Class: SparseMatrix

let T = new Triplet(100, 100);
T.addEntry(3.4, 11, 43);
T.addEntry(6.4, 99, 99);
let A = SparseMatrix.fromTriplet(T);

let B = SparseMatrix.identity(10, 10);

let d = DenseMatrix.ones(100, 1);
let C = SparseMatrix.diag(d);

Methods

---

<static> fromTriplet(T)

Initializes a sparse matrix from a Triplet object.

Parameters:

Name	Type	Description
T	module:LinearAlgebra.Triplet	A triplet object containing only the nonzero entries that need to be stored in this sparse matrix.

Returns:

Type

module:LinearAlgebra.SparseMatrix

---

<static> identity(m, n)

Initializes a m by n sparse identity matrix.

Parameters:

Name	Type	Description
m	number	The number of rows in this sparse matrix.
n	number	The number of columns in this sparse matrix.

Returns:

Type

module:LinearAlgebra.SparseMatrix

---

<static> diag(d)

Initializes a sparse diagonal matrix.

Parameters:

Name	Type	Description
d	module:LinearAlgebra.DenseMatrix	The dense vector (d.nCols() == 1) used to initialize this sparse diagonal matrix.

Returns:

Type

module:LinearAlgebra.SparseMatrix

---

transpose()

Returns the transpose of this sparse matrix.

Returns:

Type

module:LinearAlgebra.SparseMatrix

---

invertDiagonal()

Returns the inverse of this diagonal sparse matrix.

Returns:

Type

module:LinearAlgebra.SparseMatrix

---

nRows()

Returns the number of rows in this sparse matrix.

Returns:

Type

number

---

nCols()

Returns the number of columns in this sparse matrix.

Returns:

Type

number

---

nnz()

Returns the number of nonzero entries in this sparse matrix.

Returns:

Type

number

---

frobeniusNorm()

Computes the frobenius norm of this sparse matrix.

Returns:

Type

number

---

subMatrix(r0, r1, c0, c1)

Extracts a sparse sub-matrix in the range [r0, r1) x [c0, c1), i.e., a matrix
of size (r1 - r0) x (c1 - c0) starting at indices (r0, c0).

Parameters:

Name	Type	Description
r0	number	The start row index.
r1	number	The end row index (not included).
c0	number	The start column index.
c1	number	The end column index (not included).

Returns:

Type

module:LinearAlgebra.SparseMatrix

---

chol()

Returns a sparse Cholesky factorization of this sparse matrix.

Returns:

Type

module:LinearAlgebra.Cholesky

---

lu()

Returns a sparse LU factorization of this sparse matrix.

Returns:

Type

module:LinearAlgebra.LU

---

qr()

Returns a sparse QR factorization of this sparse matrix.

Returns:

Type

module:LinearAlgebra.QR

---

toDense()

Returns a dense copy of this sparse matrix.

Returns:

Type

module:LinearAlgebra.DenseMatrix

---

incrementBy(B)

A += B

Parameters:

Name	Type	Description
B	module:LinearAlgebra.SparseMatrix	The sparse matrix added to this sparse matrix.

---

decrementBy(B)

A -= B

Parameters:

Name	Type	Description
B	module:LinearAlgebra.SparseMatrix	The sparse matrix subtracted from this sparse matrix.

---

scaleBy(s)

A *= s

Parameters:

Name	Type	Description
s	number	The number this sparse matrix is scaled by.

---

plus(B)

Returns A + B

Parameters:

Name	Type	Description
B	module:LinearAlgebra.SparseMatrix	The sparse matrix added to this sparse matrix.

Returns:

Type

module:LinearAlgebra.SparseMatrix

---

minus(B)

Returns A - B

Parameters:

Name	Type	Description
B	module:LinearAlgebra.SparseMatrix	The sparse matrix subtracted from this sparse matrix.

Returns:

Type

module:LinearAlgebra.SparseMatrix

---

timesReal(s)

Returns A * s

Parameters:

Name	Type	Description
s	number	The number this sparse matrix is multiplied by.

Returns:

Type

module:LinearAlgebra.SparseMatrix

---

timesDense(X)

Returns A * X

Parameters:

Name	Type	Description
X	module:LinearAlgebra.DenseMatrix	The dense matrix this sparse matrix is multiplied by.

Returns:

Type

module:LinearAlgebra.DenseMatrix

---

timesSparse(B)

Returns A * B

Parameters:

Name	Type	Description
B	module:LinearAlgebra.SparseMatrix	The sparse matrix this sparse matrix is multiplied by.

Returns:

Type

module:LinearAlgebra.SparseMatrix