leo
cffbcd9866
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* handle special cases * extend title, description * set custom x axis description
411 lines
10 KiB
Go
411 lines
10 KiB
Go
// Copyright 2023 wanderer <a_mirre at utb dot cz>
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// SPDX-License-Identifier: GPL-3.0-or-later
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package algo
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import (
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"fmt"
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"log"
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"strconv"
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"strings"
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"sync"
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"time"
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"git.dotya.ml/wanderer/math-optim/report"
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"git.dotya.ml/wanderer/math-optim/stats"
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"git.dotya.ml/wanderer/math-optim/util"
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"gonum.org/v1/gonum/floats"
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"gonum.org/v1/plot"
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"gonum.org/v1/plot/plotter"
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"gonum.org/v1/plot/plotutil"
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"gonum.org/v1/plot/vg"
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)
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const (
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preferredFont = "Mono"
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titlePreferredFont = "Sans"
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yAxisLabel = "f(x)"
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xAxisLabel = "Generations"
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)
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// PlotMeanValsMulti creates plots for every member of 'stats.AlgoMeanVals' it
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// is handed and saves them as 'result.Pic's results into a package-global
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// slice.
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func PlotMeanValsMulti(
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w *sync.WaitGroup,
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dimens, iterations int,
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bench, fPrefix, fExt string,
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algoMeanVals ...stats.AlgoMeanVals,
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) {
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defer w.Done()
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// track time.
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start := time.Now()
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pWidth := 13 * vg.Centimeter
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pHeight := 13 * vg.Centimeter
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plotter.DefaultFont.Typeface = preferredFont
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plotter.DefaultLineStyle.Width = vg.Points(2.0)
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p := plot.New()
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pic := report.NewPic()
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p.Title.Text = fmt.Sprintf(
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"Comparison of Means (%dI) -\n%s (%dD)",
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iterations, bench, dimens,
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)
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p.X.Label.Text = "Objective func. evaluations"
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p.X.Label.TextStyle.Font.Variant = preferredFont
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p.X.Label.TextStyle.Font.Weight = 1 // Medium
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p.X.Tick.Label.Font.Variant = preferredFont
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p.Y.Label.Text = yAxisLabel
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p.Y.Label.TextStyle.Font.Variant = preferredFont
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p.Y.Label.TextStyle.Font.Weight = 1 // Medium
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p.Y.Tick.Label.Font.Variant = preferredFont
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p.Title.TextStyle.Font.Size = 14.5
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p.Title.TextStyle.Font.Variant = titlePreferredFont
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p.Title.TextStyle.Font.Weight = 2 // SemiBold
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p.Title.Padding = 3 * vg.Millimeter
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p.Legend.TextStyle.Font.Variant = preferredFont
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p.Legend.TextStyle.Font.Size = 10
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p.Legend.Top = true
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p.Legend.Padding = 2 * vg.Millimeter
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lines := make([]interface{}, 0)
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for _, v := range algoMeanVals {
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// mark the end of the X axis with the greatest of len(v)
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if greatest := float64(len(v.MeanVals)); greatest > p.X.Max {
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p.X.Max = greatest
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}
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if min := floats.Min(v.MeanVals); min < p.Y.Min {
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p.Y.Min = min
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}
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if max := floats.Max(v.MeanVals); max > p.Y.Max {
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p.Y.Max = max
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}
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pts := make(plotter.XYs, len(v.MeanVals))
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// fill the plotter with datapoints.
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for k, res := range v.MeanVals {
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pts[k].X = float64(k)
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pts[k].Y = res
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}
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lines = append(lines, v.Title, pts)
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}
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err := plotutil.AddLines(
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p,
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lines...,
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)
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if err != nil {
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log.Panic(err)
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}
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filename := util.SanitiseFName(
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fmt.Sprintf("%s%scomparison-of-means-%dI-%s-%02dD",
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report.GetPicsDir(),
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fPrefix,
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iterations,
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bench,
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dimens,
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),
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)
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// set pic file path and caption.
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pic.FilePath = filename
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// pic.Caption = strings.ReplaceAll(filename, " ", "~")
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pic.Caption = strings.ReplaceAll(
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fmt.Sprintf("Comparison of Means (%dI) - %s (%dD)",
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iterations, bench, dimens,
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),
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" ", "~")
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pic.Bench = bench
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elapsed := time.Since(start)
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info := fmt.Sprintf("saving img to file: %s%s [generated in %s]",
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filename, fExt, elapsed,
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)
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log.Println(info)
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// Save the plot to a file using the above-constructed 'filename'.
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if err := p.Save(
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pWidth,
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pHeight,
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filename+fExt,
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); err != nil {
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panic(err)
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}
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mCoMPL.Lock()
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comparisonOfMeansPicList.Pics = append(comparisonOfMeansPicList.Pics, *pic)
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mCoMPL.Unlock()
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}
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func plotMeanVals(meanVals []float64, title string, fes int) *plot.Plot {
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plotter.DefaultFont.Typeface = preferredFont
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plotter.DefaultLineStyle.Width = vg.Points(2.0)
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if fes != len(meanVals) {
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log.Fatalf("meanVals - FES mismatch: %d vs %d , bailing\n", fes, len(meanVals))
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}
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p := plot.New()
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// pic := report.NewPic()
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p.Title.Text = "Mean - " + title
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p.X.Label.Text = xAxisLabel
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// p.X.Label.Padding = 8 * vg.Millimeter
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p.X.Label.TextStyle.Font.Variant = preferredFont
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p.X.Label.TextStyle.Font.Weight = 1 // Medium
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p.X.Tick.Label.Font.Variant = preferredFont
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// p.X.Padding = 2 * vg.Millimeter
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p.Y.Label.Text = yAxisLabel
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// p.Y.Label.Padding = 2 * vg.Millimeter
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p.Y.Label.TextStyle.Font.Variant = preferredFont
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p.Y.Label.TextStyle.Font.Weight = 1 // Medium
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p.Y.Tick.Label.Font.Variant = preferredFont
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// p.Y.Padding = 1 * vg.Millimeter
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p.Title.TextStyle.Font.Size = 14.5
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p.Title.TextStyle.Font.Variant = titlePreferredFont
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p.Title.TextStyle.Font.Weight = 2 // SemiBold
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// p.Title.Padding = 5 * vg.Millimeter
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p.Title.Padding = 3 * vg.Millimeter
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// mark the end of the X axis with len(meanVals).
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p.X.Max = float64(len(meanVals))
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p.Y.Min = floats.Min(meanVals)
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p.Y.Max = floats.Max(meanVals)
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pts := make(plotter.XYs, len(meanVals))
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// fill the plotter with datapoints.
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for k, res := range meanVals {
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pts[k].X = float64(k)
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pts[k].Y = res
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}
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lines := make([]interface{}, 0)
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lines = append(lines, pts)
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err := plotutil.AddLines(
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p,
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lines...,
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)
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if err != nil {
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log.Panic(err)
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}
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return p
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}
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// violating gocognit 30, TODO(me): still split this up. fPrefix is always "plot" according to unparam.
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// nolint: gocognit,unparam
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func plotAllDims(algoStats []stats.Stats, fPrefix, fExt string, ch chan report.PicList, chMean chan report.PicList) {
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start := time.Now()
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picsDir := report.GetPicsDir()
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// create picsDir (if not exists), fail on error, no point in going on
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// parsing algoStats and computing images if we cannot save them.
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if err := util.CreatePath(picsDir); err != nil {
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log.Fatalln("went to create picsDir, there was an issue: ", err)
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}
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pL := report.NewPicList()
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pics := make([]report.Pic, 0)
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pLMean := report.NewPicList()
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picsMean := make([]report.Pic, 0)
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// since the algoStats only contains results of a single algo, it's safe to
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// set the value like this.
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pL.Algo = algoStats[0].Algo
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pLMean.Algo = algoStats[0].Algo
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pWidth := 13 * vg.Centimeter
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pHeight := 13 * vg.Centimeter
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plotter.DefaultFont.Typeface = preferredFont
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plotter.DefaultLineStyle.Width = vg.Points(1.5)
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for _, s := range algoStats {
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p := plot.New()
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pic := report.NewPic()
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p.Title.Text = fmt.Sprintf("D: %d, G: %d, I: %d",
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s.Dimens,
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s.Generations,
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s.Iterations,
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)
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// For differential evolution, add params to title.
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if strings.Contains(s.Algo, "DE") {
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p.Title.Text += fmt.Sprintf(",\nNP: %d, F: ", s.NP) +
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strconv.FormatFloat(s.F, 'f', -1, 64) + ", CR: " +
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strconv.FormatFloat(s.CR, 'f', -1, 64)
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}
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// this is latex-rendered.
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pic.Caption = strings.ReplaceAll(p.Title.Text, " ", "~")
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// since a single stat slice of algoStats only contains results of a
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// single bench func, it's safe to set the value like this.
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pL.Bench = s.BenchFuncStats[0].BenchName
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pLMean.Bench = s.BenchFuncStats[0].BenchName
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if strings.Contains(s.Algo, "DE") {
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p.X.Label.Text = "FES"
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} else {
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p.X.Label.Text = xAxisLabel
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}
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p.X.Label.TextStyle.Font.Variant = preferredFont
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p.X.Label.TextStyle.Font.Weight = 1 // Medium
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p.X.Tick.Label.Font.Variant = preferredFont
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p.Y.Label.Text = yAxisLabel
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p.Y.Label.TextStyle.Font.Variant = preferredFont
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p.Y.Label.TextStyle.Font.Weight = 1 // Medium
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p.Y.Tick.Label.Font.Variant = preferredFont
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// p.Y.Padding = 1 * vg.Millimeter
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p.Title.TextStyle.Font.Size = 14.5
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p.Title.TextStyle.Font.Variant = titlePreferredFont
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p.Title.TextStyle.Font.Weight = 2 // SemiBold
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// p.Title.Padding = 5 * vg.Millimeter
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p.Title.Padding = 3 * vg.Millimeter
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// p.Legend.TextStyle.Font.Variant = preferredFontStyle
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// p.Legend.TextStyle.Font.Size = 8
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// p.Legend.Top = true
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// p.Legend.Padding = 0 * vg.Centimeter
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// p.Add(plotter.NewGrid())
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for _, dim := range s.BenchFuncStats {
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// infinite thanks to this SO comment for the interface "hack":
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// https://stackoverflow.com/a/44872993
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lines := make([]interface{}, 0)
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for _, iter := range dim.BenchResults {
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// mark the end of the X axis with len(iter.Results).
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p.X.Max = float64(len(iter.Results))
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if floats.Min(iter.Results) < p.Y.Min {
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p.Y.Min = floats.Min(iter.Results)
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}
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if floats.Max(iter.Results) > p.Y.Max {
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p.Y.Max = floats.Max(iter.Results)
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}
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pts := make(plotter.XYs, len(iter.Results))
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// fill the plotter with datapoints.
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for k, res := range iter.Results {
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pts[k].X = float64(k)
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pts[k].Y = res
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}
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// lines = append(lines, "#"+fmt.Sprint(j), pts)
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lines = append(lines, pts)
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}
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err := plotutil.AddLines(
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p,
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lines...,
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)
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if err != nil {
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// panic (don't panic, I know) instead of a hard exit.
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log.Panic(err)
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}
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// TODO(me): add Neighbourhood param
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// TODO(me): add search space percent param
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filename := fmt.Sprintf("%s%s-%s-%s-%dD-%dG-%dI",
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picsDir,
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fPrefix,
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util.SanitiseFName(s.Algo),
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util.SanitiseFName(dim.BenchName),
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s.Dimens,
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s.Generations,
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len(dim.BenchResults),
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)
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filenameMean := filename + util.SanitiseFName(" Mean")
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// NEVER EVER ATTEMPT TO INITIALISE THIS WITH `pic`!
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picMean := report.NewPic()
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meanTitle := fmt.Sprintf("D: %d, G: %d, I: %d",
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s.Dimens,
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s.Generations,
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s.Iterations,
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)
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// this is latex-rendered.
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picMean.Caption = "Mean - " + strings.ReplaceAll(meanTitle, " ", "~")
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// set pic file path (later used in tmpl generation)
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pic.FilePath = filename
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picMean.FilePath = filenameMean
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// get the *mean* plot.
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pMean := plotMeanVals(dim.MeanVals, meanTitle, s.Generations)
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elapsed := time.Since(start)
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info := fmt.Sprintf("saving img to file: %s(-Mean)%s [generated in %s]",
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filename, fExt, elapsed,
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)
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switch {
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case s.Algo == "Random Search":
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printRandomSearch(info)
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case strings.Contains(s.Algo, "Stochastic Hill Climbing"):
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printSHC(info)
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default:
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log.Println(info)
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}
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// Save the plot to a file using the above-constructed 'filename'.
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if err := p.Save(
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pWidth,
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pHeight,
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filename+fExt,
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); err != nil {
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panic(err)
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}
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// log.Println(filename + fExt)
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// save pic.
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pics = append(pics, *pic)
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// save plot of pMean.
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if err := pMean.Save(
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pWidth,
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pHeight,
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filenameMean+fExt,
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); err != nil {
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panic(err)
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}
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// save mean pic.
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picsMean = append(picsMean, *picMean)
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}
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}
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pL.Pics = pics
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pLMean.Pics = picsMean
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ch <- *pL
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chMean <- *pLMean
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}
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