final def !=(arg0: Any): Boolean

Definition Classes: AnyRef → Any

final def ##(): Int

Definition Classes: AnyRef → Any

def *(x: Double): SparseMatrixD

Multiply this sparse matrix by scalar x.

x: the scalar to multiply by

Definition Classes: SparseMatrixD → MatriD

def *(u: VectoD): VectorD

Multiply this sparse matrix by vector u.

u: the vector to multiply by

Definition Classes: SparseMatrixD → MatriD

def *(b: MatriD): SparseMatrixD

Multiply this sparse matrix by matrix b.

b: the matrix to multiply by (requires sameCrossDimensions)

Definition Classes: SparseMatrixD → MatriD

def *(b: SparseMatrixD): SparseMatrixD

Multiply this sparse matrix by sparse matrix b, by performing a merge operation on the rows on this sparse matrix and the transpose of the b matrix.

b: the matrix to multiply by (requires sameCrossDimensions)

def **(u: VectoD): SparseMatrixD

Multiply this sparse matrix by vector u to produce another matrix (a_ij * u_j)

u: the vector to multiply by

Definition Classes: SparseMatrixD → MatriD

def **:(u: VectoD): SparseMatrixD

Multiply vector 'u' by 'this' matrix to produce another matrix 'u_i * a_ij'.

Multiply vector 'u' by 'this' matrix to produce another matrix 'u_i * a_ij'. E.g., multiply a diagonal matrix represented as a vector by a matrix. This operator is right associative.

u: the vector to multiply by

Definition Classes: SparseMatrixD → MatriD

def **=(u: VectoD): SparseMatrixD

Multiply in-place this sparse matrix by vector u to produce another matrix (a_ij * u_j)

u: the vector to multiply by

Definition Classes: SparseMatrixD → MatriD

def *:(u: VectoD): VectoD

Multiply (row) vector 'u' by 'this' matrix.

Multiply (row) vector 'u' by 'this' matrix. Note '*:' is right associative. vector = vector *: matrix

u: the vector to multiply by

Definition Classes: MatriD

def *=(x: Double): SparseMatrixD

Multiply in-place this sparse matrix by scalar x.

x: the scalar to multiply by

Definition Classes: SparseMatrixD → MatriD

def *=(b: MatriD): SparseMatrixD

Multiply in-place this sparse matrix by matrix b.

b: the matrix to multiply by (requires sameCrossDimensions)

Definition Classes: SparseMatrixD → MatriD

def *=(b: SparseMatrixD): SparseMatrixD

Multiply in-place this sparse matrix by sparse matrix b, by performing a merge operation on the rows on this sparse matrix and the transpose of the b matrix.

b: the matrix to multiply by (requires square and sameCrossDimensions)

def +(x: Double): MatrixD

Add this sparse matrix and scalar x.

Add this sparse matrix and scalar x. Note: every element will be likely filled, hence the return type is a dense matrix.

x: the scalar to add

Definition Classes: SparseMatrixD → MatriD

def +(b: MatriD): SparseMatrixD

Add 'this' sparse matrix and matrix 'b'.

Add 'this' sparse matrix and matrix 'b'. 'b' may be any subtype of MatriD.

b: the matrix to add (requires sameCrossDimensions)

Definition Classes: SparseMatrixD → MatriD

def +(b: MatrixD): SparseMatrixD

Add 'this' sparse matrix and matrix 'b'.

Add 'this' sparse matrix and matrix 'b'. FIX: if same speed as method below - remove

b: the matrix to add (requires sameCrossDimensions)

def +(u: VectoD): SparseMatrixD

Add this matrix and (row) vector u.

u: the vector to add

Definition Classes: SparseMatrixD → MatriD

def +(b: SparseMatrixD): SparseMatrixD

Add 'this' sparse matrix and sparse matrix 'b'.

b: the matrix to add (requires sameCrossDimensions)

def ++(b: MatriD): SparseMatrixD

Concatenate (row-wise) 'this' matrix and matrix 'b'.

b: the matrix to be concatenated as the new last rows in new matrix

Definition Classes: SparseMatrixD → MatriD

def ++^(b: MatriD): SparseMatrixD

Concatenate (column-wise) 'this' matrix and matrix 'b'.

b: the matrix to be concatenated as the new last columns in new matrix

Definition Classes: SparseMatrixD → MatriD

def +:(u: VectoD): SparseMatrixD

Concatenate (row) vector 'u' and 'this' matrix, i.e., prepend 'u' to 'this'.

u: the vector to be prepended as the new first row in new matrix

Definition Classes: SparseMatrixD → MatriD

def +=(x: Double): SparseMatrixD

Add in-place this sparse matrix and scalar x.

x: the scalar to add

Definition Classes: SparseMatrixD → MatriD

def +=(u: VectoD): SparseMatrixD

Add in-place this matrix and (row) vector u.

u: the vector to add

Definition Classes: SparseMatrixD → MatriD

def +=(b: MatriD): SparseMatrixD

Add in-place this sparse matrix and matrix b.

b: the matrix to add (requires sameCrossDimensions)

Definition Classes: SparseMatrixD → MatriD

def +=(b: SparseMatrixD): SparseMatrixD

Add in-place this sparse matrix and sparse matrix b.

b: the matrix to add (requires sameCrossDimensions)

def +^:(u: VectoD): SparseMatrixD

Concatenate (column) vector 'u' and 'this' matrix, i.e., prepend 'u' to 'this'.

u: the vector to be prepended as the new first column in new matrix

Definition Classes: SparseMatrixD → MatriD

def -(x: Double): MatrixD

From this sparse matrix subtract scalar x.

From this sparse matrix subtract scalar x. Note: every element will be likely filled, hence the return type is a dense matrix.

x: the scalar to subtract

Definition Classes: SparseMatrixD → MatriD

def -(u: VectoD): SparseMatrixD

From this matrix subtract (row) vector u.

u: the vector to subtract

Definition Classes: SparseMatrixD → MatriD

def -(b: MatriD): SparseMatrixD

From this sparse matrix substract matrix b.

b: the matrix to subtract (requires sameCrossDimensions)

Definition Classes: SparseMatrixD → MatriD

def -(b: SparseMatrixD): SparseMatrixD

From this sparse matrix substract matrix b.

b: the sparse matrix to subtract (requires sameCrossDimensions)

def -=(x: Double): SparseMatrixD

From this sparse matrix subtract in-place scalar x.

x: the scalar to subtract

Definition Classes: SparseMatrixD → MatriD

def -=(u: VectoD): SparseMatrixD

From this matrix subtract in-place (row) vector u.

u: the vector to subtract

Definition Classes: SparseMatrixD → MatriD

def -=(b: MatriD): SparseMatrixD

From this sparse matrix substract in-place matrix b.

b: the matrix to subtract (requires sameCrossDimensions)

Definition Classes: SparseMatrixD → MatriD

def -=(b: SparseMatrixD): SparseMatrixD

From this sparse matrix substract in-place sparse matrix b.

b: the sparse matrix to subtract (requires sameCrossDimensions)

def /(x: Double): SparseMatrixD

Divide this sparse matrix by scalar x.

x: the scalar to divide by

Definition Classes: SparseMatrixD → MatriD

def /=(x: Double): SparseMatrixD

Divide in-place this sparse matrix by scalar x.

x: the scalar to divide by

Definition Classes: SparseMatrixD → MatriD

def :+(u: VectoD): SparseMatrixD

Concatenate 'this' matrix and (row) vector 'u', i.e., append 'u' to 'this'.

u: the vector to be appended as the new last row in new matrix

Definition Classes: SparseMatrixD → MatriD

def :^+(u: VectoD): SparseMatrixD

Concatenate 'this' matrix and (column) vector 'u', i.e., append 'u' to 'this'.

u: the vector to be appended as the new last column in new matrix

Definition Classes: SparseMatrixD → MatriD

final def ==(arg0: Any): Boolean

Definition Classes: AnyRef → Any

def apply(ir: Range, jr: Range): SparseMatrixD

Get a slice this matrix row-wise on range ir and column-wise on range jr.

Get a slice this matrix row-wise on range ir and column-wise on range jr. Ex: b = a(2..4, 3..5)

ir: the row range
jr: the column range

Definition Classes: SparseMatrixD → MatriD

def apply(i: Int): VectorD

Get this sparse matrix's vector at the i-th index position (i-th row).

i: the row index

Definition Classes: SparseMatrixD → MatriD

def apply(i: Int, j: Int): Double

Get this sparse matrix's element at the i,j-th index position.

i: the row index
j: the column index

Definition Classes: SparseMatrixD → MatriD

def apply(i: Int, jr: Range): VectoD

Get a slice 'this' matrix row-wise at index 'i' and column-wise on range 'jr'.

Get a slice 'this' matrix row-wise at index 'i' and column-wise on range 'jr'. Ex: u = a(2, 3..5)

i: the row index
jr: the column range

Definition Classes: MatriD

def apply(ir: Range, j: Int): VectoD

Get a slice 'this' matrix row-wise on range 'ir' and column-wise at index j.

Get a slice 'this' matrix row-wise on range 'ir' and column-wise at index j. Ex: u = a(2..4, 3)

ir: the row range
j: the column index

Definition Classes: MatriD

final def asInstanceOf[T0]: T0

Definition Classes: Any

def bsolve(y: VectoD): VectorD

Solve for 'x' using back substitution in the equation 'u*x = y' where 'this' matrix ('u') is upper triangular (see 'lud_npp' above).

y: the constant vector

Definition Classes: SparseMatrixD → MatriD

def clean(thres: Double, relative: Boolean = true): SparseMatrixD

Clean values in matrix at or below the threshold by setting them to zero.

Clean values in matrix at or below the threshold by setting them to zero. Iterative algorithms give approximate values and if very close to zero, may throw off other calculations, e.g., in computing eigenvectors.

thres: the cutoff threshold (a small value)
relative: whether to use relative or absolute cutoff

Definition Classes: SparseMatrixD → MatriD

def clone(): AnyRef

Attributes: protected[java.lang]
Definition Classes: AnyRef
Annotations: @throws( ... )

def col(col: Int, from: Int = 0): VectorD

Get column 'col' from the matrix, returning it as a vector.

col: the column to extract from the matrix
from: the position to start extracting from

Definition Classes: SparseMatrixD → MatriD

def copy(): MatriD

Create an exact copy of 'this' m-by-n matrix.

Definition Classes: SparseMatrixD → MatriD

val d1: Int

val d2: Int

def det: Double

Compute the determinant of this sparse matrix.

Definition Classes: SparseMatrixD → MatriD

def diag(p: Int, q: Int): SparseMatrixD

Form a matrix [Ip, this, Iq] where Ir is a r by r identity matrix, by positioning the three matrices Ip, this and Iq along the diagonal.

p: the size of identity matrix Ip
q: the size of identity matrix Iq

Definition Classes: SparseMatrixD → MatriD

def diag(b: MatriD): SparseMatrixD

Combine this sparse matrix with matrix b, placing them along the diagonal and filling in the bottom left and top right regions with zeros; [this, b].

b: the matrix to combine with this matrix

Definition Classes: SparseMatrixD → MatriD

lazy val dim1: Int

Dimension 1

Definition Classes: SparseMatrixD → MatriD

lazy val dim2: Int

Dimension 2

Definition Classes: SparseMatrixD → MatriD

def dot(u: VectoD): VectorD

Compute the dot product of 'this' matrix and vector 'u', by first transposing 'this' matrix and then multiplying by 'u' (ie., 'a dot u = a.t * u').

u: the vector to multiply by (requires same first dimensions)

Definition Classes: SparseMatrixD → MatriD

def dot(b: MatriD): VectoD

Compute the dot product of 'this' matrix and matrix 'b' that results in a vector, by taking the dot product for each column 'j' of both matrices.

b: the matrix to multiply by (requires same first dimensions)

Definition Classes: SparseMatrixD → MatriD
See also: www.mathworks.com/help/matlab/ref/dot.html

final def eq(arg0: AnyRef): Boolean

Definition Classes: AnyRef

def equals(arg0: Any): Boolean

Definition Classes: AnyRef → Any

val fString: String

Format string used for printing vector values (change using 'setFormat')

Attributes: protected
Definition Classes: MatriD

def finalize(): Unit

Attributes: protected[java.lang]
Definition Classes: AnyRef
Annotations: @throws( classOf[java.lang.Throwable] )

final def flaw(method: String, message: String): Unit

Show the flaw by printing the error message.

method: the method where the error occurred
message: the error message

Definition Classes: Error

def foreach[U](f: (Array[Double]) ⇒ U): Unit

Iterate over 'this' matrix row by row applying method 'f'.

f: the function to apply

Definition Classes: MatriD

final def getClass(): Class[_]

Definition Classes: AnyRef → Any

def getDiag(k: Int = 0): VectorD

Get the kth diagonal of this matrix.

Get the kth diagonal of this matrix. Assumes dim2 >= dim1.

k: how far above the main diagonal, e.g., (-1, 0, 1) for (sub, main, super)

Definition Classes: SparseMatrixD → MatriD

def hashCode(): Int

Definition Classes: AnyRef → Any

def inverse: SparseMatrixD

Invert this sparse matrix (requires a squareMatrix) using partial pivoting.

Definition Classes: SparseMatrixD → MatriD

def inverse_ip(): SparseMatrixD

Invert in-place this sparse matrix (requires a squareMatrix).

Invert in-place this sparse matrix (requires a squareMatrix). This version uses partial pivoting.

Definition Classes: SparseMatrixD → MatriD

def inverse_npp: SparseMatrixD

Invert this sparse matrix (requires a squareMatrix) not using partial pivoting.

def isBidiagonal: Boolean

Check whether 'this' matrix is bidiagonal (has non-zero elements only in main diagonal and super-diagonal).

Check whether 'this' matrix is bidiagonal (has non-zero elements only in main diagonal and super-diagonal). The method may be overriding for efficiency.

Definition Classes: MatriD

final def isInstanceOf[T0]: Boolean

Definition Classes: Any

def isNonnegative: Boolean

Check whether this sparse matrix is nonnegative (has no negative elements).

Definition Classes: SparseMatrixD → MatriD

def isRectangular: Boolean

Check whether this sparse matrix is rectangular (all rows have the same number of columns).

Definition Classes: SparseMatrixD → MatriD

def isSquare: Boolean

Check whether 'this' matrix is square (same row and column dimensions).

Definition Classes: MatriD

def isSymmetric: Boolean

Check whether 'this' matrix is symmetric.

Definition Classes: MatriD

def isTridiagonal: Boolean

Check whether 'this' matrix is bidiagonal (has non-zero elements only in main diagonal and super-diagonal).

Check whether 'this' matrix is bidiagonal (has non-zero elements only in main diagonal and super-diagonal). The method may be overriding for efficiency.

Definition Classes: MatriD

def leDimensions(b: MatriD): Boolean

Check whether 'this' matrix dimensions are less than or equal to 'le' those of the other matrix 'b'.

b: the other matrix

Definition Classes: MatriD

def lowerT: MatriD

Return the lower triangular of 'this' matrix (rest are zero).

Definition Classes: SparseMatrixD → MatriD

def lud_ip(): (SparseMatrixD, SparseMatrixD)

Factor in-place this sparse matrix into the product of lower and upper triangular matrices (l, u) using an LU Decomposition algorithm.

Definition Classes: SparseMatrixD → MatriD

def lud_npp: (SparseMatrixD, SparseMatrixD)

Factor this sparse matrix into the product of lower and upper triangular matrices (l, u) using an LU Decomposition algorithm.

Definition Classes: SparseMatrixD → MatriD

def mag: Double

Find the magnitude of 'this' matrix, the element value farthest from zero.

Definition Classes: MatriD

def max(e: Int = dim1): Double

Find the maximum element in this sparse matrix.

e: the ending row index (exclusive) for the search

Definition Classes: SparseMatrixD → MatriD

def mdot(b: MatriD): MatriD

Compute the matrix dot product of 'this' matrix and matrix 'b', by first transposing 'this' matrix and then multiplying by 'b' (i.e., 'a dot b = a.t * b').

b: the matrix to multiply by (requires same first dimensions)

Definition Classes: SparseMatrixD → MatriD

def mean: VectoD

Compute the column means of this matrix.

Definition Classes: MatriD

def min(e: Int = dim1): Double

Find the minimum element in this sparse matrix.

e: the ending row index (exclusive) for the search

Definition Classes: SparseMatrixD → MatriD

final def ne(arg0: AnyRef): Boolean

Definition Classes: AnyRef

def norm1: Double

Compute the 1-norm of 'this' matrix, i.e., the maximum 1-norm of the column vectors.

Compute the 1-norm of 'this' matrix, i.e., the maximum 1-norm of the column vectors. This is useful for comparing matrices '(a - b).norm1'.

Definition Classes: MatriD

final def notify(): Unit

Definition Classes: AnyRef

final def notifyAll(): Unit

Definition Classes: AnyRef

def nullspace: VectorD

Compute the (right) nullspace of this m by n matrix (requires n = m + 1) by performing Gauss-Jordan reduction and extracting the negation of the last column augmented by 1.

Compute the (right) nullspace of this m by n matrix (requires n = m + 1) by performing Gauss-Jordan reduction and extracting the negation of the last column augmented by 1. The nullspace of matrix a is "this vector v times any scalar s", i.e., a*(v*s) = 0. The left nullspace of matrix a is the same as the right nullspace of a.t (a transpose).

Definition Classes: SparseMatrixD → MatriD

def nullspace_ip(): VectorD

Compute the (right) nullspace in-place of this m by n matrix (requires n = m + 1) by performing Gauss-Jordan reduction and extracting the negation of the last column augmented by 1.

Compute the (right) nullspace in-place of this m by n matrix (requires n = m + 1) by performing Gauss-Jordan reduction and extracting the negation of the last column augmented by 1. The nullspace of matrix a is "this vector v times any scalar s", i.e., a*(v*s) = 0. The left nullspace of matrix a is the same as the right nullspace of a.t (a transpose).

Definition Classes: SparseMatrixD → MatriD

val range1: Range

Range for the storage array on dimension 1 (rows)

Definition Classes: MatriD

val range2: Range

Range for the storage array on dimension 2 (columns)

Definition Classes: MatriD

def reduce: SparseMatrixD

Use Guass-Jordan reduction on this sparse matrix to make the left part embed an identity matrix.

Use Guass-Jordan reduction on this sparse matrix to make the left part embed an identity matrix. A constraint on this m by n matrix is that n >= m.

Definition Classes: SparseMatrixD → MatriD

def reduce_ip(): Unit

Use Guass-Jordan reduction in-place on this sparse matrix to make the left part embed an identity matrix.

Use Guass-Jordan reduction in-place on this sparse matrix to make the left part embed an identity matrix. A constraint on this m by n matrix is that n >= m.

Definition Classes: SparseMatrixD → MatriD

def sameCrossDimensions(b: MatriD): Boolean

Check whether 'this' matrix and the other matrix 'b' have the same cross dimensions.

b: the other matrix

Definition Classes: MatriD

def sameDimensions(b: MatriD): Boolean

Check whether 'this' matrix and the other matrix 'b' have the same dimensions.

b: the other matrix

Definition Classes: MatriD

def selectCols(colIndex: Array[Int]): SparseMatrixD

Select columns from this matrix according to the given index/basis.

Select columns from this matrix according to the given index/basis. Ex: Can be used to divide a matrix into a basis and a non-basis.

colIndex: the column index positions (e.g., (0, 2, 5))

Definition Classes: SparseMatrixD → MatriD

def selectRows(rowIndex: Array[Int]): SparseMatrixD

Select rows from this matrix according to the given index/basis.

rowIndex: the row index positions (e.g., (0, 2, 5))

Definition Classes: SparseMatrixD → MatriD

def set(i: Int, u: VectoD, j: Int = 0): Unit

Set this matrix's ith row starting at column j to the vector u.

i: the row index
u: the vector value to assign
j: the starting column index

Definition Classes: SparseMatrixD → MatriD

def set(u: Array[Array[Double]]): Unit

Set all the values in this matrix as copies of the values in 2D array u.

u: the 2D array of values to assign

Definition Classes: SparseMatrixD → MatriD

def set(x: Double): Unit

Set all the elements in this matrix to the scalar x.

x: the scalar value to assign

Definition Classes: SparseMatrixD → MatriD

def setCol(col: Int, u: VectoD): Unit

Set column 'col' of the matrix to a vector.

col: the column to set
u: the vector to assign to the column

Definition Classes: SparseMatrixD → MatriD

def setDiag(x: Double): Unit

Set the main diagonal of this matrix to the scalar x.

Set the main diagonal of this matrix to the scalar x. Assumes dim2 >= dim1.

x: the scalar to set the diagonal to

Definition Classes: SparseMatrixD → MatriD

def setDiag(u: VectoD, k: Int = 0): Unit

Set the kth diagonal of this matrix to the vector u.

Set the kth diagonal of this matrix to the vector u. Assumes dim2 >= dim1.

u: the vector to set the diagonal to
k: how far above the main diagonal, e.g., (-1, 0, 1) for (sub, main, super)

Definition Classes: SparseMatrixD → MatriD

def setFormat(newFormat: String): Unit

Set the format to the 'newFormat'.

newFormat: the new format string

Definition Classes: MatriD

def showAll(): Unit

Show all elements in this sparse matrix.

def slice(r_from: Int, r_end: Int, c_from: Int, c_end: Int): SparseMatrixD

Slice this sparse matrix row-wise r_from to r_end and column-wise c_from to c_end.

r_from: the start of the row slice
r_end: the end of the row slice
c_from: the start of the column slice
c_end: the end of the column slice

Definition Classes: SparseMatrixD → MatriD

def slice(from: Int, end: Int): SparseMatrixD

Slice this sparse matrix row-wise from to end.

from: the start row of the slice
end: the end row of the slice

Definition Classes: SparseMatrixD → MatriD

def sliceCol(from: Int, end: Int): SparseMatrixD

Slice this sparse matrix column-wise 'from' to 'end'.

from: the start column of the slice (inclusive)
end: the end column of the slice (exclusive)

Definition Classes: SparseMatrixD → MatriD

def sliceExclude(row: Int, col: Int): SparseMatrixD

Slice this sparse matrix excluding the given row and column.

row: the row to exclude
col: the column to exclude

Definition Classes: SparseMatrixD → MatriD

def solve(b: VectoD): VectorD

Solve for 'x' in the equation 'a*x = b' where 'a' is 'this' matrix.

b: the constant vector.

Definition Classes: SparseMatrixD → MatriD

def solve(lu: (MatriD, MatriD), b: VectoD): VectorD

Solve for 'x' in the equation 'l*u*x = b' (see 'lud_npp' above).

lu: the lower and upper triangular matrices
b: the constant vector

Definition Classes: SparseMatrixD → MatriD

def solve(l: MatriD, u: MatriD, b: VectoD): VectorD

Solve for x in the equation l*u*x = b (see 'lud_npp' above).

l: the lower triangular matrix
u: the upper triangular matrix
b: the constant vector

Definition Classes: SparseMatrixD → MatriD

def sum: Double

Compute the sum of this sparse matrix, i.e., the sum of its elements.

Definition Classes: SparseMatrixD → MatriD

def sumAbs: Double

Compute the abs sum of this matrix, i.e., the sum of the absolute value of its elements.

Compute the abs sum of this matrix, i.e., the sum of the absolute value of its elements. This is useful for comparing matrices (a - b).sumAbs

Definition Classes: SparseMatrixD → MatriD

def sumLower: Double

Compute the sum of the lower triangular region of this sparse matrix.

Definition Classes: SparseMatrixD → MatriD

def swap(i: Int, k: Int, col: Int = 0): Unit

Swap the elements in rows 'i' and 'k' starting from column 'col'.

i: the first row in the swap
k: the second row in the swap
col: the starting column for the swap (default 0 => whole row)

Definition Classes: MatriD

def swapCol(j: Int, l: Int, row: Int = 0): Unit

Swap the elements in columns 'j' and 'l' starting from row 'row'.

j: the first column in the swap
l: the second column in the swap
row: the starting row for the swap (default 0 => whole column)

Definition Classes: MatriD

final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes: AnyRef

def t: SparseMatrixD

Transpose this sparse matrix (rows => columns).

Definition Classes: SparseMatrixD → MatriD

def times_s(b: SparseMatrixD): SparseMatrixD

Multiply this sparse matrix by sparse matrix b using the Strassen matrix multiplication algorithm.

Multiply this sparse matrix by sparse matrix b using the Strassen matrix multiplication algorithm. Both matrices (this and b) must be square. Although the algorithm is faster than the traditional cubic algorithm, its requires more memory and is often less stable (due to round-off errors). FIX: could be make more efficient using a virtual slice (vslice) method.

b: the matrix to multiply by (it has to be a square matrix)

See also: http://en.wikipedia.org/wiki/Strassen_algorithm

def toDense: MatriD

Convert 'this' matrix to a dense matrix.

Definition Classes: SparseMatrixD → MatriD

def toInt: MatriI

Convert 'this' MatriD into a MatriI.

Definition Classes: SparseMatrixD → MatriD

def toString(): String

Show the non-zero elements in this sparse matrix.

Definition Classes: SparseMatrixD → AnyRef → Any

def trace: Double

Compute the trace of this sparse matrix, i.e., the sum of the elements on the main diagonal.

Compute the trace of this sparse matrix, i.e., the sum of the elements on the main diagonal. Should also equal the sum of the eigenvalues.

Definition Classes: SparseMatrixD → MatriD
See also: Eigen.scala

def update(ir: Range, jr: Range, b: MatriD): Unit

Set a slice this matrix row-wise on range ir and column-wise on range jr.

Set a slice this matrix row-wise on range ir and column-wise on range jr. Ex: a(2..4, 3..5) = b

ir: the row range
jr: the column range
b: the matrix to assign

Definition Classes: SparseMatrixD → MatriD

def update(i: Int, u: SortedLinkedHashMap[Int, Double]): Unit

Set this sparse matrix's row at the i-th index position to the sorted-linked-map u.

i: the row index
u: the sorted-linked-map of non-zreo values to assign

def update(i: Int, u: VectoD): Unit

Set this sparse matrix's row at the i-th index position to the vector u.

i: the row index
u: the vector value to assign

Definition Classes: SparseMatrixD → MatriD

def update(i: Int, j: Int, x: Double): Unit

Set this sparse matrix's element at the i,j-th index position to the scalar x.

Set this sparse matrix's element at the i,j-th index position to the scalar x. Only store x if it is non-zero.

i: the row index
j: the column index
x: the scalar value to assign

Definition Classes: SparseMatrixD → MatriD

def update(i: Int, jr: Range, u: VectoD): Unit

Set a slice of 'this' matrix row-wise at index 'i' and column-wise on range 'jr' to vector 'u'.

Set a slice of 'this' matrix row-wise at index 'i' and column-wise on range 'jr' to vector 'u'. Ex: a(2, 3..5) = u

i: the row index
jr: the column range
u: the vector to assign

Definition Classes: MatriD

def update(ir: Range, j: Int, u: VectoD): Unit

Set a slice of 'this' matrix row-wise on range 'ir' and column-wise at index 'j' to vector 'u'.

Set a slice of 'this' matrix row-wise on range 'ir' and column-wise at index 'j' to vector 'u'. Ex: a(2..4, 3) = u

ir: the row range
j: the column index
u: the vector to assign

Definition Classes: MatriD

def upperT: MatriD

Return the upper triangular of 'this' matrix (rest are zero).

Definition Classes: SparseMatrixD → MatriD

final def wait(): Unit

Definition Classes: AnyRef
Annotations: @throws( ... )

final def wait(arg0: Long, arg1: Int): Unit

Definition Classes: AnyRef
Annotations: @throws( ... )

final def wait(arg0: Long): Unit

Definition Classes: AnyRef
Annotations: @throws( ... )

def write(fileName: String): Unit

Write 'this' matrix to a CSV-formatted text file with name 'fileName'.

fileName: the name of file to hold the data

Definition Classes: SparseMatrixD → MatriD

def zero(m: Int, n: Int): MatriD

Create an m-by-n matrix with all elements initialized to zero.

m: the number of rows
n: the number of columns

Definition Classes: SparseMatrixD → MatriD

def ~^(p: Int): SparseMatrixD

Raise this sparse matrix to the pth power (for some integer p >= 2).

Raise this sparse matrix to the pth power (for some integer p >= 2). Caveat: should be replace by a divide and conquer algorithm.

p: the power to raise this matrix to

Definition Classes: SparseMatrixD → MatriD

Packages

SparseMatrixD

class SparseMatrixD extends MatriD with Error with Serializable

Instance Constructors

Value Members

Inherited from Serializable

Inherited from Serializable

Inherited from MatriD

Inherited from Error

Inherited from AnyRef

Inherited from Any

Ungrouped

Packages

SparseMatrixD 

class SparseMatrixD extends MatriD with Error with Serializable

Instance Constructors

Value Members

Inherited from Serializable

Inherited from Serializable

Inherited from MatriD

Inherited from Error

Inherited from AnyRef

Inherited from Any

Ungrouped

SparseMatrixD