Source: bornagain Maintainer: Debian PaN Maintainers Uploaders: Debian Science Maintainers , Mika Pflüger , Freexian Packaging Team , Picca Frédéric-Emmanuel , Roland Mas , Section: science Priority: optional Build-Depends: clang-format , cmake, debhelper-compat (= 13), dh-sequence-python3, doxygen-latex , libboost-all-dev, libcerf-dev (>= 2.3), libeigen3-dev, libformfactor-dev, libfftw3-dev, libgsl0-dev, libheinz-dev, libqt6opengl6-dev, libtiff-dev, libxkbcommon-dev, libyaml-cpp-dev, python3-dev , python3-matplotlib , python3-numpy , python3-pip , python3-yaml , qt6-base-dev, qt6-svg-dev, swig , Build-Depends-Indep: hugo , texlive-fonts-extra , texlive-xetex , Standards-Version: 4.6.2 Vcs-Browser: https://salsa.debian.org/science-team/bornagain Vcs-Git: https://salsa.debian.org/science-team/bornagain.git Homepage: https://bornagainproject.org/ Rules-Requires-Root: no Package: bornagain Architecture: any Depends: ${misc:Depends}, ${shlibs:Depends} Recommends: python3-bornagain Description: Simulate and fit X-ray and neutron GISAS -- binary BornAgain is a software package to simulate and fit small-angle scattering at grazing incidence. It supports analysis of both X-ray (GISAXS) and neutron (GISANS) data. Calculations are carried out in the framework of the distorted wave Born approximation (DWBA). BornAgain provides a graphical user interface for interactive use as well as a generic Python and C++ framework for modeling multilayer samples with smooth or rough interfaces and with various types of embedded nanoparticles. . BornAgain supports: . Layers: * Multilayers without any restrictions on the number of layers * Interface roughness correlation * Magnetic materials . Particles: * Choice between different shapes of particles (form factors) * Particles with inner structures * Assemblies of particles * Size distribution of the particles (polydispersity) . Positions of Particles: * Decoupled implementations between vertical and planar positions * Vertical distributions: particles at specific depth in layers or on top. * Planar distributions: - fully disordered systems - short-range order distribution (paracrystals) - two- and one-dimensional lattices . Input Beam: * Polarized or unpolarized neutrons * X-ray * Divergence of the input beam (wavelength, incident angles) following different distributions * Possible normalization of the input intensity . Detector: * Off specular scattering * Two-dimensional intensity matrix, function of the output angles . Use of BornAgain: * Simulation of GISAXS and GISANS from the generated sample * Fitting to reference data (experimental or numerical) * Interactions via Python scripts or Graphical User Interface . If you use BornAgain in your work, please cite C. Durniak, M. Ganeva, G. Pospelov, W. Van Herck, J. Wuttke (2015), BornAgain — Software for simulating and fitting X-ray and neutron small-angle scattering at grazing incidence, version , http://www.bornagainproject.org Package: python3-bornagain Architecture: any Depends: python3-matplotlib, python3-numpy, python3-yaml, ${misc:Depends}, ${python3:Depends}, ${shlibs:Depends} Description: Simulate and fit X-ray and neutron GISAS -- Python3 BornAgain is a software package to simulate and fit small-angle scattering at grazing incidence. It supports analysis of both X-ray (GISAXS) and neutron (GISANS) data. Calculations are carried out in the framework of the distorted wave Born approximation (DWBA). BornAgain provides a graphical user interface for interactive use as well as a generic Python and C++ framework for modeling multilayer samples with smooth or rough interfaces and with various types of embedded nanoparticles. . BornAgain supports: . Layers: * Multilayers without any restrictions on the number of layers * Interface roughness correlation * Magnetic materials . Particles: * Choice between different shapes of particles (form factors) * Particles with inner structures * Assemblies of particles * Size distribution of the particles (polydispersity) . Positions of Particles: * Decoupled implementations between vertical and planar positions * Vertical distributions: particles at specific depth in layers or on top. * Planar distributions: - fully disordered systems - short-range order distribution (paracrystals) - two- and one-dimensional lattices . Input Beam: * Polarized or unpolarized neutrons * X-ray * Divergence of the input beam (wavelength, incident angles) following different distributions * Possible normalization of the input intensity . Detector: * Off specular scattering * Two-dimensional intensity matrix, function of the output angles . Use of BornAgain: * Simulation of GISAXS and GISANS from the generated sample * Fitting to reference data (experimental or numerical) * Interactions via Python scripts or Graphical User Interface . If you use BornAgain in your work, please cite C. Durniak, M. Ganeva, G. Pospelov, W. Van Herck, J. Wuttke (2015), BornAgain — Software for simulating and fitting X-ray and neutron small-angle scattering at grazing incidence, version , http://www.bornagainproject.org . This package contains the Python bindings for use in scripts. Package: bornagain-doc Architecture: all Section: doc Depends: ${misc:Depends}, ${shlibs:Depends}, libjs-bootstrap, libjs-jquery, libjs-popper.js, fonts-open-sans, fonts-roboto, fonts-font-awesome Recommends: bornagain Multi-Arch: foreign Description: Simulate and fit X-ray and neutron GISAS -- doc BornAgain is a software package to simulate and fit small-angle scattering at grazing incidence. It supports analysis of both X-ray (GISAXS) and neutron (GISANS) data. Calculations are carried out in the framework of the distorted wave Born approximation (DWBA). BornAgain provides a graphical user interface for interactive use as well as a generic Python and C++ framework for modeling multilayer samples with smooth or rough interfaces and with various types of embedded nanoparticles. . BornAgain supports: . Layers: * Multilayers without any restrictions on the number of layers * Interface roughness correlation * Magnetic materials . Particles: * Choice between different shapes of particles (form factors) * Particles with inner structures * Assemblies of particles * Size distribution of the particles (polydispersity) . Positions of Particles: * Decoupled implementations between vertical and planar positions * Vertical distributions: particles at specific depth in layers or on top. * Planar distributions: - fully disordered systems - short-range order distribution (paracrystals) - two- and one-dimensional lattices . Input Beam: * Polarized or unpolarized neutrons * X-ray * Divergence of the input beam (wavelength, incident angles) following different distributions * Possible normalization of the input intensity . Detector: * Off specular scattering * Two-dimensional intensity matrix, function of the output angles . Use of BornAgain: * Simulation of GISAXS and GISANS from the generated sample * Fitting to reference data (experimental or numerical) * Interactions via Python scripts or Graphical User Interface . If you use BornAgain in your work, please cite C. Durniak, M. Ganeva, G. Pospelov, W. Van Herck, J. Wuttke (2015), BornAgain — Software for simulating and fitting X-ray and neutron small-angle scattering at grazing incidence, version , http://www.bornagainproject.org . This package contains the BornAgain documentation.