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A python package for powder diffraction

Project description

Introduction

RadialX is a python package for working with x-ray powder diffraction data and for simulating x-ray powder diffraction patterns from models.

The most complete documentation is available at http://pythonhosted.org/radialx/.

Fully Documented Functionalities

At present, the only 100% documented functionalities of RadialX are

  1. The simulation of powder diffraction patterns from PDB files using the utility called powderx.

  2. Displaying of diffraction image header information using the utility called headerx.

Detailed usage for powderx and headerx are explained within the documentation.

Less Documented Functionalities

Other less documented functionalities correspond to “modes” of the utility called profilex:

  • centering mode: Finding the centers of powder diffraction images in adxv binary format.

  • averaging mode: Radial integration of one or more experimental powder diffraction patterns in adxv binary format.

  • averaging mode: Scaling of several powder experimental or simulated diffraction patterns to a single experimental or simulated pattern.

  • difference mode: Calculating the difference of two scaled radially integrated experimental powder diffraction patterns.

Although profilex is fully functional and heavily tested, its user interface (i.e. config file format, etc.) is very likely to change. For example, the modes will probably be split into different different utilities and several config file parameters will probably be renamed. The profilex utility is fairly well documented by comments in the config files that populate the test/test-profilex directory of the source distribution, as explained in the documentation.

It is hoped that the entire RadialX package will be fully and heavily documented soon.

Home Page & Repository

Home Page: https://pypi.python.org/pypi/radialx/

Documentation: http://pythonhosted.org/radialx/

Repository: https://github.com/jcstroud/radialx

Project details


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radialx-0.8.15.tar.gz (127.1 kB view hashes)

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