Add Rosetta v3.15 for x86 and ARM
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# Rosetta
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The Rosetta software suite includes algorithms for computational modeling and analysis of protein structures. It has enabled notable scientific advances in computational biology, including de novo protein design, enzyme design, ligand docking, and structure prediction of biological macromolecules and macromolecular complexes.
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https://github.com/RosettaCommons/rosetta
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Executable
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#!/usr/bin/env modbuild
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pbuild::configure() {
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:
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}
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pbuild::compile() {
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cd "$SRC_DIR/main/source" || exit 1
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./scons.py -j10 mode=release bin
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}
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pbuild::install() {
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# Copy the contents of the source code into <PREFIX>
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cp -r "$SRC_DIR/main/"* "$PREFIX/"
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# Ensure target directory exists
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mkdir -p "$PREFIX/bin"
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# Copy compiled binaries to the installation directory
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install -m 755 "$SRC_DIR/main/source/bin/"* "$PREFIX/bin/"
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}
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---
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# yamllint disable rule:line-length
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format: 1
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Rosetta:
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defaults:
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group: MX
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overlay: base
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relstage: unstable
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urls:
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- url: https://downloads.rosettacommons.org/downloads/academic/${V_PKG}/rosetta_source_${V_PKG}_bundle.tar.bz2
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shasums:
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rosetta_source_3.15_bundle.tar.bz2: ac4665fb0173ac1e1ed060d4a894964d14a32aba49e3ee2f3f50e83c26ba0fb1
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versions:
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3.15:
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variants:
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- overlay: base
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systems: [.*.merlin7.psi.ch]
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target_cpus: [x86_64]
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relstage: unstable
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build_requires:
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- gcc/12.3.0
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- Python/3.9.21
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runtime_deps:
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- gcc/12.3.0
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- Python/3.9.21
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- overlay: base
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target_cpus: [aarch64]
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systems: [gpu0.*.merlin7.psi.ch]
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relstage: unstable
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build_requires:
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- gcc/12.3.0
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- Python/3.9.21
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runtime_deps:
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- gcc/12.3.0
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- Python/3.9.21
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#%Module1.0
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module-whatis "The Rosetta software suite includes algorithms for computational modeling and analysis of protein structures"
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module-url "https://github.com/RosettaCommons/rosetta"
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module-license "Rosetta Software Non-Commercial License Agreement (https://github.com/RosettaCommons/rosetta?tab=License-1-ov-file)"
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module-maintainer "João Pedro Agostinho de Sousa <joao.agostinho-de-sousa@psi.ch>"
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module-help "
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The Rosetta software suite includes algorithms for computational modeling and
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analysis of protein structures. It has enabled notable scientific advances in
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computational biology, including de novo protein design, enzyme design, ligand
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docking, and structure prediction of biological macromolecules and
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macromolecular complexes.
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"
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