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MarkSFrancis
2021-05-21 16:47:22 +01:00
parent 55ea4efc1d
commit 4f348ccb5b
1 changed files with 31 additions and 31 deletions
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62
Dynamic-Programming/Shuf.js
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@ -3,10 +3,10 @@ Given a data set of an unknown size,
Get a random sample in a random order
It's used in data analytics, often as a way to get a small random sample from a data lake or warehouse, or from a large CSV file
*/
function shuf(datasetSource, sampleSize) {
let output = fillBaseSample(datasetSource, sampleSize);
function shuf (datasetSource, sampleSize) {
const output = fillBaseSample(datasetSource, sampleSize)
return randomizeOutputFromDataset(datasetSource, output);
return randomizeOutputFromDataset(datasetSource, output)
}
/**
@ -16,39 +16,39 @@ function shuf(datasetSource, sampleSize) {
* @returns {Array.<T>} The random sample, as an array
* @template T
*/
function fillBaseSample(datasetSource, sampleSize) {
let filledIndexes = [];
let output = new Array(sampleSize);
function fillBaseSample (datasetSource, sampleSize) {
let filledIndexes = []
let output = new Array(sampleSize)
// Spread data out filling the array
while (true) {
const iterator = datasetSource.next();
if (iterator.done) break;
const iterator = datasetSource.next()
if (iterator.done) break
let insertTo = Math.floor(Math.random() * output.length);
let insertTo = Math.floor(Math.random() * output.length)
while (filledIndexes.includes(insertTo)) {
insertTo++;
insertTo++
if (insertTo === output.length) {
insertTo = 0;
insertTo = 0
}
}
output[insertTo] = {
value: iterator.value,
};
value: iterator.value
}
filledIndexes = [...filledIndexes, insertTo];
filledIndexes = [...filledIndexes, insertTo]
if (filledIndexes.length === sampleSize) {
break;
break
}
}
if (filledIndexes.length < output.length) {
// Not a large enough dataset to fill the sample - trim empty values
output = output.filter((_, i) => filledIndexes.includes(i));
output = output.filter((_, i) => filledIndexes.includes(i))
}
return output.map((o) => o.value);
return output.map((o) => o.value)
}
/**
@ -58,22 +58,22 @@ function fillBaseSample(datasetSource, sampleSize) {
* @returns {Array.<T>} The random sample, as an array
* @template T
*/
function randomizeOutputFromDataset(datasetSource, output) {
const newOutput = [...output];
let readSoFar = output.length;
function randomizeOutputFromDataset (datasetSource, output) {
const newOutput = [...output]
let readSoFar = output.length
while (true) {
const iterator = datasetSource.next();
if (iterator.done) break;
readSoFar++;
const iterator = datasetSource.next()
if (iterator.done) break
readSoFar++
const insertTo = Math.floor(Math.random() * readSoFar);
const insertTo = Math.floor(Math.random() * readSoFar)
if (insertTo < newOutput.length) {
newOutput[insertTo] = iterator.value;
newOutput[insertTo] = iterator.value
}
}
return newOutput;
return newOutput
}
const main = () => {
@ -82,15 +82,15 @@ const main = () => {
* @param {number} length The number of data items to generate
* @returns {Iterable<number>} Random iterable data
*/
function* generateRandomData(length) {
const maxValue = Math.pow(2, 31) - 1;
function * generateRandomData (length) {
const maxValue = Math.pow(2, 31) - 1
for (let i = 0; i < length; i++) {
yield Math.floor(Math.random() * maxValue);
yield Math.floor(Math.random() * maxValue)
}
}
const source = generateRandomData(1000);
const result = shuf(source, 10);
const source = generateRandomData(1000)
const result = shuf(source, 10)
console.log(result)
}
main()