napf - nanoflann wrappers for python and maybe fortran
python
As nanoflann offers template classes, separate classes are implemented in napf for each {datatype, distance metric}. All the search functions are equipped with multi-thread execution. Uses numpy.ndarray for data input and output.
Currently, the combinations of following options are supported:
data type: {double, float, int, long} (corresponds to {np.float64, np.float32, np.int32, np.int64})distance metric: {L1, L2} Note that functions return squared distances, when you use the L2 metric.
quick start
install with pip:
pip install --upgrade pip
pip install napf
Note: in case your system requires a dynamic build, you need a c++11 compatible c++ compiler. To make sure a correct compiler is chosen, set export CC=<your-c-compiler> CXX=<your-c++-compiler>
import napf
import numpy as np
data = <data in 2D array>
queries = <query points in 2D array>
kdt = napf.KDT(tree_data=data, metric=1)
distances, indices = kdt.knn_search(
queries=queries,
kneighbors=3,
nthread=4,
)
...
fortran
If you need fortran bindings, please let us know by creating an issue.
Documentation
This package uses a sphinx based documentation. An online version of the documentation can be found at napf - documentation.
If you want to build the documentation yourself use the following commands in the package root directory.
pip install -r ./docs/requirements.txt
sphinx-build -W -b html docs/source docs/build
You will find the documentation in the docs/build folder.
1 maintainer
Metadata
1 maintainer
Release files for napf 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| napf-0.1.0.tar.gz | 594.9 kB | Without provenance | Details |
Built distributions (wheels)
Total release size: 18.5 MB
Release files / napf-0.1.0.tar.gz
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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Release files / napf-0.1.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
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Yes |
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twine/5.1.0 CPython/3.12.4
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp39-cp39-macosx_11_0_arm64.whl
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp39-cp39-macosx_10_9_x86_64.whl
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Yes |
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Release files / napf-0.1.0-cp38-cp38-win_amd64.whl
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Yes |
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp38-cp38-win32.whl
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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Yes |
| Uploaded via |
twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp38-cp38-macosx_11_0_arm64.whl
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp38-cp38-macosx_10_9_x86_64.whl
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Yes |
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp37-cp37m-win_amd64.whl
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp37-cp37m-win32.whl
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Yes |
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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Yes |
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
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Yes |
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twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
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Yes |
| Uploaded via |
twine/5.1.0 CPython/3.12.4
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Release files / napf-0.1.0-cp37-cp37m-macosx_10_9_x86_64.whl
| Download URL | napf-0.1.0-cp37-cp37m-macosx_10_9_x86_64.whl |
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twine/5.1.0 CPython/3.12.4
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Security for napf 0.1.0
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