int Index::knnSearch(const Matrix<ElementType>& queries,
Matrix<int>& indices,
Matrix<DistanceType>& dists,
int knn,
size_t knn,
const SearchParams& params);
int Index::knnSearch(const Matrix<ElementType>& queries,
std::vector< std::vector<int> >& indices,
std::vector<std::vector<DistanceType> >& dists,
size_t knn,
const SearchParams& params);
\end{Verbatim}
\begin{description}
\item[query]{Matrix containing the query points. Size of matrix is ($num\_queries \times dimentionality $)}
\item[indices]{Matrix that will contain the indices of the K-nearest neighbors found (size should be at least $num\_queries \times knn$)}
\item[dists]{Matrix that will contain the distances to the K-nearest neighbors found. (size should be at least $num\_queries \times knn$). The distance values are computed by the distance function used (see \texttt{flann::set\_distance\_type} below), for example in the case of euclidean distance function, this will contain the squared euclidean distances.}
\item[queries]{Matrix containing the query points. Size of matrix is ($num\_queries \times dimentionality $)}
\item[indices]{Matrix that will contain the indices of the K-nearest neighbors found (size should be at least
$num\_queries \times knn$ for the pre-allocated version).}
\item[dists]{Matrix that will contain the distances to the K-nearest neighbors found (size should be at least
$num\_queries \times knn$ for the pre-allocated version).}
\item[knn]{Number of nearest neighbors to search for.}
\item[params]{Search parameters.} Structure containing parameters used during search.
...
...
@@ -514,19 +632,32 @@ required to achieve the specified precision was also computed, to use that value
\subsubsection{flann::Index::radiusSearch}
Performs a radius nearest neighbor search for a given query point.
Performs a radius nearest neighbor search for a set of query points. There are two signatures for this method,
one that takes pre-allocated \texttt{flann::Matrix} objects for returning the indices of and distances to the neighbors
found, and one that takes \texttt{std::vector<std::vector>} that will resized automatically as needed.
int Index::radiusSearch(const Matrix<ElementType>& query,
int Index::radiusSearch(const Matrix<ElementType>& queries,
Matrix<int>& indices,
Matrix<DistanceType>& dists,
float radius,
const SearchParams& params);
int Index::radiusSearch(const Matrix<ElementType>& queries,
std::vector< std::vector<int> >& indices,
std::vector<std::vector<DistanceType> >& dists,
float radius,
const SearchParams& params);
\end{Verbatim}
\begin{description}
\item[query]{The query point}
\item[indices]{Vector that will contain the indices of the points found within the search radius in increasing order of the distance to the query point. If the number of neighbors in the search radius is bigger than the size of this vector, the ones that don't fit in the vector are ignored. }
\item[dists]{Vector that will contain the distances to the points found within the search radius}
\item[queries]{The query point. Size of matrix is ($num\_queries \times dimentionality $).}
\item[indices]{Matrix that will contain the indices of the K-nearest neighbors found. For the pre-allocated version,
only as many neighbors are returned as many columns in this matrix. If fewer neighbors are found than
columns in this matrix, the element after that last index returned is -1. In case of the std::vector version, the rows
will be resized as needed to fit all the neighbors to be returned, except if the ``max\_neighbors'' search parameter is
set.}
\item[dists]{Matrix that will contain the distances to the K-nearest neighbors found. The same number of values are
returned here as for the \texttt{indices} matrix.}
