// prepareRegPlotData prepares predicted point for plotting.
func prepareRegPlotData(r *regression.Regression) (plotter.XYs, error) {
pts := make(plotter.XYs, 1652)
i := 1
for i <= 1652 {
pts[i-1].X = float64(i)
value, err := r.Predict([]float64{float64(i)})
if err != nil {
return pts, errors.Wrap(err, "Could not calculate predicted value")
}
pts[i-1].Y = value
i++
}
return pts, nil
}
// preformRegression performs a linear regression of create repo counts vs. day.
func performRegression(counts [][]int) *regression.Regression {
var r regression.Regression
r.SetObserved("count of created Github repos")
r.SetVar(0, "days since Jan 1 2013")
for _, count := range counts {
r.Train(regression.DataPoint(
float64(count[1]),
[]float64{float64(count[0])}))
}
r.Run()
return &r
}
func main() {
// Initialise a new regression data set
var r regression.Regression
// Load the CSV data as data points
dataFile, err := os.Open("data-no-zeros.csv")
if err != nil {
fmt.Print(err, "\n")
}
reader := csv.NewReader(dataFile)
row, err := reader.Read()
count := 0
for err == nil {
if count == 0 {
for i := 0; i < len(row); i++ {
if i == 0 {
r.SetObservedName(row[i])
} else {
r.SetVarName(i-1, row[i])
}
}
} else {
var d regression.DataPoint
d.Variables = make([]float64, len(row)-1)
for i := 0; i < len(row); i++ {
if i == 0 {
observed, _ := strconv.ParseFloat(row[i], 64)
d.Observed = observed
} else {
variable, _ := strconv.ParseFloat(row[i], 64)
d.Variables[i-1] = variable
}
}
r.AddDataPoint(d)
}
count++
row, err = reader.Read()
}
dataFile.Close()
// Run the regression
r.RunLinearRegression()
r.Dump(true)
}
func main() {
var r regression.Regression
//r.Debug = true
r.SetObservedName("Distance")
r.SetVarName(0, "Weight")
r.SetVarName(1, "Height")
r.SetVarName(2, "Blood sugar")
r.AddDataPoint(regression.DataPoint{Observed: 98, Variables: []float64{483, 343, 0.0386}})
r.AddDataPoint(regression.DataPoint{Observed: 75, Variables: []float64{227, 419, 0.0705}})
r.AddDataPoint(regression.DataPoint{Observed: 0, Variables: []float64{380, 666, 0.0245}})
r.AddDataPoint(regression.DataPoint{Observed: 20, Variables: []float64{85, 833, 0.0567}})
r.AddDataPoint(regression.DataPoint{Observed: 50, Variables: []float64{188, 182, 0.0143}})
r.AddDataPoint(regression.DataPoint{Observed: 90, Variables: []float64{783, 1148, 0.0129}})
r.RunLinearRegression()
r.Dump(true)
}