Merge pull request #1 from peastman/ljpme

Cleanup to LJ PME code

.travis.yml

@@ -109,7 +109,7 @@ before_install:
       sudo easy_install pytest;
     fi
   - if [[ "$OPENCL" == "true" ]]; then
-      wget https://jenkins.choderalab.org/userContent/AMD-APP-SDKInstaller-v3.0.130.135-GA-linux64.tar.bz2;
+      wget http://s3.amazonaws.com/omnia-ci/AMD-APP-SDKInstaller-v3.0.130.135-GA-linux64.tar.bz2;
       tar -xjf AMD-APP-SDK*.tar.bz2;
       AMDAPPSDK=${HOME}/AMDAPPSDK;
       export OPENCL_VENDOR_PATH=${AMDAPPSDK}/etc/OpenCL/vendors;
@@ -183,9 +183,9 @@ script:
 deploy:
   - provider: s3
     access_key_id:
-      secure: "AjE3nuj6kVuf21mOf0aZydW/3S/uCWsaoXC/huRxkxrmsNlnHBNGHZ9N48san1IxZAQM5pyaf7Yo9gkHur9obgq+e3lNgGvPp2mfkNXtLYcLJ46JF4kYliAtutjLWskrLg25Gu3xzF4EQkqSe0Le/oWldWWbTgvvH+KRq/vTHzI="
+      secure: "OEY0sp5FlM4kixFNVAktN6YHwKm5ieMswWCHj3MU+rWsAeGCULl/0kyKTfwCPknVlQv+SXBaPP3I4m1fv9FwHt0bbwy5EfmO4crrW8cE4ofq4vnwHi9UG77oEKKRrbxFUZD1y7ywI2W9SyVI6qfggZlJowRy9GV9Lin5vGzhqsw="
     secret_access_key:
-      secure: "ISDQNSG2t0666PULtffo4wsKLFdu622EzuZxmiTxvLkjQGQlqm5+qn1Gd5UMLk7Ts2E0psdnmSrf6LVVCfrrQO/hcZHiJw3ZslMPDBBlRr8Epwdldn98ULhVoyQKtjXjCPzroa2UZCl1RFs4Nwb/VdDlI490XV0Lp4Woj1AT8tY="
+      secure: "P7DOYn77bH5Gg1obIwCxanhH0Kgh22Pv1pCGvmI6gHXOE1dxf5pnCSQGFKO6g1K6eaN5TbTjh+BmMXmxgkqByvQ4uZtkTGlPq3HI9YeRjZE2H7bRpIYjXXRwA1RMOA3ofLDw1FXNmwMo8BtRIl4jljR5Iw5rytUZmLlk3zgtcr4="
     bucket: "docs.openmm.org"
     skip_cleanup: true
     region: us-west-1

CMakeLists.txt

@@ -174,7 +174,7 @@ ENDIF (NOT CMAKE_CXX_FLAGS_RELEASE)
 
 SET(OPENMM_LIBRARY_NAME OpenMM)
 SET(OPENMM_MAJOR_VERSION 7)
-SET(OPENMM_MINOR_VERSION 0)
+SET(OPENMM_MINOR_VERSION 1)
 SET(OPENMM_BUILD_VERSION 0)
 
 SET(OPENMM_COPYRIGHT_YEARS "2008-2015")

README.md

+[![Build Status](https://travis-ci.org/pandegroup/openmm.svg?branch=master)](https://travis-ci.org/pandegroup/openmm)
+[![Anaconda Cloud Badge](https://anaconda.org/omnia/openmm/badges/downloads.svg)](https://anaconda.org/omnia/openmm)
+
 ## OpenMM: A High Performance Molecular Dynamics Library
 
 Introduction
@@ -10,15 +13,3 @@ Getting Help
 ------------
 
 Need Help? Check out the [documentation](http://docs.openmm.org/) and [discussion forums](https://simtk.org/forums/viewforum.php?f=161).
-
-[C++ API Reference](http://docs.openmm.org/6.3.0/api-c++/namespaceOpenMM.html)
-
-[Python API Reference](http://docs.openmm.org/6.3.0/api-python/annotated.html)
-
-Badges
-------
-* Travis CI `linux` and `osx` integration tests:
-  * GitHub master [![Build Status](https://travis-ci.org/pandegroup/openmm.svg?branch=master)](https://travis-ci.org/pandegroup/openmm)
-  * `openmm-dev` recipe [![Build Status](https://travis-ci.org/omnia-md/conda-dev-recipes.svg?branch=master)](https://travis-ci.org/omnia-md/conda-dev-recipes)
-* Anaconda Cloud `openmm` conda release: [![Binstar `openmm` conda release](https://anaconda.org/omnia/openmm/badges/version.svg)](https://anaconda.org/omnia/openmm)
-* Anaconda Cloud `openmm-dev` conda package: [![Binstar `openmm-dev` conda package](https://anaconda.org/omnia/openmm-dev/badges/version.svg)](https://anaconda.org/omnia/openmm-dev)

devtools/packaging/README.md

+# Packaging OpenMM into ZIP installers
+
+## Source
+
+Start the docker container:
+```bash
+docker run -i -t --rm -v `pwd`:/io jchodera/omnia-build-box:cuda80-amd30-clang38 bash
+```
+Inside the docker container:
+```bash
+# Clone the OpenMM beta or release candidate tag $TAG
+git clone https://github.com/pandegroup/openmm.git
+cd openmm; git checkout $TAG; cd ..
+# Build and package
+source openmm/devtools/packaging/scripts/source/prepare.sh       
+source openmm/devtools/packaging/scripts/source/build.sh
+source openmm/devtools/packaging/scripts/source/package.sh
+# Recover the packages to host directory
+cp packaging/compressed/* /io
+```
+
+## Linux
+
+Start the docker container:
+```bash
+docker run -i -t --rm -v `pwd`:/io jchodera/omnia-build-box:cuda80-amd30-clang38 bash
+```
+Inside the docker container:
+```bash
+# Clone the OpenMM beta or release candidate tag $TAG
+git clone https://github.com/pandegroup/openmm.git
+cd openmm; git checkout $TAG; cd ..
+# Build and package
+source openmm/devtools/packaging/scripts/linux/prepare.sh
+source openmm/devtools/packaging/scripts/linux/build.sh
+source openmm/devtools/packaging/scripts/linux/package.sh
+# Recover the packages to host directory
+cp packaging/compressed/* /io
+```
+
+## OS X
+
+On an `osx` machine with XCode and the OS X 10.9 frameworks installed:
+```bash
+# Clone the OpenMM beta or release candidate tag $TAG
+git clone https://github.com/pandegroup/openmm.git
+cd openmm; git checkout $TAG; cd ..
+# Build and package
+source openmm/devtools/packaging/scripts/osx/prepare.sh
+source openmm/devtools/packaging/scripts/osx/build.sh
+source openmm/devtools/packaging/scripts/osx/package.sh
+```
+

devtools/packaging/scripts/linux/build.sh

@@ -3,6 +3,52 @@
 # Build script for Linux distribution, for use in automated packaging.
 # Note that this must be run from outside the checked-out openmm/ directory.
 
+#
+# For Docker build
+#
+
+# Fix hbb issues.
+# If statements needed because multiple Python versions are built in same docker image.
+if [ ! -e /opt/rh/devtoolset-2/root/usr/lib/gcc/x86_64-redhat-linux ]; then
+    ln -s /opt/rh/devtoolset-2/root/usr/lib/gcc/x86_64-CentOS-linux/ /opt/rh/devtoolset-2/root/usr/lib/gcc/x86_64-redhat-linux
+fi
+if [ ! -e /opt/rh/devtoolset-2/root/usr/include/c++/4.8.2/x86_64-redhat-linux ]; then
+    ln -s /opt/rh/devtoolset-2/root/usr/include/c++/4.8.2/x86_64-CentOS-linux/ /opt/rh/devtoolset-2/root/usr/include/c++/4.8.2/x86_64-redhat-linux
+fi
+
+# Clang paths
+export CLANG_PREFIX="/opt/clang"
+export PATH=$PATH:$CLANG_PREFIX/bin
+
+# enable devtoolset-2
+# will return an error return code because of python 3.x incompatible code, but this error is inconsequential
+#source /opt/rh/devtoolset-2/enable || true
+export PATH=/opt/rh/devtoolset-2/root/usr/bin${PATH:+:${PATH}}
+export MANPATH=/opt/rh/devtoolset-2/root/usr/share/man:$MANPATH
+export INFOPATH=/opt/rh/devtoolset-2/root/usr/share/info${INFOPATH:+:${INFOPATH}}
+export PCP_DIR=/opt/rh/devtoolset-2/root
+# Some perl Ext::MakeMaker versions install things under /usr/lib/perl5
+# even though the system otherwise would go to /usr/lib64/perl5.
+export PERL5LIB=/opt/rh/devtoolset-2/root//usr/lib64/perl5/vendor_perl/5.8.8/x86_64-linux-thread-multi:/opt/rh/devtoolset-2/root/usr/lib/perl5:/opt/rh/devtoolset-2/root//usr/lib/perl5/vendor_perl/5.8.8${PERL5LIB:+:${PERL5LIB}}
+# bz847911 workaround:
+# we need to evaluate rpm's installed run-time % { _libdir }, not rpmbuild time
+# or else /etc/ld.so.conf.d files?
+rpmlibdir=`rpm --eval "%{_libdir}"`
+# bz1017604: On 64-bit hosts, we should include also the 32-bit library path.
+if [ "$rpmlibdir" != "${rpmlibdir/lib64/}" ]; then
+  rpmlibdir32=":/opt/rh/devtoolset-2/root${rpmlibdir/lib64/lib}"
+fi
+export LD_LIBRARY_PATH=/opt/rh/devtoolset-2/root$rpmlibdir$rpmlibdir32${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
+# duplicate python site.py logic for sitepackages
+pythonvers=`python -c 'import sys; print(sys.version[:3])'`
+export PYTHONPATH=/opt/rh/devtoolset-2/root/usr/lib64/python$pythonvers/site-packages:/opt/rh/devtoolset-2/root/usr/lib/python$pythonvers/site-packages${PYTHONPATH:+:${PYTHONPATH}}
+
+# CFLAGS
+export MINIMAL_CFLAGS="-g -O3"
+export CFLAGS="$MINIMAL_CFLAGS"
+export CXXFLAGS="$MINIMAL_CFLAGS"
+export LDFLAGS="$LDPATHFLAGS"
+
 # Set relative workspace path.
 export WORKSPACE=`pwd`
 
@@ -16,23 +62,35 @@ fi
 
 CMAKE_FLAGS="-DCMAKE_INSTALL_PREFIX=$INSTALL"
 
+# Don't build tests
+CMAKE_FLAGS+=" -DBUILD_TESTING=OFF"
+
+# Use clang 3.8.1 inside omnia-build-box docker image
+CMAKE_FLAGS+=" -DCMAKE_C_COMPILER=$CLANG_PREFIX/bin/clang -DCMAKE_CXX_COMPILER=$CLANG_PREFIX/bin/clang++"
+
+# Ensure we build a release
+CMAKE_FLAGS+=" -DCMAKE_BUILD_TYPE=Release"
+
 # setting the rpath so that libOpenMMPME.so finds the right libfftw3
 #CMAKE_FLAGS+=" -DCMAKE_INSTALL_RPATH=.."
-CMAKE_FLAGS+=" -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++"
-CMAKE_FLAGS+=" -DCUDA_CUDART_LIBRARY=/usr/local/cuda-7.5/lib64/libcudart.so"
-CMAKE_FLAGS+=" -DCUDA_NVCC_EXECUTABLE=/usr/local/cuda-7.5/bin/nvcc"
-CMAKE_FLAGS+=" -DCUDA_SDK_ROOT_DIR=/usr/local/cuda-7.5/"
-CMAKE_FLAGS+=" -DCUDA_TOOLKIT_INCLUDE=/usr/local/cuda-7.5/include"
-CMAKE_FLAGS+=" -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-7.5/"
+# Use NVIDIA CUDA 8.0
+CMAKE_FLAGS+=" -DCUDA_CUDART_LIBRARY=/usr/local/cuda-8.0/lib64/libcudart.so"
+CMAKE_FLAGS+=" -DCUDA_NVCC_EXECUTABLE=/usr/local/cuda-8.0/bin/nvcc"
+CMAKE_FLAGS+=" -DCUDA_SDK_ROOT_DIR=/usr/local/cuda-8.0/"
+CMAKE_FLAGS+=" -DCUDA_TOOLKIT_INCLUDE=/usr/local/cuda-8.0/include"
+CMAKE_FLAGS+=" -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-8.0/"
+# Use AMD APP SDK 3.0
 CMAKE_FLAGS+=" -DOPENCL_INCLUDE_DIR=/opt/AMDAPPSDK-3.0/include/"
 CMAKE_FLAGS+=" -DOPENCL_LIBRARY=/opt/AMDAPPSDK-3.0/lib/x86_64/libOpenCL.so"
+# Generate API docs
 CMAKE_FLAGS+=" -DOPENMM_GENERATE_API_DOCS=ON"
-
 # Set location for FFTW3
 PREFIX="$WORKSPACE/miniconda"
 CMAKE_FLAGS+=" -DFFTW_INCLUDES=$PREFIX/include"
 CMAKE_FLAGS+=" -DFFTW_LIBRARY=$PREFIX/lib/libfftw3f.so"
 CMAKE_FLAGS+=" -DFFTW_THREADS_LIBRARY=$PREFIX/lib/libfftw3f_threads.so"
+# Necessary to find GL headers
+CMAKE_FLAGS+=" -DCMAKE_CXX_FLAGS_RELEASE=-I/usr/include/nvidia/"
 
 # Build in subdirectory.
 if [ -e build ]; then
@@ -42,7 +100,14 @@ mkdir build
 cd build
 cmake ../openmm $CMAKE_FLAGS
 make -j4 all install
+
+export CFLAGS="$MINIMAL_CFLAGS"
+export CXXFLAGS="$MINIMAL_CFLAGS"
+export LDFLAGS="$LDPATHFLAGS"
+
 make -j4 PythonInstall C++ApiDocs PythonApiDocs sphinxpdf
 
 # Install.
 make install
+
+cd ..

devtools/packaging/scripts/linux/prepare.sh

@@ -9,14 +9,14 @@ export WORKSPACE=`pwd`
 export VERSION="latest"
 export PLATFORM="Linux"
 export ARCH="x86_64"
-export MINICONDA="Miniconda2-$VERSION-$PLATFORM-$ARCH.sh"
+export MINICONDA="Miniconda3-$VERSION-$PLATFORM-$ARCH.sh"
 if [ -f miniconda ];
 then
    echo "miniconda already exists"
 else
    echo "Downloading miniconda..."
    rm -rf Miniconda-* miniconda ~/.condarc
-   wget --quiet http://repo.continuum.io/miniconda/${MINICONDA}
+   wget --quiet https://repo.continuum.io/miniconda/${MINICONDA}
    bash ${MINICONDA} -b -p miniconda
    PIP_ARGS="-U"
 fi
@@ -24,7 +24,9 @@ fi
 # Add to path.
 export PATH=$WORKSPACE/miniconda/bin:$PATH
 
+# Workaround for missing libgcrypt
+yum install -y libgcrypt
+
 # Ensure configuration is up to date.
 conda config --add channels omnia
 conda install --yes --quiet swig fftw3f pip doxygen sphinx sphinxcontrib-bibtex sphinxcontrib-lunrsearch sphinxcontrib-autodoc_doxygen lxml cmake
-

devtools/packaging/scripts/osx/build.sh

@@ -21,7 +21,7 @@ CMAKE_FLAGS="-DCMAKE_INSTALL_PREFIX=$INSTALL"
 #CMAKE_FLAGS+=" -DCMAKE_INSTALL_RPATH=.."
 CMAKE_FLAGS+=" -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++"
 CMAKE_FLAGS+=" -DCMAKE_OSX_DEPLOYMENT_TARGET=10.9"
-CMAKE_FLAGS+=" -DCMAKE_OSX_SYSROOT=/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk"
+CMAKE_FLAGS+=" -DCMAKE_OSX_SYSROOT=/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.11.sdk"
 CMAKE_FLAGS+=" -DOPENMM_GENERATE_API_DOCS=ON"
 
 # Build in subdirectory.
@@ -43,3 +43,6 @@ make -j4 PythonInstall C++ApiDocs PythonApiDocs sphinxpdf
 
 # Install.
 make install
+
+# Return to directory
+cd $WORKSPACE

devtools/packaging/scripts/osx/prepare.sh

@@ -6,18 +6,18 @@
 export WORKSPACE=`pwd`
 
 # Install miniconda
-export VERSION="Latest"
+export VERSION="latest"
 export PLATFORM="MacOSX"
 export ARCH="x86_64"
-export MINICONDA="Miniconda-$VERSION-$PLATFORM-$ARCH.sh"
-if [ -f miniconda ];
+export MINICONDA="Miniconda3-$VERSION-$PLATFORM-$ARCH.sh"
+if [ -f $WORKSPACE/miniconda ];
 then
    echo "miniconda already exists"
 else
    echo "Downloading miniconda..."
-   rm -rf Miniconda-*
-   wget --quiet http://repo.continuum.io/miniconda/${MINICONDA}
-   bash ${MINICONDA} -b -p miniconda
+   rm -rf $WORKSPACE/Miniconda3-*
+   wget https://repo.continuum.io/miniconda/${MINICONDA}
+   bash ${MINICONDA} -b -p $WORKSPACE/miniconda
    PIP_ARGS="-U"
 fi
 

devtools/packaging/scripts/source/build.sh

@@ -3,6 +3,52 @@
 # Build script for Linux distribution, for use in automated packaging.
 # Note that this must be run from outside the checked-out openmm/ directory.
 
+#
+# For Docker build
+#
+
+# Fix hbb issues.
+# If statements needed because multiple Python versions are built in same docker image.
+if [ ! -e /opt/rh/devtoolset-2/root/usr/lib/gcc/x86_64-redhat-linux ]; then
+    ln -s /opt/rh/devtoolset-2/root/usr/lib/gcc/x86_64-CentOS-linux/ /opt/rh/devtoolset-2/root/usr/lib/gcc/x86_64-redhat-linux
+fi
+if [ ! -e /opt/rh/devtoolset-2/root/usr/include/c++/4.8.2/x86_64-redhat-linux ]; then
+    ln -s /opt/rh/devtoolset-2/root/usr/include/c++/4.8.2/x86_64-CentOS-linux/ /opt/rh/devtoolset-2/root/usr/include/c++/4.8.2/x86_64-redhat-linux
+fi
+
+# Clang paths
+export CLANG_PREFIX="/opt/clang"
+export PATH=$PATH:$CLANG_PREFIX/bin
+
+# enable devtoolset-2
+# will return an error return code because of python 3.x incompatible code, but this error is inconsequential
+#source /opt/rh/devtoolset-2/enable || true
+export PATH=/opt/rh/devtoolset-2/root/usr/bin${PATH:+:${PATH}}
+export MANPATH=/opt/rh/devtoolset-2/root/usr/share/man:$MANPATH
+export INFOPATH=/opt/rh/devtoolset-2/root/usr/share/info${INFOPATH:+:${INFOPATH}}
+export PCP_DIR=/opt/rh/devtoolset-2/root
+# Some perl Ext::MakeMaker versions install things under /usr/lib/perl5
+# even though the system otherwise would go to /usr/lib64/perl5.
+export PERL5LIB=/opt/rh/devtoolset-2/root//usr/lib64/perl5/vendor_perl/5.8.8/x86_64-linux-thread-multi:/opt/rh/devtoolset-2/root/usr/lib/perl5:/opt/rh/devtoolset-2/root//usr/lib/perl5/vendor_perl/5.8.8${PERL5LIB:+:${PERL5LIB}}
+# bz847911 workaround:
+# we need to evaluate rpm's installed run-time % { _libdir }, not rpmbuild time
+# or else /etc/ld.so.conf.d files?
+rpmlibdir=`rpm --eval "%{_libdir}"`
+# bz1017604: On 64-bit hosts, we should include also the 32-bit library path.
+if [ "$rpmlibdir" != "${rpmlibdir/lib64/}" ]; then
+  rpmlibdir32=":/opt/rh/devtoolset-2/root${rpmlibdir/lib64/lib}"
+fi
+export LD_LIBRARY_PATH=/opt/rh/devtoolset-2/root$rpmlibdir$rpmlibdir32${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
+# duplicate python site.py logic for sitepackages
+pythonvers=`python -c 'import sys; print(sys.version[:3])'`
+export PYTHONPATH=/opt/rh/devtoolset-2/root/usr/lib64/python$pythonvers/site-packages:/opt/rh/devtoolset-2/root/usr/lib/python$pythonvers/site-packages${PYTHONPATH:+:${PYTHONPATH}}
+
+# CFLAGS
+export MINIMAL_CFLAGS="-g -O3"
+export CFLAGS="$MINIMAL_CFLAGS"
+export CXXFLAGS="$MINIMAL_CFLAGS"
+export LDFLAGS="$LDPATHFLAGS"
+
 # Set relative workspace path.
 export WORKSPACE=`pwd`
 
@@ -16,25 +62,35 @@ fi
 
 CMAKE_FLAGS="-DCMAKE_INSTALL_PREFIX=$INSTALL"
 
+# Don't build tests
+CMAKE_FLAGS+=" -DBUILD_TESTING=OFF"
+
+# Use clang 3.8.1 inside omnia-build-box docker image
+CMAKE_FLAGS+=" -DCMAKE_C_COMPILER=$CLANG_PREFIX/bin/clang -DCMAKE_CXX_COMPILER=$CLANG_PREFIX/bin/clang++"
+
+# Ensure we build a release
+CMAKE_FLAGS+=" -DCMAKE_BUILD_TYPE=Release"
+
 # setting the rpath so that libOpenMMPME.so finds the right libfftw3
 #CMAKE_FLAGS+=" -DCMAKE_INSTALL_RPATH=.."
-CMAKE_FLAGS+=" -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++"
-CMAKE_FLAGS+=" -DOPENMM_BUILD_AMOEBA_CUDA_LIB=OFF"
-CMAKE_FLAGS+=" -DOPENMM_BUILD_CPU_LIB=OFF"
-CMAKE_FLAGS+=" -DOPENMM_BUILD_CUDA_COMPILER_PLUGIN=OFF"
-CMAKE_FLAGS+=" -DOPENMM_BUILD_CUDA_LIB=OFF"
-CMAKE_FLAGS+=" -DOPENMM_BUILD_DRUDE_CUDA_LIB=OFF"
-CMAKE_FLAGS+=" -DOPENMM_BUILD_DRUDE_OPENCL_LIB=OFF"
-CMAKE_FLAGS+=" -DOPENMM_BUILD_OPENCL_LIB=OFF"
-CMAKE_FLAGS+=" -DOPENMM_BUILD_RPMD_CUDA_LIB=OFF"
-CMAKE_FLAGS+=" -DOPENMM_BUILD_RPMD_OPENCL_LIB=OFF"
+# Use NVIDIA CUDA 8.0
+CMAKE_FLAGS+=" -DCUDA_CUDART_LIBRARY=/usr/local/cuda-8.0/lib64/libcudart.so"
+CMAKE_FLAGS+=" -DCUDA_NVCC_EXECUTABLE=/usr/local/cuda-8.0/bin/nvcc"
+CMAKE_FLAGS+=" -DCUDA_SDK_ROOT_DIR=/usr/local/cuda-8.0/"
+CMAKE_FLAGS+=" -DCUDA_TOOLKIT_INCLUDE=/usr/local/cuda-8.0/include"
+CMAKE_FLAGS+=" -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-8.0/"
+# Use AMD APP SDK 3.0
+CMAKE_FLAGS+=" -DOPENCL_INCLUDE_DIR=/opt/AMDAPPSDK-3.0/include/"
+CMAKE_FLAGS+=" -DOPENCL_LIBRARY=/opt/AMDAPPSDK-3.0/lib/x86_64/libOpenCL.so"
+# Generate API docs
 CMAKE_FLAGS+=" -DOPENMM_GENERATE_API_DOCS=ON"
-
 # Set location for FFTW3
-#PREFIX="$WORKSPACE/miniconda"
-#CMAKE_FLAGS+=" -DFFTW_INCLUDES=$PREFIX/include"
-#CMAKE_FLAGS+=" -DFFTW_LIBRARY=$PREFIX/lib/libfftw3f.so"
-#CMAKE_FLAGS+=" -DFFTW_THREADS_LIBRARY=$PREFIX/lib/libfftw3f_threads.so"
+PREFIX="$WORKSPACE/miniconda"
+CMAKE_FLAGS+=" -DFFTW_INCLUDES=$PREFIX/include"
+CMAKE_FLAGS+=" -DFFTW_LIBRARY=$PREFIX/lib/libfftw3f.so"
+CMAKE_FLAGS+=" -DFFTW_THREADS_LIBRARY=$PREFIX/lib/libfftw3f_threads.so"
+# Necessary to find GL headers
+CMAKE_FLAGS+=" -DCMAKE_CXX_FLAGS_RELEASE=-I/usr/include/nvidia/"
 
 # Build in subdirectory.
 if [ -e build ]; then
@@ -44,7 +100,14 @@ mkdir build
 cd build
 cmake ../openmm $CMAKE_FLAGS
 make -j4 all install
+
+export CFLAGS="$MINIMAL_CFLAGS"
+export CXXFLAGS="$MINIMAL_CFLAGS"
+export LDFLAGS="$LDPATHFLAGS"
+
 make -j4 PythonInstall C++ApiDocs PythonApiDocs sphinxpdf
 
 # Install.
 make install
+
+cd ..

devtools/packaging/scripts/source/prepare.sh

@@ -5,19 +5,18 @@
 # Set relative workspace path.
 export WORKSPACE=`pwd`
 
-
 # Install miniconda
 export VERSION="latest"
 export PLATFORM="Linux"
 export ARCH="x86_64"
-export MINICONDA="Miniconda2-$VERSION-$PLATFORM-$ARCH.sh"
+export MINICONDA="Miniconda3-$VERSION-$PLATFORM-$ARCH.sh"
 if [ -f miniconda ];
 then
    echo "miniconda already exists"
 else
    echo "Downloading miniconda..."
    rm -rf Miniconda-* miniconda ~/.condarc
-   wget --quiet http://repo.continuum.io/miniconda/${MINICONDA}
+   wget --quiet https://repo.continuum.io/miniconda/${MINICONDA}
    bash ${MINICONDA} -b -p miniconda
    PIP_ARGS="-U"
 fi
@@ -25,7 +24,9 @@ fi
 # Add to path.
 export PATH=$WORKSPACE/miniconda/bin:$PATH
 
+# Workaround for missing libgcrypt
+yum install -y libgcrypt
+
 # Ensure configuration is up to date.
 conda config --add channels omnia
 conda install --yes --quiet swig fftw3f pip doxygen sphinx sphinxcontrib-bibtex sphinxcontrib-lunrsearch sphinxcontrib-autodoc_doxygen lxml cmake
-

devtools/packaging/scripts/windows/Vagrantfile

+Vagrant.configure("2") do |config|
+  config.vm.box = "gusztavvargadr/windows10ee"
+  config.vm.provision :shell, path: "prepare.ps1"
+
+  config.vm.provider :virtualbox do |vb|
+    vb.customize ["modifyvm", :id, "--memory", "2048"]
+    vb.customize ["modifyvm", :id, "--cpus", "2"]
+    vb.customize ["modifyvm", :id, "--ioapic", "on"]
+  end  
+end

devtools/packaging/scripts/windows/build.bat

+mkdir build
+cd build
+
+set FFTW=C:\Miniconda3\pkgs\fftw3f-3.3.4-vc14_2\Library
+set APPSDK=C:\Program Files (x86)\AMD APP SDK\2.9-1
+"C:\Program Files\CMake\bin\cmake.exe" .. -G "NMake Makefiles JOM" -DCMAKE_BUILD_TYPE=Release -DOPENMM_GENERATE_API_DOCS=ON ^
+    -DOPENCL_INCLUDE_DIR="%APPSDK%\include" -DOPENCL_LIBRARY="%APPSDK%\lib\x86_64\OpenCL.lib" ^
+    -DFFTW_INCLUDES="%FFTW%/include" -DFFTW_LIBRARY="%FFTW%/lib/libfftw3f-3.lib"
+
+jom
+jom PythonInstall
+jom C++ApiDocs
+jom PythonApiDocs
+REM jom sphinxpdf
+jom install
+jom PythonBdist

devtools/packaging/scripts/windows/prepare.ps1

+cd C:\Users\vagrant
+
+# Install CUDA.
+
+wget https://developer.nvidia.com/compute/cuda/8.0/prod/network_installers/cuda_8.0.44_win10_network-exe -UseBasicParsing -OutFile cuda_8.0.44_win10_network.exe
+.\cuda_8.0.44_win10_network.exe -s compiler_8.0 cudart_8.0 cufft_8.0 cufft_dev_8.0 nvrtc_8.0 nvrtc_dev_8.0 | Out-Null
+
+# Install AMD APP SDK.
+
+wget https://s3.amazonaws.com/omnia-ci/AMD-APP-SDK-v2.9-1.599.381-GA-Full-windows-64.exe -UseBasicParsing -OutFile AMD-APP-SDK-v2.9-1.599.381-GA-Full-windows-64.exe
+.\AMD-APP-SDK-v2.9-1.599.381-GA-Full-windows-64.exe /S /v/qn | Out-Null
+
+# Install Miniconda.
+
+wget https://repo.continuum.io/miniconda/Miniconda3-latest-Windows-x86_64.exe -UseBasicParsing -OutFile Miniconda3-latest-Windows-x86_64.exe
+.\Miniconda3-latest-Windows-x86_64.exe /S /D=C:\Miniconda3 | Out-Null
+
+# Install software with conda.
+
+& "C:\Miniconda3\Scripts\conda.exe" install -y -c omnia fftw3f jinja2 lxml sphinx sphinxcontrib-autodoc_doxygen sphinxcontrib-lunrsearch conda-build anaconda-client
+& "C:\Miniconda3\Scripts\pip.exe" install sphinxcontrib.bibtex
+
+# Install software with choco.
+
+choco install -y doxygen.portable swig cmake doxygen.install vcbuildtools git jom

docs-source/api-python/process-docstring.py

@@ -2,7 +2,7 @@ import re
 
 def process_docstring(app, what, name, obj, options, lines):
     """This hook edits the docstrings to replace "<tt><pre>" html tags
-    with sphinx directives.
+    and deprecated markers with sphinx directives.
     """
     def repl(m):
         s = m.group(1)
@@ -10,15 +10,19 @@ def process_docstring(app, what, name, obj, options, lines):
             s = linesep + s
         newline = '.. code-block:: c++' + linesep
         return newline + '    ' + s.replace(linesep, linesep + '    ')
-
-    if name == 'simtk.openmm.openmm.CustomTorsionForce':
-         print(lines)
+    def repl2(m):
+        s = m.group(1)
+        if not s.startswith(linesep):
+            s = linesep + s
+        newline = '|LINEBREAK|.. admonition:: Deprecated' + linesep
+        return newline + '    ' + s.replace(linesep, linesep + '    ')
 
     linesep = '|LINEBREAK|'
     joined = linesep.join(lines)
 
     joined = re.sub(r'<tt><pre>((|LINEBREAK|)?.*?)</pre></tt>', repl, joined)
     joined = re.sub(r'<tt>(.*?)</tt>', repl, joined)
+    joined = re.sub(r'@deprecated(.*?\|LINEBREAK\|)', repl2, joined, flags=re.IGNORECASE)
     lines[:] = [(l if not l.isspace() else '') for l in joined.split(linesep)]
 
 

docs-source/usersguide/application.rst

@@ -63,7 +63,7 @@ Anaconda or Miniconda.
 
 2. (Optional) If you want to run OpenMM on a GPU, install CUDA and/or OpenCL.
 
-  * If you have an Nvidia GPU, download CUDA 7.5 from
+  * If you have an Nvidia GPU, download CUDA 8.0 from
     https://developer.nvidia.com/cuda-downloads.  Be sure to install both the
     drivers and toolkit.  OpenCL is included with the CUDA drivers.
   * If you have an AMD GPU and are using Linux or Windows, download the latest
@@ -105,7 +105,7 @@ and tell it to install the command line tools.  With Xcode 4.2 and earlier, the
 command line tools are automatically installed when you install Xcode.)
 
 3. (Optional) If you have an Nvidia GPU and want to use the CUDA platform,
-download CUDA 7.5 from https://developer.nvidia.com/cuda-downloads.  Be sure to
+download CUDA 8.0 from https://developer.nvidia.com/cuda-downloads.  Be sure to
 install both the drivers and toolkit.
 
 4. (Optional) If you plan to use the CPU platform, it is recommended that you
@@ -164,14 +164,14 @@ Installing on Linux
 https://simtk.org/project/xml/downloads.xml?group_id=161, then double click the
 .zip file to expand it.
 
-2. Make sure you have Python 2.6 or higher (earlier versions will not work) and
+2. Make sure you have Python 2.7 or higher (earlier versions will not work) and
 a C++ compiler (typically :program:`gcc` or :program:`clang`) installed on your computer.  You can
 check what version of Python is installed by typing :code:`python` |--|\ :code:`version`
 into a console window.
 
 3. (Optional) If you want to run OpenMM on a GPU, install CUDA and/or OpenCL.
 
-  * If you have an Nvidia GPU, download CUDA 7.5 from
+  * If you have an Nvidia GPU, download CUDA 8.0 from
     https://developer.nvidia.com/cuda-downloads.  Be sure to install both the
     drivers and toolkit.  OpenCL is included with the CUDA drivers.
   * If you have an AMD GPU, download the latest version of the Catalyst driver
@@ -243,7 +243,7 @@ and ignore it.)
 
 4. (Optional) If you want to run OpenMM on a GPU, install CUDA and/or OpenCL.
 
-  * If you have an Nvidia GPU, download CUDA 7.5 from
+  * If you have an Nvidia GPU, download CUDA 8.0 from
     https://developer.nvidia.com/cuda-downloads.  Be sure to install both the
     drivers and toolkit.  OpenCL is included with the CUDA drivers.
   * If you have an AMD GPU, download the latest version of the Catalyst driver
@@ -2696,6 +2696,62 @@ must include an attribute called :code:`radius`\ .
 CustomGBForce also allows you to define tabulated functions.  See section
 :ref:`tabulated-functions` for details.
 
+<CustomHbondForce>
+=========================
+
+To add a CustomHbondForce to the System, include a tag that looks like this:
+
+.. code-block:: xml
+
+    <CustomHbondForce particlesPerDonor="3" particlesPerAcceptor="2" bondCutoff="2"
+        energy="scale*k*(distance(a1,d1)-r0)^2*(angle(a1,d1,d2)-theta0)^2">
+     <GlobalParameter name="scale" defaultValue="1"/>
+     <PerDonorParameter name="theta0"/>
+     <PerAcceptorParameter name="k"/>
+     <PerAcceptorParameter name="r0"/>
+     <Donor class1="H" class2="N" class3="C" theta0="2.1"/>
+     <Acceptor class1="O" class2="C" k="115.0" r0="0.2"/>
+     ...
+    </CustomHbondForce>
+
+The energy expression for the CustomHbondForce is specified by the
+:code:`energy` attribute.  This is a mathematical expression that gives the
+energy of each donor-acceptor interaction as a function of various particle coordinates,
+distances, and angles.  See the API documentation for details.  :code:`particlesPerDonor`
+specifies the number of particles that make up a donor group, and :code:`particlesPerAcceptor`
+specifies the number of particles that make up an acceptor group.
+
+The expression may depend on an arbitrary list of global, per-donor, or
+per-acceptor parameters.  Use a :code:`<GlobalParameter>` tag to define a global
+parameter, a :code:`<PerDonorParameter>` tag to define a per-donor parameter,
+and a :code:`<PerAcceptorParameter>` tag to define a per-acceptor parameter.
+
+Exclusions are created automatically based on the :code:`bondCutoff` attribute.
+If any atom of a donor is within the specified distance (measured in bonds) of
+any atom of an acceptor, an exclusion is added to prevent them from interacting
+with each other.  If a donor and an acceptor share any atom in common, that is a
+bond distance of 0, so they are always excluded.
+
+Every :code:`<Donor>` or :code:`<Acceptor>` tag defines a rule for creating donor
+or acceptor groups.  The number of atoms specified in each one must match the
+value of :code:`particlesPerDonor` or :code:`particlesPerAcceptor` specified in the
+parent tag. Each tag may identify the atoms either by type (using the attributes
+:code:`type1`\ , :code:`type2`\ , ...) or by class (using the attributes
+:code:`class1`\ , :code:`class2`\ , ...).  The force field considers every atom
+in the system (if the number of atoms is 1), every pair of bonded atoms (if the number
+of atoms is 2), or every set of three atoms where the first is bonded to the second
+and the second to the third (if the number of atoms is 3).  For each one, it searches
+for a rule whose atom types or atom classes match the atoms.  If it finds one,
+it calls :code:`addDonor()` or :code:`addAcceptor()` on the CustomHbondForce.
+Otherwise, it ignores that set and continues. The remaining attributes are the
+values to use for the per-donor and per-acceptor parameters. All parameters must
+be specified for every tag, and the attribute name must match the name of the
+parameter.  For instance, if there is a per-donor parameter with the name “k”,
+then every :code:`<Donor>` tag must include an attribute called :code:`k`\ .
+
+CustomHbondForce also allows you to define tabulated functions.  See section
+:ref:`tabulated-functions` for details.
+
 <CustomManyParticleForce>
 =========================
 
@@ -2716,7 +2772,7 @@ To add a CustomManyParticleForce to the System, include a tag that looks like th
 
 The energy expression for the CustomManyParticleForce is specified by the
 :code:`energy` attribute.  This is a mathematical expression that gives the
-energy of each pairwise interaction as a function of various particle coordinates,
+energy of each interaction as a function of various particle coordinates,
 distances, and angles.  See the API documentation for details.  :code:`particlesPerSet`
 specifies the number of particles involved in the interaction and
 :code:`permutationMode` specifies the permutation mode.

docs-source/usersguide/library.rst

@@ -395,9 +395,9 @@ downloading the Xcode Tools from the App Store.
 Windows: Visual Studio
 ----------------------
 
-On Windows systems, use the C++ compiler in Visual Studio version 10 (2010) or
-later.  You can download a free version of Visual C++ Express Edition from
-http://www.microsoft.com/express/vc/.  If you plan to use use OpenMM from
+On Windows systems, use the C++ compiler in Visual Studio 2015 or later.  You
+can download a free version of the Visual Studio C++ build tools from
+http://landinghub.visualstudio.com/visual-cpp-build-tools.  If you plan to use OpenMM from
 Python, it is critical that both OpenMM and Python be compiled with the same
 version of Visual Studio.
 
@@ -446,13 +446,13 @@ CMake.
 
 * For compiling C and Fortran API wrappers, you need:
 
-   * Python 2.6 or later (http://www.python.org)
+   * Python 2.7 or later (http://www.python.org)
    * Doxygen (http://www.doxygen.org)
    * A Fortran compiler
 
 * For compiling the Python API wrappers, you need:
 
-   * Python 2.6 or later (http://www.python.org)
+   * Python 2.7 or later (http://www.python.org)
    * SWIG (http://www.swig.org)
    * Doxygen (http://www.doxygen.org)
 
@@ -2568,23 +2568,21 @@ install binary packages).
 Installing on Windows
 ---------------------
 
-OpenMM on Windows only works with Python 3.3, so make sure that version is
+OpenMM on Windows only works with Python 3.5, so make sure that version is
 installed before you try installing. For Python installation packages and
-instructions, go to http://python.org.  Note that if you have a 64-bit machine,
-you should still install the 32-bit version of Python since the OpenMM Python
-API binary is 32-bit.  We suggest that you install Python using the default
-options.
+instructions, go to http://python.org.  We suggest that you install Python using
+the default options.
 
 Double click on the Python API Installer icon, located in the top level
 directory for the OpenMM installation (by default, this is C:\Program
 Files\OpenMM).  This will install the OpenMM package into the Python
 installation area.  If you have more than one Python installation, you will be
-asked which Python to use—make sure to select Python 3.3.
+asked which Python to use—make sure to select Python 3.5.
 
 Installing on Linux and Mac
 ---------------------------
 
-Make sure you have Python 2.6 or later installed.  For Python installation
+Make sure you have Python 2.7 or later installed.  For Python installation
 packages and instructions, go to http://python.org.  If you do not have the
 correct Python version, install a valid version using the default options.  Most
 versions of Linux and Mac OS X have a suitable Python preinstalled.  You can
@@ -2593,7 +2591,8 @@ check by typing “\ :code:`python` |--|\ :code:`version`\ ” in a terminal win
 You must have a C++ compiler to install the OpenMM Python API.  If you are using
 a Mac, install Apple's Xcode development tools
 (http://developer.apple.com/TOOLS/Xcode) to get the needed compiler.  On other
-Unix-type systems, install gcc or clang.
+Unix-type systems, install gcc or clang.  We recommend clang, since it produces
+faster code than gcc.
 
 The install.sh script installs the Python API automatically as part of the
 installation process, so you probably already have it installed.  If for some

docs-source/usersguide/theory.rst

@@ -48,15 +48,15 @@ Angstroms or nm, and angles may be in degrees or radians.  OpenMM uses the
 following units everywhere.
 
 ===========  =================
-Quantity     Units            
+Quantity     Units
 ===========  =================
-distance     nm               
-time         ps               
+distance     nm
+time         ps
 mass         atomic mass units
-charge       proton charge    
-temperature  Kelvin           
-angle        radians          
-energy       kJ/mol           
+charge       proton charge
+temperature  Kelvin
+angle        radians
+energy       kJ/mol
 ===========  =================
 
 These units have the important feature that they form an internally consistent
@@ -373,7 +373,7 @@ where *d* is the width of the periodic box, and selects the smallest value
 for k\ :sub:`max` which gives *error* < :math:`\delta`\ .  (If the box is not square,
 k\ :sub:`max` will have a different value along each axis.)
 
-This means that the accuracy of the calculation is determined by :math:`\delta`\ . 
+This means that the accuracy of the calculation is determined by :math:`\delta`\ .
 :math:`r_\mathit{cutoff}` does not affect the accuracy of the result, but does affect the speed
 of the calculation by changing the relative costs of the direct space and
 reciprocal space sums.  You therefore should test different cutoffs to find the
@@ -520,7 +520,7 @@ and :math:`\mathbf{S}_2` be diagonal matrices containing the three radii of each
 The energy is computed as a product of three terms:
 
 .. math::
-   E=U_r(\mathbf{A}_1, \mathbf{A}_2, \mathbf{r}_{12}) \cdot \eta_{12}(\mathbf{A}_1, \mathbf{A}_2) \cdot \chi_{12}(\mathbf{A}_1, \mathbf{A}_2, \hat{\mathbf{r}}_{12}) 
+   E=U_r(\mathbf{A}_1, \mathbf{A}_2, \mathbf{r}_{12}) \cdot \eta_{12}(\mathbf{A}_1, \mathbf{A}_2) \cdot \chi_{12}(\mathbf{A}_1, \mathbf{A}_2, \hat{\mathbf{r}}_{12})
 
 The first term describes the distance dependence, and is very similar in form to
 the Lennard-Jones interaction:
@@ -920,7 +920,8 @@ of four particles.  That is, the interaction energy of each bond is given by
 
 where *f*\ (\ *...*\ ) is a user defined mathematical expression.  It may
 depend on an arbitrary set of positions {\ :math:`x_i`\ }, distances {\ :math:`r_i`\ },
-angles {\ :math:`\theta_i`\ }, and dihedral angles {\ :math:`\phi_i`\ }.
+angles {\ :math:`\theta_i`\ }, and dihedral angles {\ :math:`\phi_i`\ }
+guaranteed to be in the range [-π, π]. 
 
 Each distance, angle, or dihedral is defined by specifying a sequence of
 particles chosen from among the particles that make up the bond.  A distance
@@ -995,7 +996,7 @@ Parameters may be specified in two ways:
 * Per-particle parameters are defined by specifying a value for each particle.
 
 The energy function is evaluated one or more times for every unique set of
-:math:`N` particles in the system.  The exact number of times depends on the 
+:math:`N` particles in the system.  The exact number of times depends on the
 *permutation mode*\ .  A set of :math:`N` particles has :math:`N!` possible
 permutations.  In :code:`SinglePermutation` mode, the function is evaluated
 for a single arbitrarily chosen one of those permutations.  In

examples/benchmark.py

@@ -63,11 +63,13 @@ def runOneTest(testName, options):
             else:
                 method = app.CutoffPeriodic
                 cutoff = 1*unit.nanometers
+            friction = 1*(1/unit.picoseconds)
         else:
             ff = app.ForceField('amber99sb.xml', 'amber99_obc.xml')
             pdb = app.PDBFile('5dfr_minimized.pdb')
             method = app.CutoffNonPeriodic
             cutoff = 2*unit.nanometers
+            friction = 91*(1/unit.picoseconds)
         if options.heavy:
             dt = 0.005*unit.picoseconds
             constraints = app.AllBonds
@@ -77,7 +79,7 @@ def runOneTest(testName, options):
             constraints = app.HBonds
             hydrogenMass = None
         system = ff.createSystem(pdb.topology, nonbondedMethod=method, nonbondedCutoff=cutoff, constraints=constraints, hydrogenMass=hydrogenMass)
-        integ = mm.LangevinIntegrator(300*unit.kelvin, 91*(1/unit.picoseconds), dt)
+        integ = mm.LangevinIntegrator(300*unit.kelvin, friction, dt)
     print('Step Size: %g fs' % dt.value_in_unit(unit.femtoseconds))
     properties = {}
     initialSteps = 5

libraries/jama/include/tnt_sparse_matrix_csr.h

@@ -59,7 +59,7 @@ public:
 
 	Sparse_Matrix_CompRow(const Sparse_Matrix_CompRow &S);
 	Sparse_Matrix_CompRow(int M, int N, int nz, const T *val, 
-						const int *r, const int *c);
+						int *r, int *c);
     
 
 
@@ -93,7 +93,7 @@ public:
 */
 template <class T>
 Sparse_Matrix_CompRow<T>::Sparse_Matrix_CompRow(int M, int N, int nz,
-	const T *val, const int *r, const int *c) : val_(nz,val), 
+	const T *val, int *r, int *c) : val_(nz,val), 
 		rowptr_(M, r), colind_(nz, c), dim1_(M), dim2_(N) {}