trait MatriQ extends Error
The MatriQ
trait specifies the operations to be defined by the concrete
classes implementing Rational
matrices, i.e.,
MatrixQ - dense matrix
BidMatrixQ - bidiagonal matrix - useful for computing Singular Values
SparseMatrixQ - sparse matrix - majority of elements should be zero
SymTriMatrixQ - symmetric triangular matrix - useful for computing Eigenvalues
par.MatrixQ - parallel dense matrix
par.SparseMatrixQ - parallel sparse matrix
Some of the classes provide a few custom methods, e.g., methods beginning with "times"
or ending with "npp".
------------------------------------------------------------------------------
row-wise column-wise
Append: matrix +: vector matrix +: vector
Concatenate: matrix ++ matrix matrix ++ matrix
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-
abstract
def
*(x: Rational): MatriQ
Multiply 'this' matrix by scalar 'x'.
Multiply 'this' matrix by scalar 'x'.
- x
the scalar to multiply by
-
abstract
def
*(u: VectorQ): VectorQ
Multiply 'this' matrix by vector 'u'.
Multiply 'this' matrix by vector 'u'.
- u
the vector to multiply by
-
abstract
def
*(b: MatriQ): MatriQ
Multiply 'this' matrix and matrix 'b' for any type extending
MatriQ
.Multiply 'this' matrix and matrix 'b' for any type extending
MatriQ
. Note, subtypes of MatriQ should also implement a more efficient version, e.g.,def * (b: MatrixD): MatrixD
.- b
the matrix to add (requires leDimensions)
-
abstract
def
**(u: VectorQ): MatriQ
Multiply 'this' matrix by vector 'u' to produce another matrix (a_ij * u_j)
Multiply 'this' matrix by vector 'u' to produce another matrix (a_ij * u_j)
- u
the vector to multiply by
-
abstract
def
**=(u: VectorQ): MatriQ
Multiply in-place 'this' matrix by vector 'u' to produce another matrix (a_ij * u_j)
Multiply in-place 'this' matrix by vector 'u' to produce another matrix (a_ij * u_j)
- u
the vector to multiply by
-
abstract
def
*=(x: Rational): MatriQ
Multiply in-place 'this' matrix by scalar 'x'.
Multiply in-place 'this' matrix by scalar 'x'.
- x
the scalar to multiply by
-
abstract
def
*=(b: MatriQ): MatriQ
Multiply in-place 'this' matrix and matrix 'b' for any type extending
MatriQ
.Multiply in-place 'this' matrix and matrix 'b' for any type extending
MatriQ
. Note, subtypes of MatriQ should also implement a more efficient version, e.g.,def *= (b: MatrixD): MatrixD
.- b
the matrix to multiply by (requires leDimensions)
-
abstract
def
+(x: Rational): MatriQ
Add 'this' matrix and scalar 'x'.
Add 'this' matrix and scalar 'x'.
- x
the scalar to add
-
abstract
def
+(u: VectorQ): MatriQ
Add 'this' matrix and (row) vector 'u'.
Add 'this' matrix and (row) vector 'u'.
- u
the vector to add
-
abstract
def
+(b: MatriQ): MatriQ
Add 'this' matrix and matrix 'b' for any type extending
MatriQ
.Add 'this' matrix and matrix 'b' for any type extending
MatriQ
. Note, subtypes of MatriQ should also implement a more efficient version, e.g.,def + (b: MatrixD): MatrixD
.- b
the matrix to add (requires leDimensions)
-
abstract
def
++(b: MatriQ): MatriQ
Concatenate (row-wise) 'this' matrix and matrix 'b'.
Concatenate (row-wise) 'this' matrix and matrix 'b'.
- b
the matrix to be concatenated as the new last rows in new matrix
-
abstract
def
++^(b: MatriQ): MatriQ
Concatenate (column-wise) 'this' matrix and matrix 'b'.
Concatenate (column-wise) 'this' matrix and matrix 'b'.
- b
the matrix to be concatenated as the new last columns in new matrix
-
abstract
def
+:(u: VectorQ): MatriQ
Concatenate (row) vector 'u' and 'this' matrix, i.e., prepend 'u' to 'this'.
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
-
abstract
def
+=(x: Rational): MatriQ
Add in-place 'this' matrix and scalar 'x'.
Add in-place 'this' matrix and scalar 'x'.
- x
the scalar to add
-
abstract
def
+=(u: VectorQ): MatriQ
Add in-place 'this' matrix and (row) vector 'u'.
Add in-place 'this' matrix and (row) vector 'u'.
- u
the vector to add
-
abstract
def
+=(b: MatriQ): MatriQ
Add in-place 'this' matrix and matrix 'b' for any type extending
MatriQ
.Add in-place 'this' matrix and matrix 'b' for any type extending
MatriQ
. Note, subtypes of MatriQ should also implement a more efficient version, e.g.,def += (b: MatrixD): MatrixD
.- b
the matrix to add (requires leDimensions)
-
abstract
def
+^:(u: VectorQ): MatriQ
Concatenate (column) vector 'u' and 'this' matrix, i.e., prepend 'u' to 'this'.
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
-
abstract
def
-(x: Rational): MatriQ
From 'this' matrix subtract scalar 'x'.
From 'this' matrix subtract scalar 'x'.
- x
the scalar to subtract
-
abstract
def
-(u: VectorQ): MatriQ
From 'this' matrix subtract (row) vector 'u'.
From 'this' matrix subtract (row) vector 'u'.
- u
the vector to subtract
-
abstract
def
-(b: MatriQ): MatriQ
From 'this' matrix subtract matrix 'b' for any type extending
MatriQ
.From 'this' matrix subtract matrix 'b' for any type extending
MatriQ
. Note, subtypes of MatriQ should also implement a more efficient version, e.g.,def - (b: MatrixD): MatrixD
.- b
the matrix to subtract (requires leDimensions)
-
abstract
def
-=(x: Rational): MatriQ
From 'this' matrix subtract in-place scalar 'x'.
From 'this' matrix subtract in-place scalar 'x'.
- x
the scalar to subtract
-
abstract
def
-=(u: VectorQ): MatriQ
From 'this' matrix subtract in-place (row) vector 'u'.
From 'this' matrix subtract in-place (row) vector 'u'.
- u
the vector to subtract
-
abstract
def
-=(b: MatriQ): MatriQ
From 'this' matrix subtract in-place matrix 'b' for any type extending
MatriQ
.From 'this' matrix subtract in-place matrix 'b' for any type extending
MatriQ
. Note, subtypes of MatriQ should also implement a more efficient version, e.g.,def -= (b: MatrixD): MatrixD
.- b
the matrix to subtract (requires leDimensions)
-
abstract
def
/(x: Rational): MatriQ
Divide 'this' matrix by scalar 'x'.
Divide 'this' matrix by scalar 'x'.
- x
the scalar to divide by
-
abstract
def
/=(x: Rational): MatriQ
Divide in-place 'this' matrix by scalar 'x'.
Divide in-place 'this' matrix by scalar 'x'.
- x
the scalar to divide by
-
abstract
def
:+(u: VectorQ): MatriQ
Concatenate 'this' matrix and (row) vector 'u', i.e., append 'u' to 'this'.
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
-
abstract
def
:^+(u: VectorQ): MatriQ
Concatenate 'this' matrix and (column) vector 'u', i.e., append 'u' to 'this'.
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
-
abstract
def
apply(ir: Range, jr: Range): MatriQ
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
-
abstract
def
apply(i: Int): VectorQ
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
-
abstract
def
apply(i: Int, j: Int): Rational
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
-
abstract
def
clean(thres: Double, relative: Boolean = true): MatriQ
Clean values in 'this' matrix at or below the threshold 'thres' by setting them to zero.
Clean values in 'this' matrix at or below the threshold 'thres' 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
-
abstract
def
col(col: Int, from: Int = 0): VectorQ
Get column 'col' starting 'from' in 'this' matrix, returning it as a vector.
Get column 'col' starting 'from' in 'this' matrix, returning it as a vector.
- col
the column to extract from the matrix
- from
the position to start extracting from
-
abstract
def
det: Rational
Compute the determinant of 'this' matrix.
-
abstract
def
diag(p: Int, q: Int = 0): MatriQ
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
-
abstract
def
diag(b: MatriQ): MatriQ
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
-
abstract
val
dim1: Int
Matrix dimension 1 (# rows)
-
abstract
val
dim2: Int
Matrix dimension 2 (# columns)
-
abstract
def
dot(u: VectorQ): VectorQ
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').
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)
-
abstract
def
getDiag(k: Int = 0): VectorQ
Get the 'k'th diagonal of 'this' matrix.
Get the 'k'th diagonal of 'this' matrix. Assumes dim2 >= dim1.
- k
how far above the main diagonal, e.g., (-1, 0, 1) for (sub, main, super)
-
abstract
def
inverse: MatriQ
Invert 'this' matrix (requires a squareMatrix) and use partial pivoting.
-
abstract
def
inverse_ip: MatriQ
Invert in-place 'this' matrix (requires a squareMatrix) and use partial pivoting.
-
abstract
def
isRectangular: Boolean
Check whether 'this' matrix is rectangular (all rows have the same number of columns).
-
abstract
def
lud: (MatriQ, MatriQ)
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.
-
abstract
def
lud_ip: (MatriQ, MatriQ)
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.
-
abstract
def
max(e: Int = dim1): Rational
Find the maximum element in 'this' matrix.
Find the maximum element in 'this' matrix.
- e
the ending row index (exclusive) for the search
-
abstract
def
min(e: Int = dim1): Rational
Find the minimum element in 'this' matrix.
Find the minimum element in 'this' matrix.
- e
the ending row index (exclusive) for the search
-
abstract
def
nullspace: VectorQ
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.
nullspace (a) = set of orthogonal vectors v s.t. a * v = 0
The left nullspace of matrix 'a' is the same as the right nullspace of 'a.t'. FIX: need a more robust algorithm for computing nullspace (@see Fac_QR.scala). FIX: remove the 'n = m+1' restriction.
- See also
http://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/ax-b-and-the-four-subspaces /solving-ax-0-pivot-variables-special-solutions/MIT18_06SCF11_Ses1.7sum.pdf
-
abstract
def
nullspace_ip: VectorQ
Compute in-place 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 in-place 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.
nullspace (a) = set of orthogonal vectors v s.t. a * v = 0
The left nullspace of matrix 'a' is the same as the right nullspace of 'a.t'. FIX: need a more robust algorithm for computing nullspace (@see Fac_QR.scala). FIX: remove the 'n = m+1' restriction.
- See also
http://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/ax-b-and-the-four-subspaces /solving-ax-0-pivot-variables-special-solutions/MIT18_06SCF11_Ses1.7sum.pdf
-
abstract
def
reduce: MatriQ
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.
-
abstract
def
reduce_ip(): 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.
-
abstract
def
selectCols(colIndex: Array[Int]): MatriQ
Select columns from 'this' matrix according to the given index/basis colIndex.
Select columns from 'this' matrix according to the given index/basis colIndex. 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))
-
abstract
def
selectRows(rowIndex: Array[Int]): MatriQ
Select rows from 'this' matrix according to the given index/basis 'rowIndex'.
Select rows from 'this' matrix according to the given index/basis 'rowIndex'.
- rowIndex
the row index positions (e.g., (0, 2, 5))
-
abstract
def
set(i: Int, u: VectorQ, j: Int = 0): Unit
Set 'this' matrix's 'i'th row starting a column 'j' to the vector 'u'.
Set 'this' matrix's 'i'th row starting a column 'j' to the vector 'u'.
- i
the row index
- u
the vector value to assign
- j
the starting column index
-
abstract
def
set(u: Array[Array[Rational]]): Unit
Set the values in 'this' matrix as copies of the values in 2D array 'u'.
Set the values in 'this' matrix as copies of the values in 2D array 'u'.
- u
the 2D array of values to assign
-
abstract
def
set(x: Rational): 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
-
abstract
def
setCol(col: Int, u: VectorQ): Unit
Set column 'col' of 'this' matrix to vector 'u'.
Set column 'col' of 'this' matrix to vector 'u'.
- col
the column to set
- u
the vector to assign to the column
-
abstract
def
setDiag(x: Rational): 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
-
abstract
def
setDiag(u: VectorQ, k: Int = 0): Unit
Set the 'k'th diagonal of 'this' matrix to the vector 'u'.
Set the 'k'th 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)
-
abstract
def
slice(r_from: Int, r_end: Int, c_from: Int, c_end: Int): MatriQ
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 (inclusive)
- r_end
the end of the row slice (exclusive)
- c_from
the start of the column slice (inclusive)
- c_end
the end of the column slice (exclusive)
-
abstract
def
slice(from: Int, end: Int): MatriQ
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)
-
abstract
def
sliceCol(from: Int, end: Int): MatriQ
Slice 'this' matrix column-wise 'from' to 'end'.
Slice 'this' matrix column-wise 'from' to 'end'.
- from
the start column of the slice (inclusive)
- end
the end column of the slice (exclusive)
-
abstract
def
sliceExclude(row: Int, col: Int): MatriQ
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
-
abstract
def
solve(b: VectorQ): VectorQ
Solve for 'x' in the equation 'a*x = b' where 'a' is 'this' matrix.
Solve for 'x' in the equation 'a*x = b' where 'a' is 'this' matrix.
- b
the constant vector.
-
abstract
def
solve(l: MatriQ, u: MatriQ, b: VectorQ): VectorQ
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
-
abstract
def
sum: Rational
Compute the sum of 'this' matrix, i.e., the sum of its elements.
-
abstract
def
sumAbs: Rational
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
-
abstract
def
sumLower: Rational
Compute the sum of the lower triangular region of 'this' matrix.
-
abstract
def
t: MatriQ
Transpose 'this' matrix (rows => columns).
-
abstract
def
trace: Rational
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.
- See also
Eigen.scala
-
abstract
def
update(ir: Range, jr: Range, b: MatriQ): Unit
Set a slice of 'this' matrix row-wise on range 'ir' and column-wise on range 'jr' to matrix 'b'.
Set a slice of 'this' matrix row-wise on range 'ir' and column-wise on range 'jr' to matrix 'b'. Ex: a(2..4, 3..5) = b
- ir
the row range
- jr
the column range
- b
the matrix to assign
-
abstract
def
update(i: Int, u: VectorQ): 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
-
abstract
def
update(i: Int, j: Int, x: Rational): 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
-
abstract
def
write(fileName: String): Unit
Write 'this' matrix to a CSV-formatted text file with name 'fileName'.
Write 'this' matrix to a CSV-formatted text file with name 'fileName'.
- fileName
the name of file to hold the data
-
abstract
def
~^(p: Int): MatriQ
Raise 'this' matrix to the 'p'th power (for some integer p >= 2).
Raise 'this' matrix to the 'p'th power (for some integer p >= 2).
- p
the power to raise 'this' matrix to
Concrete Value Members
-
final
def
!=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
##(): Int
- Definition Classes
- AnyRef → Any
-
final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
apply(i: Int, jr: Range): VectorQ
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
-
def
apply(ir: Range, j: Int): VectorQ
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
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
-
def
clone(): AnyRef
- Attributes
- protected[java.lang]
- Definition Classes
- AnyRef
- Annotations
- @native() @throws( ... )
-
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)
Format string used for printing vector values (change using setFormat)
- Attributes
- protected
-
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.
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: (MM_ArrayQ) ⇒ U): Unit
Iterate over 'this' matrix row by row applying method 'f'.
Iterate over 'this' matrix row by row applying method 'f'.
- f
the function to apply
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
def
hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
def
isBidiagonal: Boolean
Check whether 'this' matrix is bidiagonal (has non-zreo elements only in main diagonal and superdiagonal).
Check whether 'this' matrix is bidiagonal (has non-zreo elements only in main diagonal and superdiagonal). The method may be overriding for efficiency.
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
def
isNonnegative: Boolean
Check whether 'this' matrix is nonnegative (has no negative elements).
-
def
isSquare: Boolean
Check whether 'this' matrix is square (same row and column dimensions).
-
def
isSymmetric: Boolean
Check whether 'this' matrix is symmetric.
-
def
isTridiagonal: Boolean
Check whether 'this' matrix is bidiagonal (has non-zreo elements only in main diagonal and superdiagonal).
Check whether 'this' matrix is bidiagonal (has non-zreo elements only in main diagonal and superdiagonal). The method may be overriding for efficiency.
-
def
leDimensions(b: MatriQ): Boolean
Check whether 'this' matrix dimensions are less than or equal to (le) those of the other matrix 'b'.
Check whether 'this' matrix dimensions are less than or equal to (le) those of the other matrix 'b'.
- b
the other matrix
-
def
mag: Rational
Find the magnitude of 'this' matrix, the element value farthest from zero.
-
def
mean: VectorQ
Compute the column means of this matrix.
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
def
norm1: Rational
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'.
-
final
def
notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
val
range1: Range
Range for the storage array on dimension 1 (rows)
Range for the storage array on dimension 1 (rows)
- Attributes
- protected
-
val
range2: Range
Range for the storage array on dimension 2 (columns)
Range for the storage array on dimension 2 (columns)
- Attributes
- protected
-
def
rank: Int
Determine the rank of 'this' m-by-n matrix by taking the upper triangular matrix 'u' 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 'u' from the LU Decomposition and counting the number of non-zero diagonal elements. Implementing classes may override this method with a better one (e.g., SVD or Rank Revealing QR).
- See also
http://en.wikipedia.org/wiki/Rank_%28linear_algebra%29
-
def
sameCrossDimensions(b: MatriQ): Boolean
Check whether 'this' matrix and the other matrix 'b' have the same cross dimensions.
Check whether 'this' matrix and the other matrix 'b' have the same cross dimensions.
- b
the other matrix
-
def
sameDimensions(b: MatriQ): Boolean
Check whether 'this' matrix and the other matrix 'b' have the same dimensions.
Check whether 'this' matrix and the other matrix 'b' have the same dimensions.
- b
the other matrix
-
def
setFormat(newFormat: String): Unit
Set the format to the 'newFormat'.
Set the format to the 'newFormat'.
- newFormat
the new format string
-
def
solve(lu: (MatriQ, MatriQ), b: VectorQ): VectorQ
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
-
def
swap(i: Int, k: Int, col: Int = 0): Unit
Swap the elements in rows 'i' and 'k' starting from column 'col'.
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)
-
def
swapCol(j: Int, l: Int, row: Int = 0): Unit
Swap the elements in columns 'j' and 'l' starting from row 'row'.
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)
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final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
def
toString(): String
- Definition Classes
- AnyRef → Any
-
def
update(i: Int, jr: Range, u: VectorQ): 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
-
def
update(ir: Range, j: Int, u: VectorQ): 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
-
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
- @native() @throws( ... )