SciBeam¶
SciBeam is a python package build on top of pandas, numpy, sicpy and matplotlib. It is aimed for quick and easy scientific time-series data analysis and visualization in physics, optics, mechanics, and many other STEM subjects.
In the context of scientific data analysis, there are a lot of situations that people have to deal with time-series data, such as time dependent experiment(e.g. temperature measurement), dynamic processes(e.g. beam propagation, chemical reaction), system long/short term behavior(e.g. noise), etc. Quite often is that data taking and result analysis is gaped by some time and effort, which could result in complains or regrets during the data analysis, like “I wish I took another measurement of … so than I could explain why …”. As such, the general guidline of scibeam is to bridge the gap between measurement and data analysis, so that time-series related experiment can be done in a more guided way.
The basic features of scibeam include but not limited to: beam propagation, single or multi-dimentional time depedent measurement, data file auto indexing, noise reduction, peak analysis, numerical fittings, etc.
Note
scibeam doesn’t support python 2.7, make sure you have the right python version (>=3.4).
GETTING STARTED
THE SCIBEAM PACKAGE
- scibeam.core package
- Submodules
- scibeam.core.base module
- scibeam.core.common module
- scibeam.core.descriptor module
- scibeam.core.dictfunc module
- scibeam.core.formatter module
- scibeam.core.gaussian module
- scibeam.core.numerical module
- scibeam.core.peak module
- scibeam.core.plot module
- scibeam.core.regexp module
- scibeam.core.tofframe module
- scibeam.core.tofseries module
- Module contents