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Architecture: amd64
Depends: python3-matplotlib, python3-numpy, python3-yaml, python3:any, libboost-iostreams1.83.0
(>= 1.83.0), libc6 (>= 2.38), libcerf2 (>= 2.4), libfftw3-double3 (>= 3.3.10),
libformfactor0.3.0 (>= 0.3.1), libgcc-s1 (>= 4.0), libgsl28 (>= 2.8+dfsg), libpython3.12t64
(>= 3.12.7), libstdc++6 (>= 14), libtiff6 (>= 4.0.3), libtiffxx6 (>= 4.0)
Description: "Simulate and fit X-ray and neutron GISAS -- Python3\n BornAgain is\
\ a software package to simulate and fit small-angle scattering at\n grazing incidence.\
\ It supports analysis of both X-ray (GISAXS) and neutron\n (GISANS) data. Calculations\
\ are carried out in the framework of the distorted\n wave Born approximation\
\ (DWBA). BornAgain provides a graphical user interface\n for interactive use\
\ as well as a generic Python and C++ framework for modeling\n multilayer samples\
\ with smooth or rough interfaces and with various types of\n embedded nanoparticles.\n\
\ .\n BornAgain supports:\n .\n Layers:\n * Multilayers without any restrictions\
\ on the number of layers\n * Interface roughness correlation\n * Magnetic materials\n\
\ .\n Particles:\n * Choice between different shapes of particles (form factors)\n\
\ * Particles with inner structures\n * Assemblies of particles\n * Size distribution\
\ of the particles (polydispersity)\n .\n Positions of Particles:\n * Decoupled\
\ implementations between vertical and planar positions\n * Vertical distributions:\
\ particles at specific depth in layers or on top.\n * Planar distributions:\n\
\ - fully disordered systems\n - short-range order distribution (paracrystals)\n\
\ - two- and one-dimensional lattices\n .\n Input Beam:\n * Polarized or unpolarized\
\ neutrons\n * X-ray\n * Divergence of the input beam (wavelength, incident\
\ angles) following\n different distributions\n * Possible normalization of\
\ the input intensity\n .\n Detector:\n * Off specular scattering\n * Two-dimensional\
\ intensity matrix, function of the output angles\n .\n Use of BornAgain:\n *\
\ Simulation of GISAXS and GISANS from the generated sample\n * Fitting to reference\
\ data (experimental or numerical)\n * Interactions via Python scripts or Graphical\
\ User Interface\n .\n If you use BornAgain in your work, please cite\n C. Durniak,\
\ M. Ganeva, G. Pospelov, W. Van Herck, J. Wuttke (2015), BornAgain\n \u2014\
\ Software for simulating and fitting X-ray and neutron small-angle\n scattering\
\ at grazing incidence, version <version you used>,\n http://www.bornagainproject.org\n\
\ .\n This package contains the Python bindings for use in scripts."
Homepage: https://bornagainproject.org/
Installed-Size: '12858'
Maintainer: Debian PaN Maintainers <debian-pan-maintainers@alioth-lists.debian.net>
Package: python3-bornagain
Priority: optional
Section: science
Source: bornagain
Version: 22~git20241119164839.81ff4bd+ds3-1
srcpkg_name: bornagain
srcpkg_version: 22~git20241119164839.81ff4bd+ds3-1