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{ lib
, stdenv
, fetchFromGitHub
, cmake
, buildExamples ? false
}:
stdenv.mkDerivation (finalAttrs: {
version = "1.5.5";
pname = "nanoflann";
src = fetchFromGitHub {
owner = "jlblancoc";
repo = "nanoflann";
rev = "v${finalAttrs.version}";
hash = "sha256-a1XX1tvXfrPCar9EGMXzxLg2bXJaK85t2Bd8CworwFk=";
};
nativeBuildInputs = [ cmake ];
cmakeFlags = [
(lib.cmakeBool "BUILD_EXAMPLES" buildExamples)
];
doCheck = true;
checkTarget = "test";
meta = {
homepage = "https://github.com/jlblancoc/nanoflann";
description = "Header only C++ library for approximate nearest neighbor search";
longDescription = ''
nanoflann is a C++11 header-only library for building KD-Trees of datasets
with different topologies: R2, R3 (point clouds), SO(2) and SO(3) (2D and
3D rotation groups). No support for approximate NN is provided. nanoflann
does not require compiling or installing. You just need to #include
<nanoflann.hpp> in your code.
This library is a fork of the flann library by Marius Muja and David
G. Lowe, and born as a child project of MRPT. Following the original
license terms, nanoflann is distributed under the BSD license. Please, for
bugs use the issues button or fork and open a pull request.
'';
changelog = "https://github.com/jlblancoc/nanoflann/blob/v${finalAttrs.version}/CHANGELOG.md";
license = lib.licenses.bsd2;
maintainers = [ lib.maintainers.AndersonTorres ];
platforms = lib.platforms.unix;
};
})
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