BinaryMX<ScX, ScY>::BinaryMX(Operation op, const MX& x, const MX& y) : op_(op) {
setDependencies(x, y);
if (ScX) {
setSparsity(y.sparsity());
} else {
setSparsity(x.sparsity());
}
}
Multiplication<TrX,TrY>::Multiplication(const MX& z, const MX& x, const MX& y){
casadi_assert_message(TrX || !TrY, "Illegal combination");
casadi_assert_message(TrX, "Not implemented");
casadi_assert_message(!TrY,"Not implemented");
casadi_assert_message(x.size1() == y.size1() && x.size2() == z.size1() && y.size2() == z.size2(),"Multiplication::Multiplication: dimension mismatch. Attempting to multiply trans(" << x.dimString() << ") with " << y.dimString() << " and add the result to " << z.dimString());
setDependencies(z,x,y);
setSparsity(z.sparsity());
}
Assertion::Assertion(const MX& x, const MX& y, const std::string & fail_message)
: fail_message_(fail_message) {
casadi_assert_message(y.is_scalar(),
"Assertion:: assertion expression y must be scalar, but got "
<< y.dim());
setDependencies(x, y);
setSparsity(x.sparsity());
}
UnaryMX::UnaryMX(Operation op, MX x) : op_(op) {
// Put a densifying node in between if necessary
if (!operation_checker<F00Checker>(op_)) {
x.densify();
}
setDependencies(x);
setSparsity(x->sparsity());
}
Multiplication::Multiplication(const MX& x, const MX& y_trans){
casadi_assert_message(x.size2() == y_trans.size2(),"Multiplication::Multiplication: dimension mismatch. Attempting to multiply " << x.dimString() << " with " << y_trans.dimString());
setDependencies(x,y_trans);
// Create the sparsity pattern for the matrix-matrix product
CRSSparsity spres = x->sparsity().patternProduct(y_trans.sparsity());
// Save sparsity
setSparsity(spres);
}
Vertcat::Vertcat(const std::vector<MX>& x) : Concat(x) {
// Construct the sparsity
casadi_assert(!x.empty());
Sparsity sp = x.front().sparsity();
for (vector<MX>::const_iterator i=x.begin()+1; i!=x.end(); ++i) {
sp.append(i->sparsity());
}
setSparsity(sp);
}
Diagcat::Diagcat(const std::vector<MX>& x) : Concat(x) {
// Construct the sparsity
casadi_assert(!x.empty());
std::vector<Sparsity> sp;
for (int i=0;i<x.size(); ++i) {
sp.push_back(x[i].sparsity());
}
setSparsity(blkdiag(sp));
}
HorzRepsum::HorzRepsum(const MX& x, int n) : n_(n) {
casadi_assert(x.size2() % n == 0);
std::vector<Sparsity> sp = horzsplit(x.sparsity(), x.size2()/n);
Sparsity block = sp[0];
for (int i=1;i<sp.size();++i) {
block = block+sp[i];
}
Sparsity goal = repmat(block, 1, n);
setDependencies(project(x, goal));
setSparsity(block);
}
EvaluationMX::EvaluationMX(const FX& fcn, const std::vector<MX> &arg) : fcn_(fcn) {
// Number inputs and outputs
int num_in = fcn.getNumInputs();
// All dependencies of the function
vector<MX> d = arg;
d.resize(num_in);
setDependencies(d);
setSparsity(CRSSparsity(1, 1, true));
}
Call::Call(const Function& fcn, const vector<MX>& arg) : fcn_(fcn) {
// Number inputs and outputs
int num_in = fcn.n_in();
casadi_assert_message(arg.size()==num_in, "Argument list length (" << arg.size()
<< ") does not match number of inputs (" << num_in << ")"
<< " for function " << fcn.name());
// Create arguments of the right dimensions and sparsity
vector<MX> arg1(num_in);
for (int i=0; i<num_in; ++i) {
arg1[i] = projectArg(arg[i], fcn_.sparsity_in(i), i);
}
setDependencies(arg1);
setSparsity(Sparsity::scalar());
}
SymbolicMX::SymbolicMX(const std::string& name, const CRSSparsity & sp) : name_(name) {
setSparsity(sp);
}
HorzRepmat::HorzRepmat(const MX& x, int n) : n_(n) {
setDependencies(x);
setSparsity(repmat(x.sparsity(), 1, n));
}
SymbolicMX::SymbolicMX(const std::string& name, int nrow, int ncol) : name_(name) {
setSparsity(Sparsity::dense(nrow, ncol));
}
SymbolicMX::SymbolicMX(const std::string& name, int n, int m) : name_(name) {
setSparsity(CRSSparsity(n,m,true));
}
Split::Split(const MX& x, const std::vector<int>& offset) : offset_(offset) {
setDependencies(x);
setSparsity(Sparsity::scalar());
}
OutputNode::OutputNode(const MX& parent, int oind) : oind_(oind){
setDependencies(parent);
// Save the sparsity pattern
setSparsity(dep(0)->sparsity(oind));
}
GetNonzeros::GetNonzeros(const Sparsity& sp, const MX& y) {
setSparsity(sp);
setDependencies(y);
}
Transpose::Transpose(const MX& x) {
setDependencies(x);
setSparsity(x.sparsity().T());
}
InnerProd::InnerProd(const MX& x, const MX& y) {
casadi_assert(x.sparsity()==y.sparsity());
setDependencies(x, y);
setSparsity(Sparsity::scalar());
}
Densification::Densification(const MX& x){
setDependencies(x);
setSparsity(CRSSparsity(x.size1(),x.size2(),true));
}
Project::Project(const MX& x, const Sparsity& sp) {
setDependencies(x);
setSparsity(Sparsity(sp));
}
Reshape::Reshape(const MX& x, Sparsity sp) {
casadi_assert(x.size()==sp.size());
setDependencies(x);
setSparsity(sp);
}
Inverse::Inverse(const MX& x) {
casadi_assert_message(x.size1()==x.size2(),
"Inverse: matrix must be square, but you supllied " << x.dimString());
setDependencies(x);
setSparsity(Sparsity::dense(x.size1(), x.size2()));
}
Determinant::Determinant(const MX& x) {
setDependencies(x);
setSparsity(Sparsity::dense(1, 1));
}
Solve<Tr>::Solve(const MX& r, const MX& A, const LinearSolver& linear_solver) : linear_solver_(linear_solver){
casadi_assert_message(r.size1() == A.size2(),"Solve::Solve: dimension mismatch.");
setDependencies(r,A);
setSparsity(r.sparsity());
}
