av.matrix is a small & fast JavaScript matrix (2D arrays) utilities library. Pure, strict and ECMAScript 5 compliant.
It extends the core Array object to supply the basics for linear Algebra (2D), in a clean, compact and speedy way where the explicit loops have been avoided. But LU()... :(
Can be combined with [av.array] (https://github.com/AbelVM/av.arrays "Small&Fast Javascript library that attaches xtra methods for arrays, including basic Descriptive Statistics functions") to get even more from your matrix!
Being arrX a Matrix:
- Constructors: A matrix can be instatiated using a wide variety of inputs:
arrA = new Matrix(); // [0]
arrB = new Matrix(n); // Zero row vector size n
arrC = new Matrix(1,m); // Zero column vector size m
arrD = new Matrix(n,m); // Zero matrix size n x m
r1 = [E11,...,E1m] ;
...
rn = [En1,..., Enm];
arrE = new Matrix(r1, ..., rn); // nxm matrix with the given rows
arrF = new Matrix([[], ..., []]); // Matrix from the given array of arrays (rows)
arrG = Matrix.Fill(n, value); // Square matrix size = n, every item = value
arrH = Matrix.Diagonal (n, value); // Diagonal matrix size = n, item(i=j) = value
arrI = Matrix.Upper(n, value); // Upper matrix size n, item(i>=j) = value
arrJ = Matrix.Lower(n, value); // Lower matrix size n, item(i<=j) = value- Algebra methods: Here is where fun begins:
arrB = arrA.scalar(value); // New matrix, where scalar multiplication of value has been applied to arrA
arrD = arrA.add(arrC); // New matrix that results of the sum of ArrA and ArrB, both of the same size.
arrF = arrA.dot(arrE); // New matrix, dot product of arrA and arrE, where size of arrA is axb and size of arrE is bxc
arrA.LU(); // Object with the matrices resulting of the LU decomposition of arrA. {"L":arrL , "U": arrU}
arrA.det(); // Returns the determinant of arrA
arrG = arrA.adjugate(); // New matrix, adjugate of arrA
arrH = arrA.inverse(); // New matrix, inverse of arrA####And several support methods!
- Properties:
Matrix.version; // String with [av.matrix] version (read-only)
arrA.size; // Array [n,m] with the size n x m of the matrix (read-only)
arrA.trace; // Number, the trace of the matrix (read-only)- Retrievers
arrA.item(i,j); // Returns the value of item(i,j)
arrA.row(i); // Returns an array with the values of row i
arrA.column(j); // Returns an array with the values of column j- Checking methods: Perform some usual checks to matrices:
arrA.samesize(arrB); // True if both matrices have the same size
arrA.is(arrB); // True if arrA == ArrB
arrA.isNaN(); // Trueif arrA has at least one NaN item
arrA.symmetric(); // True if arrA is symmetric. item(i,j)==item(j,i)
arr.square(); // True if arrA is an square matrix- Process methods: Methods that apply simple process to the current Matrix:
arrB = arrA.fill(value); // New matrix with the same size as arrA but filled with value
arrC = arrA.upper(); // New matrix, same as arrA, but item(i<j) = 0
arrD = arrA.lower(); // New matrix, same as arrA, but item(i>j) = 0
arrE = arrA.transpose(); // New matrix, transpose of arrA.
arrF = arrA.minor(i,j); // New matrix, size n-1 x m-1. Minor of itemA(i,j)- Xtra methods:
arrB = arrA.clone(); // New matrix, deep clone of arrA
arrA.tostring(sep); // Pretty print of arrA, using sep as separator of items (default sep= ', ')