go: break out data handling funcs to its own file
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SHA256:Dp8+iwKHSlrMEHzE3bJnPng70I7LEsa3IJXRH/U+idQ
103
data.go
Normal file
103
data.go
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@ -0,0 +1,103 @@
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package main
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import (
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"encoding/csv"
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"log"
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"os"
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"strconv"
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"time"
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"golang.org/x/exp/rand"
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"gonum.org/v1/gonum/stat/distuv"
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)
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// prepData generates and saves random data (along with some known outliers) to
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// a file in CSV format.
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func prepData(path string) error {
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log.Println("generating data")
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data := genData(true, randomDataSize, -1.0, 1.0)
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log.Println("generating data - done")
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log.Printf("saving data to file at '%s'\n", path)
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f, err := os.Create(path)
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if err != nil {
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log.Printf("could not save data to file at '%s'\n", path)
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return err
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}
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defer f.Close()
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w := csv.NewWriter(f)
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defer w.Flush()
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log.Println("writing data")
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err = w.WriteAll(data)
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if err != nil {
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log.Println("error writing data")
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return err
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}
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log.Println("writing data - done")
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return nil
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}
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// genData generates new random data with either normal or uniform
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// distribution. if normal is set, normal distribution is set with sigma and mu
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// values corresponding to the standard normal distribution and min/max values
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// are ignored.
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func genData(normal bool, size int, min, max float64) [][]string {
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col1 := make([]float64, size)
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col2 := make([]float64, size)
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switch {
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case !normal:
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uniform := &distuv.Uniform{
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Min: min,
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Max: max,
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Src: rand.NewSource(uint64(
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time.Now().UnixNano(),
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)),
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}
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for i := 0; i < size; i++ {
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col1[i] = uniform.Rand()
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col2[i] = uniform.Rand()
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}
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case normal:
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stdnorm := &distuv.Normal{
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Sigma: 1,
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Mu: 0,
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Src: rand.NewSource(uint64(
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time.Now().UnixNano(),
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)),
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}
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for i := 0; i < size; i++ {
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col1[i] = stdnorm.Rand()
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col2[i] = stdnorm.Rand()
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}
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}
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for i := 0; i < outliers; i++ {
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col1 = append(col1, float64(rand.Int63()))
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col2 = append(col2, float64(rand.Int63()))
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}
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data := make([][]string, 0, size+outliers)
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for i := 0; i < size+outliers; i++ {
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r1 := strconv.FormatFloat(col1[i], 'f', -1, 64)
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r2 := strconv.FormatFloat(col2[i], 'f', -1, 64)
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data = append(data, []string{r1, r2})
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}
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return data
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}
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95
main.go
95
main.go
@ -1,17 +1,12 @@
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package main
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import (
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"encoding/csv"
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"fmt"
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"log"
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"os"
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"strconv"
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"time"
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"github.com/sjwhitworth/golearn/base"
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"github.com/sjwhitworth/golearn/trees"
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"golang.org/x/exp/rand"
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"gonum.org/v1/gonum/stat/distuv"
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)
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var (
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@ -93,93 +88,3 @@ func loadData() (*base.DenseInstances, error) {
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return data, nil
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}
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// prepData generates and saves random data (along with some known outliers) to
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// a file in CSV format.
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func prepData(path string) error {
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log.Println("generating data")
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data := genData(true, randomDataSize, -1.0, 1.0)
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log.Println("generating data - done")
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log.Printf("saving data to file at '%s'\n", path)
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f, err := os.Create(path)
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if err != nil {
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log.Printf("could not save data to file at '%s'\n", path)
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return err
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}
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defer f.Close()
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w := csv.NewWriter(f)
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defer w.Flush()
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log.Println("writing data")
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err = w.WriteAll(data)
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if err != nil {
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log.Println("error writing data")
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return err
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}
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log.Println("writing data - done")
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return nil
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}
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// genData generates new random data with either normal or uniform
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// distribution. if normal is set, normal distribution is set with sigma and mu
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// values corresponding to the standard normal distribution and min/max values
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// are ignored.
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func genData(normal bool, size int, min, max float64) [][]string {
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col1 := make([]float64, size)
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col2 := make([]float64, size)
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switch {
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case !normal:
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uniform := &distuv.Uniform{
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Min: min,
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Max: max,
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Src: rand.NewSource(uint64(
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time.Now().UnixNano(),
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)),
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}
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for i := 0; i < size; i++ {
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col1[i] = uniform.Rand()
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col2[i] = uniform.Rand()
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}
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case normal:
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stdnorm := &distuv.Normal{
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Sigma: 1,
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Mu: 0,
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Src: rand.NewSource(uint64(
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time.Now().UnixNano(),
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)),
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}
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for i := 0; i < size; i++ {
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col1[i] = stdnorm.Rand()
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col2[i] = stdnorm.Rand()
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}
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}
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for i := 0; i < outliers; i++ {
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col1 = append(col1, float64(rand.Int63()))
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col2 = append(col2, float64(rand.Int63()))
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}
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data := make([][]string, 0, size+outliers)
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for i := 0; i < size+outliers; i++ {
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r1 := strconv.FormatFloat(col1[i], 'f', -1, 64)
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r2 := strconv.FormatFloat(col2[i], 'f', -1, 64)
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data = append(data, []string{r1, r2})
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}
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return data
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}
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