software developer | data scientist | IT Ninja | Physics engineer
Published
Edited
Mar 31, 2021
Importers
md`# Convolution - discrete time series
Code from https://gist.github.com/jdpigeon/1de0b43eed7ae7e4080818cad53be200`
/* Returns the discrete, linear convolution of two vectors.
** Convolution in time/space is equivalent to multiplication in the frequency domain.
This function is equivalent to numpy's convolve function with the default 'full' parameter
example :
------
vec1 = [2,3,4]
vec2 = [1,2,3]
multiply vec2 by vec1[0] = 2 4 6
multiply vec2 by vec1[1] = - 3 6 9
multiply vec2 by vec1[2] = - - 4 8 12
-----------------------------------------------
add the above three = 2 7 16 17 12
convolve(vec1, vec2) // [2,7,16,17,12]
**
*/
convolve = (vec1, vec2) => {
if (vec1.length === 0 || vec2.length === 0) {
throw new Error("Vectors can not be empty!");
}
const volume = vec1;
const kernel = vec2;
let displacement = 0;
const convVec = [];
for (let i = 0; i < volume.length; i++) {
for (let j = 0; j < kernel.length; j++) {
if (displacement + j !== convVec.length) {
convVec[displacement + j] =
convVec[displacement + j] + volume[i] * kernel[j];
} else {
convVec.push(volume[i] * kernel[j]);
}
}
displacement++;
}
return convVec;
};
a = [0, 0, 1]
b = [0, 1, 0]
convolve(a,b)
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
