CRSSparsity reshape(const CRSSparsity& a, int n, int m){
casadi_assert_message(a.numel() == n*m,
"reshape: number of elements must remain the same." << endl <<
"Input argument has shape " << a.size1() << " x " << a.size2() << " = " << a.numel() << ", while you request a reshape to " <<
n << " x " << m << " = " << n*m
);
// our strategy is: (col,rowind) -> (col,row) -> modulus calculus -> (col_new, row_new) -> sp_NZ
std::vector<int> row = a.getRow();
const std::vector<int> &col = a.col();
std::vector<int> row_new(a.size());
std::vector<int> col_new(a.size());
// int i=0;int j=0; int z =0;
for(int k=0; k<a.size(); ++k){
int i = row[k];
int j = col[k];
int z = j+i*a.size2();
row_new[k] = z/m;
col_new[k] = z%m;
}
return sp_triplet(n,m,row_new,col_new);
}
std::vector<int> getNZDense(const CRSSparsity &sp) {
std::vector<int> ret(sp.size());
std::vector<int> row = sp.getRow();
const std::vector<int> &col = sp.col();
int s2 = sp.size2();
for(int k=0;k<sp.size();k++) {
ret[k] = col[k]+row[k]*s2;
}
return ret;
}
bool dependsOn(const SXMatrix& ex, const SXMatrix &arg){
if(ex.size()==0) return false;
SXFunction temp(arg,ex);
temp.init();
CRSSparsity Jsp = temp.jacSparsity();
return Jsp.size()!=0;
}
Reshape::Reshape(const MX& x, CRSSparsity sp){
casadi_assert(x.size()==sp.size());
setDependencies(x);
setSparsity(sp);
}
