# math-lib

> Math library that contains functions for prime number computations, root finding using Newton Raphson, first and second derivative computations

Latest version **0.1.7** (published 2017-01-17) · ISC license · 0 weekly downloads

## Install

```sh
npm install math-lib
pnpm add math-lib
yarn add math-lib
bun add math-lib
```

## Health

**Score 15/100 (F)** — status: abandoned.

Positive: no vulnerabilities.

Warnings: low downloads; no types; no esm support; pre 1.0.

Negative: abandoned; low maintenance score.

## Facts

| | |
|---|---|
| Version | 0.1.7 |
| Published | 2017-01-17 |
| First published | 2016-08-01 |
| Weekly downloads | 0 |
| License | ISC |
| TypeScript types | none |
| Module format | CommonJS |
| Dependencies | 0 |
| Known vulnerabilities | 0 |
| Install scripts | no |
| GitHub stars | 0 |
| Author | Shashi Shekhar |
| Maintainers | hashishshaker |
| Keywords | math, mathematics, prime numbers, derivatives, root finding |

## Links

- npm: https://www.npmjs.com/package/math-lib
- Repository: https://github.com/hashishshaker/mathlib_js
- Homepage: https://github.com/hashishshaker/mathlib_js#readme
- Issues: https://github.com/hashishshaker/mathlib_js/issues
- npm.io page: https://npm.io/package/math-lib

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## Recent versions

- 0.1.7 (latest) — 2017-01-17
- 0.1.6 — 2017-01-16
- 0.1.4 — 2017-01-16
- 0.1.5 — 2017-01-16
- 0.1.3 — 2017-01-16
- 0.1.2 — 2016-09-04
- 0.1.1 — 2016-08-30
- 0.1.0 — 2016-08-29
- 0.0.6 — 2016-08-08
- 0.0.5 — 2016-08-08
- 0.0.4 — 2016-08-06
- 0.0.3 — 2016-08-06
- 0.0.2 — 2016-08-06
- 0.0.1 — 2016-08-01

## README

# How to use the library
```
var ml = require('math-lib');
console.log(ml().numberHelper().checkPrime(7));
```
# Function listing
## checkPrime(input)
Checks if the input number is a prime number or not. Input number should be a positive integer.

```
var nh = require('math-lib');
console.log(ml().numberHelper().checkPrime(7)); // returns true
console.log(ml().numberHelper().checkPrime(25)); // returns true
console.log(ml().numberHelper().checkPrime(-25)); // returns Error
console.log(ml().numberHelper().checkPrime(25.7)); // returns Error
```

## getFibonacciSeries(a0, a1, numberRequired)
Generates an array of Fibonacci Series that includes a0 and a1, which are passed as parameters.

```
var nh = require('math-lib');
console.log(ml().numberHelper().getFibonacciSeries(0, 1, 10)); // returns [ 0, 1, 1, 2, 3, 5, 8, 13, 21, 34 ];
```
## getFibonacciSeriesUpto(a0, a1, upperLimit)
Generates an array of Fibonacci Series upto a user specified upper limit.

```
var nh = require('math-lib');
console.log(ml().numberHelper().getFibonacciSeriesUpto(0, 1, 10)); // returns [ 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89 ];
```
## listPrimeNumbersUpto(input)
Generates a list all prime numbers up to a given input. Implements Sieve of Eratosthenes.

```
var nh = require('math-lib');
console.log(ml().numberHelper().listPrimeNumbersUpto(10)); // returns [ 2, 3, 5, 7 ]
```
## getPrimeFactors(input)
Generates a list all prime factors of a given input.
```
var nh = require('math-lib');
console.log(ml().numberHelper().getPrimeFactors(600851475143)); // returns [ 71, 839, 1471, 6857 ]
```

## computeSlope(foo, x)
Computes the first derivative (slope) of a function foo at x. Central
difference method is used to compute the first derivative. Methodology
used to compute the first derivative and the choice of step size is
detailed here: https://en.wikipedia.org/wiki/Numerical_differentiation
User has to ensure that the function foo is differentiable at x.
```
var nh = require('math-lib');
console.log(ml().numberHelper().computeSlope(function(x) {
  return x * x;
}, 2)); //returns 4.00000000
```
```
var foo2 = function(x) {
  return Math.sin(x);
};
console.log(ml().numberHelper().computeSlope(foo2, Math.PI)); // returns -0.99999999
```

## computeSlope(foo, x)
Computes the second derivative of a function foo at x. Central difference
method is used to compute the second derivative. Methodology used to compute
the second derivative and the choice of step size is detailed here:
https://en.wikipedia.org/wiki/Second_derivative
User has to ensure that the function foo is differentiable twice at x.
```
console.log('foo1', ml().numberHelper().computeSecondDerivative(function(x) {
  return x * x;
}, 2)); // returns 1.999999
```

## newtonRaphson(foo, x, numIterations)
Computes the nearest root of function foo using Newton Raphson method.
The root finding algorithm begins the search at x and iterates for the root
for the number of times as specified by the second parameter - numIterations.
```
var foo1 = function(x) {
  return x * x - 5 * x + 6;
};

function newtonRaphsonTest() {
  console.log(ml().numberHelper().newtonRaphson(foo1, -100, 100));
} // returns 2

function newtonRaphsonTest() {
  console.log(ml().numberHelper().newtonRaphson(foo1, -100, 100));
} // returns 2.999999
```

## gaussianElimination(input)
Solves a series of simultaneous equtions using Gauss Jordan Elimination.
Details of the method can be found here:
https://en.wikipedia.org/wiki/Gaussian_elimination

@param {Number[Number[]]} input - A matrix is an array of arrays of numbers.
Hence, the input is an array of arrays of numbers that describes the augmented
matrix which is an input to the method.
For example, for equations (2x + 3y = 5) and (7x + 10y = 17), the augmented
matrix that is to be passed as an input is as follows:
input = [[2, 3, 5], [7, 10, 17]];

@returns {[Number[]} - An array of array of numbers - an array output consisting
of the rightmost column of the augmented matrix.
```
var set1 = [[2, 1, -1, 8],
             [-3, -1, 2, -11],
             [-2, 1, 2, -3]];

var set2  = [[2, 3, 5], [7, 10, 17]];

console.log(ml().matrixHelper().gaussianElimination(set1));
// returns [2, 3, -1]

console.log(ml().matrixHelper().gaussianElimination(set2));
// returns [1, 2]
```

---
_Source: https://npm.io/package/math-lib · Machine-readable twin of the npm.io package page. Health data is recomputed on every publish._