Method linearSearch

python/src/ngtpy.cpp:369–425

  }

  py::object linearSearch(
   py::object query,
   size_t size = 0, 			// the number of resultant objects
   bool withDistance = true
  ) {
    py::array_t<float> qobject(query);
    py::buffer_info qinfo = qobject.request();
    NGT::Object *ngtquery = 0;
    try {
      ngtquery = NGT::Index::allocateObject(static_cast<float*>(qinfo.ptr), qinfo.size);
    } catch (NGT::Exception &e) {
      std::cerr << e.what() << std::endl;
      if (!withDistance) {
	return py::array_t<int>();
      } else {
	return py::list();
      }
    }

    NGT::SearchContainer sc(*ngtquery);
    sc.setSize(size == 0 ? defaultNumOfSearchObjects : size);	// the number of resulting objects.
    sc.setRadius(defaultRadius);				// the radius of search.
    NGT::ObjectDistances rs;
    sc.setResults(&rs);

    NGT::Index::linearSearch(sc);

    numOfDistanceComputations += sc.distanceComputationCount;

    NGT::Index::deleteObject(ngtquery);
    if (!withDistance) {
      py::array_t<int> ids(rs.size());
      py::buffer_info idsinfo = ids.request();
      int *ptr = reinterpret_cast<int*>(idsinfo.ptr);
      if (zeroNumbering) {
	for (auto ri = rs.begin(); ri != rs.end(); ++ri) {
	  *ptr++ = (*ri).id - 1;
        }
      } else {
	for (auto ri = rs.begin(); ri != rs.end(); ++ri) {
	  *ptr++ = (*ri).id;
        }
      }
      return ids;
    }
    py::list results;
    if (zeroNumbering) {
      for (auto ri = rs.begin(); ri != rs.end(); ++ri) {
	results.append(py::make_tuple((*ri).id - 1, (*ri).distance));
      }
    } else {
      for (auto ri = rs.begin(); ri != rs.end(); ++ri) {
	results.append(py::make_tuple((*ri).id, (*ri).distance));
      }
    }
    return results;
  }