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Analysis & Applications group works on PSANA project - generic framework for analysis of any experimental data. Though this framework is going to be universal, most likely it will not be simple. In this page we discuss a simple but flexible approach to analysis of data stored in HDF5 files. It is based on Python code with extensive exploitation of standard libraries. A few code examples of how to access and process data are presented at the end of this page.

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• Flexibility; HDF5 file has indexed structure, that means direct access to any data of any file from your code.
• Python is a high-level scripting language allows to write transparent and compact code based on well-elaborated standard libraries.
• In general, code in Python works slow comparing to C++, but there are libraries like NumPy written on C++, which solve this problem for manipulation with large arrays.

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• you have to know or learn Python
• current version of the h5py library works quite slow with long HDF5 files

The first issue about Python is not really a drawback. Basic concept of this high-level language can be learned from scratches for about a couple of days. In a week you will feel yourself as an expert and will enjoy programming on this powerful language. Second issue about slow h5py library is really annoying, but we hope that authors will account for our comments and its performance can be improved soon.

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