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SiLab-Bonn / Scarce

Charge collection efficiency simulation for irradiated silicon detectors.
MIT License
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=============================================== Introduction

|travis-status| |appveyor-status| |rtd-status| |coverage|

Scarce stands for s\ ilicon c\ h\ ar\ ge c\ ollection e\ fficiency and is a software to calculate the charge collection-efficiency of irradiated and segmented silicon sensors. Planar and 3D electrode configurations are supported. Additionally a collection of formulars is provided to calculate silicon properties.

Installation

The installation works with Linux and Windows. Mac OS might also work.

Linux

This installation has been tested with Ubuntu 14.04 LTS 64-bit and Anaconda Python 2.7 64-bit.

  1. Install the mesh creator gmsh:

.. code-block:: bash

sudo apt-get install gmsh

  1. Install Anaconda Python distribution:

.. code-block:: bash

wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh

For more information visit: https://www.continuum.io/downloads

  1. Install precompiled dependencies:

.. code-block:: bash

conda install numpy pytables scipy matplotlib

  1. Install sparse matrix solver (optional, increases speed):

.. code-block:: bash

pip install -e git://pysparse.git.sourceforge.net/gitroot/pysparse/pysparse#egg=PySparse ez_setup

  1. Download Scarce:

.. code-block:: bash

git checkout https://github.com/SiLab-Bonn/Scarce

  1. Install Scarce in development mode by typing:

.. code-block:: bash

cd Scarce && python setup.py develop

Windows

This installation has been tested with Windows 7 64-bit and Anaconda Python 2.7 64-bit.

  1. Install the mesh creator gmsh that can be donwloaded here:

.. code-block:: bash

http://gmsh.info/bin/Windows/gmsh-2.14.1-Windows64.zip

  1. Install 64-bit Anaconda Python 2.7 distribution that can be donwloaded here: https://www.continuum.io/downloads#windows

  2. Install precompiled dependencies by typing into the command prompt:

.. code-block:: bash

conda install numpy pytables scipy matplotlib

  1. Download Scarce here and unpack to a folder of your choise: https://github.com/SiLab-Bonn/Scarce/archive/master.zip

  2. Install Scarce in development mode by typing:

.. code-block:: bash

python setup.py develop

.. |travis-status| image:: https://travis-ci.org/SiLab-Bonn/Scarce.svg?branch=master :target: https://travis-ci.org/SiLab-Bonn/Scarce :alt: Build status

.. |appveyor-status| image:: https://ci.appveyor.com/api/projects/status/32o1x5kcss45m35d?svg=true :target: https://ci.appveyor.com/project/DavidLP/scarce :alt: Build status

.. |rtd-status| image:: https://readthedocs.org/projects/scarce/badge/?version=latest :target: http://scarce.rtfd.org :alt: Documentation

.. |coverage| image:: https://coveralls.io/repos/github/SiLab-Bonn/Scarce/badge.svg?branch=master :target: https://coveralls.io/github/SiLab-Bonn/Scarce?branch=master :alt: Coverage