depot/third_party/nixpkgs/pkgs/development/compilers/cmdstan/default.nix
Default email a0cb138ada Project import generated by Copybara.
GitOrigin-RevId: a100acd7bbf105915b0004427802286c37738fef
2023-02-02 18:25:31 +00:00

73 lines
2.2 KiB
Nix

{ lib, stdenv, fetchFromGitHub, stanc, python3, buildPackages, runtimeShell }:
stdenv.mkDerivation rec {
pname = "cmdstan";
version = "2.31.0";
src = fetchFromGitHub {
owner = "stan-dev";
repo = pname;
rev = "v${version}";
fetchSubmodules = true;
sha256 = "sha256-Uh/ZhEnbhQwC8xGFjDzH9No3VRgVbHYk2KoC+e3YhJw=";
};
nativeBuildInputs = [ stanc ];
buildFlags = [ "build" ];
enableParallelBuilding = true;
doCheck = true;
nativeCheckInputs = [ python3 ];
CXXFLAGS = lib.optionalString stdenv.isDarwin "-D_BOOST_LGAMMA";
postPatch = ''
substituteInPlace stan/lib/stan_math/make/libraries \
--replace "/usr/bin/env bash" "bash"
patchShebangs .
'' + lib.optionalString stdenv.isAarch64 ''
sed -z -i "s/TEST(CommandStansummary, check_console_output).*TEST(CommandStansummary, check_csv_output)/TEST(CommandStansummary, check_csv_output)/" \
src/test/interface/stansummary_test.cpp
'';
preConfigure = ''
mkdir -p bin
ln -s ${buildPackages.stanc}/bin/stanc bin/stanc
'';
makeFlags = lib.optional stdenv.isDarwin "arch=${stdenv.hostPlatform.darwinArch}";
checkPhase = ''
./runCmdStanTests.py -j$NIX_BUILD_CORES src/test/interface
'';
installPhase = ''
mkdir -p $out/opt $out/bin
cp -r . $out/opt/cmdstan
ln -s $out/opt/cmdstan/bin/stanc $out/bin/stanc
ln -s $out/opt/cmdstan/bin/stansummary $out/bin/stansummary
cat > $out/bin/stan <<EOF
#!${runtimeShell}
make -C $out/opt/cmdstan "\$(realpath "\$1")"
EOF
chmod a+x $out/bin/stan
'';
# Hack to ensure that patchelf --shrink-rpath get rids of a $TMPDIR reference.
preFixup = "rm -rf stan";
meta = with lib; {
description = "Command-line interface to Stan";
longDescription = ''
Stan is a probabilistic programming language implementing full Bayesian
statistical inference with MCMC sampling (NUTS, HMC), approximate Bayesian
inference with Variational inference (ADVI) and penalized maximum
likelihood estimation with Optimization (L-BFGS).
'';
homepage = "https://mc-stan.org/interfaces/cmdstan.html";
license = licenses.bsd3;
maintainers = with maintainers; [ wegank ];
platforms = platforms.unix;
};
}