Python bindings to the ObjCryst++ library.
Project description
pyobjcryst
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.
INSTALLATION
pyobjcryst is available for Python 3.7 (deprecated), and 3.8 to 3.11.
Note regarding windows: on conda-forge, pyobjcryst 2.2.3 is available for python3.7 only, and version 2.2.4 is available for python 3.8 and 3.9 using a pypy environment rather than the regular cpython interpreter.
Using conda (recommended)
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.
Using conda, we recommend installing pyobjcryst using the “conda-forge” channel
conda install -c conda-forge pyobjcryst
Note: when updating, please make sure you are upgrading both libobjcryst and pyobjcryst packages.
You can also install from the “diffpy” channel - especially if you use pyobjcryst allong with the other diffpy tools for PDF calculations, but it is not updated as often as conda-forge.
pyobjcryst is also included in the “diffpy-cmi” collection of packages for structure analysis
conda install -c diffpy diffpy-cmi
From source
The requirements are:
libobjcryst - Object-Oriented Crystallographic Library for C++, https://github.com/diffpy/libobjcryst
setuptools - tools for installing Python packages
NumPy - library for scientific computing with Python
python-dev - header files for interfacing Python with C
libboost-all-dev - Boost C++ libraries and development files
scons - software construction tool (optional)
The above requirements are easily installed through conda using e.g.:
conda install numpy compilers boost scons libobjcryst
Alternatively, 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 libobjcryst library can also be installed as per the instructions at https://github.com/diffpy/libobjcryst. Make sure other required software are also in place and then run from the pyobjcryst directory:
pip install .
You may need to use sudo with system Python so the process is allowed to copy files to system directories, unless you are installing into a conda environment. 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 executing the included tests with
python -m pyobjcryst.tests.run
An alternative way of installing pyobjcryst is to use the SCons tool, which can speed up the process by compiling C++ files in several parallel jobs (-j4):
scons -j4 install
See scons -h for description of build targets and options.
Optional graphical dependencies for jupyter notebooks
Some of the classes can produce graphical outputs, which can be displayed in a jupyter notebook:
a Crystal structure can be displayed in 3D: this requires the py3dmol and ipywidgets modules. See the notebook examples/cystal_3d_widget.ipynb
a PowderPattern can be displayed (and live-updated) if matplotlib (and optionnally ipympl) are installed. See the notebook examples/cimetidine-structure-solution-powder.ipynb
In short, pip install jupyter matplotlib ipywidgets py3dmol will give you all the required dependencies. Note that you can also use this in jupyterlab.
Note that jupyter, ipywidgets, matplotlib and ipympl can be installed using conda(-forge), but py3dmol should be installed using pip, as the conda version is obsolete.
DEVELOPMENT
pyobjcryst is an open-source software originally developed as a part of the DiffPy-CMI complex modeling initiative at the Brookhaven National Laboratory, and is also further developed at ESRF. 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=$CONDA_PREFIX export CPATH=$P/include export LIBRARY_PATH=$P/lib export LDFLAGS=-Wl,-rpath,$P/lib # compile and re-install pyobjcryst scons -j4 build=debug develop
Note the Anaconda package for the required libobjcryst library is built with a C++ compiler provided by Anaconda. This may cause incompatibility with system C++. In such case please use Anaconda C++ to build pyobjcryst.
Quick conda environment from libobjcryst and pyobjcryst sources
If conda is available, you can create a pyobjcryst environment from the git repositories (downloaded in the current directory) using:
conda create --yes --name pyobjcryst numpy matplotlib ipywidgets jupyter conda install --yes -n pyobjcryst -c conda-forge boost scons py3dmol conda activate pyobjcryst git clone https://github.com/diffpy/libobjcryst.git cd libobjcryst scons -j4 install prefix=$CONDA_PREFIX cd .. git clone https://github.com/diffpy/pyobjcryst.git cd pyobjcryst export CPATH=$CONDA_PREFIX/include export LIBRARY_PATH=$CONDA_PREFIX/lib export LDFLAGS=-Wl,-rpath,$CONDA_PREFIX/lib scons -j4 install prefix=$CONDA_PREFIX
CONTACTS
For more information on pyobjcryst please visit the project web-page
or email Prof. Simon Billinge at sb2896@columbia.edu.
You can also contact Vincent Favre-Nicolin (favre@esrf.fr) if you are using pyobjcryst outside diffpy, e.g. to display structures in a notebook, refine powder patterns or solve structures using the global optimisation algorithms, etc..
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