Uses of Class
Jama.Matrix

Packages that use Matrix
Jama   
net.talvi.puffinplot.data   
 

Uses of Matrix in Jama
 

Methods in Jama that return Matrix
 Matrix Matrix.arrayLeftDivide(Matrix B)
          Element-by-element left division, C = A.\B
 Matrix Matrix.arrayLeftDivideEquals(Matrix B)
          Element-by-element left division in place, A = A.\B
 Matrix Matrix.arrayRightDivide(Matrix B)
          Element-by-element right division, C = A./B
 Matrix Matrix.arrayRightDivideEquals(Matrix B)
          Element-by-element right division in place, A = A./B
 Matrix Matrix.arrayTimes(Matrix B)
          Element-by-element multiplication, C = A.*B
 Matrix Matrix.arrayTimesEquals(Matrix B)
          Element-by-element multiplication in place, A = A.*B
static Matrix Matrix.constructWithCopy(double[][] A)
          Construct a matrix from a copy of a 2-D array.
 Matrix Matrix.copy()
          Make a deep copy of a matrix
 Matrix EigenvalueDecomposition.getD()
          Return the block diagonal eigenvalue matrix
 Matrix QRDecomposition.getH()
          Return the Householder vectors
 Matrix CholeskyDecomposition.getL()
          Return triangular factor.
 Matrix LUDecomposition.getL()
          Return lower triangular factor
 Matrix Matrix.getMatrix(int[] r, int[] c)
          Get a submatrix.
 Matrix Matrix.getMatrix(int[] r, int j0, int j1)
          Get a submatrix.
 Matrix Matrix.getMatrix(int i0, int i1, int[] c)
          Get a submatrix.
 Matrix Matrix.getMatrix(int i0, int i1, int j0, int j1)
          Get a submatrix.
 Matrix QRDecomposition.getQ()
          Generate and return the (economy-sized) orthogonal factor
 Matrix QRDecomposition.getR()
          Return the upper triangular factor
 Matrix SingularValueDecomposition.getS()
          Return the diagonal matrix of singular values
 Matrix LUDecomposition.getU()
          Return upper triangular factor
 Matrix SingularValueDecomposition.getU()
          Return the left singular vectors
 Matrix EigenvalueDecomposition.getV()
          Return the eigenvector matrix
 Matrix SingularValueDecomposition.getV()
          Return the right singular vectors
static Matrix Matrix.identity(int m, int n)
          Generate identity matrix
 Matrix Matrix.inverse()
          Matrix inverse or pseudoinverse
 Matrix Matrix.minus(Matrix B)
          C = A - B
 Matrix Matrix.minusEquals(Matrix B)
          A = A - B
 Matrix Matrix.plus(Matrix B)
          C = A + B
 Matrix Matrix.plusEquals(Matrix B)
          A = A + B
static Matrix Matrix.random(int m, int n)
          Generate matrix with random elements
static Matrix Matrix.read(java.io.BufferedReader input)
          Read a matrix from a stream.
 Matrix CholeskyDecomposition.solve(Matrix B)
          Solve A*X = B
 Matrix LUDecomposition.solve(Matrix B)
          Solve A*X = B
 Matrix Matrix.solve(Matrix B)
          Solve A*X = B
 Matrix QRDecomposition.solve(Matrix B)
          Least squares solution of A*X = B
 Matrix Matrix.solveTranspose(Matrix B)
          Solve X*A = B, which is also A'*X' = B'
 Matrix Matrix.times(double s)
          Multiply a matrix by a scalar, C = s*A
 Matrix Matrix.times(Matrix B)
          Linear algebraic matrix multiplication, A * B
 Matrix Matrix.timesEquals(double s)
          Multiply a matrix by a scalar in place, A = s*A
 Matrix Matrix.transpose()
          Matrix transpose.
 Matrix Matrix.uminus()
          Unary minus
 

Methods in Jama with parameters of type Matrix
 Matrix Matrix.arrayLeftDivide(Matrix B)
          Element-by-element left division, C = A.\B
 Matrix Matrix.arrayLeftDivideEquals(Matrix B)
          Element-by-element left division in place, A = A.\B
 Matrix Matrix.arrayRightDivide(Matrix B)
          Element-by-element right division, C = A./B
 Matrix Matrix.arrayRightDivideEquals(Matrix B)
          Element-by-element right division in place, A = A./B
 Matrix Matrix.arrayTimes(Matrix B)
          Element-by-element multiplication, C = A.*B
 Matrix Matrix.arrayTimesEquals(Matrix B)
          Element-by-element multiplication in place, A = A.*B
 Matrix Matrix.minus(Matrix B)
          C = A - B
 Matrix Matrix.minusEquals(Matrix B)
          A = A - B
 Matrix Matrix.plus(Matrix B)
          C = A + B
 Matrix Matrix.plusEquals(Matrix B)
          A = A + B
 void Matrix.setMatrix(int[] r, int[] c, Matrix X)
          Set a submatrix.
 void Matrix.setMatrix(int[] r, int j0, int j1, Matrix X)
          Set a submatrix.
 void Matrix.setMatrix(int i0, int i1, int[] c, Matrix X)
          Set a submatrix.
 void Matrix.setMatrix(int i0, int i1, int j0, int j1, Matrix X)
          Set a submatrix.
 Matrix CholeskyDecomposition.solve(Matrix B)
          Solve A*X = B
 Matrix LUDecomposition.solve(Matrix B)
          Solve A*X = B
 Matrix Matrix.solve(Matrix B)
          Solve A*X = B
 Matrix QRDecomposition.solve(Matrix B)
          Least squares solution of A*X = B
 Matrix Matrix.solveTranspose(Matrix B)
          Solve X*A = B, which is also A'*X' = B'
 Matrix Matrix.times(Matrix B)
          Linear algebraic matrix multiplication, A * B
 

Constructors in Jama with parameters of type Matrix
CholeskyDecomposition(Matrix Arg)
          Cholesky algorithm for symmetric and positive definite matrix.
EigenvalueDecomposition(Matrix Arg)
          Check for symmetry, then construct the eigenvalue decomposition
LUDecomposition(Matrix A)
          LU Decomposition
QRDecomposition(Matrix A)
          QR Decomposition, computed by Householder reflections.
SingularValueDecomposition(Matrix Arg)
          Construct the singular value decomposition
 

Uses of Matrix in net.talvi.puffinplot.data
 

Methods in net.talvi.puffinplot.data that return Matrix
 Matrix Vec3.oTensor()
          Returns the orientation tensor of this vector.
 Matrix Eigens.toMatrix()
          Returns a matrix of the eigenvectors.
 

Constructors in net.talvi.puffinplot.data with parameters of type Matrix
Eigens(Matrix matrix)
          Create an object holding the eigenvectors and eigenvalues of the supplied matrix.
Tensor(double k11, double k22, double k33, double k12, double k23, double k13, Matrix correct1, Matrix correct2)
          Creates a tensor with the specified components and transformed using the specified matrices.