ml-matrix-convolution/lib/convolutionFFT.js

Matrix convolution: It offers the direct and the fourier transform convolution

import { FFTUtils } from 'ml-fft';
import { matrix2Array } from './util/matrix2Array.js';
export function convolutionFFT(input, kernel, opt) {
    let tmp = matrix2Array(input);
    let inputData = tmp.data;
    let options = {
        normalize: false,
        divisor: 1,
        rows: tmp.rows,
        cols: tmp.cols,
        ...opt,
    };
    let nRows, nCols;
    if (options.rows && options.cols) {
        nRows = options.rows;
        nCols = options.cols;
    }
    else {
        throw new Error(`Invalid number of rows or columns ${nRows} ${nCols}`);
    }
    let divisor = options.divisor;
    let kHeight = kernel.length;
    let kWidth = kernel[0].length;
    if (options.normalize) {
        divisor = 0;
        for (let i = 0; i < kHeight; i++) {
            for (let j = 0; j < kWidth; j++)
                divisor += kernel[i][j];
        }
    }
    if (divisor === 0) {
        throw new RangeError('convolution: The divisor is equal to zero');
    }
    let radix2Sized = FFTUtils.toRadix2(inputData, nRows, nCols);
    let conv = FFTUtils.convolute(radix2Sized.data, kernel, radix2Sized.rows, radix2Sized.cols);
    conv = FFTUtils.crop(conv, radix2Sized.rows, radix2Sized.cols, nRows, nCols);
    if (divisor !== 0 && divisor !== 1) {
        for (let i = 0; i < conv.length; i++) {
            conv[i] /= divisor;
        }
    }
    return conv;
}
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