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How to use the max function from mathjs

Find comprehensive JavaScript mathjs.max code examples handpicked from public code repositorys.

mathjs.max finds the maximum value from a given set of numbers or an array.

quantum-circuit.js

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	if(isBasicGate || !isWireInRange(wire, wireRange)){
		quirkColumn.push(1);
	}
} else {
	var basicGate = circuit.basicGates[gate.name];
	var maxWire = math.max(gate.wires);
	var minWire = math.min(gate.wires);
	var gateWires = gate.wires.slice();
	var wireRange = range(maxWire);
	if(basicGate) {

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+ 157 other calls in file

getAzDoRun.js

GitHub: adoptium/aqa-test-tools

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        ]
    ),
    3
);
const max = math.round(
    math.max(
        benchmarkMetricsCollection[
            key
        ]
    ),

+ 454 other calls in file

How does mathjs.max work?

mathjs.max takes a set of numbers or an array as input and iterates through each element to find the maximum value by comparing each element with the current maximum value, and updating the maximum value if the current element is greater than the current maximum value. Once all elements are iterated through, the maximum value is returned as the output of the function.

report

GitHub: Sable/wu-wei-benchmarking-toolkit

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  keys.environments[results[h].environment['short-name']] = true
  keys['input-sizes'][results[h].experiment['input-size']] = true

  results[h]['mean-time'] = math.mean(results[h].times)
  results[h]['std-time'] = math.std(results[h].times)
  results[h]['max-time'] = math.max(results[h].times)
  results[h]['min-time'] = math.min(results[h].times)
  a.push(results[h])
}

+ 5 other calls in file

index.js

GitHub: oflisback/markov-clustering

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  return clusters;
};

_exports.done = function done(M, i) {
  var testMatrix = math.dotPow(M, 2);
  var m = math.max(testMatrix) - math.min(testMatrix);
  return m === 0;
};

// Takes an adjectancy matrix and options

Ai Example

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const mathjs = require("mathjs");

const numbers = [2, 7, 1, 8, 4, 5];

const maxNumber = mathjs.max(numbers);

console.log(maxNumber); // Output: 8

In this example, we first import the mathjs library and create an array of numbers. We then use the mathjs.max function to find the maximum value in the array, which is 8. Finally, we print the maximum value to the console using console.log.

index.js

GitHub: oflisback/markov-clustering

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  return clusters;
};

exports.done = function done(M, i) {
  const testMatrix = math.dotPow(M, 2);
  const m = math.max(testMatrix) - math.min(testMatrix);
  return (m === 0);
};

// Takes an adjectancy matrix and options

index.js

GitHub: jly36963/notes

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// factors & multiples
math.gcd(a, b) // greatest common denominator
math.lcm(a, b) // least common multiple

// stats
math.max(numbers);
math.min(numbers);
math.quantileSeq([1, 2, 3, 4, 5], .5) // value at quantile

math.mean(numbers);

+ 6 other calls in file

jacobi.js

GitHub: DanielHernandezO/NumericalMethodsProject

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let p = triu([...A]);
let o = tril([...A]);
let l = mathjs.subtract(d,o);
let u = mathjs.subtract(d,p);
let T = mathjs.multiply(mathjs.inv(d),mathjs.add(l,u));
let re = mathjs.max(mathjs.abs(mathjs.eigs(T).values));
if(re > 1){
       logs.push({
           type: 'Error',
           text: 'Spectral radius greater than 1: the method does not converge.'

sor.js

GitHub: DanielHernandezO/NumericalMethodsProject

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let l = mathjs.subtract(d,o);
let u = mathjs.subtract(d,p);
console.log(u);
let T = mathjs.multiply(mathjs.inv(mathjs.subtract(d,mathjs.multiply(w,l))),mathjs.add(mathjs.multiply(mathjs.subtract(1,w),d),mathjs.multiply(w,u)));
console.log(T);
const re = mathjs.max(mathjs.abs(mathjs.eigs(T).values));
console.log(re);
if(re > 1){
       logs.push({
           type: 'Error',

gaussseidel.js

GitHub: DanielHernandezO/NumericalMethodsProject

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d = mathjs.diag(mathjs.diag(A));
p = triu(A);
l = mathjs.subtract(A,tril(A));
u = mathjs.subtract(A,triu(A));
T = mathjs.multiply(mathjs.inv(mathjs.subtract(d,l)),u);
re = mathjs.max(mathjs.abs(mathjs.eigs(T).values));
if(re > 1){
	console.log('Radio Espectral mayor que 1');
	console.log('el método no converge');
	return;

sor.js

GitHub: DanielHernandezO/NumericalMethodsProject

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err = tol + 1; 
z = [i,x[0],x[1],x[2],err];
while(err > tol && i<iter){
	xi = mathjs.add(mathjs.multiply(T,x),C);
	console.log(xi);
	err = mathjs.max(mathjs.sqrt(mathjs.add(mathjs.pow(mathjs.subtract(xi[0],x[0]),2),mathjs.add(mathjs.pow(mathjs.subtract(xi[1],x[1]),2),mathjs.pow(mathjs.subtract(xi[2],x[2]),2)))));
	x = xi;
}
i=i+1;
z[i][0]=i;

+ 3 other calls in file

unionHull.js

GitHub: jalbelo007/Elastoplastic_1DSprings_App

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} else {
    TOL = [[]];
}


let N = math.max(math.size(params));
let idxType = [find(forEach(params, ischar())), N + 1];

let L = math.size(idxType) - 1;
let S;

fssController.js

GitHub: Drakmord2/node-swarm-intelligence

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    let df              = mathjs.abs( mathjs.subtract(fish.next_fitness, fish.fitness));

    school_delta_f.push(df);
});

let max_delta_f = mathjs.max(school_delta_f);

school.forEach((fish) => {
    let delta_f = mathjs.subtract(fish.next_fitness, fish.fitness);

+ 3 other calls in file

index.js

GitHub: Kirigaya-Kazuton/IA

-1

+ 2 other calls in file

solve.js

GitHub: cblanken/aoc_2022

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}


function getNeighbors(matrix, x, y, z) {
    let neighbors = [];
    let size = matrix.size();
    for(let i = math.max(0, x-1); i <= math.min(size[0]-1, x+1); i++) {
        for(let j = math.max(0, y-1); j <= math.min(size[1]-1, y+1); j++) {
            for(let k = math.max(0, z-1); k <= math.min(size[2]-1, z+1); k++) {
                if (i === x && j === y && k === z) { continue; }
                neighbors.push([i, j, k]);

+ 15 other calls in file

methods-erp.js

GitHub: MissDejavu/bci-video-player

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rv = rv.map(v => (v - mean) / std);

const percentage = percentile / 100 / 2;
const min = m.min(rv);
// const min = m.quantileSeq(rv, percentage);
const max = m.max(rv);
// const max = m.quantileSeq(rv, 1 - percentage);
for (let i = 0; i < len; i++) {
    if (rv[i] < min) rv[i] = min;
    else if (rv[i] > max) rv[i] = max;

Statistics.js

GitHub: PauQuintasTorra/api-TFG

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    this.matrix = matrix;
    this.counter = this.matrix[0].length * this.matrix.length;
}

getMax(){
    return math.max(math.flatten(this.matrix));
}

getMin(){
    return math.min(math.flatten(this.matrix));

optimization.js

GitHub: mljs/optimization

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    var vector = vertices[i];
    y.push(f(vector));
}

var low = Util.getIndexRow(y, math.min(y));
var high = Util.getIndexRow(y, math.max(y));
var li = high;
var ho = low;

for(var i = 0; i <= size; ++i) {

+ 9 other calls in file

Other functions in mathjs

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mathjs.evaluate is the most popular function in mathjs (87200 examples)

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