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** NOTE:** cuSpatial depends on [ cuDF] ( https://github.com/rapidsai/cudf ) and
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[ RMM] ( https://github.com/rapidsai/rmm ) from [ RAPIDS] ( https://rapids.ai/ ) .
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- ## Implemented operations:
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+ ## Operations
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+
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cuSpatial supports the following operations on spatial and trajectory data:
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1 . Spatial window query
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2 . Point-in-polygon test
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3 . Haversine distance
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4 . Hausdorff distance
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5 . Deriving trajectories from point location data
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6 . Computing distance/speed of trajectories
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7 . Computing spatial bounding boxes of trajectories
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+ 8 . Quadtree-based indexing for large-scale point data
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+ 9 . Quadtree-based point-in-polygon spatial join
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+ 10 . Quadtree-based point-to-polyline nearest neighbor distance
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+
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+ Future support is planned for the following operations:
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- Future support is planned for the following operations.
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1 . Temporal window query
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2 . Temporal point query (year+month+day+hour+minute+second+millisecond)
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- 3 . Point-to-polyline nearest neighbor distance
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- 4 . Grid-based indexing for points and polygons
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- 5 . Quadtree-based indexing for large-scale point data
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- 6 . R-Tree-based indexing for Polygons/Polylines
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+ 3 . Grid-based indexing for points and polygons
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+ 4 . R-Tree-based indexing for Polygons/Polylines
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## Install from Conda
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To install via conda:
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- ```
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+ ``` shell
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conda install -c conda-forge -c rapidsai-nightly cuspatial
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```
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## Install from Source
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To build and install cuSpatial from source:
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### Install dependencies
@@ -46,28 +53,31 @@ environment created in step 3 is active.
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1 . export ` CUSPATIAL_HOME=$(pwd)/cuspatial `
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2 . clone the cuSpatial repo
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- ```
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- git clone --recurse-submodules https://github.com/rapidsai/cuspatial.git $CUSPATIAL_HOME
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- ```
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+ ``` shell
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+ git clone --recurse-submodules https://github.com/rapidsai/cuspatial.git $CUSPATIAL_HOME
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+ ```
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- 3 . Compile and install
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- Similar to cuDF (version 0.11), simplely run 'build.sh' diectly under $CUSPATIAL_HOME<br >
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- Note that a "build" dir is created automatically under $CUSPATIAL_HOME/cpp
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+ 3 . Compile and install
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- 4 . Run C++/Python test code < br >
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+ Similar to cuDF (version 0.20), simply run ` build.sh ` diectly under ` $CUSPATIAL_HOME ` .
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- Some tests using inline data can be run directly, e.g.,
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- ```
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- $CUSPATIAL_HOME/cpp/build/gtests/LEGACY_HAUSDORFF_TEST
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- $CUSPATIAL_HOME/cpp/build/gtests/POINT_IN_POLYGON_TEST
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- python python/cuspatial/cuspatial/tests/legacy/test_hausdorff_distance.py
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- python python/cuspatial/cuspatial/tests/test_pip.py
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- ```
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+ Note that a "build" dir is created automatically under ` $CUSPATIAL_HOME/cpp ` .
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+ 4 . Run C++/Python test code
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+
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+ Some tests using inline data can be run directly, e.g.:
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+
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+ ``` shell
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+ $CUSPATIAL_HOME /cpp/build/gtests/LEGACY_HAUSDORFF_TEST
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+ $CUSPATIAL_HOME /cpp/build/gtests/POINT_IN_POLYGON_TEST
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+ python python/cuspatial/cuspatial/tests/legacy/test_hausdorff_distance.py
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+ python python/cuspatial/cuspatial/tests/test_pip.py
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+ ```
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- Some other tests involve I/O from data files under $CUSPATIAL_HOME/test_fixtures.
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- For example, $CUSPATIAL_HOME/cpp/build/gtests/SHAPEFILE_READER_TEST requires three
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- pre-generated polygon shapefiles that contain 0, 1 and 2 polygons, respectively. They are available at
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- $CUSPATIAL_HOME/test_fixtures/shapefiles <br >
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+ Some other tests involve I/O from data files under $CUSPATIAL_HOME/test_fixtures.
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+ For example, $CUSPATIAL_HOME/cpp/build/gtests/SHAPEFILE_READER_TEST requires three
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+ pre-generated polygon shapefiles that contain 0, 1 and 2 polygons, respectively. They are available at
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+ $CUSPATIAL_HOME/test_fixtures/shapefiles <br >
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** NOTE:** Currently, cuSpatial supports reading point/polyine/polygon data using
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Structure of Array (SoA) format and a [ shapefile reader] ( ./cpp/src/io/shp )
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