/* ************************************************************************* */
Ordering Ordering::ColamdConstrainedFirst(const VariableIndex& variableIndex,
const std::vector<Key>& constrainFirst, bool forceOrder) {
gttic(Ordering_COLAMDConstrainedFirst);
const int none = -1;
size_t n = variableIndex.size();
std::vector<int> cmember(n, none);
// Build a mapping to look up sorted Key indices by Key
FastMap<Key, size_t> keyIndices;
size_t j = 0;
for (auto key_factors: variableIndex)
keyIndices.insert(keyIndices.end(), make_pair(key_factors.first, j++));
// If at least some variables are not constrained to be last, constrain the
// ones that should be constrained.
int group = 0;
for (Key key: constrainFirst) {
cmember[keyIndices.at(key)] = group;
if (forceOrder)
++group;
}
if (!forceOrder && !constrainFirst.empty())
++group;
for(int& c: cmember)
if (c == none)
c = group;
return Ordering::ColamdConstrained(variableIndex, cmember);
}
/* ************************************************************************* */
Ordering Ordering::ColamdConstrainedLast(const VariableIndex& variableIndex,
const std::vector<Key>& constrainLast, bool forceOrder) {
gttic(Ordering_COLAMDConstrainedLast);
size_t n = variableIndex.size();
std::vector<int> cmember(n, 0);
// Build a mapping to look up sorted Key indices by Key
// TODO(frank): think of a way to not build this
FastMap<Key, size_t> keyIndices;
size_t j = 0;
for (auto key_factors: variableIndex)
keyIndices.insert(keyIndices.end(), make_pair(key_factors.first, j++));
// If at least some variables are not constrained to be last, constrain the
// ones that should be constrained.
int group = (constrainLast.size() != n ? 1 : 0);
for (Key key: constrainLast) {
cmember[keyIndices.at(key)] = group;
if (forceOrder)
++group;
}
return Ordering::ColamdConstrained(variableIndex, cmember);
}
/* ************************************************************************* */
Ordering Ordering::ColamdConstrained(const VariableIndex& variableIndex,
const FastMap<Key, int>& groups) {
gttic(Ordering_COLAMDConstrained);
size_t n = variableIndex.size();
std::vector<int> cmember(n, 0);
// Build a mapping to look up sorted Key indices by Key
FastMap<Key, size_t> keyIndices;
size_t j = 0;
for (auto key_factors: variableIndex)
keyIndices.insert(keyIndices.end(), make_pair(key_factors.first, j++));
// Assign groups
typedef FastMap<Key, int>::value_type key_group;
for(const key_group& p: groups) {
// FIXME: check that no groups are skipped
cmember[keyIndices.at(p.first)] = p.second;
}
return Ordering::ColamdConstrained(variableIndex, cmember);
}
/* ************************************************************************* */
Ordering Ordering::ColamdConstrainedLast(const VariableIndex& variableIndex,
const std::vector<Key>& constrainLast, bool forceOrder) {
gttic(Ordering_COLAMDConstrainedLast);
size_t n = variableIndex.size();
std::vector<int> cmember(n, 0);
// Build a mapping to look up sorted Key indices by Key
FastMap<Key, size_t> keyIndices;
size_t j = 0;
BOOST_FOREACH(const VariableIndex::value_type key_factors, variableIndex)
keyIndices.insert(keyIndices.end(), make_pair(key_factors.first, j++));
// If at least some variables are not constrained to be last, constrain the
// ones that should be constrained.
int group = (constrainLast.size() != n ? 1 : 0);
BOOST_FOREACH(Key key, constrainLast) {
cmember[keyIndices.at(key)] = group;
if (forceOrder)
++group;
}
/* ************************************************************************* */
Ordering Ordering::COLAMDConstrained(
const VariableIndex& variableIndex, std::vector<int>& cmember)
{
gttic(Ordering_COLAMDConstrained);
gttic(Prepare);
size_t nEntries = variableIndex.nEntries(), nFactors = variableIndex.nFactors(), nVars = variableIndex.size();
// Convert to compressed column major format colamd wants it in (== MATLAB format!)
size_t Alen = ccolamd_recommended((int)nEntries, (int)nFactors, (int)nVars); /* colamd arg 3: size of the array A */
vector<int> A = vector<int>(Alen); /* colamd arg 4: row indices of A, of size Alen */
vector<int> p = vector<int>(nVars + 1); /* colamd arg 5: column pointers of A, of size n_col+1 */
// Fill in input data for COLAMD
p[0] = 0;
int count = 0;
vector<Key> keys(nVars); // Array to store the keys in the order we add them so we can retrieve them in permuted order
size_t index = 0;
BOOST_FOREACH(const VariableIndex::value_type key_factors, variableIndex) {
// Arrange factor indices into COLAMD format
const VariableIndex::Factors& column = key_factors.second;
size_t lastFactorId = numeric_limits<size_t>::max();
BOOST_FOREACH(size_t factorIndex, column) {
if(lastFactorId != numeric_limits<size_t>::max())
assert(factorIndex > lastFactorId);
A[count++] = (int)factorIndex; // copy sparse column
}
p[index+1] = count; // column j (base 1) goes from A[j-1] to A[j]-1
// Store key in array and increment index
keys[index] = key_factors.first;
++ index;
}
assert((size_t)count == variableIndex.nEntries());
//double* knobs = NULL; /* colamd arg 6: parameters (uses defaults if NULL) */
double knobs[CCOLAMD_KNOBS];
ccolamd_set_defaults(knobs);
knobs[CCOLAMD_DENSE_ROW]=-1;
knobs[CCOLAMD_DENSE_COL]=-1;
int stats[CCOLAMD_STATS]; /* colamd arg 7: colamd output statistics and error codes */
gttoc(Prepare);
// call colamd, result will be in p
/* returns (1) if successful, (0) otherwise*/
if(nVars > 0) {
gttic(ccolamd);
int rv = ccolamd((int)nFactors, (int)nVars, (int)Alen, &A[0], &p[0], knobs, stats, &cmember[0]);
if(rv != 1)
throw runtime_error((boost::format("ccolamd failed with return value %1%")%rv).str());
}
// ccolamd_report(stats);
gttic(Fill_Ordering);
// Convert elimination ordering in p to an ordering
Ordering result;
result.resize(nVars);
for(size_t j = 0; j < nVars; ++j)
result[j] = keys[p[j]];
gttoc(Fill_Ordering);
return result;
}
/* ************************************************************************* */
Ordering Ordering::COLAMD(const VariableIndex& variableIndex)
{
// Call constrained version with all groups set to zero
vector<int> dummy_groups(variableIndex.size(), 0);
return Ordering::COLAMDConstrained(variableIndex, dummy_groups);
}
