Pyspectr provides nuclear spectroscopy tools, specifically targeted to use with the his/drr histogram files used by the upak library. Apart from reading the binary input files, it provides some tools like half-life fitting, peak-fitting and pydamm program, mimicking the DAMM program from the upak. Users are encouraged to use pydamm within ipython3 shell, as it offers a great advantages over standard python3 shell, such as tab-completion with history search, input/outputs registry (as in Maxima or Mathematica), etc. However, it is also possible to work with pydamm within the standard python3 shell.
This package requires the following modules:
- numpy (http://www.numpy.org/)
- matplotlib (http://matplotlib.org/, https://github.com/matplotlib/matplotlib)
- lmfit (https://github.com/newville/lmfit-py, http://cars9.uchicago.edu/software/python/lmfit/)
It is also recommended to install the ipython shell:
- ipython (http://ipython.org/) (make sure it links to python3 or use ipython3) However, the standard python shell will also work.
In a typical Linux distribution the numpy, matplotlib and ipython should be included in the package manager repositories (note that python3 version is needed). If they are missing the github repositories include information about the building and installation procedure (it is very simple). The lmfit library on the github includes the standard pythons distutils setup script and is also very easy to install.
!!! Now on Pypi.org !!! All you need now is: $ pip3 install scipy (or only matplotlib and numpy) $ pip3 install lmfit $ pip3 install Pyspectr and you should be good to go.
or via: Once the required libraries are in place, install the Pyspectr with: python3 setup.py build sudo python3 setup.py install
Happy New Year (1/2/2020)! New functions added for histogram adding, histogram file zeroing, and some other requested capability for log state persistence and count display.
Important note for use with ipython3! in order to have the correct interactivity functionality begin the ipython session with the magic command %matplotlib.
In [1]: %matplotlib
and/or use the startup script 00-pyspectr.py in the directory ~/.ipython/profile_default/startup/ (Linux) or similar for other distros. This magic puts matplotlib interactivity in the correct shell loop. See ipython documentation for further detail.
Pydamm is a DAMM-like python module, so a typical session starts with importing the pydamm module:
from Pyspectr.pydamm import *
The main class for the data analysis is the Experiment, it requires a file name (.his) to be given in the constructor:
e = Experiment('data_file.his') or tar gzipped file (.tgz, .tar.gz): e = Experiment('data_file.tgz')
Once the Experiment object is created follow DAMM-like syntax to display and analyze the data:
e.d(100) e.dl(0, 1000) e.gx(1000, (212, 214)) ...
However, there are some useful things that the DAMM couldn't do easily. Check functions like Experiment.show_registry(), Experiment.gamma_gamma_spectra(), Experiment.fit_decay(), ...
Finally remember about the python's build-in help(), that should allow you to investigate the available variables and methods. While the documentation is far from being perfect, at least it should give you a hint about possibilities.
This script fits the peaks in a .his or .txt spectrum file. The peak function include the Gaussian function, skewed Gaussian and more. The fit configuration is done via XML config file, see spectrum_fitter_example.xml
This script fits the grow-in/decay pattern, typical in the experiments with the Moving Tape Collector. Available models include 1st and 2nd isotope in the chain, isomeric decay, diffusion corrected decay and more. See grow_decay_example.xml for XML config file structure.
This script is placed in the startup directory for proper functionality of Pyspectr/matplotlib interactivity.