SrFit - Structure refinement from diffraction data

## Project description

Configurable code for solving atomic structures.

The diffpy.srfit package provides the framework for building a global optimizer on the fly from components such as function calculators (that calculate different data spectra), regression algorithms and structure models. The software is capable of co-refinement using multiple information sources or models. It provides a uniform interface for various regression algorithms. The target function being optimized can be specified by the user according to the data available.

Within the diffpy.srfit framework, any parameter used in describing the structure of a material can be passed as a refinable variable to the global optimizer. Once parameters are declared as variables they can easily be turned “on” or “off”, i.e. fixed or allowed to vary. Additionally, variables may be constrained to obey mathematical relationships with other parameters or variables used in the structural model. Restraints can be applied to variables, which adds a penalty to the refinement process commensurate with the deviation from the known value or range. The cost function can also be customized by the user. If the refinement contains multiple models, each model can have its own cost function which will be properly weighted and combined to obtain the total cost function. Additionally, diffpy.srfit is designed to be extensible, allowing the user to integrate external calculators to perform co-refinements with other techniques.

## REQUIREMENTS

The diffpy.srfit package requires Python 2.6 or 2.7 and the following software:

• setuptools - software distribution tools for Python

• NumPy - numerical mathematics and fast array operations for Python

• SciPy - scientific libraries for Python

• matplotlib - python plotting library

Recommended software:

Optimizations involving crystal structures or molecules require

Optimizations involving pair distribution functions PDF or bond valence sums require

Optimizations involving small angle scattering or shape characteristic functions from the diffpy.srfit.sas module require

• sans.pr - module for calculation of P(R) in small-angle scattering from the SasView project, http://www.sasview.org

On Ubuntu Linux, the required software can easily be installed using the system package manager:

sudo apt-get install \
python-setuptools python-numpy python-scipy python-matplotlib

For Mac OS X systems with the MacPorts package manager, the required software can be installed with

sudo port install \
python27 py27-setuptools py27-numpy py27-scipy py27-matplotlib

When installing for MacPorts, make sure the MacPorts bin directory is the first in the system PATH and that python27 is selected as the default Python version in MacPorts:

sudo port select --set python python27

For other required packages see their respective web pages for installation instructions.

## INSTALLATION

The easiest option is to use the latest DiffPy-CMI release bundle from http://www.diffpy.org, which comes with diffpy.srfit and all other recommended software included.

Or, use easy_install to download and install the latest release from Python Package Index

sudo easy_install diffpy.srfit

If you prefer to install from sources, make sure all required software packages are in place and then run

sudo python setup.py install

This installs diffpy.srfit for all users in the default system location. If administrator (root) access is not available, see the usage info from python setup.py install --help for options to install to user-writable directories. The installation integrity can be verified by changing to the HOME directory and running

python -m diffpy.srfit.tests.run

## DEVELOPMENT

diffpy.srfit is an open-source software developed as a part of the DiffPy-CMI complex modeling initiative at the Brookhaven National Laboratory. The diffpy.srfit sources are hosted at https://github.com/diffpy/diffpy.srfit.

Feel free to fork the project and contribute. To install diffpy.srfit in a development mode, with its sources being directly used by Python rather than copied to a package directory, use

python setup.py develop --user

## ACKNOWLEDGEMENT

Part of the source code in _abc.py and _ordereddict.py was derived from Python 2.7 at http://www.python.org/download/source; while other code observable.py was derived from the 1.0 version of the Caltech “Pyre” project.

## CONTACTS

http://www.diffpy.org

or email Prof. Simon Billinge at sb2896@columbia.edu.

## Project details

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