\(\newcommand{\W}[1]{ \; #1 \; }\) \(\newcommand{\R}[1]{ {\rm #1} }\) \(\newcommand{\B}[1]{ {\bf #1} }\) \(\newcommand{\D}[2]{ \frac{\partial #1}{\partial #2} }\) \(\newcommand{\DD}[3]{ \frac{\partial^2 #1}{\partial #2 \partial #3} }\) \(\newcommand{\Dpow}[2]{ \frac{\partial^{#1}}{\partial {#2}^{#1}} }\) \(\newcommand{\dpow}[2]{ \frac{ {\rm d}^{#1}}{{\rm d}\, {#2}^{#1}} }\)
sparsity_sub.cpp¶
View page sourceSparsity Patterns For a Subset of Variables: Example and Test¶
See Also¶
ForSparseJac¶
The routine ForSparseJac is used to compute the sparsity for both the full Jacobian (see s ) and a subset of the Jacobian (see s2 ).
RevSparseHes¶
The routine RevSparseHes is used to compute both sparsity for both the full Hessian (see h ) and a subset of the Hessian (see h2 ).
# include <cppad/cppad.hpp>
bool sparsity_sub(void)
{ // C++ source code
bool ok = true;
//
using std::cout;
using CppAD::vector;
using CppAD::AD;
using CppAD::vectorBool;
size_t n = 4;
size_t m = n-1;
vector< AD<double> > ax(n), ay(m);
for(size_t j = 0; j < n; j++)
ax[j] = double(j+1);
CppAD::Independent(ax);
for(size_t i = 0; i < m; i++)
ay[i] = (ax[i+1] - ax[i]) * (ax[i+1] - ax[i]);
CppAD::ADFun<double> f(ax, ay);
// Evaluate the full Jacobian sparsity pattern for f
vectorBool r(n * n), s(m * n);
for(size_t j = 0 ; j < n; j++)
{ for(size_t i = 0; i < n; i++)
r[i * n + j] = (i == j);
}
s = f.ForSparseJac(n, r);
// evaluate the sparsity for the Hessian of f_0 + ... + f_{m-1}
vectorBool t(m), h(n * n);
for(size_t i = 0; i < m; i++)
t[i] = true;
h = f.RevSparseHes(n, t);
// evaluate the Jacobian sparsity pattern for first n/2 components of x
size_t n2 = n / 2;
vectorBool r2(n * n2), s2(m * n2);
for(size_t j = 0 ; j < n2; j++)
{ for(size_t i = 0; i < n; i++)
r2[i * n2 + j] = (i == j);
}
s2 = f.ForSparseJac(n2, r2);
// evaluate the sparsity for the subset of Hessian of
// f_0 + ... + f_{m-1} where first partial has only first n/2 components
vectorBool h2(n2 * n);
h2 = f.RevSparseHes(n2, t);
// check sparsity pattern for Jacobian
for(size_t i = 0; i < m; i++)
{ for(size_t j = 0; j < n2; j++)
ok &= s2[i * n2 + j] == s[i * n + j];
}
// check sparsity pattern for Hessian
for(size_t i = 0; i < n2; i++)
{ for(size_t j = 0; j < n; j++)
ok &= h2[i * n + j] == h[i * n + j];
}
return ok;
}