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
}
// An example of making a histogram.
func Example_histogram() *plot.Plot {
rand.Seed(int64(0))
n := 10000
vals := make(plotter.Values, n)
for i := 0; i < n; i++ {
vals[i] = rand.NormFloat64()
}
p, err := plot.New()
if err != nil {
panic(err)
}
p.Title.Text = "Histogram"
h, err := plotter.NewHist(vals, 16)
if err != nil {
panic(err)
}
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
}
// Plots the historgram using plotinum
func Histogram(r RetCalc) {
//eb := all_paths.End_balances()
eb := make([]float64, len(r.All_paths), len(r.All_paths))
incs := r.RunIncomes()
for i := range incs {
eb[i] = incs[i]
}
v := make(plotter.Values, len(eb))
for i := range v {
v[i] = eb[i]
}
p, err := plot.New()
if err != nil {
panic(err)
}
p.Title.Text = "Histogram"
h, err := plotter.NewHist(v, 100)
if err != nil {
panic(err)
}
//h.Normalize(1)
p.Add(h)
if err := p.Save(4, 4, "hist.png"); err != nil {
panic(err)
}
fmt.Println(h)
}
func Histogram(popFitness []float64, selFitness []float64, gen int) {
popValues := make(plotter.Values, len(popFitness))
selValues := make(plotter.Values, len(selFitness))
for i := range popValues {
popValues[i] = popFitness[i]
}
for j := range selValues {
selValues[j] = selFitness[j]
}
p, err := plot.New()
if err != nil {
panic(err)
}
p.Title.Text = fmt.Sprint("Generation ", gen)
p.X.Label.Text = "Fitness"
p.Y.Label.Text = "Number of individuals"
hPop, err := plotter.NewHist(popValues, 10)
if err != nil {
panic(err)
}
// hPop.Normalize(100)
gray := color.RGBA{0, 0, 0, 64}
hPop.FillColor = gray
hSel, err := plotter.NewHist(selValues, 10)
if err != nil {
panic(err)
}
//hSel.Normalize(100)
blue := color.RGBA{0, 61, 245, 64}
hSel.FillColor = blue
p.X.Min, p.X.Max = 0.0, 1.0
p.Y.Min, p.Y.Max = 0, float64(len(popValues))
p.Add(hPop)
p.Add(hSel)
if err := p.Save(8, 4, fmt.Sprintf("hist_gen_%v.svg", gen)); err != nil {
panic(err)
}
}
// createHistogram creates a histogram from given data and bin numbers
func createHistogram(data []float64, n int) {
p, err := plot.New()
if err != nil {
panic(err)
}
p.Add(plotter.NewGrid())
histdata := valuer{data}
p.Add(plotter.NewHist(histdata, n))
p.X.Label.Text = "time / ps"
p.Y.Label.Text = "frequency"
p.Title.Text = fmt.Sprintf("Frequency of lifetime data from lifetime.txt. %v bins.", n)
if err := p.Save(5, 5, fmt.Sprintf("out/Histogram with %v bins.png", n)); err != nil {
panic(err)
}
}
// Builds a histogram from a []float64 slice :)
func HistoFromSlice(slice []float64) *plotter.Histogram {
fmt.Println("HistoFromSlice() call - slice analytics:")
fmt.Printf("Max: %f\n", analytics.MaxF64(slice))
fmt.Printf("Min: %f\n", analytics.MinF64(slice))
fmt.Printf("Avg: %f\n", analytics.AvgF64(slice))
v := make(plotter.Values, len(slice))
for i := range v {
v[i] = slice[i]
}
h, err := plotter.NewHist(v, 150)
if err != nil {
panic(err)
}
return h
}
