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A web database for experimental results of research
A database with a web interface for storing the experimental results of research, aimed at ease of adding new types of data. Goal is to make adding as simple as one day for an unexperienced in programming scientist to add a new type of data similar to an existing type, by preparing two - three files analogues to the existing ones. An experienced programmer should need only one day to one week for adding a totally new kind of data like arrays with more dimensions that was available before.
The Plot.py project tries to supply a measurement data visualization and treatment framework being easy to use while keeping the freedom for advanced users to execute additional data treatment algorithms.
Plotting is done via gnuplot and the script used to produce the graphs can be exported for later use/changes.
Many raw experimental data types (mostly of x-ray and neutron scattering experiments) are supported with more to be added on user request.
The data treatment includes non-linear fitting, integration and differentiation, peak-finder and more. User python code can be executed in the integrated IPython console.
Python library to perform electronic structure calculations with tight binding models in different types of lattices and different dimensionalities. It allows to include different terms in the Hamiltonian as sublattice, exchange field or magnetic field. Provides functions to calculate different Green functions, band structure, density of states, transport using Landauer formula, topological invariants, etc.
DiagSim is a collection of Python modules for simulating beam diagnostics in particle accelerators, at the moment only cavity BPMs, with other types of BPMs and other diagnostics to follow. Or so we think. Anyway, we use beam data exported from beam trackers, trace the signals through the diagnostics and processing, so that they can be processed as real data, and the input and measured beam parameters can be compared.
Dimenso is a library of numeric types for .Net and Java, that obey dimensional analysis and permit calculations with physical quantities. Due to the lack of C++ - like templates with numeric arguments, code generation is employed using Python.