scikitplot.cexternals

C-External libraries vendored for high-performance extensions for Scikit-Plots.

This package contains optimized C/C++ and template-based libraries that are bundled with Scikit-Plots to provide fast numerical, geometric, and algorithmic capabilities used in advanced visualization and machine learning workflows.

These modules wrap native backends (e.g. Annoy, NumCpp, F2PY-generated code) through Python extension interfaces to ensure consistent performance and availability across environments, without relying on separate system installs.

User guide. See the C-Externals (experimental) section for further details.

Spotify ANNoy as submodule.

High-level Python interface for the C++ Annoy backend.

Spotify Annoy (Approximate Nearest Neighbors Oh Yeah).

Exports:

• Annoy → low-level C-extension type (stable)

• AnnoyBase → alias of annoylib.Annoy Index

• AnnoyIndex → alias of annoylib.Annoy Index

See also

• ANNoy

• spotify/annoy

• https://pypi.org/project/annoy

Note

• https://www.sandgarden.com/learn/faiss

• https://www.sandgarden.com/learn/annoy-approximate-nearest-neighbors-oh-yeah

See also

• https://en.wikipedia.org/wiki/Nearest_neighbor_search

• https://www.researchgate.net/publication/386374637_Optimizing_Domain-Specific_Image_Retrieval_A_Benchmark_of_FAISS_and_Annoy_with_Fine-Tuned_Features

• https://www.researchgate.net/publication/363234433_Analysis_of_Image_Similarity_Using_CNN_and_ANNOY

• https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/XboxInnerProduct.pdf

• https://link.springer.com/chapter/10.1007/978-981-97-7831-7_2

References

[1]

Spotify AB. (2013, Feb 20). “Approximate Nearest Neighbors Oh Yeah” Github. https://pypi.org/project/annoy

Examples

>>> # from annoy import AnnoyIndex
>>> from scikitplot.annoy import Annoy, AnnoyBase, AnnoyIndex, Index
>>> f = 40  # vector dimensionality
>>> t = AnnoyIndex(f, "angular")  # Length of item vector and metric
>>> t.add_item(0, [1] * f)
>>> t.build(10)  # Build 10 trees
>>> t.get_nns_by_item(0, 1)  # Find nearest neighbor

User guide. See the ANNoy (experimental) section for further details.

_annoy	High-level Python interface for the C++ Annoy backend.
_annoy.Annoy	Compiled with GCC/Clang.
_annoy.AnnoyBase	alias of Annoy

astropy stats as submodule.

Astropy is a package intended to contain core functionality and some common tools needed for performing astronomy and astrophysics research with Python. It also provides an index for other astronomy packages and tools for managing them.

Documentation is available in the docstrings and online at https://www.astropy.org/.

User guide. See the Astropy (experimental) section for further details.

_astropy	Astropy is a package intended to contain core functionality and some common tools needed for performing astronomy and astrophysics research with Python.
_astropy.stats	This subpackage contains statistical tools provided for or used by Astropy.

NumPy f2py as submodule.

Fortran to Python Interface Generator.

Copyright 1999 – 2011 Pearu Peterson all rights reserved. Copyright 2011 – present NumPy Developers. Permission to use, modify, and distribute this software is given under the terms of the NumPy License.

NO WARRANTY IS EXPRESSED OR IMPLIED. USE AT YOUR OWN RISK.

See also

• https://stdlib.fortran-lang.org/lists/modules.html

• https://numpy.org/doc/stable/f2py/index.html

• https://scipy.github.io/old-wiki/pages/Cookbook/f2py_and_NumPy.html

• https://scipy-cookbook.readthedocs.io/items/F2Py.html

• https://scipy-cookbook.readthedocs.io/items/idx_interfacing_with_other_languages.html

User guide. See the f2py (experimental) section for further details.

_f2py	Fortran to Python Interface Generator.
_f2py.get_include	Return the directory that contains the fortranobject.c and .h files.

NumCpp header’s as submodule.

NumCpp: A Templatized Header Only C++ Library with Implementation of the Python NumPy-Compatible API.

See also

• dpilger26/NumCpp

• Author: David Pilger

• License: MIT

Compilers:

• C++ Standards: C++17 C++20 C++23

• MSVC Visual Studio: 2022

• GCC GNU: 13.3, 14.2

• Clang LLVM: 18, 19

• Boost Versions: 1.73+

User guide. See the NumCpp Header Only C++ (experimental) section for further details.

_numcpp

NumCpp: A Templatized Header Only C++ Library with Implementation of the Python NumPy-Compatible API.