forked from mirrors/nixpkgs
4ea8f051ac
Co-Authored-By: Daniel Schaefer <git@danielschaefer.me>
79 lines
2.5 KiB
Nix
79 lines
2.5 KiB
Nix
{ stdenv
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, fetchzip
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, fetchFromGitHub
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, cmake
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, fftw
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, fftwFloat
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, enablePython ? false
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, pythonPackages
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, llvmPackages
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}:
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let
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# CMake recipes are needed to build galario
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# Build process would usually download them
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great-cmake-cookoff = fetchzip {
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url = "https://github.com/UCL/GreatCMakeCookOff/archive/v2.1.9.tar.gz";
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sha256 = "1yd53b5gx38g6f44jmjk4lc4igs3p25z6616hfb7aq79ly01q0w2";
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};
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in
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stdenv.mkDerivation rec {
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pname = "galario";
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version = "1.2.1";
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src = fetchFromGitHub {
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owner = "mtazzari";
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repo = pname;
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rev = "v${version}";
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sha256 = "1akz7md7ly16a89zr880c265habakqdg9sj8iil90klqa0i21w6g";
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};
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nativeBuildInputs = [ cmake ];
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buildInputs = [ fftw fftwFloat ]
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++ stdenv.lib.optional enablePython pythonPackages.python
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++ stdenv.lib.optional stdenv.isDarwin llvmPackages.openmp
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;
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propagatedBuildInputs = stdenv.lib.optional enablePython [
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pythonPackages.numpy
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pythonPackages.cython
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pythonPackages.pytest
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];
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checkInputs = stdenv.lib.optional enablePython pythonPackages.scipy;
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preConfigure = ''
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mkdir -p build/external/src
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cp -r ${great-cmake-cookoff} build/external/src/GreatCMakeCookOff
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chmod -R 777 build/external/src/GreatCMakeCookOff
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'';
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preCheck = ''
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${if stdenv.isDarwin then "export DYLD_LIBRARY_PATH=$(pwd)/src/" else "export LD_LIBRARY_PATH=$(pwd)/src/"}
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${if enablePython then "sed -i -e 's|^#!.*|#!${stdenv.shell}|' python/py.test.sh" else ""}
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'';
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doCheck = true;
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postInstall = stdenv.lib.optionalString (stdenv.isDarwin && enablePython) ''
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install_name_tool -change libgalario.dylib $out/lib/libgalario.dylib $out/lib/python*/site-packages/galario/double/libcommon.so
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install_name_tool -change libgalario_single.dylib $out/lib/libgalario_single.dylib $out/lib/python*/site-packages/galario/single/libcommon.so
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'';
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meta = with stdenv.lib; {
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description = "GPU Accelerated Library for Analysing Radio Interferometer Observations";
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longDescription = ''
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Galario is a library that exploits the computing power of modern
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graphic cards (GPUs) to accelerate the comparison of model
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predictions to radio interferometer observations. Namely, it
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speeds up the computation of the synthetic visibilities given a
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model image (or an axisymmetric brightness profile) and their
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comparison to the observations.
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'';
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homepage = "https://mtazzari.github.io/galario/";
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license = licenses.lgpl3;
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maintainers = [ maintainers.smaret ];
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platforms = platforms.all;
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};
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}
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