PyWI CTA wrapper - a signal processing library for Imaging Atmospheric Cherenkov Telescopes
Project description
PyWI CTA - A CTA wrapper for PyWI
Copyright (c) 2016-2018 Jeremie DECOCK (www.jdhp.org)
Online documentation: https://jeremiedecock.github.io/pywi-cta/
Source code: https://github.com/jeremiedecock/pywi-cta
Issue tracker: https://github.com/jeremiedecock/pywi-cta/issues
PyWI-CTA on PyPI: https://pypi.org/project/pywicta/
PyWI-CTA on Anaconda Cloud: https://anaconda.org/jdhp/pywicta
Description
PyWI-CTA is a ctapipe wrapper for PyWI.
Note:
This project is in beta stage.
Dependencies
PyWI-CTA has the following strict requirements:
PyWI-CTA also depends on other packages for optional features:
Pillow (a.k.a. PIL) to read and write many image formats (PNG, JPEG, TIFF, …)
Astropy to provide Fits file format
Matplotlib 1.5 or later to provide plotting functionality
However, note that these only need to be installed if those particular features are needed. pywicta will import even if these dependencies are not installed.
Installation
PyWI-CTA and its dependencies may be installed using the Anaconda or Miniconda package system. We recommend creating a conda virtual environment first, to isolate the installed version and dependencies from your master environment (this is optional).
The following command will set up a conda virtual environment, add the necessary package channels, and download PyWI-CTA and its dependencies. The file environment.yml can be found in this repository. Note this is beta stage software and is not yet stable enough for end-users (expect large API changes until the first stable 1.0 release).
conda env create -n pywi-cta -f environment.yml source activate pywi-cta pip install pywicta --no-deps
If you have already installed ctapipe following the official installation procedure, you can add PyWI-CTA to the cta virtual environment like this:
source activate cta pip install pywicta --no-deps
Developers should follow the development install instructions found in the documentation.
Cosmostat iSAP Sparce2D installation
Download http://www.cosmostat.org/wp-content/uploads/2014/12/ISAP_V3.1.tgz (see http://www.cosmostat.org/software/isap/)
Unzip this archive, go to the “sparse2d” directory and compile the sparse2d library. It should generate two executables named mr_transform and mr_filter:
tar -xzvf ISAP_V3.1.tgz cd ISAP_V3.1/cxx tar -xzvf sparse2d_V1.1.tgz cd sparse2d compile the content of this directory
An automated compilation and installation script for Linux is available here (author: Tino Michael).
Example
Get a simtel file (e.g. from there)
In your system terminal, from the directory that contains the sample image, type the following commands (where SIMTEL_FILE is the path to your simtel file):
pywicta-mrtransform -f common_hard_filtering -t 13.,1.5 -L mask --camid LSTCam --max-images 1 --plot SIMTEL_FILE pywicta-mrfilter -K -k -C1 -m3 -n4 -s2,4.5,3.5,3 --kill-isolated-pixels --camid LSTCam --max-images 1 --plot SIMTEL_FILE
Type pywicta-mrtransform -h or pywicta-mrfilter -h to display the list of available options and their documentation.
IPython/Jupyter Notebooks
PyWI provide some Jupyter notebooks that can be used as examples or tutorials.
PyWI Notebooks on GitHub: https://github.com/jeremiedecock/pywi-cta-notebooks
PyWI Notebooks on Anaconda Cloud: https://anaconda.org/jdhp/notebooks
Bug reports
To search for bugs or report them, please use the PyWI Bug Tracker at:
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