pywicta 0.1.dev18

PyWI CTA wrapper - a signal processing library for Imaging Atmospheric Cherenkov Telescopes

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 on PyPI: https://pypi.org/project/pywicta/

• PyWI 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 has the following strict requirements:

• Python 3.5 or 3.6

• Numpy

PyWI also depends on other packages for optional features:

• Scipy

• Scikit-image

• Pillow (a.k.a. PIL) to read and write many image formats (PNG, JPEG, TIFF, …)

• Astropy to provide Fits file format

• Pandas

• Matplotlib 1.5 or later to provide plotting functionality

• PyWI

• Cosmostat iSAP Sparce2D

However, note that these only need to be installed if those particular features are needed. PyWI will import even if these dependencies are not installed.

Installation

Using pip

Most major projects upload official packages to the Python Package Index. They can be installed on most operating systems using Python standard pip package manager.

Note that you need to have Python3.x and pip already installed on your system.

Warning

Users of the Anaconda python distribution should follow the instructions for Anaconda install (see Using conda bellow).

Note

You will need a C compiler (e.g. gcc or clang) to be installed to install some dependencies (e.g. Numpy).

Note

The --no-deps flag is optional, but highly recommended if you already have Numpy installed, since otherwise pip will sometimes try to “help” you by upgrading your Numpy installation, which may not always be desired.

Note

If you get a PermissionError this means that you do not have the required administrative access to install new packages to your Python installation. In this case you may consider using the --user option to install the package into your home directory. You can read more about how to do this in the pip documentation.

Alternatively, if you intend to do development on other software that uses PyWI, such as an affiliated package, consider installing PyWI into a virtualenv.

Do not install PyWI or other third-party packages using sudo unless you are fully aware of the risks.

On MacOSX and Gnu/Linux

You can install PyWI using the following command (in a terminal):

pip install pywicta --no-deps

As an alternative, you can install PyWI from the downloaded source code:

python3 setup.py install --no-deps

If PyWI is already installed on your system you can upgrade it with this command:

pip install --upgrade pywicta

To uninstall PyWI, type:

pip uninstall pywicta

On Windows

You can install PyWI using the following command (in a command prompt):

py -m pip install pywicta --no-deps

As an alternative, you can install PyWI from the downloaded source code:

py setup.py install --no-deps

If PyWI is already installed on your system you can upgrade it with this command:

py -m pip install --upgrade pywicta

To uninstall PyWI, type:

py -m uninstall pywicta

Using conda

To install this package with conda run in a terminal:

conda install -c jdhp pywicta

So far, the PyWI Anaconda package is only available for MacOSX. A package for Linux and Windows will be available soon.

Note

Attempting to use pip to upgrade your installation of PyWI may result in a corrupted installation.

Cosmostat iSAP Sparce2D installation

1. Download http://www.cosmostat.org/wp-content/uploads/2014/12/ISAP_V3.1.tgz (see http://www.cosmostat.org/software/isap/)

2. 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 there (author: Tino Michael).

Example

1. Get a simtel file (e.g. from there)

2. 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

3. 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:

https://github.com/jeremiedecock/pywi-cta/issues