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feat: add scatterplot svg library (#12)
* feat: add scatterplot svg library * [ADD]: README.md and increasing variables in ScatterPlot structure * [FIX]: type.gno * Feat: Better description of gnov * test CI PR * Fix: CI Checks fmt * Fix: Coding style * Fix: CI const -> type.gno * Fix: CI check type.gno * Fix: CI check scatterplot.gno * Fix: CI check scatterplot_test.gno * Add: godoc for niceStep function * Fix: Godoc format corrected * Name change and Godoc for RenderAxes * Fix: Name and README.md * Fix: Files name * Fix: Name of the package --------- Co-authored-by: Leon <[email protected]>
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‎packages/p/pierre115/gnovisual/README.md‎

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# GnoVisual
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Package `gnovisual` renders scatter plots as SVG images. It takes a list of (x, y) points and draws them as circles on a 2D canvas, with optional support for displaying a linear regression line.
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## Usage
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```go
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import "gno.land/p/pierre115/gnovisual"
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func main() {
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plot := scatterplot.ScatterPlot{
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Points: []scatterplot.Point{
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{X: 100, Y: 0, Label: "A"},
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{X: 101, Y: 20, Label: "B"},
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{X: 102, Y: 40, Label: "C"},
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{X: 103, Y: 60, Label: "D"},
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},
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Title: "Sales Growth",
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XAxis: "Years",
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YAxis: "Sales",
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FlagRe: true,
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Maxticks: 20,
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Width: 800,
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Height: 800,
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}
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svg := plot.Render()
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// Use the SVG output
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}
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```
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## API
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### Point
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```go
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type Point struct {
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X, Y float64 // Coordinates of the point
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Color string // Color of the point
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Label string // Label associated with the point
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}
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```
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### ScatterPlot
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```go
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type ScatterPlot struct {
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Points []Point // Data points to plot
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Title string // Plot title
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XAxis string // X-axis label
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YAxis string // Y-axis label
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FlagRe bool // Enable linear regression line (default: false)
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Maxticks int // Number of tick marks on axes
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Width int // Plot width in pixels
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Height int // Plot height in pixels
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}
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```
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## Features
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### Linear Regression
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Set `FlagRe` to `true` to display a linear regression line fitted to your data points. The regression equation will be displayed in the top-left corner of the plot.
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## Example
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Here's a complete example showing sales growth over time:
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```go
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plot := scatterplot.ScatterPlot{
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Points: []scatterplot.Point{
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{X: 2020, Y: 150, Label: "Q1"},
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{X: 2021, Y: 230, Label: "Q2"},
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{X: 2022, Y: 310, Label: "Q3"},
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{X: 2023, Y: 405, Label: "Q4"},
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},
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Title: "Quarterly Sales Performance",
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XAxis: "Year",
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YAxis: "Revenue (k$)",
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FlagRe: true,
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Maxticks: 10,
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Width: 600,
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Height: 400,
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}
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```
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This will generate an SVG scatter plot with a regression line showing the trend in sales growth.

‎packages/p/pierre115/gnovisual/gnomod.toml‎

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module = "gno.land/p/pierre115/gnovisual"
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gno = "0.9"

‎packages/p/pierre115/gnovisual/linearyflag.gno‎

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package gnovisual
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import (
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"math"
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"gno.land/p/nt/ufmt"
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)
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// Function to get slope and intercept with linear way
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func LinearRegression(points []Point) (slope, intercept float64) {
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n := float64(len(points))
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sumX := float64(0)
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sumY := float64(0)
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sumXY := float64(0)
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sumX2 := float64(0)
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for _, p := range points {
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sumX += p.X
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sumY += p.Y
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sumXY += p.X * p.Y
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sumX2 += p.X * p.X
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}
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slope = (n*sumXY - sumX*sumY) / (n*sumX2 - sumX*sumX)
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intercept = (sumY - slope*sumX) / n
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return
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}
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// Calcul the regression line and return as SVG string
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func RenderReFlag(points []Point, minX, maxX, minY, maxY float64, canvasWidth, canvasHeight int) string {
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slope, intercept := LinearRegression(points)
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xStart := minX
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xEnd := maxX
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yStart := slope*xStart + intercept
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yEnd := slope*xEnd + intercept
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// Normalize with the canvas data
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nx1 := 40 + (xStart-minX)/(maxX-minX)*float64(canvasWidth-60)
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ny1 := float64(canvasHeight-40) - (yStart-minY)/(maxY-minY)*float64(canvasHeight-60)
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nx2 := 40 + (xEnd-minX)/(maxX-minX)*float64(canvasWidth-60)
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ny2 := float64(canvasHeight-40) - (yEnd-minY)/(maxY-minY)*float64(canvasHeight-60)
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// calcul of angle
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dx := nx2 - nx1
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dy := ny2 - ny1
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angleRad := math.Atan2(dy, dx)
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angleDeg := angleRad * 180 / math.Pi
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svgOut := ""
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// SVG Rectangle as regression line
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svgOut += ufmt.Sprintf(
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`<rect x="%d" y="%d" width="%d" height="1" fill="black" transform="rotate(%.2f %d %d)"/>`,
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int(nx1), int(ny1),
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int(math.Hypot(nx2-nx1, ny2-ny1)),
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angleDeg, int(nx1), int(ny1),
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)
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// Equation of the line
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equation := ufmt.Sprintf("y = %.2fx + %.2f", slope, intercept)
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svgOut += ufmt.Sprintf(
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`<text x="50" y="20" style="font-size:12px;font-family:'Inter var',sans-serif;" fill="black">Equation : %s</text>`,
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equation,
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)
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return svgOut
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}

‎packages/p/pierre115/gnovisual/scatterplot.gno‎

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// Package gnovisual provides functionality to render a scatter plot as an SVG image.
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// It takes a list of points (x,y) and draws them as circles on a 2D .
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// You can also apply Flags.
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package gnovisual
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import (
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"math"
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"gno.land/p/nt/ufmt"
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)
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const (
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DefaultWidth = 750
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DefaultHeight = 500
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DefaultMaxTicks = 10
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)
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// Get max ticks for axis
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func (sp ScatterPlot) GetMaxTicks() int {
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if sp.maxTicks == 0 {
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return DefaultMaxTicks
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}
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return sp.maxTicks
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}
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// Get width of the svg
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func (sp ScatterPlot) GetWidth() int {
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if sp.Width == 0 {
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return DefaultWidth
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}
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return sp.Width
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}
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// Get height of the svg
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func (sp ScatterPlot) GetHeight() int {
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if sp.Height == 0 {
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return DefaultHeight
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}
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return sp.Height
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}
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// NiceStep calculates a visually pleasing axis step size based on the data range and maximum number of ticks.
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func niceStep(sp ScatterPlot, rangeVal float64) float64 {
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var niceBase float64
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maxTicks := sp.GetMaxTicks()
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rawStep := rangeVal / float64(maxTicks)
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exponent := math.Floor(math.Log10(rawStep))
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fraction := rawStep / math.Pow(10, exponent)
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switch {
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case fraction < 1.5:
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niceBase = 1
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case fraction < 3:
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niceBase = 2
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case fraction < 7:
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niceBase = 5
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default:
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niceBase = 10
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}
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return niceBase * math.Pow(10, exponent)
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}
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// StepXY use the ideal steps calculated by nicestep function for both axis
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func StepXY(sp ScatterPlot, maxX, maxY, minX, minY float64) (float64, float64, float64, float64, float64, float64) {
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rangeX := maxX - minX
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stepX := niceStep(sp, rangeX)
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startX := math.Floor(minX/stepX) * stepX
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endX := math.Ceil(maxX/stepX) * stepX
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rangeY := maxY - minY
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stepY := niceStep(sp, rangeY)
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startY := math.Floor(minY/stepY) * stepY
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endY := math.Ceil(maxY/stepY) * stepY
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return stepX, startX, endX, stepY, startY, endY
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}
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// RenderAxes renders the chart axes and their corresponding titles, returning the result as SVG-formatted strings for display.
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func RenderAxes(sp ScatterPlot, Width, Height int, maxX, maxY, minX, minY float64) string {
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svgOut := ""
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// Axe Y
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svgOut += ufmt.Sprintf(`<rect x="%d" y="%d" width="%d" height="%d" fill="black"/>`, 40, Height-40, Width-60, 1)
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svgOut += ufmt.Sprintf(
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`<text x="%d" y="%d" style="font-family:'Inter var',sans-serif;font-size:%dpx;text-anchor:middle;" transform="rotate(-90 %d %d)" fill="black">%s</text>`,
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10, Height/2, 12, 15, Height/2, sp.YAxis,
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)
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// Axe X
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svgOut += ufmt.Sprintf(`<rect x="%d" y="%d" width="%d" height="%d" fill="black"/>`, 40, 20, 1, Height-60)
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svgOut += ufmt.Sprintf(
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`<text x="%d" y="%d" style="font-family:'Inter var',sans-serif;font-size:%dpx;text-anchor:middle;" fill="black">%s</text>`,
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Width/2, Height-10, 12, sp.XAxis,
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)
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// Scale helpers
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scaleX := func(val float64) float64 {
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return 40 + (val-minX)/(maxX-minX)*float64(Width-60)
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}
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scaleY := func(val float64) float64 {
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return float64(Height-40) - (val-minY)/(maxY-minY)*float64(Height-60)
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}
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// Nicesteps calcul for graduation
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stepX, startX, endX, stepY, startY, endY := StepXY(sp, maxX, maxY, minX, minY)
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// Graduation X
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for val := startX; val <= endX; val += stepX {
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nx := scaleX(val)
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y := float64(Height - 40)
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svgOut += ufmt.Sprintf(`<rect x="%d" y="%d" width="%d" height="%d" fill="black"/>`, int(nx), int(y), 1, 5)
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svgOut += ufmt.Sprintf(`<text x="%d" y="%d" style="font-size:%dpx;text-anchor:middle;" fill="black">%.1f</text>`, int(nx), int(y)+18, 11, val)
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}
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// Graduation Y
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for val := startY; val <= endY; val += stepY {
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ny := scaleY(val)
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x := float64(40)
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svgOut += ufmt.Sprintf(`<rect x="%d" y="%d" width="%d" height="%d" fill="black"/>`, int(x)-5, int(ny), 5, 1)
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svgOut += ufmt.Sprintf(`<text x="%d" y="%d" style="font-size:%dpx;text-anchor:end;" fill="black">%.1f</text>`, int(x)-8, int(ny)+4, 11, val)
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}
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return svgOut
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}
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// Returns an img svg markup as a string, including a markdown header if a non-empty title is provided.
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// The function need a Point struct, two axes titles and a flag.
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// You can see existings flags in the Readme.md
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func (sp ScatterPlot) String() string {
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const (
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pointRadius = 2
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)
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Width := sp.GetWidth()
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Height := sp.GetHeight()
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if len(sp.Points) == 0 {
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return "\nscatterplot fails: no data provided"
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}
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// calcul min/max
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minX, minY := sp.Points[0].X, sp.Points[0].Y
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maxX, maxY := sp.Points[0].X, sp.Points[0].Y
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for _, p := range sp.Points {
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if p.X > maxX {
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maxX = p.X
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}
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if p.X < minX {
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minX = p.X
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}
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if p.Y > maxY {
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maxY = p.Y
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}
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if p.Y < minY {
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minY = p.Y
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}
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}
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svgOut := ""
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svgOut += RenderAxes(sp, Width, Height, maxX, maxY, minX, minY)
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// Draw Points and labels
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for _, p := range sp.Points {
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nx := 40 + (p.X-minX)/(maxX-minX)*float64(Width-60)
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ny := float64(Height-40) - (p.Y-minY)/(maxY-minY)*float64(Height-60)
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svgOut += ufmt.Sprintf(`<circle cx="%d" cy="%d" r="%d" fill="%s"/>`, int(nx), int(ny), pointRadius, p.Color)
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if p.Label != "" {
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svgOut += ufmt.Sprintf(
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`<text x="%d" y="%d" style="font-family:'Inter var',sans-serif;font-size:10px;text-anchor:middle;" fill="#333">%s</text>`,
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int(nx)+5, int(ny)+12, p.Label,
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)
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}
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}
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// Flags :
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if sp.FlagRe == true {
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svgOut += RenderReFlag(sp.Points, minX, maxX, minY, maxY, Width, Height)
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}
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// Draw Title
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if sp.Title != "" {
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svgOut += ufmt.Sprintf(`<text x="%d" y="%d" style="font-family:'Inter var',sans-serif;font-size:16px;text-anchor:middle;" fill="black">%s</text>`,
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Width/2, 20, sp.Title,
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)
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}
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return svgOut
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}

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