Package: python3-pyfai-dbg
Source: pyfai
Version: 0.19.0+dfsg1-1build1
Architecture: amd64
Maintainer: Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
Original-Maintainer: Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
Installed-Size: 72649
Depends: python3-fabio-dbg, python3-h5py-dbg, python3-matplotlib-dbg, python3-numexpr-dbg, python3-numpy-dbg, python3-pyfai (= 0.19.0+dfsg1-1build1), python3-pyopencl-dbg, python3-pyqt5-dbg, python3-scipy-dbg, python3-silx-dbg (>= 0.10.1), python3-tk-dbg, python3-numpy (>= 1:1.16.0~rc1), python3-numpy-abi9, python3-dbg (<< 3.9), python3-dbg (>= 3.8~), libc6 (>= 2.29), libgcc-s1 (>= 3.0), libgomp1 (>= 6), libstdc++6 (>= 5)
Section: debug
Priority: optional
Homepage: https://github.com/silx-kit/pyFAI
Description: Fast Azimuthal Integration scripts - Python3 debug
 PyFAI is a Python library for azimuthal integration; it allows the conversion
 of diffraction images taken with 2D detectors like CCD cameras into X-Ray
 powder patterns that can be used by other software like Rietveld refinement
 tools (i.e. FullProf), phase analysis or texture analysis.
 .
 As PyFAI is a library, its main goal is to be integrated in other tools like
 PyMca, LiMa or EDNA. To perform online data analysis, the precise description
 of the experimental setup has to be known. This is the reason why PyFAI
 includes geometry optimization code working on "powder rings" of reference
 samples. Alternatively, PyFAI can also import geometries fitted with other
 tools like Fit2D.
 .
 PyFAI has been designed to work with any kind of detector with any geometry
 (transmission, reflection, off-axis, ...). It uses the Python library FabIO
 to read most images taken by diffractometer.
 .
 This package contains the extension built for the Python 3 debug
 interpreter.
Build-Ids: 03c367afbea5c2160d9919193ddea88abde36a3c 04c05e83e807c4cfe4f457556589ae8372c3de70 0862660f3a14765d1a90e5e86d46449adb82dff0 108c46fd0d6a4b03edaa86b813a7634561c39168 12449d98e9a593c76addae46daa56dee42477efe 175fa762b0930b45d4796c2735c383dac0d21bb0 17f23d05b5292dfebc8c357e81c2d3f7b4ecd1c3 3110a321c210c07b5a54c842b32d253835481abe 333b6e8b067ce95acec68647ed0147bf382019d6 33edb247a9a57e43190cb0488ace44f327fc17ab 351513280c13d9e915a26673593fb3f700c3fa63 356a842c5c0c07e647aa1158da4b9d75aa4cf434 46b1c4cc7c363bf782298f6a0e505bcef63c6f37 5e29b9dc5156b1c004886873002e1b17906d5e67 5ed3db65dedca3ad52eb88cd44e6c6edd5da250b 6f9fbe9c122045edaf1df3f85fecf04e51f6ff8e 71e80228406c07764a8551eb1e1202900bf72810 76120af31d3dd75506447e1dd61a8d6297e062d9 7f5bddde394f7f41e41be2f42ba1054bef7aa351 8fbb93ef778a8a0a712104c28a55d896e1aabb7b a3bba68fce9972e478cc35ec059e5e345a7e54e5 b7f2c55d2c0e264e598f1c9d0808c679ce5895d7 ca4bd009c374b83011d3bd2532d6dc1c171de37e d119db668b011c47a87fc8e0ea858def41b86d7a e567345424c6ab3659f3f6852d1a01bac9cc77b3
