Vector.cpp
0977af1299aaefficient_neuronet

Vector.cpp
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			#include "DenseVector.h"
			///////////////////////////////////////////////////////////////////////////////
			//* performs a matrix-vector multiply with optional transposes BLAS version
			void MultMv(const Matrix<double> &A, const Vector<double> &v, DenseVector<double> &c,
			const bool At, double a, double b)
			{
			static char t[2] = {'N','T'};
			char *ta=t+At;
			int sA[2] = {A.nRows(), A.nCols()}; // sizes of A
			int sV[2] = {v.size(), 1}; // sizes of v

			GCK(A, v, sA[!At]!=sV[0], "MultAB<double>: matrix-vector multiply");
			if (c.size() != sA[At])
			{
			c.resize(sA[At]); // set size of C to final size
			c.zero();
			}
			// get pointers to the matrix sizes needed by BLAS
			int *M = sA+At; // # of rows in op[A] (op[A] = A' if At='T' else A)
			int *N = sV+1; // # of cols in op[B]
			int *K = sA+!At; // # of cols in op[A] or # of rows in op[B]

			double pa=A.get_ptr(), pv=v.get_ptr(), *pc=c.get_ptr();

			#ifdef COL_STORAGE
			dgemm_(ta, t, M, N, K, &a, pa, sA, pv, sV, &b, pc, M);
			#else
			dgemm_(t, ta, N, M, K, &a, pv, sV+1, pa, sA+1, &b, pc, N);
			#endif
			}