bool IndexDescriptor::areIndexOptionsEquivalent(const IndexDescriptor* other) const {
if (isSparse() != other->isSparse()) {
return false;
}
if (!isIdIndex() && unique() != other->unique()) {
// Note: { _id: 1 } or { _id: -1 } implies unique: true.
return false;
}
// Then compare the rest of the options.
std::map<StringData, BSONElement> existingOptionsMap;
populateOptionsMap(existingOptionsMap, infoObj());
std::map<StringData, BSONElement> newOptionsMap;
populateOptionsMap(newOptionsMap, other->infoObj());
return existingOptionsMap.size() == newOptionsMap.size() &&
std::equal(existingOptionsMap.begin(),
existingOptionsMap.end(),
newOptionsMap.begin(),
[](const std::pair<StringData, BSONElement>& lhs,
const std::pair<StringData, BSONElement>& rhs) {
return lhs.first == rhs.first &&
SimpleBSONElementComparator::kInstance.evaluate(lhs.second ==
rhs.second);
});
}
bool isPushOnly
(
void
)
{
return (isSparse() && sparseMeta.pushOnly);
}
int SVMConfiguration::getDataDim() {
if(isSparse()) {
return this->sparse_data.n_rows;
} else {
return this->data.n_cols;
}
}
bool isStaged
(
void
)
{
// NOTE: also tested by SPQR/Tcov, but not flagged as such in cov output
return (isSparse() && sparseMeta.isStaged);
}
bool IndexDescriptor::areIndexOptionsEquivalent( const IndexDescriptor* other ) const {
if ( isSparse() != other->isSparse() ) {
return false;
}
if ( !isIdIndex() &&
unique() != other->unique() ) {
// Note: { _id: 1 } or { _id: -1 } implies unique: true.
return false;
}
// Then compare the rest of the options.
std::map<StringData, BSONElement> existingOptionsMap;
populateOptionsMap( existingOptionsMap, infoObj() );
std::map<StringData, BSONElement> newOptionsMap;
populateOptionsMap( newOptionsMap, other->infoObj() );
return existingOptionsMap == newOptionsMap;
}
cv::SparseMat MxArray::toSparseMat() const
{
// Check if it's sparse.
if (!isSparse() || !isDouble())
mexErrMsgIdAndTxt("mexopencv:error", "MxArray is not sparse");
// Create cv::SparseMat.
const mwSize m = mxGetM(p_), n = mxGetN(p_);
const int dims[] = {m, n};
cv::SparseMat mat(2, dims, CV_32F);
// Copy data.
const mwIndex *ir = mxGetIr(p_);
const mwIndex *jc = mxGetJc(p_);
const double *pr = mxGetPr(p_);
if (!ir || !jc || !pr)
mexErrMsgIdAndTxt("mexopencv:error", "Null pointer error");
for (mwIndex j=0; j<n; ++j) {
const mwIndex start = jc[j], end = jc[j + 1] - 1;
// (row,col) <= val.
for (mwIndex i = start; i <= end; ++i)
mat.ref<float>(ir[i], j) = static_cast<float>(pr[i]);
}
return mat;
}
