Phase Focus Limited of Sheffield, UK, has an international portfolio
of patents and pending applications which relate to ptychography.
A current list is available here <http://www.phasefocus.com/patents/>__.
Phase Focus grants royalty free licences of its patent rights for
non-commercial academic research use, for reconstruction of simulated
data and for reconstruction of data obtained at synchrotrons at X-ray
wavelengths. These licenses can be applied for online by
clicking on this link <http://www.phasefocus.com/licence/>__.
Phase Focus asserts that the software we have made available for download may be capable of being used in circumstances which may fall within the claims of one or more of the Phase Focus patents. Phase Focus advises that you apply for a licence from it before downloading any software from this website.
|ptypysite|
.. image:: https://github.com/ptycho/ptypy/actions/workflows/test.yml/badge.svg?branch=master :target: https://github.com/ptycho/ptypy/actions/workflows/test.yml
|ptypy| [#pronounciation] [#ptypypaper] is a framework for scientific ptychography compiled by P. Thibault and B. Enders and other authors (see AUTHORS).
It is the result of years of experience in the field of ptychography condensed into a versatile python package. The package covers the whole path of ptychographic analysis after the actual experiment is completed
The main idea of ptypy is: "Flexibility and Scalabality through abstraction". Most often, you will find a class for every concept of ptychography in |ptypy|. Using these or other more abstract base classes, new ideas may be developed in a rapid manner without the cumbersome overhead of data management, memory access or distributed computing. Additionally, |ptypy| provides a rich set of utilities and helper functions, especially for input and output
To get started quickly, please find the official documentation on
the project pages <http://ptycho.github.io/ptypy>__
or have a look at the examples in the templates directory.
Difference Map [#dm] algorithm engine with power bound constraint [#power].
Maximum Likelihood [#ml]_ engine with preconditioners and regularizers.
A few more engines (RAAR, sDR, ePIE, ...).
Fully parallelized using the Massage Passing Interface
(MPI <https://en.wikipedia.org/wiki/Message_Passing_Interface>_).
Simply execute your script with::
$ mpiexec -n [nodes] python
GPU acceleration based on custom kernels, CuPy or PyCUDA/reikna.
See examples in templates/accelerate, templates/engines/cupy and templates/engines/pycuda.
A client-server approach for visualization and control based on
ZeroMQ <http://www.zeromq.org>_ .
The reconstruction may run on a remote hpc cluster while your desktop
computer displays the reconstruction progress.
Mixed-state reconstructions of probe and object [#states]_ for overcoming partial coherence or related phenomena.
On-the-fly reconstructions (while data is being acquired) using the
the PtyScan <http://http://ptycho.github.io/ptypy/rst/ptypy.core.html#ptypy.core.data.PtyScan>_
class in the linking mode <http://ptycho.github.io/ptypy/rst/data_management.html#case-flyscan>_
Installation should be as simple as ::
$ pip install .
or, as a user, ::
$ pip install . --user
Ptypy depends on standard python packages:
| We support an accelerated version of | ptypy | for CUDA-capable GPUs based on our own kernels and the
CuPy <https://cupy.dev/>_ package. We recommend to install the dependencies for this version like so. |
|---|
$ conda env create -f accelerate/cuda_cupy/dependencies.yml
$ conda activate ptypy_cupy
(ptypy_cupy)$ pip install .| The complete documentation <http://ptycho.github.io/ptypy/content.html#contents>_ .
| Starting from a clean slate?
| Check out the installation instructions <http://ptycho.github.io/ptypy/rst/getting_started.html#installation>_ .
| You want to understand the inner principles of ptypy without
having to browse the source code?
| Have a look at the tutorials about its special classes <http://ptycho.github.io/ptypy/rst/concept.html#concepts>_ .
| Only interested in |ptypy|'s data file structure and
management? Indulge yourself here <http://ptycho.github.io/ptypy/rst/data_management.html#ptyd-file>__ for the structure and here <http://ptycho.github.io/ptypy/rst/data_management.html#ptypy-data>__ for the concepts.
<http://github.com/ptycho/ptypy/issues>_<http://github.com/ptycho/ptypy>_If you are having issues, please let us know.
.. |ptypy| replace:: PtyPy
.. |ptypysite| image:: https://ptycho.github.io/ptypy/_static/logo_100px.png :target: https://ptycho.github.io/ptypy/
.. [#pronounciation] Pronounced typy, forget the p, as in psychology.
.. [#ptypypaper] B.Enders and P.Thibault, Proc. R. Soc. A 472, doi <http://doi.org/10.1098/rspa.2016.0640>__
.. [#states] P.Thibault and A.Menzel, Nature 494, 68 (2013), doi <http://dx.doi.org/10.1038/nature11806>__
.. [#dm] P.Thibault, M.Dierolf et al., Science 321, 7 (2009), doi <http://dx.doi.org/10.1126/science.1158573>__
.. [#ml] P.Thibault and M.Guizar-Sicairos, New J. of Phys. 14, 6 (2012), doi <http://dx.doi.org/10.1088/1367-2630/14/6/063004>__
.. [#power] K.Giewekemeyer et al., PNAS 108, 2 (2007), suppl. material <https://www.pnas.org/doi/10.1073/pnas.0905846107#supplementary-materials>, doi <https://doi.org/10.1073/pnas.0905846107>