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package data
import (
"github.com/mumax/3/util"
)
// Resample returns a slice of new size N,
// using nearest neighbor interpolation over the input slice.
func Resample(in *Slice, N [3]int) *Slice {
if in.Size() == N {
return in // nothing to do
}
In := in.Tensors()
out := NewSlice(in.NComp(), N)
Out := out.Tensors()
size1 := SizeOf(In[0])
size2 := SizeOf(Out[0])
for c := range Out {
for i := range Out[c] {
i1 := (i * size1[Z]) / size2[Z]
for j := range Out[c][i] {
j1 := (j * size1[Y]) / size2[Y]
for k := range Out[c][i][j] {
k1 := (k * size1[X]) / size2[X]
Out[c][i][j][k] = In[c][i1][j1][k1]
}
}
}
}
return out
}
// Downsample returns a slice of new size N, smaller than in.Size().
// Averaging interpolation over the input slice.
// In is returned untouched if the sizes are equal.
func Downsample(In [][][][]float32, N [3]int) [][][][]float32 {
if SizeOf(In[0]) == N {
return In // nothing to do
}
nComp := len(In)
out := NewSlice(nComp, N)
Out := out.Tensors()
srcsize := SizeOf(In[0])
dstsize := SizeOf(Out[0])
Dx := dstsize[X]
Dy := dstsize[Y]
Dz := dstsize[Z]
Sx := srcsize[X]
Sy := srcsize[Y]
Sz := srcsize[Z]
scalex := Sx / Dx
scaley := Sy / Dy
scalez := Sz / Dz
util.Assert(scalex > 0 && scaley > 0)
for c := range Out {
for iz := 0; iz < Dz; iz++ {
for iy := 0; iy < Dy; iy++ {
for ix := 0; ix < Dx; ix++ {
sum, n := 0.0, 0.0
for I := 0; I < scalez; I++ {
i2 := iz*scalez + I
for J := 0; J < scaley; J++ {
j2 := iy*scaley + J
for K := 0; K < scalex; K++ {
k2 := ix*scalex + K
if i2 < Sz && j2 < Sy && k2 < Sx {
sum += float64(In[c][i2][j2][k2])
n++
}
}
}
}
Out[c][iz][iy][ix] = float32(sum / n)
}
}
}
}
return Out
}
// Returns the 3D size of block
func SizeOf(block [][][]float32) [3]int {
return [3]int{len(block[0][0]), len(block[0]), len(block)}
}
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