Python bindings to ObjCryst++, the Object-Oriented Crystallographic Library.
The documentation for this release of pyobjcryst can be found on-line at http://diffpy.github.io/pyobjcryst.
pyobjcryst requires Python 2.7, C++ compiler and the following software:
libobjcryst- Object-Oriented Crystallographic Library for C++, https://github.com/diffpy/libobjcrystsetuptools- tools for installing Python packagesNumPy- library for scientific computing with Pythonscons- software constructions tool (1.0 or later)python-dev- header files for interfacing Python with Clibboost-all-dev- Boost C++ libraries and development files
We recommend to use Anaconda Python as it allows to install all software dependencies together with pyobjcryst. For other Python distributions it is necessary to install the required software separately. As an example, on Ubuntu Linux the required software can be installed using
sudo apt-get install \ python-setuptools python-numpy scons \ build-essential python-dev libboost-all-dev
The preferred method is to use Anaconda Python and install from the "diffpy" channel of Anaconda packages
conda config --add channels diffpy conda install pyobjcryst
pyobjcryst is also included in the "diffpy-cmi" collection of packages for structure analysis
conda install diffpy-cmi
If you prefer to use other Python distribution or install from sources, you must first install the libobjcryst library as per the instructions at https://github.com/diffpy/libobjcryst. Make sure other required software is also in place and then run:
python setup.py install
You may need to use sudo with system Python so the process is
allowed to copy files to system directories. If administrator (root)
access is not available, see the usage information from
python setup.py install --help for options to install to
a user-writable location. The installation integrity can be verified by
changing to the HOME directory and running
python -m pyobjcryst.tests.run
An alternative way of installing pyobjcryst is to use the SCons tool, which can speed up the installation by compiling C++ files in several parallel jobs (-j4):
scons -j4 install
See scons -h for description of build targets and options.
pyobjcryst is an open-source software developed as a part of the DiffPy-CMI complex modeling initiative at the Brookhaven National Laboratory. The pyobjcryst sources are hosted at https://github.com/diffpy/pyobjcryst.
Feel free to fork the project and contribute. To install pyobjcryst in a development mode, where its sources are directly used by Python rather than copied to a system directory, use
python setup.py develop --user
When developing it is preferable to compile the C++ files with
SCons using the build=develop option, which compiles the extension
module with debug information and C-assertions checks
scons -j4 build=debug develop
The build script checks for a presence of sconsvars.py file, which
can be used to permanently set the build variable. The SCons
construction environment can be further customized in a sconscript.local
script. The package integrity can be verified by executing unit tests with
scons -j4 test.
When developing with Anaconda Python it is essential to specify
header path, library path and runtime library path for the active
Anaconda environment. This can be achieved by setting the CPATH,
LIBRARY_PATH and LDFLAGS environment variables as follows:
# resolve the prefix directory P of the active Anaconda environment P="$(conda info --json | grep default_prefix | cut -d\" -f4)" export CPATH=$P/include export LIBRARY_PATH=$P/lib export LDFLAGS=-Wl,-rpath,$P/lib # compile and re-install pyobjcryst scons -j4 build=debug develop
On Mac OS X the distributed Anaconda packages are built for operating
system version 10.6, which may be incompatible with codes compiled on a
newer OS. To avoid this problem set the environment variable
MACOSX_DEPLOYMENT_TARGET=10.6. This allows to build pyobjcryst
against the Anaconda package for the libobjcryst library.
For more information on pyobjcryst please visit the project web-page
or email Prof. Simon Billinge at sb2896@columbia.edu.