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f0e64ce16f
Manual migration for the sake of by-name migration is no longer discouraged since #340235.
49 lines
1.5 KiB
Nix
49 lines
1.5 KiB
Nix
{ lib
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, stdenv
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, fetchFromGitHub
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, cmake
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, buildExamples ? false
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}:
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stdenv.mkDerivation (finalAttrs: {
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version = "1.6.1";
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pname = "nanoflann";
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src = fetchFromGitHub {
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owner = "jlblancoc";
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repo = "nanoflann";
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rev = "v${finalAttrs.version}";
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hash = "sha256-likFHzaP/1yYfr6+rDWM2+YEKOk5G5P8UFC3xb2bEOo=";
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};
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nativeBuildInputs = [ cmake ];
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cmakeFlags = [
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(lib.cmakeBool "BUILD_EXAMPLES" buildExamples)
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];
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doCheck = true;
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checkTarget = "test";
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meta = {
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homepage = "https://github.com/jlblancoc/nanoflann";
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description = "Header only C++ library for approximate nearest neighbor search";
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longDescription = ''
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nanoflann is a C++11 header-only library for building KD-Trees of datasets
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with different topologies: R2, R3 (point clouds), SO(2) and SO(3) (2D and
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3D rotation groups). No support for approximate NN is provided. nanoflann
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does not require compiling or installing. You just need to #include
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<nanoflann.hpp> in your code.
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This library is a fork of the flann library by Marius Muja and David
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G. Lowe, and born as a child project of MRPT. Following the original
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license terms, nanoflann is distributed under the BSD license. Please, for
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bugs use the issues button or fork and open a pull request.
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'';
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changelog = "https://github.com/jlblancoc/nanoflann/blob/v${finalAttrs.version}/CHANGELOG.md";
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license = lib.licenses.bsd2;
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maintainers = [ lib.maintainers.AndersonTorres ];
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platforms = lib.platforms.unix;
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};
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})
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