Eigenjs NPM | npm.io

EigenJS

The goal of this project is to port Eigen library into JavaScript for linear algebar.

Installation

OS X (XCode & Command Line Tools)
Linux (GCC >= 4.8):

$ npm install eigenjs

Windows7/8 (Visual Studio 2012):

$ npm install eigenjs --msvs_version=2012

API

Complex
Matrix
- Matrix Class Methods
- Matrix Instance Methods
Complex Matrix
- Complex Matrix Class Methods
- Complex Matrix Instance Methods
Vector inherits from Matrix
- Vector Class Methods
- Vector Instance Methods
Complex Vector inherits from CMatrix
- Complex Vector Class Methods
- Complex Vector Instance Methods
Row Vector inherits from Matrix
- Row Vector Class Methods
- Row Vector Instance Methods
Complex Row Vector inherits from CMatrix
- Complex Row Vector Class Methods
- Complex Row Vector Instance Methods
Matrix Block inherits from Matrix
- Matrix Block Class Methods
  - MatrixBlock(mat, startRow, startCol, blockRows, blockCols)
  - MatrixBlock(mblock, startRow, startCol, blockRows, blockCols)
- Matrix Block Instance Methods
Complex Matrix Block inherits from CMatrix
- Complex Matrix Block Class Methods
  - CMatrixBlock(cmat, startRow, startCol, blockRows, blockCols)
  - CMatrixBlock(cmblock, startRow, startCol, blockRows, blockCols)
- Complex Matrix Block Instance Methods
Vector Block inherits from Vector and MatrixBlock
- Vector Block Class Methods
  - VectorBlock(vec, startRow, blockRows)
  - VectorBlock(vblock, startRow, blockRows)
- Vector Block Instance Methods
Complex Vector Block inherits from CVector and CMatrixBlock
- Complex Vector Block Class Methods
  - CVectorBlock(cvec, startRow, blockRows)
  - CVectorBlock(cvblock, startRow, blockRows)
- Complex Vector Block Instance Methods
Row Vector Block inherits from RowVector and MatrixBlock
- Row Vector Block Class Methods
  - RowVectorBlock(rvec, startCol, blockCols)
  - RowVectorBlock(rvblock, startCol, blockCols)
- Row Vector Block Instance Methods
Complex Row Vector Block inherits from CRowVector and CMatrixBlock
- Complex Row Vector Block Class Methods
  - CRowVectorBlock(crvec, startCol, blockCols)
  - CRowVectorBlock(crvblock, startCol, blockCols)
- Complex Row Vector Block Instance Methods
Partial Pivoting LU
- Partial Pivoting LU Class Methods
  - PartialPivLU(mat)
  - PartialPivLU(mblock)
- Partial Pivoting LU Instance Methods
Complex Partial Pivoting LU
- Complex Partial Pivoting LU Class Methods
  - CPartialPivLU(cmat)
  - CPartialPivLU(cmblock)
- Complex Partial Pivoting LU Instance Methods
Full Pivoting LU
- Full Pivoting LU Class Methods
  - FullPivLU(mat)
  - FullPivLU(mblock)
- Full Pivoting LU Instance Methods
Complex Full Pivoting LU
- Complex Full Pivoting LU Class Methods
  - CFullPivLU(cmat)
  - CFullPivLU(cmblock)
- Complex Full Pivoting LU Instance Methods

Complex

Complex Class Methods

Complex(real, imag)

var C = require('eigenjs').Complex
  , c = new C(3, -4);
console.log('c = %s', c);

c = (3,-4)

Complex.polar(scalar, scalar)

var C = require('eigenjs').Complex
  , rho = 5
  , theta = -0.9272952180016122
  , c = C.polar(rho, theta);
console.log(c.conj().toString());
console.log(c.real * Math.cos(c.imag));
console.log(c.real * Math.sin(c.imag));

(5,0.927295)
3.0000000000000004
-3.9999999999999996

Complex.cos(scalar)

Complex.cos(comp)

var C = require('eigenjs').Complex
  , c1 = new C(Math.PI/4, 0)
  , c2 = C.cos(c1);
console.log(c2.toString());

(0.707107,-0)

Complex.cosh(scalar)

Complex.cosh(comp)

var C = require('eigenjs').Complex
  , c1 = new C(0, 0)
  , c2 = C.cosh(c1);
console.log(c2.toString());

(1,0)

Complex.exp(scalar)

Complex.exp(comp)

var C = require('eigenjs').Complex
  , c1 = new C(1, 0)
  , c2 = C.exp(c1);
console.log(c2.toString());

(2.71828,0)

Complex.log(scalar)

Complex.log(comp)

var C = require('eigenjs').Complex
  , c1 = new C(Math.E, 0)
  , c2 = C.log(c1);
console.log(c2.toString());

(1,0)

Complex.log10(scalar)

Complex.log10(comp)

var C = require('eigenjs').Complex
  , c1 = new C(1000, 0)
  , c2 = C.log10(c1);
console.log(c2.toString());

(3,0)

Complex.pow(scalar, scalar)

Complex.pow(scalar, comp)

Complex.pow(comp, scalar)

Complex.pow(comp, comp)

var C = require('eigenjs').Complex
  , c = C.pow(2, 3)
console.log(c.toString());

(8,0)

Complex.sin(scalar)

Complex.sin(comp)

var C = require('eigenjs').Complex
  , c1 = new C(Math.PI/4, 0)
  , c2 = C.sin(c1);
console.log(c2.toString());

(0.707107,0)

Complex.sinh(scalar)

Complex.sinh(comp)

var C = require('eigenjs').Complex
  , c1 = new C(0, 0)
  , c2 = C.sinh(c1);
console.log(c2.toString());

(0,0)

Complex.sqrt(scalar)

Complex.sqrt(comp)

var C = require('eigenjs').Complex
  , c1 = new C(9, 0)
  , c2 = C.sqrt(c1);
console.log(c2.toString());

(3,0)

Complex.tan(scalar)

Complex.tan(comp)

var C = require('eigenjs').Complex
  , c1 = new C(Math.PI/4, 0)
  , c2 = C.tan(c1);
console.log(c2.toString());

(1,0)

Complex.tanh(scalar)

Complex.tanh(comp)

var C = require('eigenjs').Complex
  , c1 = new C(Infinity, 0)
  , c2 = C.tanh(c1);
console.log(c2.toString());

(1,0)

Complex.acos(scalar)

Complex.acos(comp)

var C = require('eigenjs').Complex
  , c1 = new C(1, 0)
  , c2 = C.acos(c1);
console.log(c2.toString());

(0,0)

Complex.acosh(scalar)

Complex.acosh(comp)

var C = require('eigenjs').Complex
  , c1 = new C(1.54308, 0)
  , c2 = C.acosh(c1);
console.log(c2.toString());

(0.999999,0)

Complex.asin(scalar)

Complex.asin(comp)

var C = require('eigenjs').Complex
  , c1 = new C(1, 0)
  , c2 = C.asin(c1);
console.log(c2.toString());

(1.5708,7.82511e-09)

Complex.asinh(scalar)

Complex.asinh(comp)

var C = require('eigenjs').Complex
  , c1 = new C(1, 0)
  , c2 = C.asinh(c1);
console.log(c2.toString());

(0.881374,0)

Complex.atan(scalar)

Complex.atan(comp)

var C = require('eigenjs').Complex
  , c1 = new C(Infinity, 0)
  , c2 = C.atan(c1);
console.log(c2.toString());

(1.5708,0)

Complex.atanh(scalar)

Complex.atanh(comp)

var C = require('eigenjs').Complex
  , c1 = new C(1, 0)
  , c2 = C.atanh(c1);
console.log(c2.toString());

(inf,0)

Complex Instance Methods

comp.abs()

var C = require('eigenjs').Complex
  , c = new C(3, -4);
console.log(c.abs());

comp.arg()

var C = require('eigenjs').Complex
  , c = new C(3, -4);
console.log(c.arg());
console.log('(%d,%d)', c.abs() * Math.cos(c.arg()), c.abs() * Math.sin(c.arg()));

-0.9272952180016122
(3.0000000000000004,-3.9999999999999996)

comp.norm()

var C = require('eigenjs').Complex
  , c = new C(3, -4);
console.log(c.norm());

comp.conj()

var C = require('eigenjs').Complex
  , c = new C(3, -4);
console.log(c.conj().toString());

(3,4)

comp.proj(scalar)

comp.proj(comp)

var C = require('eigenjs').Complex
  , c1 = new C(0, -Infinity)
  , c2 = C.proj(c1);
console.log(c2.toString());

(inf, -0)

comp.add(scalar)

comp.add(comp)

var C = require('eigenjs').Complex
  , c1 = new C(3, 0)
  , c2 = new C(0, 4)
  , c3 = c1.add(c2);
console.log(c3.toString());

(3,4)

comp.adda(scalar)

comp.adda(comp)

var C = require('eigenjs').Complex
  , c1 = new C(3, 0)
  , c2 = new C(0, 4);
c1.adda(c2);
console.log(c1.toString());

(3,4)

comp.sub(scalar)

comp.sub(comp)

var C = require('eigenjs').Complex
  , c1 = new C(3, 4)
  , c2 = new C(2, -3)
  , c3 = c1.sub(c2);
console.log(c3.toString());

(1,7)

comp.suba(scalar)

comp.suba(comp)

var C = require('eigenjs').Complex
  , c1 = new C(5, 8)
  , c2 = new C(-3, 4);
c1.suba(c2);
console.log(c1.toString());

(8,4)

comp.mul(scalar)

comp.mul(comp)

comp.mul(mat)

comp.mul(vec)

comp.mul(rvec)

comp.mul(mblock)

comp.mul(vblock)

comp.mul(rvblock)

comp.mul(cmat)

comp.mul(cvec)

comp.mul(crvec)

comp.mul(cmblock)

comp.mul(cvblock)

comp.mul(crvblock)

var C = require('eigenjs').Complex
  , c1 = new C(1, 8)
  , c2 = new C(6, 4)
  , c3 = c1.mul(c2);
console.log(c3.toString());

(-26,52)

comp.mula(scalar)

comp.mula(comp)

var C = require('eigenjs').Complex
  , c1 = new C(3, 1)
  , c2 = new C(2, 4)
c1.mula(c2);
console.log(c1.toString());

(2,14)

comp.div(scalar)

comp.div(comp)

var C = require('eigenjs').Complex
  , c1 = new C(4, 8)
  , c2 = new C(2, 0)
  , c3 = c1.div(c2);
console.log(c3.toString());

(2,4)

comp.diva(scalar)

comp.diva(comp)

var C = require('eigenjs').Complex
  , c1 = new C(3, 9)
  , c2 = new C(9, 0)
c1.diva(c2);
console.log(c2.toString());

(0.333333,1)

comp.equals(scalar)

comp.equals(comp)

var C = require('eigenjs').Complex
  , c1 = new C(1, 0)
  , c2 = c1.conj();
console.log(c1.equals(c2));

true

comp.isApprox(comp, prec = 1e-12)

var C = require('eigenjs').Complex
  , c1 = new C(1/3, 0)
  , c2 = new C(0.3333, 0);
console.log(c1.isApprox(c2, 1e-3));

true

comp.toString()

var C = require('eigenjs').Complex
  , c = new C(3, -4);
console.log(c.toString());

(3,-4)

Complex Properties

comp.real

comp.imag

var C = require('eigenjs').Complex
  , c = new C(3, -4);
c.real = 6;
c.imag = 8;
console.log('(%d,%d)', c.real, c.imag);

(6,8)

Matrix

Matrix Class Methods

Matrix(mat)

Matrix(vec)

Matrix(rvec)

Matrix(mblock)

Matrix(vblock)

Matrix(rvblock)

var M = require('eigenjs').Matrix
  , mat = new M.Random(2, 3)
  , mat2 = new M(mat);
console.log('mat =\n%s\n', mat);
console.log('mat2 =\n%s', mat2);

mat =
  0.381981  -0.373117  -0.866239
-0.0467884  -0.981309  -0.885573

mat2 =
  0.381981  -0.373117  -0.866239
-0.0467884  -0.981309  -0.885573

Matrix(rows, cols)

var M = require('eigenjs').Matrix
  , mat = new M(2, 3);
console.log('mat =\n%s', mat);

mat =
0 0 0
0 0 0

Matrix.Zero(n)

Matrix.Zero(rows, cols)

var M = require('eigenjs').Matrix
  , mat = M.Zero(2, 3);
console.log('mat = \n%s', mat);

mat =
0 0 0
0 0 0

Matrix.Ones(n)

Matrix.Ones(rows, cols)

var M = require('eigenjs').Matrix
  , mat = M.Ones(2, 3);
console.log('mat = \n%s', mat);

mat =
1 1 1
1 1 1

Matrix.Constant(rows, cols, scalar)

Matrix.Constant(rows, cols, comp)

var M = require('eigenjs').Matrix
  , mat = M.Constant(4, 4, 0.6);
console.log('mat = \n%s', mat);

mat =
0.6 0.6 0.6 0.6
0.6 0.6 0.6 0.6
0.6 0.6 0.6 0.6
0.6 0.6 0.6 0.6

Matrix.Random(n)

Matrix.Random(rows, cols)

var M = require('eigenjs').Matrix
  , mat = M.Random(2, 3);
console.log('mat = \n%s', mat);

mat =
-0.421952 -0.671276  0.547419
 0.260209  -0.13622  0.464891

Matrix.Identity(n)

Matrix.Identity(rows, cols)

var M = require('eigenjs').Matrix
  , mat1 = M.Identity(2)
  , mat2 = M.Identity(2, 3);
console.log('mat1 = \n%s', mat1);
console.log('mat2 = \n%s', mat2);

mat1 =
1 0
0 1
mat2 =
1 0 0
0 1 0

Matrix Instance Methods

mat.rows()

mat.cols()

var M = require('eigenjs').Matrix
  , mat = new M(2, 3);
console.log(mat.rows());
console.log(mat.cols());

2
3

mat.set(row, col, scalar)

var M = require('eigenjs').Matrix
  , mat = new M(2, 2);
mat.set(0, 0, 1)
   .set(0, 1, 2)
   .set(1, 0, 3)
   .set(1, 1, 4);
console.log('mat = \n%s', mat);

mat =
1 2
3 4

mat.set(scalar_array)

var M = require('eigenjs').Matrix
  , mat = new M(3, 3);
mat.set([
  1, 2, 3,
  4, 5, 6,
  7, 8, 9
]);
console.log('mat = \n%s', mat);

mat.get(row, col)

var M = require('eigenjs').Matrix
  , mat = new M(2, 2);
mat.set([
  1, 2,
  3, 4
]);
console.log(mat.get(0, 0) + ' ' + mat.get(0, 1));
console.log(mat.get(1, 0) + ' ' + mat.get(1, 1));

1 2
3 4

mat.assign(mat)

mat.assign(vec)

mat.assign(rvec)

mat.assign(mblock)

mat.assign(vblock)

mat.assign(rvblock)

var M = require('eigenjs').Matrix
  , mat = M.Random(4, 4);
mat.assign(M.Zero(4, 4));
console.log('mat = \n%s', mat);

mat.value()

Returns the unique coefficient of a 1x1 expression

var M = require('eigenjs').Matrix
  , mat = M.Random(1, 1);
console.log('%d', mat.value());

-0.7131525574778916

mat.setZero()

var M = require('eigenjs').Matrix
  , mat = new M.Random(3, 3);
console.log('mat =\n%s\n', mat);
console.log('mat =\n%s', mat.setZero());

mat =
 0.244911 -0.752925 -0.562905
 0.215088 -0.406688 -0.750836
 0.983236  0.800109  0.695126

mat =
0 0 0
0 0 0
0 0 0

mat.setOnes()

var M = require('eigenjs').Matrix
  , mat = new M.Zero(3, 3);
console.log('mat =\n%s\n', mat);
console.log('mat =\n%s', mat.setOnes());

mat.setConstant(scalar)

var M = require('eigenjs').Matrix
  , mat = new M.Zero(3, 3);
console.log('mat =\n%s\n', mat);
console.log('mat =\n%s', mat.setConstant(0.6));

mat =
0 0 0
0 0 0
0 0 0

mat =
0.6 0.6 0.6
0.6 0.6 0.6
0.6 0.6 0.6

mat.setRandom()

var M = require('eigenjs').Matrix
  , mat = new M.Zero(3, 3);
console.log('mat =\n%s\n', mat);
console.log('mat =\n%s', mat.setRandom());

mat =
0 0 0
0 0 0
0 0 0

mat =
 -0.292434 -0.0673437   0.283946
 -0.938224   0.154289   0.283845
 -0.725773  -0.862362   0.583097

mat.setIdentity()

var M = require('eigenjs').Matrix
  , mat = new M.Zero(3, 3);
console.log('mat =\n%s\n', mat);
console.log('mat =\n%s', mat.setIdentity());

mat.setDiagonal(index, vec)

mat.setDiagonal(index, rvec)

var M = require('eigenjs').Matrix
  , mat = new M.Zero(3, 3)
  , dia = mat.diagonal(1);
console.log('mat =\n%s\n', mat);
dia.setRandom();
console.log('mat =\n%s', mat.setDiagonal(1, dia));

mat =
0 0 0
0 0 0
0 0 0

mat =
        0 -0.294006         0
        0         0  0.634569
        0         0         0

mat.block(startRow, startCol, blockRows, blockCols)

var M = require('eigenjs').Matrix
  , mat = new M.Identity(4, 4)
  , mblock = mat.block(1, 1, 2, 2);
mblock.assign(M.Random(2, 2));
console.log('mat =\n%s', mat);

mat =
        1         0         0         0
        0 -0.822352  0.533723         0
        0  0.721993  0.287646         0
        0         0         0         1

mat.row(n)

var Eigen = require('eigenjs')
  , M = Eigen.Matrix
  , RV = Eigen.RowVector
  , mat = new M.Zero(3, 3)
  , mblock = mat.row(1);
mblock.assign(RV.Random(3));
console.log('mat =\n%s', mat);

mat =
        0         0         0
-0.843392 -0.891355  0.991578
        0         0         0

mat.col(n)

var Eigen = require('eigenjs')
  , M = Eigen.Matrix
  , V = Eigen.Vector
  , mat = new M.Zero(3, 3)
  , mblock = mat.col(1);
mblock.assign(V.Random(3));
console.log('mat =\n%s', mat);

mat =
         0   0.674939          0
         0  -0.303923          0
         0 -0.0302965          0

mat.topRows(n)

Returns a block consisting of the top rows of *this.

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5,  3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.topRows(2));

 7  9 -5  3
-2 -6  1  0

mat.bottomRows(n)

Returns a block consisting of the bottom rows of *this.

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5,  3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.bottomRows(2));

 6 -3  0  9
 6  6  3  9

mat.middleRows(startRow, n)

Returns a block consisting of a range of rows of *this.

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5,  3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.middleRows(1, 2));

-2 -6  1  0
 6 -3  0  9

mat.leftCols(n)

Returns a block consisting of the left columns of *this.

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5,  3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.leftCols(2));

mat.rightCols(n)

Returns a block consisting of the right columns of *this.

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5,  3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.rightCols(2));

mat.middleCols(startCol, n)

Returns a block consisting of a range of columns of *this.

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5,  3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.middleCols(1, 2));

mat.topLeftCorner(cRows, cCols)

Returns a block consisting of a top-left corner of *this.

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5,  3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.topLeftCorner(2, 2));

 7  9
-2 -6

mat.topRightCorner(cRows, cCols)

Returns a block consisting of a top-right corner of *this.

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5,  3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.topRightCorner(2, 2));

-5  3
 1  0

mat.bottomLeftCorner(cRows, cCols)

Returns a block consisting of a bottom-left corner of *this.

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5,  3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.bottomLeftCorner(2, 2));

 6 -3
 6  6

mat.bottomRightCorner(cRows, cCols)

Returns a block consisting of a bottom-right corner of *this.

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5,  3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.bottomRightCorner(2, 2));

0 9
3 9

mat.replicate(rowFactor, colFactor)

var M = require('eigenjs').Matrix
  , mat = new M(3, 1).set([
             7,
            -2,
             6
          ]);
console.log('%s', mat.replicate(2, 5));

 7  7  7  7  7
-2 -2 -2 -2 -2
 6  6  6  6  6
 7  7  7  7  7
-2 -2 -2 -2 -2
 6  6  6  6  6

mat.add(mat)

mat.add(vec)

mat.add(rvec)

mat.add(mblock)

mat.add(vblock)

mat.add(rvblock)

mat.add(cmat)

mat.add(cvec)

mat.add(crvec)

mat.add(cmblock)

mat.add(cvblock)

mat.add(crvblock)

var M = require('eigenjs').Matrix
  , mat1 = new M(2, 2)
  , mat2 = new M(2, 2)
  , mat3;
mat1.set([
  1, 3,
  2, 4
]);
mat2.set([
  5, 6,
  7, 8
]);
mat3 = mat1.add(mat2);
console.log('mat3 = \n%s', mat3);

mat3 =
 6  9
 9 12

mat.adda(mat)

mat.adda(vec)

mat.adda(rvec)

mat.adda(mblock)

mat.adda(vblock)

mat.adda(rvblock)

var M = require('eigenjs').Matrix
  , mat1 = new M(2, 2)
  , mat2 = new M(2, 2);
mat1.set([
  1, 3,
  2, 4
]);
mat2.set([
  5, 6,
  7, 8
]);
mat1.adda(mat2);
console.log('mat1 = \n%s', mat1);

mat1 =
 6  9
 9 12

mat.sub(mat)

mat.sub(vec)

mat.sub(rvec)

mat.sub(mblock)

mat.sub(vblock)

mat.sub(rvblock)

mat.sub(cmat)

mat.sub(cvet)

mat.sub(crvet)

mat.sub(cmblock)

mat.sub(cvblock)

mat.sub(crvblock)

var M = require('eigenjs').Matrix
  , mat1 = new M(2, 2)
  , mat2 = new M(2, 2)
  , mat3;
mat1.set([
  1, 3,
  2, 4
]);
mat2.set([
  5, 6,
  7, 8
]);
mat3 = mat1.sub(mat2);
console.log('mat3 = \n%s', mat3);

mat3 =
-4 -3
-5 -4

mat.suba(mat)

mat.suba(vec)

mat.suba(rvec)

mat.suba(mblock)

mat.suba(vblock)

mat.suba(rvblock)

var M = require('eigenjs').Matrix
  , mat1 = new M(2, 2)
  , mat2 = new M(2, 2);
mat1.set([
  1, 3,
  2, 4
]);
mat2.set([
  5, 6,
  7, 8
]);
mat1.suba(mat2);
console.log('mat1 = \n%s', mat1);

mat1 =
-4 -3
-5 -4

mat.mul(scalar)

mat.mul(comp)

mat.mul(mat)

mat.mul(vec)

mat.mul(rvec)

mat.mul(mblock)

mat.mul(vblock)

mat.mul(rvblock)

mat.mul(cmat)

mat.mul(cvec)

mat.mul(crvec)

mat.mul(cvblock)

mat.mul(crvblock)

var M = require('eigenjs').Matrix
  , mat1 = new M(2, 3)
  , vec = new M(3, 1)
  , mat2;
mat1.set([
  1, 2, 3,
  4, 5, 6
]);
vec.set([
  1,
  6,
  8
]);
mat2 = mat1.mul(vec);
console.log('mat2 = \n%s', mat2);

mat2 =
37
82

mat.mula(scalar)

mat.mula(mat)

mat.mula(vec)

mat.mula(rvec)

mat.mula(mblock)

mat.mula(vblock)

mat.mula(rvblock)

var M = require('eigenjs').Matrix
  , mat = new M(2, 3)
  , vec = new M(3, 1);
mat.set([
  1, 2, 3,
  4, 5, 6
]);
vec.set([
  1,
  6,
  8
]);
mat.mula(vec);
console.log('mat = \n%s', mat);

mat =
37
82

mat.div(scalar)

mat.div(comp)

var M = require('eigenjs').Matrix
  , mat1 = new M(2, 2)
  , mat2;
mat1.set([
  1, 2,
  3, 4
]);
mat2 = mat1.div(2);
console.log('mat2 = \n%s', mat2);

mat2 =
0.5   1
1.5   2

mat.diva(scalar)

var M = require('eigenjs').Matrix
  , mat = new M(2, 2);
mat.set([
  1, 2,
  3, 4
]);
mat.diva(2);
console.log('mat = \n%s', mat);

mat =
0.5   1
1.5   2

mat.transpose()

var M = require('eigenjs').Matrix
  , mat1 = new M.Random(3, 2)
  , mat2 = mat1.transpose();
console.log('mat1 = \n%s', mat1);
console.log('mat2 = \n%s', mat2);

mat1 =
 -0.112813  -0.325566
-0.0500345   0.213005
 -0.930346  -0.022705
mat2 =
 -0.112813 -0.0500345  -0.930346
 -0.325566   0.213005  -0.022705

mat.conjugate()

var M = require('eigenjs').Matrix
  , mat1 = new M.Random(2, 2)
  , mat2 = mat1.conjugate();
console.log(mat1.equals(mat2));

true

mat.adjoint()

var M = require('eigenjs').Matrix
  , mat1 = new M.Random(3, 2)
  , mat2 = mat1.adjoint();
console.log('mat1 = \n%s', mat1);
console.log('mat2 = \n%s', mat2);

mat1 =
 0.997487 0.0670765
 0.770148 -0.645138
 -0.12185 -0.835853
mat2 =
 0.997487  0.770148  -0.12185
0.0670765 -0.645138 -0.835853

mat.determinant()

Returns the determinant of this matrix. This method uses class PartialPivLU.

var M = require('eigenjs').Matrix
  , mat = new M.Random(2, 2);
console.log('mat = \n%s\n', mat);
console.log('det = %d', mat.determinant());

mat =
 0.132371 -0.813862
 0.758326  -0.58171

det = 0.540171350604003

mat.inverse()

Returns the matrix inverse of this matrix. This method uses class PartialPivLU.

var M = require('eigenjs').Matrix
  , mat = new M(3, 3).set([
            1, 2, 3,
            0, 1, 4,
            5, 6, 0
          ])
  , inv = mat.inverse();
console.log('inv = \n%s', inv);

inv =
-24  18   5
 20 -15  -4
 -5   4   1

mat.trace()

var M = require('eigenjs').Matrix
  , mat = new M(2, 3).set([
            1, 2, 3,
            4, 5, 6
          ])
  , tr = mat.trace();
console.log('mat = \n%s\n', mat);
console.log('tr = ', tr);

mat =
1 2 3
4 5 6

tr =  6

mat.diagonal(index = 0)

var M = require('eigenjs').Matrix
  , mat = new M(4, 4).set([
             7,  9, -5, -3,
            -2, -6,  1,  0,
             6, -3,  0,  9,
             6,  6,  3,  9
          ]);
console.log('%s', mat.diagonal(1).transpose());
console.log('%s', mat.diagonal(-2).transpose());

9 1 9
6 6

mat.norm()

Returns the Frobenius norm.

var M = require('eigenjs').Matrix
  , mat = new M(3, 3).set([
            1, 2, 3,
            4, 5, 6,
            7, 8, 9
          ]);
console.log('%d', mat.norm());

16.881943016134134

mat.redux(func)

func Function The result of a full redux operation on the whoie matrix or vector using func.

var M = require('eigenjs').Matrix
  , mat = new M(3, 3).set([
            1, 2, 3,
            4, 5, 6,
            7, 8, 9
          ])
  , func = function(a, b) { return a + b; };
console.log('%d', mat.redux(func));

mat.sum()

var M = require('eigenjs').Matrix
  , mat = new M(3, 3).set([
            1, 2, 3,
            4, 5, 6,
            7, 8, 9
          ]);
console.log('%d', mat.sum());

mat.prod()

var M = require('eigenjs').Matrix
  , mat = new M(3, 3).set([
            1, 2, 3,
            4, 5, 6,
            7, 8, 9
          ]);
console.log('%d', mat.prod());

mat.mean()

var M = require('eigenjs').Matrix
  , mat = new M(3, 3).set([
            1, 2, 3,
            4, 5, 6,
            7, 8, 9
          ]);
console.log('%d', mat.mean());

mat.visit(func)

func Function Applies the func to the whole coefficients of the matrix or vector.

var M = require('eigenjs').Matrix
  , mat = new M(3, 3).set([
            1, 2, 3,
            4, 5, 6,
            7, 8, 9
          ]);
mat.visit(function(value, row, col) {
  console.log('mat(%d, %d) = %d', row, col, value);
});

mat(0, 0) = 1
mat(1, 0) = 4
mat(2, 0) = 7
mat(0, 1) = 2
mat(1, 1) = 5
mat(2, 1) = 8
mat(0, 2) = 3
mat(1, 2) = 6
mat(2, 2) = 9

mat.maxCoeff()

var M = require('eigenjs').Matrix
  , mat = new M.Random(3, 3);
console.log('mat = \n%s\n', mat);
console.log('max = %d', mat.maxCoeff());

mat =
  0.175793  -0.547068  -0.959701
  0.561311  -0.579446   0.297471
-0.0382309  -0.743676  -0.411312

max = 0.5613114636211243

mat.maxCoeff(obj)

obj Object

var M = require('eigenjs').Matrix
  , mat = new M.Random(3, 3)
  , obj = {};
console.log('mat = \n%s\n', mat);
console.log('max = %s', mat.maxCoeff(obj));
console.log('obj = %s', JSON.stringify(obj));

mat =
 -0.68294  0.690895 -0.698356
-0.174138 -0.119934  0.733219
-0.743578  0.262349 -0.795382

max = 0.7332185766348702
obj = {"maxCoeff":0.7332185766348702,"rowId":1,"colId":2}

mat.maxCoeff(func)

func Function

var M = require('eigenjs').Matrix
  , mat = new M.Random(3, 3)
  , func = function(rowId, colId) {
             console.log('rowId = %d, colId = %d', rowId, colId);
           };
console.log('mat = \n%s\n', mat);
console.log('max = %d', mat.maxCoeff(func));

mat =
-0.552622 -0.355055  0.141004
0.0814275   0.58272  -0.13819
 0.552011 -0.217758 -0.551142

rowId = 1, colId = 1
max = 0.5827204285109044

mat.minCoeff()

var M = require('eigenjs').Matrix
  , mat = new M.Random(3, 3);
console.log('mat = \n%s\n', mat);
console.log('min = %d', mat.minCoeff());

mat =
-0.725041  0.511321   0.29833
 0.233345  -0.22101 0.0355704
-0.167162 -0.514649 -0.168438

min = -0.7250411527813604

mat.minCoeff(obj)

obj Object

var M = require('eigenjs').Matrix
  , mat = new M.Random(3, 3)
  , obj = {};
console.log('mat = \n%s\n', mat);
console.log('min = %d', mat.minCoeff(obj));
console.log('obj = %s', JSON.stringify(obj));

mat =
  0.74568  0.870563  -0.82341
 0.636928 -0.455949  0.944912
 0.855648  0.872564  -0.87055

min = -0.8705498761825962
obj = {"minCoeff":-0.8705498761825962,"rowId":2,"colId":2}

mat.minCoeff(func)

func Function

var M = require('eigenjs').Matrix
  , mat = new M.Random(3, 3)
  , func = function(rowId, colId) {
             console.log('rowId = %d, colId = %d', rowId, colId);
           };
console.log('mat = \n%s\n', mat);
console.log('min = %d', mat.minCoeff(func));

 0.371743  0.261372  0.144462
-0.111958  0.884582  -0.02937
 0.314765 -0.823458  0.378298

rowId = 2, colId = 1
min = -0.8234578174648144

mat.equals(mat)

mat.equals(vec)

mat.equals(rvec)

mat.equals(mblock)

mat.equals(vblock)

mat.equals(rvblock)

var M = require('eigenjs').Matrix
  , mat1 = new M(2, 2)
  , mat2 = new M(2, 2)
  , mat3 = new M(2, 2);
mat1.set([
  1, 2,
  3, 4
]);
mat2.set([
  1, 0,
  0, 1
]);
mat3.set([
  0, 2,
  3, 3
]);
console.log(mat1.equals(mat2.add(mat3)));

true

mat.isApprox(mat, prec = 1e-12)

mat.isApprox(vec, prec = 1e-12)

mat.isApprox(rvec, prec = 1e-12)

mat.isApprox(mblock, prec = 1e-12)

mat.isApprox(vblock, prec = 1e-12)

mat.isApprox(rvblock, prec = 1e-12)

var M = require('eigenjs').Matrix
  , mat1 = new M(2, 2)
  , mat2 = new M(2, 2);
mat1.set([
  1, 3,
  5, 7
]).diva(11);
mat2.set([
  0.091, 0.273,
  0.455, 0.636
]);
console.log(mat1.isApprox(mat2, 1e-3));

true

mat.isSquare()

var M = require('eigenjs').Matrix
  , mat1 = new M(4, 4)
  , mat2 = new M(3, 2);
console.log(mat1.isSquare());
console.log(mat2.isSquare());

true
false

mat.isZero(prec = 1e-12)

var M = require('eigenjs').Matrix
  , mat = new M(2, 3).set([
            0,      0, 0.0001,
            0,      0,      0
          ]);
console.log(mat.isZero());
console.log(mat.isZero(1e-3));

false
true

mat.isOnes(prec = 1e-12)

var M = require('eigenjs').Matrix
  , mat = new M(2, 3).set([
            1,      1, 1.0001,
            1, 0.9997,      1
          ]);
console.log(mat.isOnes());
console.log(mat.isOnes(1e-3));

false
true

mat.isIdentity(prec = 1e-12)

var M = require('eigenjs').Matrix
  , mat = new M(3, 3).set([
            1,       0, 0.0001,
            0,  0.9997,      0,
            0,       0,      1
          ]);
console.log(mat.isIdentity());
console.log(mat.isIdentity(1e-3));

false
true

mat.isDiagonal(prec = 1e-12)

var M = require('eigenjs').Matrix
  , mat = new M(3, 3).set([
            1e+04,     0,     1,
                0, 1e+04,     0,
                0,     0, 1e+04
          ]);
console.log(mat.isDiagonal());
console.log(mat.isDiagonal(1e-3));

false
true

mat.all()

Returns true if all coefficients are true.

var M = require('eigenjs').Matrix
  , mat = new M.Constant(3, 3, 1);
console.log('mat = \n%s\n%s\n', mat, mat.all());
mat.set(0, 0, 0);
console.log('mat = \n%s\n%s', mat, mat.all());

mat =
1 1 1
1 1 1
1 1 1
true

mat =
0 1 1
1 1 1
1 1 1
false

mat.any()

Returns true if at least one coefficient is true.

var M = require('eigenjs').Matrix
  , mat = new M.Zero(3, 3);
console.log('mat = \n%s\n%s\n', mat, mat.any());
mat.set(0, 0, 1);
console.log('mat = \n%s\n%s', mat, mat.any());

mat =
0 0 0
0 0 0
0 0 0
false

mat =
1 0 0
0 0 0
0 0 0
true

mat.count()

Returns the number of coefficients which evaluate to true.

var M = require('eigenjs').Matrix
  , mat = new M.Zero(3, 3);
mat.block(0, 1, 3, 2).setOnes();
console.log('mat = \n%s\n', mat);
console.log('%d', mat.count());

mat.allFinite()

Returns true if *this contains only finite numbers, i.e., no NaN and no +/-INF values.

var M = require('eigenjs').Matrix
  , mat = new M.Random(3, 3);
console.log('mat = \n%s\n%s\n', mat, mat.allFinite());
mat.set(0, 0, Infinity);
console.log('mat = \n%s\n%s', mat, mat.allFinite());

mat =
 0.202332  0.271506 -0.887678
 0.592388 -0.806422  0.799406
  0.26443  0.461303 -0.389755
true

mat =
      inf  0.271506 -0.887678
 0.592388 -0.806422  0.799406
  0.26443  0.461303 -0.389755
false

mat.hasNaN()

Returns true if *this contains at least one Not A Number (NaN).

var M = require('eigenjs').Matrix
  , mat = new M.Zero(3, 3);
console.log('mat = \n%s\n%s\n', mat, mat.hasNaN());
mat.set(1, 1, NaN);
console.log('mat = \n%s\n%s', mat, mat.hasNaN());

mat =
0 0 0
0 0 0
0 0 0
false

mat =
  0   0   0
  0 nan   0
  0   0   0
true

mat.partialPivLu()

Returns the partial-pivoting LU decomposition of *this.

var M = require('eigenjs').Matrix
  , mat = new M(3, 3).set([
            1, 4, 5,
            4, 2, 6,
            5, 6, 3
          ])
  , pplu = mat.partialPivLu();
console.log('P = \n%s\n', pplu.permutationP());
console.log('L = \n%s\n', pplu.matrixL());
console.log('U = \n%s', pplu.matrixU());

P =
0 0 1
0 1 0
1 0 0

L =
  1   0   0
0.8   1   0
0.2  -1   1

U =
   5    6    3
   0 -2.8  3.6
   0    0    8

mat.fullPivLu()

Returns the full-pivoting LU decomposition of *this.

var M = require('eigenjs').Matrix
  , mat = new M(2, 4).set([
             1,  1,  1,  3,
             1,  2, -1,  4
          ])
  , fplu = mat.fullPivLu();
console.log('P = \n%s\n', fplu.permutationP());
console.log('L = \n%s\n', fplu.matrixL());
console.log('U = \n%s\n', fplu.matrixU());
console.log('Q = \n%s', fplu.permutationQ());

P =
0 1
1 0

L =
   1    0
0.75    1

U =
   4   -1    2    1
   0 1.75 -0.5 0.25

Q =
0 0 0 1
0 0 1 0
0 1 0 0
1 0 0 0

mat.toString(options)

options Object
- precision Number Default=6. The number of digits for floating point values.
- fullPrecision Booleam Default=false. If set to true, then the number of digits will be computed to match the full precision of each floating-point type.
- dontAlignCols Booleam Default=false. If set to true, it allows to disable the alignment of columnt, resulting in faster code.
- coeffSeparator String Default=' '. The string printed between two coefficients of the same row.
- rowSepara