js-mat

JavaScript library for representation and mathematical operations using matrix

Usage

Import the package as:
``
import {mat} from '../mat/Mat'
`
Create a matrix of random values:
`
var M: mat.Matrix = mat.rand(3,3); // create a 3x3 matrix
`

Create a null matrix:
`
var M: mat.Matrix = mat.zeros(2,5); // create a 2x5 null matrix
`

Create a matrix of ones:
`
var M: mat.Matrix = mat.ones(2,2) // create a 2x2 matrix of ones
`

Create an identity matrix:
`
var I: mat.Matrix = mat.eye(4); // identity matrix of size 4x4
`

Create a matrix from a 2D array:
`
// We show you two ways of doing it

// Using constructor
var M: mat.matrix = new mat.Matrix([
[1,2,3],
[4,5,6],
[7,8,9]
]);

// Using the matrix function
var M: mat.Matrix = mat.matrix([
[1,2,3],
[4,5,6],
[7,8,9]
]);
`

Create a matrix from another matrix
`
var M1: mat.Matrix = mat.rand(3,6);
var M2: mat.Matrix = new mat.Matrix(M1); // equal to M1
`

Operations

Addition:
`
var M1 = new Matrix([
[12,7,9],
[5,-2,3]
]);
var M2 = new Matrix([
[-3.6, 0, 5.4],
[-12,-2,7]
]);

var result = M1.add(M2);
// [8.4, 7, 14.4]
// [-7, -4, -10]
`

Substraction:
`
var M1 = new Matrix([
[12,7,9],
[5,-2,3]
]);
var M2 = new Matrix([
[-3.6, 0, 5.4],
[-12,-2,7]
]);

var result = M1.subtract(M2); // M1.diff(M2) also works
// [15.6, 7.0, 3.6]
// [17.0, 0, -4.0]
`

Multiplication:
`
// Multiply two matrices
var M1 = new Matrix([
[1, 2, 9],
[-3, 7, 1]
]);

var M2 = new Matrix([
[-5, 1],
[3, 12],
[1, 1]
]);

var result = M1.multiply(M2); // M1.dot(M2) also works
// [10, 34]
// [37, 82]
`

`
// Multiply a matrix by a constant
var M1 = new Matrix([
[1, 2, 9],
[-3, 7, 1]
]);

var result = M1.multiply(5);
// [5, 10, 45]
// [-15, 35, 5]
`

Determinant:
`
var M = new Matrix([
[5, -2, 2, 7],
[1, 0, 0, 3],
[-3, 1, 5, 0],
[3, -1, -9, 4]
]);

M.det(); // returns 88
`

Inverse:
`
var M = new Matrix([
[5, -2, 2, 7],
[1, 0, 0, 3],
[-3, 1, 5, 0],
[3, -1, -9, 4]
]);

M.inv();

// [-0.1364, 0.8636, -0.6818, -0.4091]
// [-0.6364, 2.3636, -0.9318, -0.6591]
// [0.0455, 0.0455, -0.0227, -0.1136]
// [0.0455, 0.0455, 0.2273, 0.1364]
`

Transpose:
`
var M = new Matrix([
[5, -2, 2, 7],
[1, 0, 0, 3],
[-3, 1, 5, 0]
]);

M.T; // or also M.transpose()
// [5, 1, -3]
// [-2, 0, 1]
// [2, 0, 5]
// [7, 3, 0]
`

Cofactor Matrix:
`
var M = new Matrix([
[5, -2, 2, 7],
[1, 0, 0, 3],
[-3, 1, 5, 0],
[3, -1, -9, 4]
]);

M.cof();

// [-12, -56, 4, 4]
// [76, 208, 4, 4]
// [-60, -82, -2, 20]
// [-36, -58, -10, 12]
`

Adjoint:
`
var M = new Matrix([
[5, -2, 2, 7],
[1, 0, 0, 3],
[-3, 1, 5, 0],
[3, -1, -9, 4]
]);

M.adj();

// [ -12, 76, -60, -36 ]
// [ -56, 208, -82, -58 ]
// [ 4, 4, -2, -10 ]
// [ 4, 4, 20, 12 ]
`

Minor:
`
// Calculate the determinant when removing the given row and column indexes
var M = new Matrix([
[5, -2, 2, 7],
[1, 0, 0, 3],
[-3, 1, 5, 0],
[3, -1, -9, 4]
]);

M.minor(0,1); // returns 56
`

And more matrix operations including:
* Horizontal concatenation: `M1.horzcat(M2)`
* Vetical concatenation: `M1.vertcat(M2)`
* Add row: `M.addRow(row)`
* Add column: `M.addColumn(column)`
* Remove row: `M.deleteRow(index)`
* Delete column: `M.deleteColumn(index)`
* Compare: `M1.equals(M2)`
* map/apply: `M.map(x => x2), M.apply(x => x2)`
* arange: `Matrix.arange(2, 10, 0.5)`
* linspace: `Matrix.linspace(0, 10, 100)`
* reshape: `M.reshape([2,3])`
* flatten/ravel: `M.flatten(), M.ravel()`
* diag: `M.diag()``

Examples

* Solve a system of linear equations using Least Squares method
* Find the roots of a system of equations using Newton-Raphson method
* Perform Linear Regression method
* Perform Logistic Regression
Note: There are a lot more examples. but we highlights the ones that implements a lot of the functionalities mentioned above