SAPPHiRE — A Framework for HiSPARC
SAPPHiRE is a Simulation and Analysis Program Package for HiSPARC Research and Education. It was created in the process of completing the PhD research of David Fokkema. The history of this repository contains the complete simulation, analysis and plot generation code that formed the basis for David's thesis. Arne de Laat took over development of SAPPHiRE while working on his own PhD research.
This repository is created with a sole purpose in mind: to enable HiSPARC students, teachers and researchers to easily gain access to the data and perform common simulation and analysis tasks. Historically, starting work on the data, or extending an existing analysis code, has involved elaborate installation instructions, heavy customizations to the software, countless hours going over opaque parts of code and a general feeling of anguish and despair. SAPPHiRE's ultimate goal: no more of that.
Required: Python 2.7. pip will take care of dependencies, but installing numpy, scipy and pytables from a python distribution is preferred. We use miniconda, which includes the conda package manager.
First, install conda and optionally create a virtualenv:
$ conda create --name hisparc python=2.7 numpy scipy pytables $ source activate hisparc
or alternatively just install the dependencies:
$ conda install numpy scipy pytables
Then, using pip:
$ pip install hisparc-sapphire
This should install sapphire with all requirements. More extensive
installation instructions are available in the documentation in the
doc/ directory. You can compile them using Sphinx, or you can
follow this link: http://docs.hisparc.nl/sapphire/.
To check if it worked start Python and load the package:
Install python 2.7 (preferably using conda) as described above but clone the sapphire repo instead of installing using pip:
$ git clone https://github.com/HiSPARC/sapphire.git $ cd sapphire $ python setup.py develop
Important: First check if the last commit passes the tests on Travis CI!
To release a new version modify the version number in
create a commit for the new release with a title like 'Bump version to vX.Y.Z'
and a message that contains a summary of the most important changes since the
last release. Then tag the commit and push it to GitHub:
$ git tag vX.Y.Z $ git push --tags
Then upload the new version to PyPI (this requires the
$ python setup.py sdist bdist_wheel upload
The latest version is then available from PyPI.