120 lines
2.7 KiB
Go
120 lines
2.7 KiB
Go
package chart
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import (
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"fmt"
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)
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// Interface Assertions.
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var (
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_ Series = (*LinearSeries)(nil)
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_ FirstValuesProvider = (*LinearSeries)(nil)
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_ LastValuesProvider = (*LinearSeries)(nil)
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)
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// LinearSeries is a series that plots a line in a given domain.
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type LinearSeries struct {
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Name string
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Style Style
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YAxis YAxisType
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XValues []float64
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InnerSeries LinearCoefficientProvider
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m float64
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b float64
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stdev float64
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avg float64
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}
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// GetName returns the name of the time series.
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func (ls LinearSeries) GetName() string {
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return ls.Name
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}
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// GetStyle returns the line style.
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func (ls LinearSeries) GetStyle() Style {
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return ls.Style
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}
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// GetYAxis returns which YAxis the series draws on.
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func (ls LinearSeries) GetYAxis() YAxisType {
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return ls.YAxis
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}
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// Len returns the number of elements in the series.
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func (ls LinearSeries) Len() int {
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return len(ls.XValues)
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}
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// GetEndIndex returns the effective limit end.
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func (ls LinearSeries) GetEndIndex() int {
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return len(ls.XValues) - 1
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}
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// GetValues gets a value at a given index.
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func (ls *LinearSeries) GetValues(index int) (x, y float64) {
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if ls.InnerSeries == nil || len(ls.XValues) == 0 {
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return
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}
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if ls.IsZero() {
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ls.computeCoefficients()
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}
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x = ls.XValues[index]
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y = (ls.m * ls.normalize(x)) + ls.b
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return
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}
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// GetFirstValues computes the first linear regression value.
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func (ls *LinearSeries) GetFirstValues() (x, y float64) {
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if ls.InnerSeries == nil || len(ls.XValues) == 0 {
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return
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}
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if ls.IsZero() {
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ls.computeCoefficients()
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}
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x, y = ls.GetValues(0)
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return
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}
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// GetLastValues computes the last linear regression value.
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func (ls *LinearSeries) GetLastValues() (x, y float64) {
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if ls.InnerSeries == nil || len(ls.XValues) == 0 {
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return
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}
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if ls.IsZero() {
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ls.computeCoefficients()
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}
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x, y = ls.GetValues(ls.GetEndIndex())
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return
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}
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// Render renders the series.
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func (ls *LinearSeries) Render(r Renderer, canvasBox Box, xrange, yrange Range, defaults Style) {
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Draw.LineSeries(r, canvasBox, xrange, yrange, ls.Style.InheritFrom(defaults), ls)
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}
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// Validate validates the series.
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func (ls LinearSeries) Validate() error {
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if ls.InnerSeries == nil {
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return fmt.Errorf("linear regression series requires InnerSeries to be set")
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}
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return nil
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}
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// IsZero returns if the linear series has computed coefficients or not.
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func (ls LinearSeries) IsZero() bool {
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return ls.m == 0 && ls.b == 0
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}
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// computeCoefficients computes the `m` and `b` terms in the linear formula given by `y = mx+b`.
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func (ls *LinearSeries) computeCoefficients() {
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ls.m, ls.b, ls.stdev, ls.avg = ls.InnerSeries.Coefficients()
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}
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func (ls *LinearSeries) normalize(xvalue float64) float64 {
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if ls.avg > 0 && ls.stdev > 0 {
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return (xvalue - ls.avg) / ls.stdev
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}
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return xvalue
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}
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