SparseStorage<DataType>::SparseStorage(const Sparsity& sparsity, const std::vector<DataType>& d)
: sparsity_(sparsity), data_(d) {
casadi_assert_message(sparsity.size()==d.size(),
"Size mismatch." << std::endl << "You supplied a sparsity of "
<< sparsity_.dimString()
<< ", but the supplied vector is of length " << d.size());
}
/// Convert scalar to matrix
inline static MX toMatrix(const MX& x, const Sparsity& sp) {
if (x.size()==sp.size()) {
return x;
} else {
return MX(sp, x);
}
}
MX GenericCall::projectArg(const MX& x, const Sparsity& sp, int i) {
if (x.size()==sp.size()) {
// Insert sparsity projection nodes if needed
return project(x, sp);
} else {
// Different dimensions
if (x.is_empty() || sp.is_empty()) { // NOTE: To permissive?
// Replace nulls with zeros of the right dimension
return MX::zeros(sp);
} else if (x.is_scalar()) {
// Scalar argument means set all
return MX(sp, x);
} else if (x.size1()==sp.size2() && x.size2()==sp.size1() && sp.is_vector()) {
// Transposed vector
return projectArg(x.T(), sp, i);
} else {
// Mismatching dimensions
casadi_error("Cannot create function call node: Dimension mismatch for argument "
<< i << ". Argument has shape " << x.size()
<< " but function input has shape " << sp.size());
}
}
}
Reshape::Reshape(const MX& x, Sparsity sp) {
casadi_assert(x.size()==sp.size());
setDependencies(x);
setSparsity(sp);
}
SparseStorage<DataType>::SparseStorage(const Sparsity& sparsity, const DataType& val) :
sparsity_(sparsity), data_(sparsity.size(), val) {}
