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Copyright (2015-2018) C. Le Losq.
Rampy is a Python library that aims at helping processing spectroscopic data, such as Raman, Infrared or XAS spectra. It offers, for instance, functions to subtract baselines as well as to stack, resample or smooth spectra. It aims at facilitating the use of Python in processing spectroscopic data. It integrates within a workflow that uses Numpy/Scipy as well as optimisation libraries such as lmfit or emcee, for instance.
The /examples/ folder contain various examples.
Rampy is tested on Python 2.7 and 3.6 (see Travis badge; no garantee that it works on other Python versions)
The following libraries are required and indicated in setup.py:
- Scipy
- Numpy >= 1.12
- sklearn
- pandas
Optional dependencies:
- gcvspline (you need a working FORTRAN compiler for its installation... Warning Windows users! Check you FORTRAN compiler!)
Installation of gcvspline is strongly recommended for use of the rampy.rameau() class.
Additional libraries for model fitting may be wanted:
- lmfit & aeval (http://cars9.uchicago.edu/software/python/lmfit/)
- emcee
Install with pip:
pip install rampy
If the installation fails at the stage where gcvspline is installed, and seems related to a problem with FORTRAN compilation, please check the status of your FORTRAN compiler.
The fastest way will be to upload any fortran code and try building it.
OSX Sierra and High Sierra may run into problems with the assembler in some case, fixed by adding the line
export PATH="/usr/bin/$PATH"
in the .bash_profile file.
See the /example folder.
Updated February 2018