Top 10 Examples of "simple-statistics in functional component" in JavaScript
Dive into secure and efficient coding practices with our curated list of the top 10 examples showcasing 'simple-statistics' in functional components in JavaScript. Our advanced machine learning engine meticulously scans each line of code, cross-referencing millions of open source libraries to ensure your implementation is not just functional, but also robust and secure. Elevate your React applications to new heights by mastering the art of handling side effects, API calls, and asynchronous operations with confidence and precision.
it('statistics methods on fields of array', () => {
const data = [];
for (let i = 1; i <= 10; i++) {
// 1~10
data.push({
a: [i, i + 10, [-i, i * i, [-i * i, 1 / i]]],
});
}
const dv = new DataSet.View().source(data);
const values = flattenDeep(dv.getColumn('a'));
expect(dv.max('a')).to.equal(max(values));
expect(dv.min('a')).to.equal(min(values));
expect(dv.mean('a')).to.equal(mean(values));
expect(dv.average('a')).to.equal(mean(values));
expect(dv.median('a')).to.equal(median(values));
expect(dv.mode('a')).to.equal(mode(values));
expect(dv.quantile('a', 0.5)).to.equal(quantile(values, 0.5));
expect(dv.quantiles('a', [0, 0.1, 0.5])).to.eql(map([0, 0.1, 0.5], (p) => quantile(values, p)));
expect(dv.quantilesByFraction('a', 4)).to.eql(map([0, 0.25, 0.5, 0.75, 1], (p) => quantile(values, p)));
expect(dv.standardDeviation('a')).to.equal(standardDeviation(values));
expect(dv.sum('a')).to.equal(sum(values));
expect(dv.variance('a')).to.equal(variance(values));
expect(dv.range('a')).to.eql([min(values), max(values)]);
});
});function calculateLinearFit(datapoints){
var data = [];
for(var j=0;j< datapoints.length;j++){
if(datapoints[j][0] !== null) {
data.push([j, datapoints[j][0]]);
}
}
var line = ss.linear_regression()
.data(data)
.line()
var gradient = ss.linear_regression()
.data(data)
.m()
//winston.info('stijgings percentage: ' + (line(data.length-1)-line(0))/ line(0)) / data.length * 100;
//winston.info('gradient: ' + gradient * 100);
//winston.info('line(0): ' + line(0));
//winston.info('line(data.length-1): ' + line(data.length-1));
/* if no valid number is calculated, return null*/
var result = !isNaN(Math.round(((((line(data.length-1)-line(0))/ line(0)) / data.length) * 100 * 100)* 100) / 100) ? Math.round(((((line(data.length-1)-line(0))/ line(0)) / data.length) * 100 * 100)* 100) / 100 : null;
return result;it('statistics methods on fields of array', () => {
const data = [];
for (let i = 1; i <= 10; i++) {
// 1~10
data.push({
a: [i, i + 10, [-i, i * i, [-i * i, 1 / i]]],
});
}
const dv = new DataSet.View().source(data);
const values = flattenDeep(dv.getColumn('a'));
expect(dv.max('a')).to.equal(max(values));
expect(dv.min('a')).to.equal(min(values));
expect(dv.mean('a')).to.equal(mean(values));
expect(dv.average('a')).to.equal(mean(values));
expect(dv.median('a')).to.equal(median(values));
expect(dv.mode('a')).to.equal(mode(values));
expect(dv.quantile('a', 0.5)).to.equal(quantile(values, 0.5));
expect(dv.quantiles('a', [0, 0.1, 0.5])).to.eql(map([0, 0.1, 0.5], (p) => quantile(values, p)));
expect(dv.quantilesByFraction('a', 4)).to.eql(map([0, 0.25, 0.5, 0.75, 1], (p) => quantile(values, p)));
expect(dv.standardDeviation('a')).to.equal(standardDeviation(values));
expect(dv.sum('a')).to.equal(sum(values));
expect(dv.variance('a')).to.equal(variance(values));
expect(dv.range('a')).to.eql([min(values), max(values)]);
});
});source._backend.getTile(0,0,0, function(err, vtile, headers) {
if (err) throw err;
var tile = vtile;
var layerInfo = profiler.layerInfo(tile);
// Tile has a 'coastline' layer
var coastline = _(layerInfo).where({ name: 'coastline' })[0];
t.ok(coastline);
// Tile contains 4177 features
t.equal(coastline.coordCount.length, 1437);
t.equal(coastline.features, 1437);
// Longest/shortest features
t.equal(ss.max(coastline.coordCount), 380);
t.equal(ss.min(coastline.coordCount), 2);
// Most/least duplication
t.equal(ss.max(coastline.duplicateCoordCount), 0);
t.equal(ss.min(coastline.duplicateCoordCount), 0);
// Max/Min distance between consecutive coords
var diff = Math.abs(ss.max(coastline.coordDistance) - 570446.5598775251);
t.ok(diff < 0.1);
t.equal(ss.min(coastline.coordDistance), 1181.6043940629547);
// Expected jsonsize
t.equal(coastline.jsonsize, 520120);
t.end();
});
});}, function (err, result) {
process.stdout.write(' DONE!\n\n');
if (err) {
console.log(err);
process.exit(1);
}
console.log('Response Times:');
console.log('Min: ' + Math.floor(ss.min(result)) + 'ms');
console.log('Max: ' + Math.floor(ss.max(result)) + 'ms');
console.log('95th: ' + Math.floor(ss.quantile(result, 0.95)) + 'ms');
console.log('Std Dev: ' + Math.floor(ss.standardDeviation(result)) + 'ms');
console.log('\nRedis Cache:');
redisStats(api);
console.log('\nUser Cache:');
userStats(api);
process.exit(0); // TODO shutdown cleanly
api.client._client.shutdown();
});
}}, function (err, result) {
process.stdout.write(' DONE!\n\n');
if (err) {
console.log(err);
process.exit(1);
}
console.log('Response Times:');
console.log('Min: ' + Math.floor(ss.min(result)) + 'ms');
console.log('Max: ' + Math.floor(ss.max(result)) + 'ms');
console.log('95th: ' + Math.floor(ss.quantile(result, 0.95)) + 'ms');
console.log('Std Dev: ' + Math.floor(ss.standardDeviation(result)) + 'ms');
console.log('\nRedis Cache:');
redisStats(api);
console.log('\nUser Cache:');
userStats(api);
process.exit(0); // TODO shutdown cleanly
api.client._client.shutdown();
});
}[100, 500, 1000, 2000, 3000, 5000, 10000].forEach(function(nRounds){
let nSimulations = 20
let results = []
for(let i = 0; i < nSimulations; i++){
// console.log(`do simulation ${i} with ${nRounds} rounds`)
var result = PokerHand.MonteCarlo.simulateOddsIfAllIn(nRounds, holeCards, communityCards, nbOtherPlayers)
results.push(result)
}
// compute stats on the results
let mean = SimpleStats.mean(results)
let stddev = SimpleStats.standardDeviation(results)
let max = SimpleStats.max(results)
let min = SimpleStats.min(results)
console.log(`nRounds ${nRounds.toString().padStart(5)} : mean ${mean.toFixed(6)} (${Math.round(mean*100).toString().padStart(2)}%) - stddev ${stddev.toFixed(6)} - delta min/max [${(min-mean).toFixed(6)}, ${(max-mean).toFixed(6)}]`)
})forIn(groups, (group) => {
const totalSum = sum(group.map((row: any) => row[field]));
if (totalSum === 0) {
console.warn(`Invalid data: total sum of field ${field} is 0!`);
}
const innerGroups = partition(group, [dimension]);
forIn(innerGroups, (innerGroup) => {
const innerSum = sum(innerGroup.map((row: any) => row[field]));
// const resultRow = pick(innerGroup[0], union(groupBy, [ dimension ]));
const resultRow = innerGroup[0];
// FIXME in case dimension and field is the same
const dimensionValue = resultRow[dimension];
resultRow[field] = innerSum;
resultRow[dimension] = dimensionValue;
if (totalSum === 0) {
resultRow[as!] = 0;
} else {
resultRow[as!] = innerSum / totalSum;function safeQuantile(values: number[], q: number | number[]): any {
// Handle cases when `values` is empty gracefully
if (values.length > 0) {
return quantile(values, q as any)
} else if (typeof q === 'number') {
return 0
} else {
return q.map(() => 0)
}
}data.weeks.push(year.weeks[w]);
}
for (var wd = 0; wd < 7; wd++) {
data.weekDays[wd] = data.weekDays[wd].concat(year.weekDays[wd]);
}
data.days = data.days.concat(year.days);
}
// districtData.data = data;
// calculate means
districtData.meanYears = ss.mean(data.years);
districtData.meanMonth = ss.mean(data.month);
for (var l = 0; l < 12; l++) {
if (data.yearMonth[l].length === 0) {
districtData.meanYearMonth[l] = 0;
}
else if (data.yearMonth[l].length === 1) {
districtData.meanYearMonth[l] = data.yearMonth[l][0];
}
else {
districtData.meanYearMonth[l] = ss.mean(data.yearMonth[l]);
}
if (output.districts.length === 0) {
output.meanYearMonth[l] = districtData.meanYearMonth[l];
}
else {