/**
* 17.
* @brief Multiply one scalar with matrix.
* @param[in] A The matrix.
* @param[in] a The scalar.
* @param[out] B B is overwritten with (A*B).
*/
static void multiply(const matrix_type& A,
const value_type& a,
matrix_type& B) {
/** Result matrices should always be of the right size */
B.Resize(A.Height(), A.Width());
/** Get the matrix dimensions. */
const int m = A.Height();
const int n = A.Width();
/** Simple scalar-matrix product. */
for (int i=0; i<m; ++i)
for (int j=0; j<n; ++j)
B.Set(i, j, (a*A.Get(i, j)));
}
/**
* 16.
* @brief Compute the element-wise product of two matrices.
* @param[in] A the first matrix.
* @param[in] B the second matrix.
* @param[out] C the result, which contains A.*B.
*/
static void elementwiseProduct(const matrix_type& A,
const matrix_type& B,
matrix_type& C) {
/** Result matrices should always be of the right size */
C.Resize (A.Height(), A.Width());
/* Get the matrix dimensions */
const int m = A.Height();
const int n = A.Width();
/* Simple element-wise product */
for (int i=0; i<m; ++i)
for (int j=0; j<n; ++j)
C.Set(i, j, (A.Get(i,j)*B.Get(i,j)));
}
/**
* 13.
* @brief Copy the contents of a matrix.
* @param[out] A A is overwritten with B.
* @param[in] B The matrix to be copied.
*/
static void copy (matrix_type &A, const matrix_type &B) {
/** Result matrices should always be of the right size */
A.Resize (B.Height(), B.Width());
/** This one is pretty simple, but the order is different */
elem::Copy (B, A);
}
/**
* 6.
* @brief Compute the matrix transpose.
* @param[in] A The matrix to be transposed.
* @param[out] B B is overwritten with A^{T}
*/
static void transpose (const matrix_type& A,
matrix_type& B) {
/** Result matrices should always have sufficient space */
B.Resize(A.Width(), A.Height());
/** Compute transpose */
elem::Transpose (A, B);
}
/**
* 5.
* @brief Multiply one matrix with another.
* @param[in] A The first matrix
* @param[in] B The second matrix
* @param[out] C C is overwritten with (A*B)
*/
static void multiply (const matrix_type& A,
const matrix_type& B,
matrix_type& C) {
/** Result matrices should always have sufficient space */
C.Resize(A.Height(), B.Width());
/** We have to do a Gemm */
elem::Gemm (elem::NORMAL, elem::NORMAL, 1.0, A, B, 0.0, C);
}
/**
* 8.
* @brief Compute the inverse of a matrix.
* @param[in] A The (non-singular and square) matrix to be inverted.
* @param[out] B B is overwritten with A's inverse.
*/
static void inv(const matrix_type& A,
matrix_type& B) {
/** Assume that the matrix has an inverse */
const int n = A.Height();
/** First, copy over an identity as the right hand side */
B = eye(n);
/** Solve the linear system using LU */
elem::lu::SolveAfter(elem::NORMAL, A, B);
}
/**
* 7.
* @brief Compute element-wise negation of a matrix.
* @param[in] A The matrix to be negated.
* @param[out] B B is overwritten with -1.0*A
*/
static void negation (const matrix_type& A,
matrix_type& B) {
/** Result matrices should always have sufficient space */
B.Resize(A.Height(), A.Width());
/** Copy over the matrix */
elem::Copy (A, B);
/** Multiply by -1.0 */
elem::Scal(-1.0, B);
}
/**
* 4.
* @brief Subtract one matrix from another.
* @param[in] A The first matrix
* @param[in] B The second matrix
* @param[out] C C is overwritten with (A-B)
*/
static void minus (const matrix_type& A,
const matrix_type& B,
matrix_type& C) {
/** Result matrices should always have sufficient space */
C.Resize(A.Height(), A.Width());
/** first copy the matrix over */
elem::Copy (A, C);
/** now, subtract the other matrix in */
elem::Axpy (-1.0, B, C);
}
/**
* Apply rowwise the sketching transform that is described by the
* the transform with output sketch_of_A.
*/
void apply (const matrix_type& A,
output_matrix_type& sketch_of_A,
rowwise_tag dimension) const {
const value_type *a = A.LockedBuffer();
El::Int lda = A.LDim();
value_type *sa = sketch_of_A.Buffer();
El::Int ldsa = sketch_of_A.LDim();
for (El::Int j = 0; j < data_type::_S; j++)
for (El::Int i = 0; i < A.Height(); i++)
sa[j * ldsa + i] = a[data_type::_samples[j] * lda + i];
}
void apply_impl_vdist(const matrix_type& A,
output_matrix_type& sketch_of_A,
skylark::sketch::rowwise_tag tag) const {
matrix_type sketch_of_A_STAR_RD(A.Height(),
data_type::_S);
dense_transform_t<matrix_type, matrix_type, ValuesAccessor>
transform(*this);
transform.apply(A, sketch_of_A_STAR_RD, tag);
sketch_of_A = sketch_of_A_STAR_RD;
}
/**
* 1.
* @brief A function to return the number of rows in a matrix
* @param[in] A The matrix for which we need the number of rows.
* @return number of rows in A
*/
static int getNumRows (const matrix_type& A) { return A.Height(); }
/**
* 9.
* @brief Compute the trace of a matrix.
* @param[in] A The (square) matrix whose trace is to be computed.
* @return Trace of A
*/
static value_type trace(const matrix_type& A) {
value_type traceVal = 0.0;
for (int i=0; i<A.Height(); ++i) traceVal += A.Get(i,i);
return traceVal;
}