Open-Harbor/osrm-backend
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases 3 Wiki Activity

Initial non-building match plugin

Browse Source
This commit is contained in:
Patrick Niklaus 2016-02-18 02:21:47 +01:00
parent 5b18278ee5
commit 7d51a76e79
3 changed files with 398 additions and 343 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

7
include/engine/api/match_parameters.hpp
View File

@ -14,8 +14,11 @@ namespace api
struct MatchParameters : public RouteParameters
{
std::vector<unsigned> timestamps;
bool IsValid() const;
std::vector<boost::optional<unsigned>> timestamps;
bool IsValid() const
{
return timestamps.empty() || timestamps.size() == coordinates.size();
}
};
}

346
include/engine/plugins/match.hpp
View File

@ -2,25 +2,12 @@
#define MATCH_HPP
#include "engine/plugins/plugin_base.hpp"
#include "engine/api/match_parameters.hpp"
#include "engine/map_matching/bayes_classifier.hpp"
#include "engine/object_encoder.hpp"
#include "engine/search_engine.hpp"
#include "engine/guidance/textual_route_annotation.hpp"
#include "engine/guidance/segment_list.hpp"
#include "engine/api_response_generator.hpp"
#include "engine/routing_algorithms/map_matching.hpp"
#include "util/coordinate_calculation.hpp"
#include "util/integer_range.hpp"
#include "util/json_logger.hpp"
#include "util/json_util.hpp"
#include "util/string_util.hpp"
#include <cstdlib>
#include <algorithm>
#include <memory>
#include <string>
#include <vector>
namespace osrm
@ -30,10 +17,8 @@ namespace engine
namespace plugins
{
template <class DataFacadeT> class MapMatchingPlugin : public BasePlugin
class MatchingPlugin : public BasePlugin
{
std::shared_ptr<SearchEngine<DataFacadeT>> search_engine_ptr;
using SubMatching = routing_algorithms::SubMatching;
using SubMatchingList = routing_algorithms::SubMatchingList;
using CandidateLists = routing_algorithms::CandidateLists;
@ -43,8 +28,8 @@ template <class DataFacadeT> class MapMatchingPlugin : public BasePlugin
using TraceClassification = ClassifierT::ClassificationT;
public:
MapMatchingPlugin(DataFacadeT *facade, const int max_locations_map_matching)
: descriptor_string("match"), facade(facade),
MatchingPlugin(datafacade::BaseDataFacade &facade_, const int max_locations_map_matching)
: BasePlugin(facade_),
max_locations_map_matching(max_locations_map_matching),
// the values were derived from fitting a laplace distribution
// to the values of manually classified traces
@ -52,332 +37,11 @@ template <class DataFacadeT> class MapMatchingPlugin : public BasePlugin
map_matching::LaplaceDistribution(0.054385, 0.458432),
0.696774) // valid apriori probability
{
search_engine_ptr = std::make_shared<SearchEngine<DataFacadeT>>(facade);
}
virtual ~MapMatchingPlugin() {}
const std::string GetDescriptor() const final override { return descriptor_string; }
TraceClassification
classify(const float trace_length, const float matched_length, const int removed_points) const
{
(void)removed_points; // unused
const double distance_feature = -std::log(trace_length) + std::log(matched_length);
// matched to the same point
if (!std::isfinite(distance_feature))
{
return std::make_pair(ClassifierT::ClassLabel::NEGATIVE, 1.0);
}
const auto label_with_confidence = classifier.classify(distance_feature);
return label_with_confidence;
}
CandidateLists getCandidates(
const std::vector<util::FixedPointCoordinate> &input_coords,
const std::vector<std::pair<const int, const boost::optional<int>>> &input_bearings,
const double gps_precision,
std::vector<double> &sub_trace_lengths)
{
CandidateLists candidates_lists;
// assuming gps_precision is the standard deviation of a normal distribution that
// models GPS noise (in this model), this should give us the correct search radius
// with > 99% confidence
double query_radius = 3 * gps_precision;
double last_distance =
util::coordinate_calculation::haversineDistance(input_coords[0], input_coords[1]);
sub_trace_lengths.resize(input_coords.size());
sub_trace_lengths[0] = 0;
for (const auto current_coordinate : util::irange<std::size_t>(0, input_coords.size()))
{
bool allow_uturn = false;
if (0 < current_coordinate)
{
last_distance = util::coordinate_calculation::haversineDistance(
input_coords[current_coordinate - 1], input_coords[current_coordinate]);
sub_trace_lengths[current_coordinate] +=
sub_trace_lengths[current_coordinate - 1] + last_distance;
}
if (input_coords.size() - 1 > current_coordinate && 0 < current_coordinate)
{
double turn_angle = util::coordinate_calculation::computeAngle(
input_coords[current_coordinate - 1], input_coords[current_coordinate],
input_coords[current_coordinate + 1]);
// sharp turns indicate a possible uturn
if (turn_angle <= 90.0 || turn_angle >= 270.0)
{
allow_uturn = true;
}
}
// Use bearing values if supplied, otherwise fallback to 0,180 defaults
auto bearing = input_bearings.size() > 0 ? input_bearings[current_coordinate].first : 0;
auto range = input_bearings.size() > 0
? (input_bearings[current_coordinate].second
? *input_bearings[current_coordinate].second
: 10)
: 180;
auto candidates = facade->NearestPhantomNodesInRange(input_coords[current_coordinate],
query_radius, bearing, range);
if (candidates.size() == 0)
{
break;
}
// sort by forward id, then by reverse id and then by distance
std::sort(
candidates.begin(), candidates.end(),
[](const PhantomNodeWithDistance &lhs, const PhantomNodeWithDistance &rhs)
{
return lhs.phantom_node.forward_node_id < rhs.phantom_node.forward_node_id ||
(lhs.phantom_node.forward_node_id == rhs.phantom_node.forward_node_id &&
(lhs.phantom_node.reverse_node_id < rhs.phantom_node.reverse_node_id ||
(lhs.phantom_node.reverse_node_id ==
rhs.phantom_node.reverse_node_id &&
lhs.distance < rhs.distance)));
});
auto new_end = std::unique(
candidates.begin(), candidates.end(),
[](const PhantomNodeWithDistance &lhs, const PhantomNodeWithDistance &rhs)
{
return lhs.phantom_node.forward_node_id == rhs.phantom_node.forward_node_id &&
lhs.phantom_node.reverse_node_id == rhs.phantom_node.reverse_node_id;
});
candidates.resize(new_end - candidates.begin());
if (!allow_uturn)
{
const auto compact_size = candidates.size();
for (const auto i : util::irange<std::size_t>(0, compact_size))
{
// Split edge if it is bidirectional and append reverse direction to end of list
if (candidates[i].phantom_node.forward_node_id != SPECIAL_NODEID &&
candidates[i].phantom_node.reverse_node_id != SPECIAL_NODEID)
{
PhantomNode reverse_node(candidates[i].phantom_node);
reverse_node.forward_node_id = SPECIAL_NODEID;
candidates.push_back(
PhantomNodeWithDistance{reverse_node, candidates[i].distance});
candidates[i].phantom_node.reverse_node_id = SPECIAL_NODEID;
}
}
}
// sort by distance to make pruning effective
std::sort(candidates.begin(), candidates.end(),
[](const PhantomNodeWithDistance &lhs, const PhantomNodeWithDistance &rhs)
{
return lhs.distance < rhs.distance;
});
candidates_lists.push_back(std::move(candidates));
}
return candidates_lists;
}
util::json::Object submatchingToJSON(const SubMatching &sub,
const RouteParameters &route_parameters,
const InternalRouteResult &raw_route)
{
util::json::Object subtrace;
if (route_parameters.classify)
{
subtrace.values["confidence"] = sub.confidence;
}
auto response_generator = MakeApiResponseGenerator(facade);
subtrace.values["hint_data"] = response_generator.BuildHintData(raw_route);
if (route_parameters.geometry || route_parameters.print_instructions)
{
using SegmentList = guidance::SegmentList<DataFacadeT>;
// Passing false to extract_alternative extracts the route.
const constexpr bool EXTRACT_ROUTE = false;
// by passing false to segment_list, we skip the douglas peucker simplification
// and mark all segments as necessary within the generation process
const constexpr bool NO_ROUTE_SIMPLIFICATION = false;
SegmentList segment_list(raw_route, EXTRACT_ROUTE, route_parameters.zoom_level,
NO_ROUTE_SIMPLIFICATION, facade);
if (route_parameters.geometry)
{
subtrace.values["geometry"] =
response_generator.GetGeometry(route_parameters.compression, segment_list);
}
if (route_parameters.print_instructions)
{
subtrace.values["instructions"] =
guidance::AnnotateRoute<DataFacadeT>(segment_list.Get(), facade);
}
util::json::Object json_route_summary;
json_route_summary.values["total_distance"] = segment_list.GetDistance();
json_route_summary.values["total_time"] = segment_list.GetDuration();
subtrace.values["route_summary"] = json_route_summary;
}
subtrace.values["indices"] = util::json::make_array(sub.indices);
util::json::Array points;
for (const auto &node : sub.nodes)
{
points.values.emplace_back(
util::json::make_array(node.location.lat / COORDINATE_PRECISION,
node.location.lon / COORDINATE_PRECISION));
}
subtrace.values["matched_points"] = points;
util::json::Array names;
for (const auto &node : sub.nodes)
{
names.values.emplace_back(facade->get_name_for_id(node.name_id));
}
subtrace.values["matched_names"] = names;
return subtrace;
}
Status HandleRequest(const RouteParameters &route_parameters,
util::json::Object &json_result) final override
{
// enforce maximum number of locations for performance reasons
if (max_locations_map_matching > 0 &&
static_cast<int>(route_parameters.coordinates.size()) > max_locations_map_matching)
{
json_result.values["status_message"] = "Too many coordinates";
return Status::Error;
}
// check number of parameters
if (!check_all_coordinates(route_parameters.coordinates))
{
json_result.values["status_message"] = "Invalid coordinates";
return Status::Error;
}
std::vector<double> sub_trace_lengths;
const auto &input_coords = route_parameters.coordinates;
const auto &input_timestamps = route_parameters.timestamps;
const auto &input_bearings = route_parameters.bearings;
if (input_timestamps.size() > 0 && input_coords.size() != input_timestamps.size())
{
json_result.values["status_message"] =
"Number of timestamps does not match number of coordinates";
return Status::Error;
}
if (input_bearings.size() > 0 && input_coords.size() != input_bearings.size())
{
json_result.values["status_message"] =
"Number of bearings does not match number of coordinates";
return Status::Error;
}
// at least two coordinates are needed for map matching
if (static_cast<int>(input_coords.size()) < 2)
{
json_result.values["status_message"] = "At least two coordinates needed";
return Status::Error;
}
const auto candidates_lists = getCandidates(
input_coords, input_bearings, route_parameters.gps_precision, sub_trace_lengths);
if (candidates_lists.size() != input_coords.size())
{
BOOST_ASSERT(candidates_lists.size() < input_coords.size());
json_result.values["status_message"] =
std::string("Could not find a matching segment for coordinate ") +
std::to_string(candidates_lists.size());
return Status::NoSegment;
}
// setup logging if enabled
if (util::json::Logger::get())
util::json::Logger::get()->initialize("matching");
// call the actual map matching
SubMatchingList sub_matchings;
search_engine_ptr->map_matching(candidates_lists, input_coords, input_timestamps,
route_parameters.matching_beta,
route_parameters.gps_precision, sub_matchings);
util::json::Array matchings;
for (auto &sub : sub_matchings)
{
// classify result
if (route_parameters.classify)
{
double trace_length =
sub_trace_lengths[sub.indices.back()] - sub_trace_lengths[sub.indices.front()];
TraceClassification classification =
classify(trace_length, sub.length,
(sub.indices.back() - sub.indices.front() + 1) - sub.nodes.size());
if (classification.first == ClassifierT::ClassLabel::POSITIVE)
{
sub.confidence = classification.second;
}
else
{
sub.confidence = 1 - classification.second;
}
}
BOOST_ASSERT(sub.nodes.size() > 1);
// FIXME we only run this to obtain the geometry
// The clean way would be to get this directly from the map matching plugin
InternalRouteResult raw_route;
PhantomNodes current_phantom_node_pair;
for (unsigned i = 0; i < sub.nodes.size() - 1; ++i)
{
current_phantom_node_pair.source_phantom = sub.nodes[i];
current_phantom_node_pair.target_phantom = sub.nodes[i + 1];
BOOST_ASSERT(current_phantom_node_pair.source_phantom.IsValid());
BOOST_ASSERT(current_phantom_node_pair.target_phantom.IsValid());
raw_route.segment_end_coordinates.emplace_back(current_phantom_node_pair);
}
search_engine_ptr->shortest_path(
raw_route.segment_end_coordinates,
std::vector<bool>(raw_route.segment_end_coordinates.size() + 1, true), raw_route);
BOOST_ASSERT(raw_route.shortest_path_length != INVALID_EDGE_WEIGHT);
matchings.values.emplace_back(submatchingToJSON(sub, route_parameters, raw_route));
}
if (util::json::Logger::get())
util::json::Logger::get()->render("matching", json_result);
json_result.values["matchings"] = matchings;
if (sub_matchings.empty())
{
json_result.values["status_message"] = "Cannot find matchings";
return Status::EmptyResult;
}
json_result.values["status_message"] = "Found matchings";
return Status::Ok;
}
Status HandleRequest(const MatchParameters &parameters, util::json::Object &json_result);
private:
std::string descriptor_string;
DataFacadeT *facade;
int max_locations_map_matching;
ClassifierT classifier;
};

388
src/engine/plugins/match.cpp Normal file
View File

@ -0,0 +1,388 @@
#ifndef MATCH_HPP
#define MATCH_HPP
#include "engine/plugins/plugin_base.hpp"
#include "engine/map_matching/bayes_classifier.hpp"
#include "engine/object_encoder.hpp"
#include "engine/search_engine.hpp"
#include "engine/guidance/textual_route_annotation.hpp"
#include "engine/guidance/segment_list.hpp"
#include "engine/api_response_generator.hpp"
#include "engine/routing_algorithms/map_matching.hpp"
#include "util/coordinate_calculation.hpp"
#include "util/integer_range.hpp"
#include "util/json_logger.hpp"
#include "util/json_util.hpp"
#include "util/string_util.hpp"
#include <cstdlib>
#include <algorithm>
#include <memory>
#include <string>
#include <vector>
namespace osrm
{
namespace engine
{
namespace plugins
{
template <class DataFacadeT> class MapMatchingPlugin : public BasePlugin
{
std::shared_ptr<SearchEngine<DataFacadeT>> search_engine_ptr;
using SubMatching = routing_algorithms::SubMatching;
using SubMatchingList = routing_algorithms::SubMatchingList;
using CandidateLists = routing_algorithms::CandidateLists;
using ClassifierT = map_matching::BayesClassifier<map_matching::LaplaceDistribution,
map_matching::LaplaceDistribution,
double>;
using TraceClassification = ClassifierT::ClassificationT;
public:
MapMatchingPlugin(DataFacadeT *facade, const int max_locations_map_matching)
: descriptor_string("match"), facade(facade),
max_locations_map_matching(max_locations_map_matching),
// the values where derived from fitting a laplace distribution
// to the values of manually classified traces
classifier(map_matching::LaplaceDistribution(0.005986, 0.016646),
map_matching::LaplaceDistribution(0.054385, 0.458432),
0.696774) // valid apriori probability
{
search_engine_ptr = std::make_shared<SearchEngine<DataFacadeT>>(facade);
}
virtual ~MapMatchingPlugin() {}
const std::string GetDescriptor() const final override { return descriptor_string; }
TraceClassification
classify(const float trace_length, const float matched_length, const int removed_points) const
{
(void)removed_points; // unused
const double distance_feature = -std::log(trace_length) + std::log(matched_length);
// matched to the same point
if (!std::isfinite(distance_feature))
{
return std::make_pair(ClassifierT::ClassLabel::NEGATIVE, 1.0);
}
const auto label_with_confidence = classifier.classify(distance_feature);
return label_with_confidence;
}
CandidateLists getCandidates(
const std::vector<util::FixedPointCoordinate> &input_coords,
const std::vector<std::pair<const int, const boost::optional<int>>> &input_bearings,
const double gps_precision,
std::vector<double> &sub_trace_lengths)
{
CandidateLists candidates_lists;
// assuming gps_precision is the standard deviation of a normal distribution that
// models GPS noise (in this model), this should give us the correct search radius
// with > 99% confidence
double query_radius = 3 * gps_precision;
double last_distance =
util::coordinate_calculation::haversineDistance(input_coords[0], input_coords[1]);
sub_trace_lengths.resize(input_coords.size());
sub_trace_lengths[0] = 0;
for (const auto current_coordinate : util::irange<std::size_t>(0, input_coords.size()))
{
bool allow_uturn = false;
if (0 < current_coordinate)
{
last_distance = util::coordinate_calculation::haversineDistance(
input_coords[current_coordinate - 1], input_coords[current_coordinate]);
sub_trace_lengths[current_coordinate] +=
sub_trace_lengths[current_coordinate - 1] + last_distance;
}
if (input_coords.size() - 1 > current_coordinate && 0 < current_coordinate)
{
double turn_angle = util::coordinate_calculation::computeAngle(
input_coords[current_coordinate - 1], input_coords[current_coordinate],
input_coords[current_coordinate + 1]);
// sharp turns indicate a possible uturn
if (turn_angle <= 90.0 || turn_angle >= 270.0)
{
allow_uturn = true;
}
}
// Use bearing values if supplied, otherwise fallback to 0,180 defaults
auto bearing = input_bearings.size() > 0 ? input_bearings[current_coordinate].first : 0;
auto range = input_bearings.size() > 0
? (input_bearings[current_coordinate].second
? *input_bearings[current_coordinate].second
: 10)
: 180;
auto candidates = facade->NearestPhantomNodesInRange(input_coords[current_coordinate],
query_radius, bearing, range);
if (candidates.size() == 0)
{
break;
}
// sort by forward id, then by reverse id and then by distance
std::sort(
candidates.begin(), candidates.end(),
[](const PhantomNodeWithDistance &lhs, const PhantomNodeWithDistance &rhs)
{
return lhs.phantom_node.forward_node_id < rhs.phantom_node.forward_node_id ||
(lhs.phantom_node.forward_node_id == rhs.phantom_node.forward_node_id &&
(lhs.phantom_node.reverse_node_id < rhs.phantom_node.reverse_node_id ||
(lhs.phantom_node.reverse_node_id ==
rhs.phantom_node.reverse_node_id &&
lhs.distance < rhs.distance)));
});
auto new_end = std::unique(
candidates.begin(), candidates.end(),
[](const PhantomNodeWithDistance &lhs, const PhantomNodeWithDistance &rhs)
{
return lhs.phantom_node.forward_node_id == rhs.phantom_node.forward_node_id &&
lhs.phantom_node.reverse_node_id == rhs.phantom_node.reverse_node_id;
});
candidates.resize(new_end - candidates.begin());
if (!allow_uturn)
{
const auto compact_size = candidates.size();
for (const auto i : util::irange<std::size_t>(0, compact_size))
{
// Split edge if it is bidirectional and append reverse direction to end of list
if (candidates[i].phantom_node.forward_node_id != SPECIAL_NODEID &&
candidates[i].phantom_node.reverse_node_id != SPECIAL_NODEID)
{
PhantomNode reverse_node(candidates[i].phantom_node);
reverse_node.forward_node_id = SPECIAL_NODEID;
candidates.push_back(
PhantomNodeWithDistance{reverse_node, candidates[i].distance});
candidates[i].phantom_node.reverse_node_id = SPECIAL_NODEID;
}
}
}
// sort by distance to make pruning effective
std::sort(candidates.begin(), candidates.end(),
[](const PhantomNodeWithDistance &lhs, const PhantomNodeWithDistance &rhs)
{
return lhs.distance < rhs.distance;
});
candidates_lists.push_back(std::move(candidates));
}
return candidates_lists;
}
util::json::Object submatchingToJSON(const SubMatching &sub,
const RouteParameters &route_parameters,
const InternalRouteResult &raw_route)
{
util::json::Object subtrace;
if (route_parameters.classify)
{
subtrace.values["confidence"] = sub.confidence;
}
auto response_generator = MakeApiResponseGenerator(facade);
subtrace.values["hint_data"] = response_generator.BuildHintData(raw_route);
if (route_parameters.geometry || route_parameters.print_instructions)
{
using SegmentList = guidance::SegmentList<DataFacadeT>;
// Passing false to extract_alternative extracts the route.
const constexpr bool EXTRACT_ROUTE = false;
// by passing false to segment_list, we skip the douglas peucker simplification
// and mark all segments as necessary within the generation process
const constexpr bool NO_ROUTE_SIMPLIFICATION = false;
SegmentList segment_list(raw_route, EXTRACT_ROUTE, route_parameters.zoom_level,
NO_ROUTE_SIMPLIFICATION, facade);
if (route_parameters.geometry)
{
subtrace.values["geometry"] =
response_generator.GetGeometry(route_parameters.compression, segment_list);
}
if (route_parameters.print_instructions)
{
subtrace.values["instructions"] =
guidance::AnnotateRoute<DataFacadeT>(segment_list.Get(), facade);
}
util::json::Object json_route_summary;
json_route_summary.values["total_distance"] = segment_list.GetDistance();
json_route_summary.values["total_time"] = segment_list.GetDuration();
subtrace.values["route_summary"] = json_route_summary;
}
subtrace.values["indices"] = util::json::make_array(sub.indices);
util::json::Array points;
for (const auto &node : sub.nodes)
{
points.values.emplace_back(
util::json::make_array(node.location.lat / COORDINATE_PRECISION,
node.location.lon / COORDINATE_PRECISION));
}
subtrace.values["matched_points"] = points;
util::json::Array names;
for (const auto &node : sub.nodes)
{
names.values.emplace_back(facade->get_name_for_id(node.name_id));
}
subtrace.values["matched_names"] = names;
return subtrace;
}
Status HandleRequest(const RouteParameters &route_parameters,
util::json::Object &json_result) final override
{
// enforce maximum number of locations for performance reasons
if (max_locations_map_matching > 0 &&
static_cast<int>(route_parameters.coordinates.size()) > max_locations_map_matching)
{
json_result.values["status_message"] = "Too many coodindates";
return Status::Error;
}
// check number of parameters
if (!check_all_coordinates(route_parameters.coordinates))
{
json_result.values["status_message"] = "Invalid coordinates";
return Status::Error;
}
std::vector<double> sub_trace_lengths;
const auto &input_coords = route_parameters.coordinates;
const auto &input_timestamps = route_parameters.timestamps;
const auto &input_bearings = route_parameters.bearings;
if (input_timestamps.size() > 0 && input_coords.size() != input_timestamps.size())
{
json_result.values["status_message"] =
"Number of timestamps does not match number of coordinates";
return Status::Error;
}
if (input_bearings.size() > 0 && input_coords.size() != input_bearings.size())
{
json_result.values["status_message"] =
"Number of bearings does not match number of coordinates";
return Status::Error;
}
// at least two coordinates are needed for map matching
if (static_cast<int>(input_coords.size()) < 2)
{
json_result.values["status_message"] = "At least two coordinates needed";
return Status::Error;
}
const auto candidates_lists = getCandidates(
input_coords, input_bearings, route_parameters.gps_precision, sub_trace_lengths);
if (candidates_lists.size() != input_coords.size())
{
BOOST_ASSERT(candidates_lists.size() < input_coords.size());
json_result.values["status_message"] =
std::string("Could not find a matching segment for coordinate ") +
std::to_string(candidates_lists.size());
return Status::NoSegment;
}
// setup logging if enabled
if (util::json::Logger::get())
util::json::Logger::get()->initialize("matching");
// call the actual map matching
SubMatchingList sub_matchings;
search_engine_ptr->map_matching(candidates_lists, input_coords, input_timestamps,
route_parameters.matching_beta,
route_parameters.gps_precision, sub_matchings);
util::json::Array matchings;
for (auto &sub : sub_matchings)
{
// classify result
if (route_parameters.classify)
{
double trace_length =
sub_trace_lengths[sub.indices.back()] - sub_trace_lengths[sub.indices.front()];
TraceClassification classification =
classify(trace_length, sub.length,
(sub.indices.back() - sub.indices.front() + 1) - sub.nodes.size());
if (classification.first == ClassifierT::ClassLabel::POSITIVE)
{
sub.confidence = classification.second;
}
else
{
sub.confidence = 1 - classification.second;
}
}
BOOST_ASSERT(sub.nodes.size() > 1);
// FIXME we only run this to obtain the geometry
// The clean way would be to get this directly from the map matching plugin
InternalRouteResult raw_route;
PhantomNodes current_phantom_node_pair;
for (unsigned i = 0; i < sub.nodes.size() - 1; ++i)
{
current_phantom_node_pair.source_phantom = sub.nodes[i];
current_phantom_node_pair.target_phantom = sub.nodes[i + 1];
BOOST_ASSERT(current_phantom_node_pair.source_phantom.IsValid());
BOOST_ASSERT(current_phantom_node_pair.target_phantom.IsValid());
raw_route.segment_end_coordinates.emplace_back(current_phantom_node_pair);
}
search_engine_ptr->shortest_path(
raw_route.segment_end_coordinates,
std::vector<bool>(raw_route.segment_end_coordinates.size() + 1, true), raw_route);
BOOST_ASSERT(raw_route.shortest_path_length != INVALID_EDGE_WEIGHT);
matchings.values.emplace_back(submatchingToJSON(sub, route_parameters, raw_route));
}
if (util::json::Logger::get())
util::json::Logger::get()->render("matching", json_result);
json_result.values["matchings"] = matchings;
if (sub_matchings.empty())
{
json_result.values["status_message"] = "Cannot find matchings";
return Status::EmptyResult;
}
json_result.values["status_message"] = "Found matchings";
return Status::Ok;
}
private:
std::string descriptor_string;
DataFacadeT *facade;
int max_locations_map_matching;
ClassifierT classifier;
};
}
}
}
#endif // MATCH_HPP