Method batchSearch

python/src/ngtpy.cpp:427–467

  }

  void batchSearch(
    py::array_t<float> queries,
    BatchResults &results,
    size_t size,
    bool withDistance = true
  ) {
    const py::buffer_info &qinfo = queries.request();
    const std::vector<long int> &qshape = qinfo.shape;
    auto nOfQueries = qshape[0];
    size_t dimension = qshape[1];
    auto *queryPtr = static_cast<float*>(qinfo.ptr);
    size = size > 0 ? size : defaultNumOfSearchObjects;

    results.results.clear();
    results.resultList.clear();
    results.results.resize(nOfQueries);
    results.size = 0;

#pragma omp parallel for schedule(dynamic)
    for (int idx = 0; idx < nOfQueries; idx++) {
      float *qptr = queryPtr + idx * dimension;
      std::vector<float> qvector(static_cast<float*>(qptr), static_cast<float*>(qptr) + dimension);
      NGT::SearchQuery sc(qvector);
      sc.setSize(size);
      sc.setRadius(defaultRadius);
      sc.setExpectedAccuracy(defaultExpectedAccuracy);
      sc.setEpsilon(defaultEpsilon);
      sc.setEdgeSize(defaultEdgeSize);
#ifdef NGT_REFINEMENT
      sc.setRefinementExpansion(defaultResultExpansion);	// set refinement expansion.
#endif
      if (treeIndex) {
        NGT::Index::search(sc);
      } else {
        NGT::Index::searchUsingOnlyGraph(sc);
      }
      results.results[idx] = std::move(sc.getWorkingResult());
    }
    results.size = results.results.size();
    return;
  }

  void remove(size_t id) {
    id = zeroNumbering ? id + 1 : id;