPlot that represents
// the distribution of the given values.  The style of
// the box plot is that used for Tukey's schematic
// plots is ``Exploratory Data Analysis.''
//
// An error is returned if the boxplot is created with
// no values.
//
// The fence values are 1.5x the interquartile before
// the first quartile and after the third quartile.  Any
// value that is outside of the fences are drawn as
// Outside points.  The adjacent values (to which the
// whiskers stretch) are the minimum and maximum
// values that are not outside the fences.
func NewBoxPlot(w vg.Length, loc float64, values Valuer) *BoxPlot {
	b := new(BoxPlot)
	b.Location = loc
	b.Width = w
	b.CapWidth = 3 * w / 4
	b.GlyphStyle = DefaultGlyphStyle
	b.BoxStyle = DefaultLineStyle
	b.MedianStyle = DefaultLineStyle
	b.WhiskerStyle = plot.LineStyle{
		Width:  vg.Points(0.5),
		Dashes: []vg.Length{vg.Points(4), vg.Points(2)},
	}

	b.Values = CopyValues(values)
	sorted := CopyValues(values)
	sort.Float64s(sorted)
	if len(sorted) == 0 {
		b.Width = 0
		b.GlyphStyle.Radius = 0
		b.BoxStyle.Width = 0
		b.MedianStyle.Width = 0
		b.WhiskerStyle.Width = 0
		return b
	} else if len(sorted) == 1 {
		b.Median = sorted[0]
		b.Quartile1 = sorted[0]
		b.Quartile3 = sorted[0]
	} else {
		b.Median = median(sorted)
		b.Quartile1 = median(sorted[:len(sorted)/2])
		b.Quartile3 = median(sorted[len(sorted)/2:])
	}
	b.Min = sorted[0]
	b.Max = sorted[len(sorted)-1]

	low := b.Quartile1 - 1.5*(b.Quartile3-b.Quartile1)
	high := b.Quartile3 + 1.5*(b.Quartile3-b.Quartile1)
	b.AdjLow = math.Inf(1)
	b.AdjHigh = math.Inf(-1)
	for i, v := range b.Values {
		if v > high || v < low {
			b.Outside = append(b.Outside, i)
			continue
		}
		if v < b.AdjLow {
			b.AdjLow = v
		}
		if v > b.AdjHigh {
			b.AdjHigh = v
		}
	}

	return b
}

func linesPlot() *plot.Plot {
	// Get some random points
	rand.Seed(int64(0))
	n := 10
	scatterData := randomPoints(n)
	lineData := randomPoints(n)
	linePointsData := randomPoints(n)

	// Create a new plot, set its title and
	// axis labels.
	p, err := plot.New()
	if err != nil {
		panic(err)
	}
	p.Title.Text = "Points Example"
	p.X.Label.Text = "X"
	p.Y.Label.Text = "Y"
	// Draw a grid behind the data
	p.Add(plotter.NewGrid())

	// Make a scatter plotter and set its style.
	s, err := plotter.NewScatter(scatterData)
	if err != nil {
		panic(err)
	}
	s.GlyphStyle.Color = color.RGBA{R: 255, B: 128, A: 255}

	// Make a line plotter and set its style.
	l, err := plotter.NewLine(lineData)
	if err != nil {
		panic(err)
	}
	l.LineStyle.Width = vg.Points(1)
	l.LineStyle.Dashes = []vg.Length{vg.Points(5), vg.Points(5)}
	l.LineStyle.Color = color.RGBA{B: 255, A: 255}

	// Make a line plotter with points and set its style.
	lpLine, lpPoints, err := plotter.NewLinePoints(linePointsData)
	if err != nil {
		panic(err)
	}
	lpLine.Color = color.RGBA{G: 255, A: 255}
	lpPoints.Shape = plot.PyramidGlyph{}
	lpPoints.Color = color.RGBA{R: 255, A: 255}

	// Add the plotters to the plot, with a legend
	// entry for each
	p.Add(s, l, lpLine, lpPoints)
	p.Legend.Add("scatter", s)
	p.Legend.Add("line", l)
	p.Legend.Add("line points", lpLine, lpPoints)
	return p
}

// Example_horizontalBoxPlots draws horizontal boxplots
// with some labels on their points.
func Example_horizontalBoxPlots() *plot.Plot {
	rand.Seed(int64(0))
	n := 100
	uniform := make(valueLabels, n)
	normal := make(valueLabels, n)
	expon := make(valueLabels, n)
	for i := 0; i < n; i++ {
		uniform[i].Value = rand.Float64()
		uniform[i].Label = fmt.Sprintf("%4.4f", uniform[i].Value)
		normal[i].Value = rand.NormFloat64()
		normal[i].Label = fmt.Sprintf("%4.4f", normal[i].Value)
		expon[i].Value = rand.ExpFloat64()
		expon[i].Label = fmt.Sprintf("%4.4f", expon[i].Value)
	}

	p, err := plot.New()
	if err != nil {
		panic(err)
	}
	p.Title.Text = "Horizontal Box Plot"
	p.X.Label.Text = "plotter.Values"

	// Make boxes for our data and add them to the plot.
	uniBox := must(plotter.MakeHorizBoxPlot(vg.Points(20), 0, uniform)).(plotter.HorizBoxPlot)
	uniLabels, err := uniBox.OutsideLabels(uniform)
	if err != nil {
		panic(err)
	}

	normBox := must(plotter.MakeHorizBoxPlot(vg.Points(20), 1, normal)).(plotter.HorizBoxPlot)
	normLabels, err := normBox.OutsideLabels(normal)
	if err != nil {
		panic(err)
	}

	expBox := must(plotter.MakeHorizBoxPlot(vg.Points(20), 2, expon)).(plotter.HorizBoxPlot)
	expLabels, err := expBox.OutsideLabels(expon)
	if err != nil {
		panic(err)
	}
	p.Add(uniBox, uniLabels, normBox, normLabels, expBox, expLabels)

	// Add a GlyphBox plotter for debugging.
	p.Add(plotter.NewGlyphBoxes())

	// Set the Y axis of the plot to nominal with
	// the given names for y=0, y=1 and y=2.
	p.NominalY("Uniform\nDistribution", "Normal\nDistribution",
		"Exponential\nDistribution")
	return p
}

// Example_verticalBoxPlots draws vertical boxplots
// with some labels on their points.
func Example_verticalBoxPlots() *plot.Plot {
	rand.Seed(int64(0))
	n := 100
	uniform := make(valueLabels, n)
	normal := make(valueLabels, n)
	expon := make(valueLabels, n)
	for i := 0; i < n; i++ {
		uniform[i].Value = rand.Float64()
		uniform[i].Label = fmt.Sprintf("%4.4f", uniform[i].Value)
		normal[i].Value = rand.NormFloat64()
		normal[i].Label = fmt.Sprintf("%4.4f", normal[i].Value)
		expon[i].Value = rand.ExpFloat64()
		expon[i].Label = fmt.Sprintf("%4.4f", expon[i].Value)
	}

	p, err := plot.New()
	if err != nil {
		panic(err)
	}
	p.Title.Text = "Box Plot"
	p.Y.Label.Text = "plotter.Values"

	// Make boxes for our data and add them to the plot.
	uniBox := plotter.NewBoxPlot(vg.Points(20), 0, uniform)
	uniLabels, err := uniBox.OutsideLabels(uniform)
	if err != nil {
		panic(err)
	}

	normBox := plotter.NewBoxPlot(vg.Points(20), 1, normal)
	normLabels, err := normBox.OutsideLabels(normal)
	if err != nil {
		panic(err)
	}

	expBox := plotter.NewBoxPlot(vg.Points(20), 2, expon)
	expLabels, err := expBox.OutsideLabels(expon)
	if err != nil {
		panic(err)
	}

	p.Add(uniBox, uniLabels, normBox, normLabels, expBox, expLabels)

	// Set the X axis of the plot to nominal with
	// the given names for x=0, x=1 and x=2.
	p.NominalX("Uniform\nDistribution", "Normal\nDistribution",
		"Exponential\nDistribution")
	return p
}

func histPlot() *plot.Plot {
	// Draw some random values from the standard
	// normal distribution.
	rand.Seed(int64(0))
	v := make(plotter.Values, 1000)
	for i := range v {
		v[i] = rand.NormFloat64()
	}

	// Make a plot and set its title.
	p, err := plot.New()
	if err != nil {
		panic(err)
	}
	p.Title.Text = "Histogram"

	// Create a histogram of our values drawn
	// from the standard normal.
	h, err := plotter.NewHist(v, 16)
	if err != nil {
		panic(err)
	}
	// Normalize the area under the histogram to
	// sum to one.
	h.Normalize(1)
	p.Add(h)

	// The normal distribution function
	norm := plotter.NewFunction(stdNorm)
	norm.Color = color.RGBA{R: 255, A: 255}
	norm.Width = vg.Points(2)
	p.Add(norm)
	return p
}

func plotData(name string, xs, ys []float64) {
	p, err := plot.New()
	if err != nil {
		fmt.Printf("Cannot create new plot: %s\n", err)
		return
	}
	p.Title.Text = "Chernoff lower bound"
	p.X.Label.Text = "Sigma"
	p.X.Min = 0.2
	p.X.Max = 0.5
	p.Y.Label.Text = "Probability of correct detection"
	p.Y.Min = 0.9
	p.Y.Max = 1.0
	p.Add(plotter.NewGrid())

	l := plotter.NewLine(dataset(xs, ys))
	l.LineStyle.Width = vg.Points(1)
	//l.LineStyle.Dashes = []vg.Length(vg.Points(5), vg.Points(5))
	l.LineStyle.Color = color.RGBA{B: 255, A: 255}

	p.Add(l)
	if err := p.Save(4, 4, name); err != nil {
		fmt.Printf("Save to '%s' failed: %s\n", name, err)
	}
}

func plotData(name string, us, ys, ts, fs []float64) {
	p, err := plot.New()
	if err != nil {
		fmt.Printf("Cannot create new plot: %s\n", err)
		return
	}
	p.Title.Text = "Least-square fit of convex function"
	p.X.Min = -0.1
	p.X.Max = 2.3
	p.Y.Min = -1.1
	p.Y.Max = 7.2
	p.Add(plotter.NewGrid())

	pts := plotter.NewScatter(dataset(us, ys))
	pts.GlyphStyle.Color = color.RGBA{R: 255, A: 255}

	fit := plotter.NewLine(dataset(ts, fs))
	fit.LineStyle.Width = vg.Points(1)
	fit.LineStyle.Color = color.RGBA{B: 255, A: 255}

	p.Add(pts)
	p.Add(fit)
	if err := p.Save(4, 4, name); err != nil {
		fmt.Printf("Save to '%s' failed: %s\n", name, err)
	}
}