Two-dimensional discrete Fourier transform

The examples on this page show how the kontrast.discreteFourierTransform() function can be used to compute the discrete Fourier transform of 2D data sets. Please refer to the documentation on the discrete Fourier transform for details on all individual input and output properties.

let xCount = 256
let yCount = 256

let xRange = 1
let yRange = 2

let xInterval = xRange / xCount
let yInterval = yRange / yCount

let realPart = new Float64Array(xCount * yCount)

for (let i = 0; i < xCount; i++) {
  for (let j = 0; j < yCount; j++) {
    let x = (xRange * i) / xCount
    let y = (yRange * j) / yCount
    realPart[i + j * xCount] =
      Math.sin(2 * Math.PI * 30 * x) + Math.sin(2 * Math.PI * 12 * y)
  }
}

let spectrum = kontrast.discreteFourierTransform({
  realPart: realPart,
  domainInterval: [xInterval, yInterval],
  dataCount: [xCount, yCount],
})

console.log(spectrum)

dataImage.data = {
  x: {
    type: 'contiguous',
    start: 0,
    end: xRange,
    count: xCount,
  },
  y: {
    type: 'discontiguous',
    start: 0,
    end: yRange,
    count: yCount,
  },
  color: realPart,
}

spectrumImage.data = {
  kx: {
    type: 'contiguous',
    start: spectrum.domainBinStart[0],
    end: spectrum.domainBinEnd[0],
    count: spectrum.dataCount[0],
  },
  ky: {
    type: 'discontiguous',
    start: spectrum.domainBinStart[1],
    end: spectrum.domainBinEnd[1],
    count: spectrum.dataCount[1],
  },
  color: spectrum.absoluteValue,
}

showEverything()