dragonboard_testbench

A collection of programs to help with DRS4 calibration of the LST test data of the dragon_cam.

Installation

The easiest way to install this is to use the (Python Conda Distribution)[https://www.continuum.io/downloads]. Once installed you can install some dependencies using

conda install numpy scipy pandas matplotlib pytables pyqt=5

Now you can install the dragonboard_testbench by using pip

pip install git+https://github.com/cta-observatory/dragonboard_testbench

or, if you are developing

git clone http://github.com/cta-observatory/dragonboard_testbench
pip install -e dragonboard_testbench

Usage

DragonViewer

Use the dragonviewer executable to view some data, it is in your $PATH after you installed this module.

dragoviewer [<inputfile>]

If you do not provide <inputfile>, a file dialog will open

Scripts

Use python offset_calculation.py <inputfiles> ... [options] to convert raw data.dat files to .hdf5 files that can be used by further scripts.

Use python fit_delta_t.py <inputfile> <outputfile> [options] to calculate a powerlaw fit a*x^b+c for every cell.

Use python calibration_performance.py <inputfile> <fit_constants> <offsets> <outputfile> [options] to plot an overview of the performance of all calibration techniques

Running the tests

We are using pytest, install with

$ conda install pytest

or, if you are not using anaconda,

pip install pytest

You can then run the tests using:

py.test

in the base directory, the output could look like this if everything goes well:

$ py.test
===================== test session starts ============================
platform linux -- Python 3.5.1, pytest-2.8.5, py-1.4.31, pluggy-0.3.1
rootdir: /home/maxnoe/Uni/CTA/dragonboard_testbench, inifile: 
collected 2 items 

dragonboard/tests/test_runningstats.py ..

================== 2 passed in 0.28 seconds ==========================