WillItFit:  a framework for fitting of constrained models to small-angle scattering data

Martin Cramer Pedersen; Lise Arleth; Kell Mortensen

doi:10.1107/s0021889813026022

WillItFit: a framework for fitting of constrained models to small-angle scattering data

Martin Cramer Pedersen, Lise Arleth, Kell Mortensen

Xray and Neutron Science

28 Citations (Scopus)

Abstract

A software framework for analysis of small-angle scattering data is presented. On the basis of molecular constraints and prior knowledge of the chemical composition of the sample, the software is capable of simultaneously fitting small-angle X-ray and neutron scattering data to analytical or semi-analytical models of biomacromolecules. The software features various fitting routines along with the possibility of incorporating instrumental resolution effects on the fit. Finally, trust region estimation, based on the profile likelihood strategy, is implemented. The algorithms and models are written in C, whereas the user interface is written in Python. Parallelization is implemented using the OpenMP extensions to C. The source code is available for free upon request or via the associated code repository. The software runs on Linux, Windows and OSX and is available as an open-source initiative published under the General Publishing License.

Original language	English
Article number	1894-1898
Journal	Journal of Applied Crystallography
Volume	46
Issue number	Part 6
ISSN	0021-8898
DOIs	https://doi.org/10.1107/s0021889813026022
Publication status	Published - 1 Dec 2013

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title = "WillItFit: a framework for fitting of constrained models to small-angle scattering data",

abstract = "A software framework for analysis of small-angle scattering data is presented. On the basis of molecular constraints and prior knowledge of the chemical composition of the sample, the software is capable of simultaneously fitting small-angle X-ray and neutron scattering data to analytical or semi-analytical models of biomacromolecules. The software features various fitting routines along with the possibility of incorporating instrumental resolution effects on the fit. Finally, trust region estimation, based on the profile likelihood strategy, is implemented. The algorithms and models are written in C, whereas the user interface is written in Python. Parallelization is implemented using the OpenMP extensions to C. The source code is available for free upon request or via the associated code repository. The software runs on Linux, Windows and OSX and is available as an open-source initiative published under the General Publishing License.",

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AU - Pedersen, Martin Cramer

AU - Arleth, Lise

AU - Mortensen, Kell

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N2 - A software framework for analysis of small-angle scattering data is presented. On the basis of molecular constraints and prior knowledge of the chemical composition of the sample, the software is capable of simultaneously fitting small-angle X-ray and neutron scattering data to analytical or semi-analytical models of biomacromolecules. The software features various fitting routines along with the possibility of incorporating instrumental resolution effects on the fit. Finally, trust region estimation, based on the profile likelihood strategy, is implemented. The algorithms and models are written in C, whereas the user interface is written in Python. Parallelization is implemented using the OpenMP extensions to C. The source code is available for free upon request or via the associated code repository. The software runs on Linux, Windows and OSX and is available as an open-source initiative published under the General Publishing License.

AB - A software framework for analysis of small-angle scattering data is presented. On the basis of molecular constraints and prior knowledge of the chemical composition of the sample, the software is capable of simultaneously fitting small-angle X-ray and neutron scattering data to analytical or semi-analytical models of biomacromolecules. The software features various fitting routines along with the possibility of incorporating instrumental resolution effects on the fit. Finally, trust region estimation, based on the profile likelihood strategy, is implemented. The algorithms and models are written in C, whereas the user interface is written in Python. Parallelization is implemented using the OpenMP extensions to C. The source code is available for free upon request or via the associated code repository. The software runs on Linux, Windows and OSX and is available as an open-source initiative published under the General Publishing License.

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DO - 10.1107/s0021889813026022

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JO - Journal of Applied Crystallography

JF - Journal of Applied Crystallography

IS - Part 6

M1 - 1894-1898

ER -

WillItFit: a framework for fitting of constrained models to small-angle scattering data

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