ml-fft

ml-fft

fft library for the ml libraries.

Installation

$ npm install ml-fft

1D FFT and IFFT

var n = 16; 
var nCols = n; 
FFT.init(nCols);
var re = new Array(nCols);
var im = new Array(nCols);

for(var i=0;i<nCols;i++){
   re[i]=i;
   im[i]=nCols-i-1;
}

FFT.fft(re, im);
FFT.ifft(re, im);

2D FFT and 2D IFFT

data contains the matrix. The even rows contain the real part, the odd rows contain the imaginary part.

var n = 4;
var nRows = n;
var nCols = n;
var data = new Array(nRows*nCols);
for(var i=0;i<nRows;i++){
    for(var j=0;j<nCols;j++){
        data[i*nCols+j]=i+j;
    }
}
var ftData = FFTUtils.fft2DArray(data, nCols, nCols);
var ftRows = nRows * 2;
var ftCols = nCols / 2 + 1;
var iftData =  FFTUtils.ifft2DArray(ftData, ftRows, ftCols);

Convolute Matrices

var n=1024;
var data = new Uint32Array(n*n);
for(var i=0;i<n;i++){
    for(var j=0;j<n;j++){
        data[i*n+j]=i+j;
    }
}

var kn = nks[nki];
var kernel = new Array(kn);
for(var i=0;i<kn;i++){
  kernel[i]=new Array(kn);
  for(var j=0;j<kn;j++){
      kernel[i][j]=i+j;
  }
}

var convolutedData = convoluteFFT(data, kernel, n, n);

License

MIT