A Python MuSR data analysis graphical interface, based on classes, designed for jupyter.
Released under the MIT licence.
v. 2.0.alpha major refactoring. For the time being works only via jupyter-lab notebooks (mugui is broken) Once cloned, run:
jupyter-laband launch the example/Tst_xxx.ipynb notebooks (check path to suitable data files for the tested type of fit)
Each notebook shows how to perform * TF calibration, both single group (A1-calib) and multigroup (A2-calib), either sequential or global * single run fit (A1), * sequential single run fits (B1), * single run multi-group fit (A2), either sequential or global with plots: static for single fit, animated plots for multiple fits (both sequential or global) and optional fft
Linux installation instructions, Valid on WIN10 that has a linux shell, to come. Docs not updated yet
----Old installation instructions (v 1.1) * Make sure you have python, standard on linux, and jupyter lab. Otherwise install them (see https://docs.python.org/3/using/windows.html, https://docs.python.org/3/using/mac.html, jupyter.readthedoc.io). * Install mujpy. Clone or download from https://github.com/RDeRenzi/mujpy, unzip into the directory of your choice:
cd mujpy/mujpy/musr2py
make
sudo make install- Check dependencies, see requirements.txt. When the first mujpy release is on Pipy, pip will sort this out.
Start jupyter lab:
jupyter-lab- Copy example/Tst_xxx_ipynb to a path of your choice and modify path /home/roberto.derenzi/mujpy/log/ accordingly
Documentatation on the GUI usage at http://mujpy.readthedocs.io/en/latest/ obsolete. DOcs to come