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| author | Po-Chuan Hsieh <sunpoet@FreeBSD.org> | 2023-08-21 16:51:54 +0000 |
|---|---|---|
| committer | Po-Chuan Hsieh <sunpoet@FreeBSD.org> | 2023-08-21 17:01:58 +0000 |
| commit | 7b98bdd020b1fa27dd7273303461332eb3010682 (patch) | |
| tree | 3143d146f5bc1e5f9990c9a1d4184277845d4d38 | |
| parent | 664ad19ced52ff61f57992d6e661a807e60b6a69 (diff) | |
| download | ports-7b98bdd020b1fa27dd7273303461332eb3010682.tar.gz ports-7b98bdd020b1fa27dd7273303461332eb3010682.zip | |
devel/py-pykdtree: Add py-pykdtree 1.3.7.post0
pykdtree is a kd-tree implementation for fast nearest neighbour search in
Python. The aim is to be the fastest implementation around for common use cases
(low dimensions and low number of neighbours) for both tree construction and
queries.
The implementation is based on scipy.spatial.cKDTree and libANN by combining the
best features from both and focus on implementation efficiency.
The interface is similar to that of scipy.spatial.cKDTree except only Euclidean
distance measure is supported.
Queries are optionally multithreaded using OpenMP.
| -rw-r--r-- | devel/Makefile | 1 | ||||
| -rw-r--r-- | devel/py-pykdtree/Makefile | 23 | ||||
| -rw-r--r-- | devel/py-pykdtree/distinfo | 3 | ||||
| -rw-r--r-- | devel/py-pykdtree/pkg-descr | 12 |
4 files changed, 39 insertions, 0 deletions
diff --git a/devel/Makefile b/devel/Makefile index 998961787754..8ed8329ce0d4 100644 --- a/devel/Makefile +++ b/devel/Makefile @@ -5282,6 +5282,7 @@ SUBDIR += py-pyintelowl SUBDIR += py-pyjq SUBDIR += py-pyjsparser + SUBDIR += py-pykdtree SUBDIR += py-pylama SUBDIR += py-pylev SUBDIR += py-pylibsrtp diff --git a/devel/py-pykdtree/Makefile b/devel/py-pykdtree/Makefile new file mode 100644 index 000000000000..152d9fb520d2 --- /dev/null +++ b/devel/py-pykdtree/Makefile @@ -0,0 +1,23 @@ +PORTNAME= pykdtree +PORTVERSION= 1.3.7.post0 +CATEGORIES= devel python +MASTER_SITES= PYPI +PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} + +MAINTAINER= sunpoet@FreeBSD.org +COMMENT= Fast kd-tree implementation with OpenMP-enabled queries +WWW= https://github.com/storpipfugl/pykdtree + +LICENSE= LGPL3 +LICENSE_FILE= ${WRKSRC}/LICENSE.txt + +BUILD_DEPENDS= ${PYTHON_PKGNAMEPREFIX}numpy>=0,1:math/py-numpy@${PY_FLAVOR} +RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}numpy>=0,1:math/py-numpy@${PY_FLAVOR} + +USES= python +USE_PYTHON= autoplist concurrent distutils + +post-install: + ${FIND} ${STAGEDIR}${PYTHON_SITELIBDIR} -name '*.so' -exec ${STRIP_CMD} {} + + +.include <bsd.port.mk> diff --git a/devel/py-pykdtree/distinfo b/devel/py-pykdtree/distinfo new file mode 100644 index 000000000000..16b8c479e9fc --- /dev/null +++ b/devel/py-pykdtree/distinfo @@ -0,0 +1,3 @@ +TIMESTAMP = 1692211615 +SHA256 (pykdtree-1.3.7.post0.tar.gz) = eca1d61d33db621ef8027eb691ae88db9c65d196aba4b2cc90c190cb90bb508e +SIZE (pykdtree-1.3.7.post0.tar.gz) = 84509 diff --git a/devel/py-pykdtree/pkg-descr b/devel/py-pykdtree/pkg-descr new file mode 100644 index 000000000000..aaae7459c719 --- /dev/null +++ b/devel/py-pykdtree/pkg-descr @@ -0,0 +1,12 @@ +pykdtree is a kd-tree implementation for fast nearest neighbour search in +Python. The aim is to be the fastest implementation around for common use cases +(low dimensions and low number of neighbours) for both tree construction and +queries. + +The implementation is based on scipy.spatial.cKDTree and libANN by combining the +best features from both and focus on implementation efficiency. + +The interface is similar to that of scipy.spatial.cKDTree except only Euclidean +distance measure is supported. + +Queries are optionally multithreaded using OpenMP. |