MatrixN

Instance Constructors

new MatrixN(u: MatrixN[T])(implicit arg0: ClassTag[T], arg1: Numeric[T])

Construct a matrix and assign values from matrix u.
Construct a matrix and assign values from matrix u.
u
the matrix of values to assign
new MatrixN(u: Array[VectorN[T]])(implicit arg0: ClassTag[T], arg1: Numeric[T])

Construct a matrix and assign values from array of vectors u.
Construct a matrix and assign values from array of vectors u.
u
the 2D array of values to assign
new MatrixN(dim: (Int, Int), u: T*)(implicit arg0: ClassTag[T], arg1: Numeric[T])

Construct a matrix from repeated values.
Construct a matrix from repeated values.
dim
the (row, column) dimensions
u
the repeated values
new MatrixN(u: Array[Array[T]])(implicit arg0: ClassTag[T], arg1: Numeric[T])

Construct a matrix and assign values from array of arrays u.
Construct a matrix and assign values from array of arrays u.
u
the 2D array of values to assign
new MatrixN(dim1: Int, x: T, y: T)(implicit arg0: ClassTag[T], arg1: Numeric[T])

Construct a dim1 by dim1 square matrix with x assigned on the diagonal and y assigned off the diagonal.
Construct a dim1 by dim1 square matrix with x assigned on the diagonal and y assigned off the diagonal. To obtain an identity matrix, let x = 1 and y = 0.
dim1
the row and column dimension
x
the scalar value to assign on the diagonal
y
the scalar value to assign off the diagonal
new MatrixN(dim1: Int, dim2: Int, x: T)(implicit arg0: ClassTag[T], arg1: Numeric[T])

Construct a dim1 by dim2 matrix and assign each element the value x.
Construct a dim1 by dim2 matrix and assign each element the value x.
dim1
the row dimension
dim2
the column dimesion
x
the scalar value to assign
new MatrixN(dim1: Int)(implicit arg0: ClassTag[T], arg1: Numeric[T])

Construct a dim1 by dim1 square matrix.
Construct a dim1 by dim1 square matrix.
dim1
the row and column dimension
new MatrixN(d1: Int, d2: Int, v: Array[Array[T]] = null)(implicit arg0: ClassTag[T], arg1: Numeric[T])

d1
the first/row dimension
d2
the second/column dimension
v
the 2D array used to store matrix elements

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
def *(x: T): MatrixN[T]

Multiply this matrix by scalar x.
Multiply this matrix by scalar x.
x
the scalar to multiply by

Definition Classes
MatrixN → Matrix
def *(u: VectorD): VectorD

Multiply this matrix by vector u (efficient solution).
Multiply this matrix by vector u (efficient solution).
u
the vector to multiply by
def *(u: VectorN[T]): VectorN[T]

Multiply this matrix by vector u (efficient solution).
Multiply this matrix by vector u (efficient solution).
u
the vector to multiply by

Definition Classes
MatrixN → Matrix
def *(b: MatrixN[T]): MatrixN[T]

Multiply this matrix by matrix b (efficient solution).
Multiply this matrix by matrix b (efficient solution).
b
the matrix to multiply by (requires sameCrossDimensions)
def **(u: VectorN[T]): MatrixN[T]

Multiply this matrix by vector u to produce another matrix (a_ij * b_j)
Multiply this matrix by vector u to produce another matrix (a_ij * b_j)
u
the vector to multiply by

Definition Classes
MatrixN → Matrix
def **=(u: VectorN[T]): MatrixN[T]

Multiply in-place this matrix by vector u to produce another matrix (a_ij * b_j)
Multiply in-place this matrix by vector u to produce another matrix (a_ij * b_j)
u
the vector to multiply by

Definition Classes
MatrixN → Matrix
def *=(x: T): MatrixN[T]

Multiply in-place this matrix by scalar x.
Multiply in-place this matrix by scalar x.
x
the scalar to multiply by

Definition Classes
MatrixN → Matrix
def *=(b: MatrixN[T]): MatrixN[T]

Multiply in-place this matrix by matrix b.
Multiply in-place this matrix by matrix b. If b and this reference the same matrix (b == this), a copy of the this matrix is made.
b
the matrix to multiply by (requires square and sameCrossDimensions)
def +(x: T): MatrixN[T]

Add this matrix and scalar x.
Add this matrix and scalar x.
x
the scalar to add

Definition Classes
MatrixN → Matrix
def +(u: MatrixN[T]): MatrixN[T]

Add this matrix and matrix u.
Add this matrix and matrix u.
u
the matrix to add (requires leDimensions)
def ++(u: VectorN[T]): MatrixN[T]

Concatenate this matrix and vector u.
Concatenate this matrix and vector u.
u
the vector to be concatenated as the new last row in matrix

Definition Classes
MatrixN → Matrix
def +=(x: T): MatrixN[T]

Add in-place this matrix and scalar x.
Add in-place this matrix and scalar x.
x
the scalar to add

Definition Classes
MatrixN → Matrix
def +=(b: MatrixN[T]): MatrixN[T]

Add in-place this matrix and matrix b.
Add in-place this matrix and matrix b.
b
the matrix to add (requires leDimensions)
def -(x: T): MatrixN[T]

From this matrix subtract scalar x.
From this matrix subtract scalar x.
x
the scalar to subtract

Definition Classes
MatrixN → Matrix
def -(b: MatrixN[T]): MatrixN[T]

From this matrix subtract matrix b.
From this matrix subtract matrix b.
b
the matrix to subtract (requires leDimensions)
def -=(x: T): MatrixN[T]

From this matrix subtract in-place scalar x.
From this matrix subtract in-place scalar x.
x
the scalar to subtract

Definition Classes
MatrixN → Matrix
def -=(b: MatrixN[T]): MatrixN[T]

From this matrix subtract in-place matrix b.
From this matrix subtract in-place matrix b.
b
the matrix to subtract (requires leDimensions)
def /(x: T)(implicit fr: Fractional[T]): MatrixN[T]

Divide this matrix by scalar x.
Divide this matrix by scalar x.
x
the scalar to divide by

Definition Classes
MatrixN → Matrix
def /=(x: T)(implicit fr: Fractional[T]): MatrixN[T]

Divide in-place this matrix by scalar x.
Divide in-place this matrix by scalar x.
x
the scalar to divide by

Definition Classes
MatrixN → Matrix
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
val _0: T

Numeric zero (0)
val _1: T

Numeric one (1)
val _1n: T

Numeric minus one (-1)
def apply(i: Int, jr: Range): VectorN[T]

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
MatrixN → Matrix
def apply(ir: Range, j: Int): VectorN[T]

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
MatrixN → Matrix
def apply(ir: Range, jr: Range): MatrixN[T]

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
MatrixN → Matrix
def apply(i: Int): VectorN[T]

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

Definition Classes
MatrixN → Matrix
def apply(i: Int, j: Int): T

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

Definition Classes
MatrixN → Matrix
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clean(thres: T, relative: Boolean = true)(implicit fr: Fractional[T]): MatrixN[T]

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
MatrixN → Matrix
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def col(col: Int, from: Int = 0): VectorN[T]

Get column 'col' from the matrix, returning it as a vector.
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
MatrixN → Matrix
val d1: Int

the first/row dimension
val d2: Int

the second/column dimension
def det: T

Compute the determinant of this matrix.
Compute the determinant of this matrix. The value of the determinant indicates, among other things, whether there is a unique solution to a system of linear equations (a nonzero determinant).

Definition Classes
MatrixN → Matrix
def diag(p: Int, q: Int): MatrixN[T]

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.
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
MatrixN → Matrix
def diag(b: MatrixN[T]): MatrixN[T]

Combine this matrix with matrix b, placing them along the diagonal and filling in the bottom left and top right regions with zeros; [this, b].
Combine this 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
lazy val dim1: Int

Dimension 1
Dimension 1

Definition Classes
MatrixN → Matrix
lazy val dim2: Int

Dimension 2
Dimension 2

Definition Classes
MatrixN → Matrix
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
def flaw(method: String, message: String): Unit

Show the flaw by printing the error message.
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[T]) ⇒ U): Unit

Iterate over the matrix row by row.
Iterate over the matrix row by row.
f
the function to apply

Definition Classes
Matrix
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def getDiag(k: Int = 0): VectorN[T]

Get kth main diagonal of this matrix.
Get kth main 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
MatrixN → Matrix
def hashCode(): Int

Definition Classes
AnyRef → Any
def inverse(implicit fr: Fractional[T]): MatrixN[T]

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

Definition Classes
MatrixN → Matrix
def inverse_ip(implicit fr: Fractional[T]): MatrixN[T]

Invert in-place this matrix (requires a squareMatrix) using partial pivoting.
Invert in-place this matrix (requires a squareMatrix) using partial pivoting.

Definition Classes
MatrixN → Matrix
def inverse_npp(implicit fr: Fractional[T]): MatrixN[T]

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

Definition Classes
MatrixN → Matrix
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def isNonnegative: Boolean

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

Definition Classes
MatrixN → Matrix
def isRectangular: Boolean

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

Definition Classes
MatrixN → Matrix
def isSquare: Boolean

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

Definition Classes
Matrix
def isSymmetric: Boolean

Check whether this matrix is symmetric.
Check whether this matrix is symmetric.

Definition Classes
Matrix
def leDimensions(b: Matrix[T]): Boolean

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

Definition Classes
Matrix
def lud(implicit fr: Fractional[T]): (MatrixN[T], MatrixN[T])

Decompose this matrix into the product of lower and upper triangular matrices (l, u) using the LU Decomposition algorithm.
Decompose this matrix into the product of lower and upper triangular matrices (l, u) using the LU Decomposition algorithm. This version uses partial pivoting.

Definition Classes
MatrixN → Matrix
def lud_ip(implicit fr: Fractional[T]): (MatrixN[T], MatrixN[T])

Decompose in-place this matrix into the product of lower and upper triangular matrices (l, u) using the LU Decomposition algorithm.
Decompose in-place this matrix into the product of lower and upper triangular matrices (l, u) using the LU Decomposition algorithm. This version uses partial pivoting.

Definition Classes
MatrixN → Matrix
def lud_npp(implicit fr: Fractional[T]): (MatrixN[T], MatrixN[T])

Decompose this matrix into the product of upper and lower triangular matrices (l, u) using the LU Decomposition algorithm.
Decompose this matrix into the product of upper and lower triangular matrices (l, u) using the LU Decomposition algorithm. This version uses no partial pivoting.
def mag: T

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

Definition Classes
MatrixN → Matrix
def max(e: Int = dim1): T

Find the maximum element in this matrix.
Find the maximum element in this matrix.
e
the ending row index (exclusive) for the search

Definition Classes
MatrixN → Matrix
def min(e: Int = dim1): T

Find the minimum element in this matrix.
Find the minimum element in this matrix.
e
the ending row index (exclusive) for the search

Definition Classes
MatrixN → Matrix
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def norm1: T

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
MatrixN → Matrix
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val nu: Numeric[T]

Import Numeric evidence (gets nu val from superclass)
def nullspace(implicit fr: Fractional[T]): VectorN[T]

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
MatrixN → Matrix
def nullspace_ip(implicit fr: Fractional[T]): VectorN[T]

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
MatrixN → Matrix
val range1: Range

Range for the storage array on dimension 1 (rows)
Range for the storage array on dimension 1 (rows)

Attributes
protected
Definition Classes
Matrix
val range2: Range

Range for the storage array on dimension 2 (columns)
Range for the storage array on dimension 2 (columns)

Attributes
protected
Definition Classes
Matrix
def rank(implicit fr: Fractional[T]): Int

Determine the rank of this m by n matrix by taking the upper triangular matrix from the LU Decomposition and counting the number of non-zero diagonal elements.
Determine the rank of this m by n matrix by taking the upper triangular matrix from the LU Decomposition and counting the number of non-zero diagonal elements. FIX: should implement in implementing classes.

Definition Classes
Matrix
def reduce(implicit fr: Fractional[T]): MatrixN[T]

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

Definition Classes
MatrixN → Matrix
def reduce_ip(implicit fr: Fractional[T]): Unit

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

Definition Classes
MatrixN → Matrix
def sameCrossDimensions(b: Matrix[T]): Boolean

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

Definition Classes
Matrix
def sameDimensions(b: Matrix[T]): Boolean

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

Definition Classes
Matrix
def selectCols(colIndex: Array[Int]): MatrixN[T]

Select columns from this matrix according to the given index/basis.
Select columns from this matrix according to the given index/basis.
colIndex
the column index positions (e.g., (0, 2, 5))

Definition Classes
MatrixN → Matrix
def selectRows(rowIndex: Array[Int]): MatrixN[T]

Select rows from this matrix according to the given index/basis.
Select rows from this matrix according to the given index/basis.
rowIndex
the row index positions (e.g., (0, 2, 5))

Definition Classes
MatrixN → Matrix
def set(i: Int, u: VectorN[T], j: Int = 0): Unit

Set this matrix's ith row starting at column j to the vector u.
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
MatrixN → Matrix
def set(u: Array[Array[T]]): Unit

Set all the values in this matrix as copies of the values in 2D array u.
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
MatrixN → Matrix
def set(x: T): Unit

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

Definition Classes
MatrixN → Matrix
def setCol(col: Int, u: VectorN[T]): Unit

Set column 'col' of the matrix to a vector.
Set column 'col' of the matrix to a vector.
col
the column to set
u
the vector to assign to the column

Definition Classes
MatrixN → Matrix
def setDiag(x: T): 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
MatrixN → Matrix
def setDiag(u: VectorN[T], 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
MatrixN → Matrix
def slice(r_from: Int, r_end: Int, c_from: Int, c_end: Int): MatrixN[T]

Slice this matrix row-wise r_from to r_end and column-wise c_from to c_end.
Slice this 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
MatrixN → Matrix
def slice(from: Int, end: Int): MatrixN[T]

Slice this matrix row-wise from to end.
Slice this matrix row-wise from to end.
from
the start row of the slice (inclusive)
end
the end row of the slice (exclusive)

Definition Classes
MatrixN → Matrix
def sliceExclude(row: Int, col: Int): MatrixN[T]

Slice this matrix excluding the given row and column.
Slice this matrix excluding the given row and column.
row
the row to exclude
col
the column to exclude

Definition Classes
MatrixN → Matrix
def solve(b: VectorN[T])(implicit fr: Fractional[T]): VectorN[T]

Solve for x in the equation a*x = b where a is this matrix (see lud above).
Solve for x in the equation a*x = b where a is this matrix (see lud above).
b
the constant vector.

Definition Classes
MatrixN → Matrix
def solve(lu: (Matrix[T], Matrix[T]), b: VectorN[T])(implicit fr: Fractional[T]): VectorN[T]

Solve for x in the equation l*u*x = b (see lud above).
Solve for x in the equation l*u*x = b (see lud above).
lu
the lower and upper triangular matrices
b
the constant vector

Definition Classes
MatrixN → Matrix
def solve(l: Matrix[T], u: Matrix[T], b: VectorN[T])(implicit fr: Fractional[T]): VectorN[T]

Solve for x in the equation l*u*x = b (see lud above).
Solve for x in the equation l*u*x = b (see lud above).
l
the lower triangular matrix
u
the upper triangular matrix
b
the constant vector

Definition Classes
MatrixN → Matrix
def sum: T

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

Definition Classes
MatrixN → Matrix
def sumAbs: T

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
MatrixN → Matrix
def sumLower: T

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

Definition Classes
MatrixN → Matrix
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def t: MatrixN[T]

Transpose this matrix (rows => columns).
Transpose this matrix (rows => columns).

Definition Classes
MatrixN → Matrix
def toString(): String

Convert this matrix to a string.
Convert this matrix to a string.

Definition Classes
MatrixN → AnyRef → Any
def trace: T

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

Definition Classes
MatrixN → Matrix
See also
Eigen.scala
def update(i: Int, jr: Range, u: VectorN[T]): Unit

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

Definition Classes
MatrixN → Matrix
def update(ir: Range, j: Int, u: VectorN[T]): Unit

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

Definition Classes
MatrixN → Matrix
def update(ir: Range, jr: Range, b: MatrixN[T]): 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
def update(i: Int, u: VectorN[T]): Unit

Set this matrix's row at the i-th index position to the vector u.
Set this 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
MatrixN → Matrix
def update(i: Int, j: Int, x: T): Unit

Set this matrix's element at the i,j-th index position to the scalar x.
Set this matrix's element at the i,j-th index position to the scalar x.
i
the row index
j
the column index
x
the scalar value to assign

Definition Classes
MatrixN → Matrix
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 ~^(p: Int): MatrixN[T]

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

Related Docs: object MatrixN | package gen

class MatrixN[T] extends Matrix[T] with Error with Serializable

Instance Constructors

new MatrixN(u: MatrixN[T])(implicit arg0: ClassTag[T], arg1: Numeric[T])

new MatrixN(u: Array[VectorN[T]])(implicit arg0: ClassTag[T], arg1: Numeric[T])

new MatrixN(dim: (Int, Int), u: T*)(implicit arg0: ClassTag[T], arg1: Numeric[T])

new MatrixN(u: Array[Array[T]])(implicit arg0: ClassTag[T], arg1: Numeric[T])

new MatrixN(dim1: Int, x: T, y: T)(implicit arg0: ClassTag[T], arg1: Numeric[T])

new MatrixN(dim1: Int, dim2: Int, x: T)(implicit arg0: ClassTag[T], arg1: Numeric[T])

new MatrixN(dim1: Int)(implicit arg0: ClassTag[T], arg1: Numeric[T])

new MatrixN(d1: Int, d2: Int, v: Array[Array[T]] = null)(implicit arg0: ClassTag[T], arg1: Numeric[T])

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

def *(x: T): MatrixN[T]

def *(u: VectorD): VectorD

def *(u: VectorN[T]): VectorN[T]

def *(b: MatrixN[T]): MatrixN[T]

def **(u: VectorN[T]): MatrixN[T]

def **=(u: VectorN[T]): MatrixN[T]

def *=(x: T): MatrixN[T]

def *=(b: MatrixN[T]): MatrixN[T]

def +(x: T): MatrixN[T]

def +(u: MatrixN[T]): MatrixN[T]

def ++(u: VectorN[T]): MatrixN[T]

def +=(x: T): MatrixN[T]

def +=(b: MatrixN[T]): MatrixN[T]

def -(x: T): MatrixN[T]

def -(b: MatrixN[T]): MatrixN[T]

def -=(x: T): MatrixN[T]

def -=(b: MatrixN[T]): MatrixN[T]

def /(x: T)(implicit fr: Fractional[T]): MatrixN[T]

def /=(x: T)(implicit fr: Fractional[T]): MatrixN[T]

final def ==(arg0: Any): Boolean

val _0: T

val _1: T

val _1n: T

def apply(i: Int, jr: Range): VectorN[T]

def apply(ir: Range, j: Int): VectorN[T]

def apply(ir: Range, jr: Range): MatrixN[T]

def apply(i: Int): VectorN[T]

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

final def asInstanceOf[T0]: T0

def clean(thres: T, relative: Boolean = true)(implicit fr: Fractional[T]): MatrixN[T]

def clone(): AnyRef

def col(col: Int, from: Int = 0): VectorN[T]

val d1: Int

val d2: Int

def det: T

def diag(p: Int, q: Int): MatrixN[T]

def diag(b: MatrixN[T]): MatrixN[T]

lazy val dim1: Int

lazy val dim2: Int

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

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

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

final def getClass(): Class[_]

def getDiag(k: Int = 0): VectorN[T]

def hashCode(): Int

def inverse(implicit fr: Fractional[T]): MatrixN[T]

def inverse_ip(implicit fr: Fractional[T]): MatrixN[T]

def inverse_npp(implicit fr: Fractional[T]): MatrixN[T]

final def isInstanceOf[T0]: Boolean

def isNonnegative: Boolean

def isRectangular: Boolean

def isSquare: Boolean

def isSymmetric: Boolean

def leDimensions(b: Matrix[T]): Boolean

def lud(implicit fr: Fractional[T]): (MatrixN[T], MatrixN[T])

def lud_ip(implicit fr: Fractional[T]): (MatrixN[T], MatrixN[T])

def lud_npp(implicit fr: Fractional[T]): (MatrixN[T], MatrixN[T])

def mag: T

def max(e: Int = dim1): T

def min(e: Int = dim1): T

final def ne(arg0: AnyRef): Boolean

def norm1: T

final def notify(): Unit