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template<typename FunctorType, typename Scalar>
DenseIndex ei_fdjac1(
const FunctorType &Functor,
Matrix< Scalar, Dynamic, 1 > &x,
Matrix< Scalar, Dynamic, 1 > &fvec,
Matrix< Scalar, Dynamic, Dynamic > &fjac,
DenseIndex ml, DenseIndex mu,
Scalar epsfcn)
{
typedef DenseIndex Index;
/* Local variables */
Scalar h;
Index j, k;
Scalar eps, temp;
Index msum;
int iflag;
Index start, length;
/* Function Body */
const Scalar epsmch = NumTraits<Scalar>::epsilon();
const Index n = x.size();
assert(fvec.size()==n);
Matrix< Scalar, Dynamic, 1 > wa1(n);
Matrix< Scalar, Dynamic, 1 > wa2(n);
eps = ei_sqrt(std::max(epsfcn,epsmch));
msum = ml + mu + 1;
if (msum >= n) {
/* computation of dense approximate jacobian. */
for (j = 0; j < n; ++j) {
temp = x[j];
h = eps * ei_abs(temp);
if (h == 0.)
h = eps;
x[j] = temp + h;
iflag = Functor(x, wa1);
if (iflag < 0)
return iflag;
x[j] = temp;
fjac.col(j) = (wa1-fvec)/h;
}
}else {
/* computation of banded approximate jacobian. */
for (k = 0; k < msum; ++k) {
for (j = k; (msum<0) ? (j>n): (j<n); j += msum) {
wa2[j] = x[j];
h = eps * ei_abs(wa2[j]);
if (h == 0.) h = eps;
x[j] = wa2[j] + h;
}
iflag = Functor(x, wa1);
if (iflag < 0)
return iflag;
for (j = k; (msum<0) ? (j>n): (j<n); j += msum) {
x[j] = wa2[j];
h = eps * ei_abs(wa2[j]);
if (h == 0.) h = eps;
fjac.col(j).setZero();
start = std::max<Index>(0,j-mu);
length = std::min(n-1, j+ml) - start + 1;
fjac.col(j).segment(start, length) = ( wa1.segment(start, length)-fvec.segment(start, length))/h;
}
}
}
return 0;
}
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