C++ Epetra_SerialDenseMatrix::N方法代码示例

//=========================================================================
// checks the signatures of two matrices
bool identicalSignatures(Epetra_SerialDenseMatrix& a, Epetra_SerialDenseMatrix& b, bool testLDA) {

	if((a.M()  != b.M()  )|| // check properties first
		 (a.N()  != b.N()  )||
		 (a.CV() != b.CV() ))
		return(false);

	if(testLDA == true)      // if we are coming from op= c->c #2 (have enough space)
		if(a.LDA() != b.LDA()) // then we don't check LDA (but we do check it in the test function)
			return(false);

	if(a.CV() == View) { // if we're still here, we need to check the data
		if(a.A() != b.A()) // for a view, this just means checking the pointers
			return(false);   // for a copy, this means checking each element
	}
	else { // CV == Copy
		const int m = a.M();
		const int n = a.N();
		for(int i = 0; i < m; i++)
			for(int j = 0; j < n; j++) {
				if(a(i,j) != b(i,j))
					return(false);
			}
	}

	return(true); // if we're still here, signatures are identical
}

//=============================================================================
int Epetra_SerialDenseSVD::SetVectors(Epetra_SerialDenseMatrix & X_in, Epetra_SerialDenseMatrix & B_in)
{
  if (B_in.M()!=X_in.M() || B_in.N() != X_in.N()) EPETRA_CHK_ERR(-1);
  if (B_in.A()==0) EPETRA_CHK_ERR(-2);
  if (B_in.LDA()<1) EPETRA_CHK_ERR(-3);
  if (X_in.A()==0) EPETRA_CHK_ERR(-4);
  if (X_in.LDA()<1) EPETRA_CHK_ERR(-5);

  ResetVectors();
  LHS_ = &X_in;
  RHS_ = &B_in;
  NRHS_ = B_in.N();

  B_ = B_in.A();
  LDB_ = B_in.LDA();
  X_ = X_in.A();
  LDX_ = X_in.LDA();
  return(0);
}

int Epetra_FECrsMatrix::ReplaceGlobalValues(const Epetra_LongLongSerialDenseVector& indices,
              const Epetra_SerialDenseMatrix& values,
              int format)
{
  if (indices.Length() != values.M() || indices.Length() != values.N()) {
    return(-1);
  }

  return( ReplaceGlobalValues(indices.Length(), indices.Values(),
            values.A(), format) );
}

//=========================================================================
// checks if two matrices are independent or not
bool seperateData(Epetra_SerialDenseMatrix& a, Epetra_SerialDenseMatrix& b) {
	bool seperate;

	int r = EPETRA_MIN(a.M(),b.M()) / 2; // ensures (r,c) is valid
	int c = EPETRA_MIN(a.N(),b.N()) / 2; // in both matrices

	double orig_a = a(r,c);
	double new_value = a(r,c) + 1;
	if(b(r,c) == new_value) // there's a chance b could be independent, but
		new_value++;          // already have new_value in (r,c).
	
	a(r,c) = new_value;
	if(b(r,c) == new_value)
		seperate = false;
	else
		seperate = true;

	a(r,c) = orig_a; // undo change we made to a

	return(seperate);
}

//=============================================================================
int Epetra_SerialDenseSVD::SetMatrix(Epetra_SerialDenseMatrix & A_in) {
  ResetMatrix();
  Matrix_ = &A_in;
//  Factor_ = &A_in;
  M_ = A_in.M();
  N_ = A_in.N();
  Min_MN_ = EPETRA_MIN(M_,N_);
  LDA_ = A_in.LDA();
//  LDAF_ = LDA_;
  A_ = A_in.A();
//  AF_ = A_in.A();
  return(0);
}