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Add product function #377

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Add product function #377

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dolsem
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@dolsem dolsem commented Feb 16, 2024

Description

This PR adds a product function that takes N arrays as arguments and outputs the Cartesian product, for example:

produce(['a', 'b'], [1, 2]) // => [['a', 1], ['a', 2], ['b', 1], ['b', 2]]

Checklist

  • Changes are covered by tests if behavior has been changed or added
  • Tests have 100% coverage
  • If code changes were made, the version in package.json has been bumped (matching semver)
  • If code changes were made, the yarn build command has been run and to update the cdn directory
  • If code changes were made, the documentation (in the /docs directory) has been updated

Resolves

If the PR resolves an open issue tag it here. For example, Resolves #34

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@aleclarson
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Hey @dolsem, we might be interested in merging this over at the Radashi fork. You're invited to re-submit this PR there, but please specify how you use this function. 😄

P.S. You can read my post to learn more about the differences between Radashi and its predecessor.

@BarleyBig
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BarleyBig commented Aug 21, 2024

Hey @dolsem
I found your Cartesian product function code, Is very beautifully and has extremely high performance.
I think we can do some more optimization.

Cartesian product generally generates a relatively long result array, and the array size may be adjusted many times during the process. We can completely pre-calculate the length of the result array and initialize it,
like this:
const result = new Array(arrays.reduce((pre, curr) => pre * curr.length, 1));

indices init can be simpler and faster. Using const indices = arrays.map(() => 0) will be faster than new Array(arrays.length).fill(0)
The complete example is as follows:

export function product(arrays) {
    if (!arrays || !arrays.length || arrays.some(p => p.length < 1)) {
        return [];
    }
    const indices = arrays.map(() => 0)
    let currentIndex = arrays.length - 1;
    let resultIndex = 0
    const result = new Array(arrays.reduce((pre, curr) => pre * curr.length, 1));
    while (indices[0] < arrays[0].length) {
        result[resultIndex] = indices.map((j, i) => arrays[i][j])
        indices[currentIndex] += 1;
        while (currentIndex > 0 && indices[currentIndex] === arrays[currentIndex].length) {
            indices[currentIndex] = 0;
            indices[currentIndex - 1] += 1;
            currentIndex -= 1;
        }
        currentIndex = arrays.length - 1;
        resultIndex++
    }
    return result;
}

I ran some benchmarks and found it to be nearly 10% faster。
Thank you for creating such a useful function. I look forward to hearing your thoughts.

@aleclarson
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A similar implementation is being developed at this PR: radashi-org/radashi#241

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3 participants