33afbf39f6
checkInputs used to be added to nativeBuildInputs. Now we have nativeCheckInputs to do that instead. Doing this treewide change allows to keep hashes identical to before the introduction of nativeCheckInputs.
74 lines
2.2 KiB
Nix
74 lines
2.2 KiB
Nix
{ lib, stdenv, fetchFromGitHub, stanc, python3, buildPackages, runtimeShell }:
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stdenv.mkDerivation rec {
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pname = "cmdstan";
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version = "2.31.0";
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src = fetchFromGitHub {
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owner = "stan-dev";
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repo = pname;
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rev = "v${version}";
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fetchSubmodules = true;
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sha256 = "sha256-Uh/ZhEnbhQwC8xGFjDzH9No3VRgVbHYk2KoC+e3YhJw=";
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};
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nativeBuildInputs = [ stanc ];
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buildFlags = [ "build" ];
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enableParallelBuilding = true;
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doCheck = true;
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nativeCheckInputs = [ python3 ];
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CXXFLAGS = lib.optionalString stdenv.isDarwin "-D_BOOST_LGAMMA";
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postPatch = ''
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substituteInPlace stan/lib/stan_math/make/libraries \
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--replace "/usr/bin/env bash" "bash"
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patchShebangs .
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'' + lib.optionalString stdenv.isAarch64 ''
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sed -z -i "s/TEST(CommandStansummary, check_console_output).*TEST(CommandStansummary, check_csv_output)/TEST(CommandStansummary, check_csv_output)/" \
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src/test/interface/stansummary_test.cpp
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'';
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preConfigure = ''
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mkdir -p bin
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ln -s ${buildPackages.stanc}/bin/stanc bin/stanc
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'';
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makeFlags = lib.optional stdenv.isDarwin "arch=${stdenv.hostPlatform.darwinArch}";
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checkPhase = ''
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./runCmdStanTests.py -j$NIX_BUILD_CORES src/test/interface
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'';
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installPhase = ''
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mkdir -p $out/opt $out/bin
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cp -r . $out/opt/cmdstan
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ln -s $out/opt/cmdstan/bin/stanc $out/bin/stanc
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ln -s $out/opt/cmdstan/bin/stansummary $out/bin/stansummary
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cat > $out/bin/stan <<EOF
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#!${runtimeShell}
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make -C $out/opt/cmdstan "\$(realpath "\$1")"
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EOF
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chmod a+x $out/bin/stan
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'';
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# Hack to ensure that patchelf --shrink-rpath get rids of a $TMPDIR reference.
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preFixup = "rm -rf stan";
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meta = with lib; {
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description = "Command-line interface to Stan";
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longDescription = ''
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Stan is a probabilistic programming language implementing full Bayesian
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statistical inference with MCMC sampling (NUTS, HMC), approximate Bayesian
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inference with Variational inference (ADVI) and penalized maximum
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likelihood estimation with Optimization (L-BFGS).
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'';
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homepage = "https://mc-stan.org/interfaces/cmdstan.html";
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license = licenses.bsd3;
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maintainers = with maintainers; [ wegank ];
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platforms = platforms.unix;
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};
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}
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