Hybrid distributed code for high speed tomographic reconstruction with iterative reconstruction and a priori knowledge capabilities. PyHST2 (formerly known as PyHST) has been engineered to sustain the high data flow typical of the third generation synchrotron facilities (10 terabytes per experiment) by adopting a distributed and pipelined architecture. The code implements, beside a default filtered backprojection reconstruction, iterative reconstruction techniques with a-priori knowledge. The latter are used to improve the reconstruction quality or in order to reduce the required data volume and reach a given quality goal. The implemented a-priori knowledge techniques are based on the total variation penalisation and a new recently found convex functional which is based on overlapping patches.

Licenses GNU General Public License 3.0
Categories Data analysis Data reduction Tomography
Software Requirements -
Hardware Requirements -
Platforms Linux
Languages C C++ CUDA Python
Input Formats HDF5 EDF JPEG2000
Output Formats RAW TIFF EDF
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Available on the central cluster. Refer to the documentation about how to use it

Documentation / Tutorials


Example data sets


Reference 1 Reference 2

Instruments BM05 (ESRF) ID11 (ESRF) ID16A-NI (ESRF) ID16B-NA (ESRF) ID17 (ESRF) ID19 (ESRF)
This software is used at these institutes
There are 1 example datasets for this software
File Size Download
TEST_PYHST2.tgz 2.1 GB Download