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|
package tensor
import (
"log"
"math"
"math/rand"
"reflect"
"sort"
"github.com/chewxy/math32"
)
// SortIndex is similar to numpy's argsort
// TODO: tidy this up
func SortIndex(in interface{}) (out []int) {
switch list := in.(type) {
case []int:
orig := make([]int, len(list))
out = make([]int, len(list))
copy(orig, list)
sort.Ints(list)
for i, s := range list {
for j, o := range orig {
if o == s {
out[i] = j
break
}
}
}
case []float64:
orig := make([]float64, len(list))
out = make([]int, len(list))
copy(orig, list)
sort.Float64s(list)
for i, s := range list {
for j, o := range orig {
if o == s {
out[i] = j
break
}
}
}
case sort.Interface:
sort.Sort(list)
log.Printf("TODO: SortIndex for sort.Interface not yet done.")
}
return
}
// SampleIndex samples a slice or a Tensor.
// TODO: tidy this up.
func SampleIndex(in interface{}) int {
// var l int
switch list := in.(type) {
case []int:
var sum, i int
// l = len(list)
r := rand.Int()
for {
sum += list[i]
if sum > r && i > 0 {
return i
}
i++
}
case []float64:
var sum float64
var i int
// l = len(list)
r := rand.Float64()
for {
sum += list[i]
if sum > r && i > 0 {
return i
}
i++
}
case *Dense:
var i int
switch list.t.Kind() {
case reflect.Float64:
var sum float64
r := rand.Float64()
data := list.Float64s()
// l = len(data)
for {
datum := data[i]
if math.IsNaN(datum) || math.IsInf(datum, 0) {
return i
}
sum += datum
if sum > r && i > 0 {
return i
}
i++
}
case reflect.Float32:
var sum float32
r := rand.Float32()
data := list.Float32s()
// l = len(data)
for {
datum := data[i]
if math32.IsNaN(datum) || math32.IsInf(datum, 0) {
return i
}
sum += datum
if sum > r && i > 0 {
return i
}
i++
}
default:
panic("not yet implemented")
}
default:
panic("Not yet implemented")
}
return -1
}
|
