|
|
Prev | Next |
int f2cad::daxpy_(integer *n, doublereal *da, doublereal *dx, integer *incx, doublereal *dy, integer *incy);
daxpy.f
to compute
\[
\left( \begin{array}{c}
f_0 \\
f_1
\end{array} \right)
=
5
\left( \begin{array}{c}
x_0 \\
x_1
\end{array} \right)
+
\left( \begin{array}{c}
3 \\
4
\end{array} \right)
\]
Using the f2cad_link
routines
f2cad::Independent and f2cad::Dependent,
this defines the function
\[
f(x) =
\left( \begin{array}{c}
5 x_0 + 3 \\
5 x_1 + 4
\end{array} \right)
\]
We check that the derivative of this function,
calculated using the f2cad::Partial routine, satisfies
\[
f^{(1)} (x)
=
\left( \begin{array}{cc}
5 & 0 \\
0 & 5
\end{array} \right)
\]
# include <f2cad/daxpy.hpp>
test_result daxpy(void)
{ bool ok = true;
// Input values for daxpy
doublereal a = 5.;
integer n = 2;
doublereal x[2];
x[0] = 1.;
x[1] = 2.;
integer incx = 1;
integer m = 2;
doublereal f[2];
f[0] = 3.;
f[1] = 4.;
integer incf = 1;
// declare independent variables
f2cad::Independent(n, x);
// set f = a * x + f
f2cad::daxpy_(&n, &a, x, &incx, f, &incf);
// declare dependent variables
f2cad::Dependent(m, f);
double p;
p = f2cad::Partial<doublereal>(0, 0);
ok &= f2cad::near_equal(p, 5., 1e-10, 1e-10);
p = f2cad::Partial<doublereal>(1, 0);
ok &= f2cad::near_equal(p, 0., 1e-10, 1e-10);
p = f2cad::Partial<doublereal>(0, 1);
ok &= f2cad::near_equal(p, 0., 1e-10, 1e-10);
p = f2cad::Partial<doublereal>(1, 1);
ok &= f2cad::near_equal(p, 5., 1e-10, 1e-10);
if( ok )
return test_pass;
return test_fail;
}