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Remove gpuCI scripts. #904

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merged 3 commits into from
Feb 10, 2023
Merged

Remove gpuCI scripts. #904

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cad980f
Remove gpuCI scripts.
bdice Feb 6, 2023
fb7d46b
Update README.
bdice Feb 6, 2023
8869c54
Merge branch 'branch-23.04' into remove-gpuci-scripts
ajschmidt8 Feb 10, 2023
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Update README.
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@bdice
bdice committed Feb 6, 2023
commit fb7d46b7f8df09703992e8242181577e2d12088c
10 changes: 4 additions & 6 deletions README.md
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# <div align="left"><img src="https://rapids.ai/assets/images/rapids_logo.png" width="90px"/>&nbsp;cuSpatial - GPU-Accelerated Spatial and Trajectory Data Management and Analytics Library</div>

[![Build Status](https://gpuci.gpuopenanalytics.com/job/rapidsai/job/gpuci/job/cuspatial/job/branches/job/cuspatial-branch-pipeline/badge/icon)](https://gpuci.gpuopenanalytics.com/job/rapidsai/job/gpuci/job/cuspatial/job/branches/job/cuspatial-branch-pipeline/)

**NOTE:** cuSpatial depends on [cuDF](https://github.com/rapidsai/cudf) and
[RMM](https://github.com/rapidsai/rmm) from [RAPIDS](https://rapids.ai/).

Expand Down Expand Up @@ -59,7 +57,7 @@ git clone https://github.com/rapidsai/cuspatial.git $CUSPATIAL_HOME
2. clone the cuSpatial repo

```shell
conda env update --file conda/environments/all_cuda-115_arch-x86_64.yaml
conda env update --file conda/environments/all_cuda-115_arch-x86_64.yaml
```

### Build and install cuSpatial
Expand Down Expand Up @@ -87,10 +85,10 @@ conda env update --file conda/environments/all_cuda-115_arch-x86_64.yaml
pre-generated polygon shapefiles that contain 0, 1 and 2 polygons, respectively. They are available at
`$CUSPATIAL_HOME/test_fixtures/shapefiles` <br>

**NOTE:** Currently, cuSpatial supports reading point/polyine/polygon data using
**NOTE:** Currently, cuSpatial supports reading point/polyline/polygon data using
Structure of Array (SoA) format and a [shapefile reader](./cpp/src/io/shp)
to read polygon data from a shapefile.
Alternatively, python users can read any point/polyine/polygon data using
Alternatively, python users can read any point/polyline/polygon data using
existing python packages, e.g., [Shapely](https://pypi.org/project/Shapely/)
and [Fiona](https://github.com/Toblerity/Fiona),to generate numpy arrays and feed them to
[cuSpatial python APIs](https://docs.rapids.ai/api/cuspatial/stable/).
[cuSpatial Python APIs](https://docs.rapids.ai/api/cuspatial/stable/).