From 2b0ee8c693dab64cb724b6f781e61c41a961d590 Mon Sep 17 00:00:00 2001
From: leo <wanderer@dotya.ml>
Date: Sun, 14 May 2023 21:30:22 +0200
Subject: [PATCH] go: break out data handling funcs to its own file

---
 data.go | 103 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 main.go |  95 ---------------------------------------------------
 2 files changed, 103 insertions(+), 95 deletions(-)
 create mode 100644 data.go

diff --git a/data.go b/data.go
new file mode 100644
index 0000000..36aacc7
--- /dev/null
+++ b/data.go
@@ -0,0 +1,103 @@
+package main
+
+import (
+	"encoding/csv"
+	"log"
+	"os"
+	"strconv"
+	"time"
+
+	"golang.org/x/exp/rand"
+
+	"gonum.org/v1/gonum/stat/distuv"
+)
+
+// prepData generates and saves random data (along with some known outliers) to
+// a file in CSV format.
+func prepData(path string) error {
+	log.Println("generating data")
+
+	data := genData(true, randomDataSize, -1.0, 1.0)
+
+	log.Println("generating data - done")
+	log.Printf("saving data to file at '%s'\n", path)
+
+	f, err := os.Create(path)
+	if err != nil {
+		log.Printf("could not save data to file at '%s'\n", path)
+		return err
+	}
+
+	defer f.Close()
+
+	w := csv.NewWriter(f)
+
+	defer w.Flush()
+
+	log.Println("writing data")
+
+	err = w.WriteAll(data)
+	if err != nil {
+		log.Println("error writing data")
+		return err
+	}
+
+	log.Println("writing data - done")
+
+	return nil
+}
+
+// genData generates new random data with either normal or uniform
+// distribution. if normal is set, normal distribution is set with sigma and mu
+// values corresponding to the standard normal distribution and min/max values
+// are ignored.
+func genData(normal bool, size int, min, max float64) [][]string {
+	col1 := make([]float64, size)
+	col2 := make([]float64, size)
+
+	switch {
+	case !normal:
+		uniform := &distuv.Uniform{
+			Min: min,
+			Max: max,
+			Src: rand.NewSource(uint64(
+				time.Now().UnixNano(),
+			)),
+		}
+
+		for i := 0; i < size; i++ {
+			col1[i] = uniform.Rand()
+			col2[i] = uniform.Rand()
+		}
+
+	case normal:
+		stdnorm := &distuv.Normal{
+			Sigma: 1,
+			Mu:    0,
+			Src: rand.NewSource(uint64(
+				time.Now().UnixNano(),
+			)),
+		}
+
+		for i := 0; i < size; i++ {
+			col1[i] = stdnorm.Rand()
+			col2[i] = stdnorm.Rand()
+		}
+	}
+
+	for i := 0; i < outliers; i++ {
+		col1 = append(col1, float64(rand.Int63()))
+		col2 = append(col2, float64(rand.Int63()))
+	}
+
+	data := make([][]string, 0, size+outliers)
+
+	for i := 0; i < size+outliers; i++ {
+		r1 := strconv.FormatFloat(col1[i], 'f', -1, 64)
+		r2 := strconv.FormatFloat(col2[i], 'f', -1, 64)
+
+		data = append(data, []string{r1, r2})
+	}
+
+	return data
+}
diff --git a/main.go b/main.go
index 3ef785d..bad0a48 100644
--- a/main.go
+++ b/main.go
@@ -1,17 +1,12 @@
 package main
 
 import (
-	"encoding/csv"
 	"fmt"
 	"log"
 	"os"
-	"strconv"
-	"time"
 
 	"github.com/sjwhitworth/golearn/base"
 	"github.com/sjwhitworth/golearn/trees"
-	"golang.org/x/exp/rand"
-	"gonum.org/v1/gonum/stat/distuv"
 )
 
 var (
@@ -93,93 +88,3 @@ func loadData() (*base.DenseInstances, error) {
 
 	return data, nil
 }
-
-// prepData generates and saves random data (along with some known outliers) to
-// a file in CSV format.
-func prepData(path string) error {
-	log.Println("generating data")
-
-	data := genData(true, randomDataSize, -1.0, 1.0)
-
-	log.Println("generating data - done")
-	log.Printf("saving data to file at '%s'\n", path)
-
-	f, err := os.Create(path)
-	if err != nil {
-		log.Printf("could not save data to file at '%s'\n", path)
-		return err
-	}
-
-	defer f.Close()
-
-	w := csv.NewWriter(f)
-
-	defer w.Flush()
-
-	log.Println("writing data")
-
-	err = w.WriteAll(data)
-	if err != nil {
-		log.Println("error writing data")
-		return err
-	}
-
-	log.Println("writing data - done")
-
-	return nil
-}
-
-// genData generates new random data with either normal or uniform
-// distribution. if normal is set, normal distribution is set with sigma and mu
-// values corresponding to the standard normal distribution and min/max values
-// are ignored.
-func genData(normal bool, size int, min, max float64) [][]string {
-	col1 := make([]float64, size)
-	col2 := make([]float64, size)
-
-	switch {
-	case !normal:
-		uniform := &distuv.Uniform{
-			Min: min,
-			Max: max,
-			Src: rand.NewSource(uint64(
-				time.Now().UnixNano(),
-			)),
-		}
-
-		for i := 0; i < size; i++ {
-			col1[i] = uniform.Rand()
-			col2[i] = uniform.Rand()
-		}
-
-	case normal:
-		stdnorm := &distuv.Normal{
-			Sigma: 1,
-			Mu:    0,
-			Src: rand.NewSource(uint64(
-				time.Now().UnixNano(),
-			)),
-		}
-
-		for i := 0; i < size; i++ {
-			col1[i] = stdnorm.Rand()
-			col2[i] = stdnorm.Rand()
-		}
-	}
-
-	for i := 0; i < outliers; i++ {
-		col1 = append(col1, float64(rand.Int63()))
-		col2 = append(col2, float64(rand.Int63()))
-	}
-
-	data := make([][]string, 0, size+outliers)
-
-	for i := 0; i < size+outliers; i++ {
-		r1 := strconv.FormatFloat(col1[i], 'f', -1, 64)
-		r2 := strconv.FormatFloat(col2[i], 'f', -1, 64)
-
-		data = append(data, []string{r1, r2})
-	}
-
-	return data
-}