| Port details |
- py-pykdtree Fast kd-tree implementation with OpenMP-enabled queries
- 1.3.12 devel
 =0      1.3.11Version of this port present on the latest quarterly branch. - Maintainer: sunpoet@FreeBSD.org
- Port Added: 2023-08-21 17:15:27
- Last Update: 2024-04-20 18:28:24
- Commit Hash: 10127c6
- Also Listed In: python
- License: LGPL3
- WWW:
- https://github.com/storpipfugl/pykdtree
- Description:
- 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.
  ¦  ¦  ¦  ¦ 
- Manual pages:
- FreshPorts has no man page information for this port.
- pkg-plist: as obtained via:
make generate-plist - There is no configure plist information for this port.
- Dependency lines:
-
- ${PYTHON_PKGNAMEPREFIX}pykdtree>0:devel/py-pykdtree@${PY_FLAVOR}
- To install the port:
- cd /usr/ports/devel/py-pykdtree/ && make install clean
- To add the package, run one of these commands:
- pkg install devel/py-pykdtree
- pkg install py39-pykdtree
NOTE: If this package has multiple flavors (see below), then use one of them instead of the name specified above.
NOTE: This is a Python port. Instead of py39-pykdtree listed in the above command, you can pick from the names under the Packages section.- PKGNAME: py39-pykdtree
- Package flavors (<flavor>: <package>)
- distinfo:
- TIMESTAMP = 1713624700
SHA256 (pykdtree-1.3.12.tar.gz) = cc20b2a67c64056485a314d2c2b6dba354af7ee1c8fb8dae1be6f2936a374341
SIZE (pykdtree-1.3.12.tar.gz) = 25065
Packages (timestamps in pop-ups are UTC):
- Dependencies
- NOTE: FreshPorts displays only information on required and default dependencies. Optional dependencies are not covered.
- Build dependencies:
-
- py39-cython3>=0 : lang/cython3@py39
- py39-numpy>=0,1 : math/py-numpy@py39
- py39-setuptools>=0 : devel/py-setuptools@py39
- py39-wheel>=0 : devel/py-wheel@py39
- python3.9 : lang/python39
- py39-build>=0 : devel/py-build@py39
- py39-installer>=0 : devel/py-installer@py39
- Test dependencies:
-
- python3.9 : lang/python39
- Runtime dependencies:
-
- py39-numpy>=0,1 : math/py-numpy@py39
- python3.9 : lang/python39
- There are no ports dependent upon this port
Configuration Options:- No options to configure
- Options name:
- devel_py-pykdtree
- USES:
- python:3.9+
- FreshPorts was unable to extract/find any pkg message
- Master Sites:
|
Number of commits found: 7
| Commit History - (may be incomplete: for full details, see links to repositories near top of page) |
| Commit | Credits | Log message |
|---|
1.3.12
20 Apr 2024 18:28:24
 |
Po-Chuan Hsieh (sunpoet) |
devel/py-pykdtree: Update to 1.3.12
Changes: https://github.com/storpipfugl/pykdtree/releases |
1.3.11
09 Mar 2024 14:06:03
|
Po-Chuan Hsieh (sunpoet) |
devel/py-pykdtree: Update to 1.3.11
Changes: https://github.com/storpipfugl/pykdtree/releases |
1.3.10
21 Feb 2024 15:07:42
|
Po-Chuan Hsieh (sunpoet) |
devel/py-pykdtree: Fix build with cython 0.29.37+ |
1.3.10
17 Feb 2024 06:05:56
|
Muhammad Moinur Rahman (bofh) |
devel/py-pykdtree: mark BROKEN
Backend subprocess exited when trying to invoke build_wheel |
1.3.10
01 Dec 2023 22:11:44
|
Po-Chuan Hsieh (sunpoet) |
devel/py-pykdtree: Update to 1.3.10
- Convert to USE_PYTHON=pep517
Changes: https://github.com/storpipfugl/pykdtree/releases |
1.3.9
11 Oct 2023 12:58:00
|
Po-Chuan Hsieh (sunpoet) |
devel/py-pykdtree: Update to 1.3.9
Changes: https://github.com/storpipfugl/pykdtree/releases |
1.3.7.post0
21 Aug 2023 17:01:58
|
Po-Chuan Hsieh (sunpoet) |
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. |
Number of commits found: 7
|
As an Amazon Associate I earn from qualifying purchases.