fft
Version:
A Fast Fourier Transform library for JS.
166 lines (120 loc) • 4.3 kB
HTML
<head>
<title>fft.js</title>
<script src='lib/real.js'></script>
<script src='lib/complex.js'></script>
<script>
function kahanDiff(x, xOffset, xStride, y, yOffset, yStride, n, run) {
var sum = 0.0, compensation = 0.0
for (var i = 0; i < x.length / run / xStride; i++) {
for (var j = 0; j < run; j++) {
var v = Math.abs(x[xOffset + run * xStride * i + j] - y[yOffset + run * yStride * i + j] / n) - compensation
var t = sum + v
compensation = (t - sum) - v
sum = t
if (isNaN(sum)) {
debugger
}
}
}
return sum
}
function kahanStrideDiff(x, xOffset, xStride, run) {
var sum = 0.0, compensation = 0.0
for (var i = 0; i < x.length / run / xStride; i++) {
for (var j = run; j < run * xStride; j++) {
var v = Math.abs(x[xOffset + run * xStride * i + j]) - compensation
var t = sum + v
compensation = (t - sum) - v
sum = t
if (isNaN(sum)) {
debugger
}
}
}
return sum
}
function kahanOffsetDiff(x, xOffset) {
var sum = 0.0, compensation = 0.0
for (var i = 0; i < xOffset; i++) {
var v = Math.abs(x[i]) - compensation
var t = sum + v
compensation = (t - sum) - v
sum = t
if (isNaN(sum)) {
debugger
}
}
return sum
}
function testComplex(n) {
var i = new Float64Array(2 * n), o1 = new Float64Array(2 * n), o2 = new Float64Array(2 * n)
var fft = new FFT.complex(n, false), ifft = new FFT.complex(n, true)
for (var j = 0; j < (2 * n); j++) {
i[j] = Math.random()
}
fft.process(o1, 0, 1, i, 0, 1)
ifft.process(o2, 0, 1, o1, 0, 1)
return kahanDiff(i, 0, 1, o2, 0, 1, n, 2)
}
function testComplexStride(n) {
var iStride = ~~(12 * Math.random()) + 1, o1Stride = ~~(16 * Math.random()) + 1, o2Stride = ~~(5 * Math.random()) + 1
var i = new Float64Array(2 * iStride * n), o1 = new Float64Array(2 * o1Stride * n), o2 = new Float64Array(2 * o2Stride * n)
var fft = new FFT.complex(n, false), ifft = new FFT.complex(n, true)
for (var j = 0; j < n; j++) {
i[2 * j * iStride + 0] = Math.random()
i[2 * j * iStride + 1] = Math.random()
}
fft.process(o1, 0, o1Stride, i, 0, iStride)
ifft.process(o2, 0, o2Stride, o1, 0, o1Stride)
return [kahanDiff(i, 0, iStride, o2, 0, o2Stride, n, 2), kahanStrideDiff(o2, 0, o2Stride, 2)]
}
function testRealToComplex(n) {
var i = new Float64Array(n), o1 = new Float64Array(2 * n), o2 = new Float64Array(2 * n)
var fft = new FFT.complex(n, false), ifft = new FFT.complex(n, true)
for (var j = 0; j < n; j++) {
i[j] = Math.random()
}
fft.process(o1, 0, 1, i, 0, 1, 'real')
ifft.process(o2, 0, 1, o1, 0, 1)
return [kahanDiff(i, 0, 1, o2, 0, 2, n, 1), kahanStrideDiff(o2, 2, 1)]
}
function testRealToComplexWithOffset(n) {
var iOffset = ~~(12 * Math.random()), o1Offset = ~~(12 * Math.random()), o2Offset = ~~(12 * Math.random())
var i = new Float64Array(iOffset + n), o1 = new Float64Array(o1Offset + 2 * n), o2 = new Float64Array(o2Offset + 2 * n)
var fft = new FFT.complex(n, false), ifft = new FFT.complex(n, true)
for (var j = 0; j < n; j++) {
i[iOffset + j] = Math.random()
}
fft.process(o1, o1Offset, 1, i, iOffset, 1, 'real')
ifft.process(o2, o2Offset, 1, o1, o1Offset, 1)
return [kahanDiff(i, 1, o2, 2, n, 1), kahanStrideDiff(o2, 2, 1), kahanOffsetDiff(o1, o1Offset), kahanOffsetDiff(o2, o2Offset)]
}
var count = 0
for (var i = 2; i < 100; i++) {
var v = testComplex(i)
if (isNaN(v) || v > 1e-12) {
console.log('Complex', i, v), count++
}
}
for (var i = 2; i < 100; i++) {
var v = testComplexStride(i)
if (isNaN(v[0]) || v[0] > 1e-12 || v[1] > 0) {
console.log('Complex Strided', i, v), count++
}
}
for (var i = 2; i < 100; i++) {
var v = testRealToComplex(i)
if (isNaN(v[0]) || isNaN(v[1]) || v[0] > 1e-12 || v[1] > 1e-12) {
console.log('Real to Complex', i, v), count++
}
}
for (var i = 2; i < 100; i++) {
var v = testRealToComplexWithOffset(i)
if (isNaN(v[0]) || isNaN(v[1]) || isNaN(v[2]) || isNaN(v[3]) || v[0] > 1e-12 || v[1] > 1e-12 || v[2] > 0 || v[3] > 0) {
console.log('Real to Complex Offset', i, v), count++
}
}
console.log("Failcount", count)
</script>
</head>