本文整理汇总了C++中cppad::ADFun::Jacobian方法的典型用法代码示例。如果您正苦于以下问题：C++ ADFun::Jacobian方法的具体用法？C++ ADFun::Jacobian怎么用？C++ ADFun::Jacobian使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类cppad::ADFun的用法示例。
在下文中一共展示了ADFun::Jacobian方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: link_ode
bool link_ode(
size_t size ,
size_t repeat ,
CppAD::vector<double> &x ,
CppAD::vector<double> &jacobian
)
{
// speed test global option values
if( global_option["atomic"] )
return false;
// optimization options: no conditional skips or compare operators
std::string options="no_compare_op";
// --------------------------------------------------------------------
// setup
assert( x.size() == size );
assert( jacobian.size() == size * size );
typedef CppAD::AD<double> ADScalar;
typedef CppAD::vector<ADScalar> ADVector;
size_t j;
size_t p = 0; // use ode to calculate function values
size_t n = size; // number of independent variables
size_t m = n; // number of dependent variables
ADVector X(n), Y(m); // independent and dependent variables
CppAD::ADFun<double> f; // AD function
// -------------------------------------------------------------
if( ! global_option["onetape"] ) while(repeat--)
{ // choose next x value
uniform_01(n, x);
for(j = 0; j < n; j++)
X[j] = x[j];
// declare the independent variable vector
Independent(X);
// evaluate function
CppAD::ode_evaluate(X, p, Y);
// create function object f : X -> Y
f.Dependent(X, Y);
if( global_option["optimize"] )
f.optimize(options);
// skip comparison operators
f.compare_change_count(0);
jacobian = f.Jacobian(x);
}
else
{ // an x value
uniform_01(n, x);
for(j = 0; j < n; j++)
X[j] = x[j];
// declare the independent variable vector
Independent(X);
// evaluate function
CppAD::ode_evaluate(X, p, Y);
// create function object f : X -> Y
f.Dependent(X, Y);
if( global_option["optimize"] )
f.optimize(options);
// skip comparison operators
f.compare_change_count(0);
while(repeat--)
{ // get next argument value
uniform_01(n, x);
// evaluate jacobian
jacobian = f.Jacobian(x);
}
}
return true;
}示例2: mexFunction
//.........这里部分代码省略.........
}
else if(!strcmp(mode,"hstr")) {
imode = 6;
//Can't allocate here until we know sparsity pattern
}
else
mexErrMsgTxt("Unknown mode - options are 'obj', 'grad', 'con', 'jac', 'jacstr', 'hess' or 'hstr'");
mxFree(mode);
//Ensure we did have x for normal callbacks
if(imode != 4 && imode != 6 && nrhs < 2)
mexErrMsgTxt("You must supply the callback mode and input vector.");
//Call Req Callback
switch(imode)
{
case 0: //objective
*v = objective(xvec);
break;
case 1: //gradient
//Check if we have recorded the objective yet
if(obj.Memory()==0) { //new, tape operations
vector< CppAD::AD<double> > X(getNoVar());
memcpy(&X[0],x,getNoVar()*sizeof(double));
CppAD::Independent(X);
vector< CppAD::AD<double> > Y(1);
Y[0] = objective(X);
obj = CppAD::ADFun<double>(X, Y);
//obj.optimize();
mexAtExit(mexExit); //also register memory clear function
//mexPrintf("Evaluated Tape for Gradient\n");
}
//Evaluate "Jacobian" for gradient
memcpy(v,&(obj.Jacobian(xvec)[0]),getNoVar()*sizeof(double));
break;
case 2: //constraints
//Check if we have constraint memory yet
if(cvec.empty())
cvec.resize(getNoCon()); //allocate it
//Evaluate Constraints
constraints(xvec,cvec);
//Copy Out
memcpy(v,&cvec[0],getNoCon()*sizeof(double));
break;
case 3: //jacobian
case 4: //jacobian structure
//Check if we have recorded the constraints yet
if(con.Memory()==0){ //new, tape operations
vector< CppAD::AD<double> > X(getNoVar());
memcpy(&X[0],x,getNoVar()*sizeof(double));
CppAD::Independent(X);
vector< CppAD::AD<double> > Y(getNoCon());
constraints(X,Y);
con = CppAD::ADFun<double>(X, Y);
//con.optimize();
mexAtExit(mexExit); //also register memory clear function
//mexPrintf("Evaluated Tape for Jacobian\n");
}
//Check if we have the sparsity pattern yet
if(jstr.empty()) {
vector<set<size_t>> r(getNoVar());
for(size_t i = 0; i < getNoVar(); i++)
r[i].insert(i); //identity matrix
jstr.resize(getNoCon());
jstr = con.ForSparseJac(getNoVar(),r,true); //note transpose
//Determine nnzs