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Files | Functions
Trajectory APIs

APIs related to trajectories. More...

Files

file  trajectory.hpp
 
file  trajectory.cuh
 

Functions

template<typename IdInputIt , typename PointInputIt , typename TimestampInputIt , typename IdOutputIt , typename PointOutputIt , typename TimestampOutputIt , typename OffsetType = std::int32_t>
std::unique_ptr< rmm::device_uvector< OffsetType > > cuspatial::derive_trajectories (IdInputIt ids_first, IdInputIt ids_last, PointInputIt points_first, TimestampInputIt timestamps_first, IdOutputIt ids_output_first, PointOutputIt points_output_first, TimestampOutputIt timestamps_output_first, rmm::cuda_stream_view stream=rmm::cuda_stream_default, rmm::mr::device_memory_resource *mr=rmm::mr::get_current_device_resource())
 Derive trajectories from object ids, points, and timestamps.
 
template<typename IdInputIt , typename PointInputIt , typename TimestampInputIt , typename OutputIt , typename IndexT = iterator_value_type<IdInputIt>>
OutputIt cuspatial::trajectory_distances_and_speeds (IndexT num_trajectories, IdInputIt ids_first, IdInputIt ids_last, PointInputIt points_first, TimestampInputIt timestamps_first, OutputIt distances_and_speeds_first, rmm::cuda_stream_view stream=rmm::cuda_stream_default)
 Compute the total distance (in meters) and average speed (in m/s) of objects in trajectories.
 
std::pair< std::unique_ptr< cudf::table >, std::unique_ptr< cudf::column > > cuspatial::derive_trajectories (cudf::column_view const &object_id, cudf::column_view const &x, cudf::column_view const &y, cudf::column_view const &timestamp, rmm::mr::device_memory_resource *mr=rmm::mr::get_current_device_resource())
 Derive trajectories from object ids, points, and timestamps.
 
std::unique_ptr< cudf::table > cuspatial::trajectory_distances_and_speeds (cudf::size_type num_trajectories, cudf::column_view const &object_id, cudf::column_view const &x, cudf::column_view const &y, cudf::column_view const &timestamp, rmm::mr::device_memory_resource *mr=rmm::mr::get_current_device_resource())
 Compute the distance and speed of objects in a trajectory. Groups the timestamp, x, and y, columns by object id to determine unique trajectories, then computes the average distance and speed for all routes in each trajectory.
 
std::unique_ptr< cudf::table > cuspatial::trajectory_bounding_boxes (cudf::size_type num_trajectories, cudf::column_view const &object_id, cudf::column_view const &x, cudf::column_view const &y, rmm::mr::device_memory_resource *mr=rmm::mr::get_current_device_resource())
 Compute the spatial bounding boxes of trajectories. Groups the x, y, and timestamp columns by object id to determine unique trajectories, then computes the minimum bounding box to contain all routes in each trajectory.
 

Detailed Description

APIs related to trajectories.

Function Documentation

◆ derive_trajectories() [1/2]

std::pair< std::unique_ptr< cudf::table >, std::unique_ptr< cudf::column > > cuspatial::derive_trajectories ( cudf::column_view const & object_id,
cudf::column_view const & x,
cudf::column_view const & y,
cudf::column_view const & timestamp,
rmm::mr::device_memory_resource * mr = rmm::mr::get_current_device_resource() )

Derive trajectories from object ids, points, and timestamps.

Groups the input object ids to determine unique trajectories. Returns a table with the trajectory ids, the number of objects in each trajectory, and the offset position of the first object for each trajectory in the input object ids column.

Parameters
object_idcolumn of object (e.g., vehicle) ids
xcoordinates (in kilometers)
ycoordinates (in kilometers)
timestampcolumn of timestamps in any resolution
mrThe optional resource to use for output device memory allocations
Exceptions
cuspatial::logic_errorIf object_id isn't cudf::type_id::INT32
cuspatial::logic_errorIf x and y are different types
cuspatial::logic_errorIf timestamp isn't a cudf::TIMESTAMP type
cuspatial::logic_errorIf object_id, x, y, or timestamp contain nulls
cuspatial::logic_errorIf object_id, x, y, and timestamp are different sizes
Returns
an std::pair<table, column>:
  1. table of (object_id, x, y, timestamp) sorted by (object_id, timestamp)
  2. int32 column of start positions for each trajectory's first object

◆ derive_trajectories() [2/2]

template<typename IdInputIt , typename PointInputIt , typename TimestampInputIt , typename IdOutputIt , typename PointOutputIt , typename TimestampOutputIt , typename OffsetType = std::int32_t>
std::unique_ptr< rmm::device_uvector< OffsetType > > cuspatial::derive_trajectories ( IdInputIt ids_first,
IdInputIt ids_last,
PointInputIt points_first,
TimestampInputIt timestamps_first,
IdOutputIt ids_output_first,
PointOutputIt points_output_first,
TimestampOutputIt timestamps_output_first,
rmm::cuda_stream_view stream = rmm::cuda_stream_default,
rmm::mr::device_memory_resource * mr = rmm::mr::get_current_device_resource() )

Derive trajectories from object ids, points, and timestamps.

Output points and timestamps are reordered to be grouped by object ID and ordered by timestamp within groups. Returns a vector containing the offset index of the first object of each trajectory in the output.

Template Parameters
IdInputItIterator over object IDs. Must meet the requirements of LegacyRandomAccessIterator and be device-readable.
PointInputItIterator over points. Must meet the requirements of LegacyRandomAccessIterator and be device-readable.
TimestampInputItIterator over timestamps. Must meet the requirements of LegacyRandomAccessIterator and be device-readable.
IdOutputItIterator over output object IDs. Must meet the requirements of LegacyRandomAccessIterator and be device-writeable.
PointOutputItIterator over output points. Must meet the requirements of LegacyRandomAccessIterator and be device-writeable.
TimestampOutputItIterator over output timestamps. Must meet the requirements of LegacyRandomAccessIterator and be device-writeable.
Parameters
ids_firstbeginning of the range of input object ids
ids_lastend of the range of input object ids
points_firstbeginning of the range of input point (x,y) coordinates
timestamps_firstbeginning of the range of input timestamps
ids_out_firstbeginning of the range of output object ids
points_out_firstbeginning of the range of output point (x,y) coordinates
timestamps_out_firstbeginning of the range of output timestamps
streamthe CUDA stream on which to perform computations and allocate memory.
mroptional resource to use for output device memory allocations
Returns
a unique_ptr to a device_uvector containing the offset index of the first object of each trajectory in the sorted output. These offsets can be used to access the sorted output data.
Precondition
There must be no overlap between any of the input and output ranges.
The type of the object IDs and timestamps must support strict weak ordering via comparison operators.

◆ trajectory_bounding_boxes()

std::unique_ptr< cudf::table > cuspatial::trajectory_bounding_boxes ( cudf::size_type num_trajectories,
cudf::column_view const & object_id,
cudf::column_view const & x,
cudf::column_view const & y,
rmm::mr::device_memory_resource * mr = rmm::mr::get_current_device_resource() )

Compute the spatial bounding boxes of trajectories. Groups the x, y, and timestamp columns by object id to determine unique trajectories, then computes the minimum bounding box to contain all routes in each trajectory.

Note
Assumes object_id, timestamp, x, y presorted by (object_id, timestamp).
Parameters
num_trajectoriesnumber of trajectories (unique object ids)
object_idcolumn of object (e.g., vehicle) ids
xcoordinates (in kilometers)
ycoordinates (in kilometers)
mrThe optional resource to use for output device memory allocations
Exceptions
cuspatial::logic_errorIf object_id isn't cudf::type_id::INT32
cuspatial::logic_errorIf x and y are different types
cuspatial::logic_errorIf object_id, x, or y contain nulls
cuspatial::logic_errorIf object_id, x, and y are different sizes
Returns
a cudf table of bounding boxes with length num_trajectories and four columns: x_min - the minimum x-coordinate of each bounding box in kilometers y_min - the minimum y-coordinate of each bounding box in kilometers x_max - the maximum x-coordinate of each bounding box in kilometers y_max - the maximum y-coordinate of each bounding box in kilometers

◆ trajectory_distances_and_speeds() [1/2]

std::unique_ptr< cudf::table > cuspatial::trajectory_distances_and_speeds ( cudf::size_type num_trajectories,
cudf::column_view const & object_id,
cudf::column_view const & x,
cudf::column_view const & y,
cudf::column_view const & timestamp,
rmm::mr::device_memory_resource * mr = rmm::mr::get_current_device_resource() )

Compute the distance and speed of objects in a trajectory. Groups the timestamp, x, and y, columns by object id to determine unique trajectories, then computes the average distance and speed for all routes in each trajectory.

Note
Assumes object_id, timestamp, x, y presorted by (object_id, timestamp).
Parameters
num_trajectoriesnumber of trajectories (unique object ids)
object_idcolumn of object (e.g., vehicle) ids
xcoordinates (in kilometers)
ycoordinates (in kilometers)
timestampcolumn of timestamps in any resolution
mrThe optional resource to use for output device memory allocations
Exceptions
cuspatial::logic_errorIf object_id isn't cudf::type_id::INT32
cuspatial::logic_errorIf x and y are different types
cuspatial::logic_errorIf timestamp isn't a cudf::TIMESTAMP type
cuspatial::logic_errorIf object_id, x, y, or timestamp contain nulls
cuspatial::logic_errorIf object_id, x, y, and timestamp are different sizes
Returns
a cuDF table of distances (meters) and speeds (meters/second) whose length is num_trajectories, sorted by object_id.

◆ trajectory_distances_and_speeds() [2/2]

template<typename IdInputIt , typename PointInputIt , typename TimestampInputIt , typename OutputIt , typename IndexT = iterator_value_type<IdInputIt>>
OutputIt cuspatial::trajectory_distances_and_speeds ( IndexT num_trajectories,
IdInputIt ids_first,
IdInputIt ids_last,
PointInputIt points_first,
TimestampInputIt timestamps_first,
OutputIt distances_and_speeds_first,
rmm::cuda_stream_view stream = rmm::cuda_stream_default )

Compute the total distance (in meters) and average speed (in m/s) of objects in trajectories.

Note
Assumes object_id, timestamp, x, y presorted by (object_id, timestamp).
Template Parameters
IdInputItIterator over object IDs. Must meet the requirements of LegacyRandomAccessIterator and be device-readable.
PointInputItIterator over points. Must meet the requirements of LegacyRandomAccessIterator and be device-readable.
TimestampInputItIterator over timestamps. Must meet the requirements of LegacyRandomAccessIterator and be device-readable.
OutputItIterator over output (distance, speed) pairs. Must meet the requirements of LegacyRandomAccessIterator and be device-writeable.
IndexTThe type of the object IDs.
Parameters
num_trajectoriesnumber of trajectories (unique object ids)
ids_firstbeginning of the range of input object ids
ids_lastend of the range of input object ids
points_firstbeginning of the range of input point (x,y) coordinates
timestamps_firstbeginning of the range of input timestamps
distances_and_speeds_firstbeginning of the range of output (distance, speed) pairs
streamthe CUDA stream on which to perform computations and allocate memory.
Returns
An iterator to the end of the range of output (distance, speed) pairs.