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NeutronPy is a collection of commonly used tools aimed at facilitating the analysis of neutron scattering data. NeutronPy is built primarily using the numpy and scipy python libraries, with a translation of ResLib 3.4c (MatLab) routines for Instrument resolution calculations.

Project description

NeutronPy is a python library with commonly used tools for neutron scattering measurements, primarily for Triple Axis Spectrometer data, but easily applied to other types of data, including some reduced Time of Flight data. Below is a non-exhaustive list of Neutronpy’s features:

  • Triple Axis Spectrometer resolution function calculation (Translated from ResLib), including
    • Resolution ellipses

    • Instrument visualization

    • Convolution

  • Time of Flight Spectrometer resolution function calculation (based on Violini et al doi:10.1016/j.nima.2013.10.042 ), including
    • Resolution ellipses

  • Structure factor calculation, including
    • Structure factors with support for
      • Mass Normalization

      • Debye-Waller factor

      • Unit cell visualization

    • Single-ion magnetic form factor calculation

  • Least-Squares fitting (custom interface for scipy.optimize.leastsq using lmfit features), including
    • Built-in physical models

  • Basic data operations
    • Binning

    • Normalization (time/monitor)

    • Calculated peak integrated intensity, position, and width

    • Plotting

    • Slicing

  • Loading from common TAS file types, including
    • SPICE

    • ICE

    • ICP

    • MAD

See Roadmap for panned future features.

David M Fobes started development of NeutronPy while in the Neutron Scattering Group, part of the Condensed Matter Physics & Materials Science Department (CMPMSD) at Brookhaven National Laboratory, and has continued within the MPA-CMMS and A-1 groups of Los Alamos National Laboratory. Both are US Department of Energy, Office of Basic Energy Sciences funded laboratories.

NeutronPy is a work-in-progress (see the Roadmap in the wiki for indications of new upcoming features) and as such, still has many bugs, so use at your own risk; see Disclaimer. To report bugs or suggest features see Contributions.

Requirements

The following packages are required to install this library:

  • Python >= 3.6

  • numpy >= 1.10.0

  • scipy >= 1.0.0

  • lmfit >= 0.9.5

  • matplotlib >= 2.0.0

  • h5py

The following package is required to use the neutronpy entry-point gui optional feature

  • pyqt5 >= 5.4.1

The following packages are required to test this library:

  • pytest >= 3

  • mock

Installation

It is recommended that you use anaconda or pip to install NeutronPy:

conda install -c neutronpy neutronpy

or:

pip install neutronpy

See Installation for more detailed instructions.

Documentation

Documentation is available at neutronpy.github.io, or can be built using sphinx by navigating to the doc/ folder and executing make html; results will be in the doc/_build/ folder.

To ask questions you may either request access to the Neutronpy Slack Team, or create a Github issue.

Building documentation requires the following additional packages:

  • sphinx>=1.4

  • releases>=1.5.0

  • numpydoc>=0.8.0

  • neutronpy_rtd_sphinx_theme

Contributions

Contributions may be made by submitting a pull-request for review using the fork-and-pull method on GitHub. Feature requests and bug reports can be made using the GitHub issues interface. Please read the development guide for details on how to best contribute.

To discuss development you may request access to the Neutronpy Slack Team.

Disclaimer

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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