Hall A Analyzer

h1. Software Setup Instructions for 2018 Hall A & C Data Analysis Workshop

In order to run the interactive tutorials, certain software should be available to you:

* @bash@ (shell)

* @git@ (version control)

* ROOT with Python bindings

* Hall C analyzer (@hcana@)

* Python 2.7 and/or 3.4+

* Various Python packages, all available via pip:

** numpy

** scipy

** matplotlib

** pandas

** uproot

** ipython

** notebook

Scripts and data files can be downloaded/accessed over the network during the workshop.

There are essentially three approaches to get a usable software environment, in order of preference:

# *Recommended:* Use our pre-configured "Virtual Machine Image":https://hallaweb.jlab.org/data_reduc/AnaWork2018/VirtualBox/ for "VirtualBox":https://www.virtualbox.org/. This will yield consistent results on all supported platforms (Windows, macOS, recent Linuxes), but will consume significantly more system resources than a native installation. The installation of VirtualBox may be challenging on some Linux systems. 

# Install all required software locally on your machine. This will yield the fastest performance, but may be time-consuming and error-prone. Installation on Windows can be challenging since much of the software and scripts is designed for a Unix-like environment. Recommended for advanced users.

# Access a machine with a suitable environment remotely, _e.g._ the JLab @ifarm@ systems. This is a last resort since performance will be lower and there may still be compatibility problems. For graphics, your system requires an X server installed locally.

If your machine is reasonably powerful (_e.g._ i5 CPU, 4+ GB RAM, 30-40 GB free disk space) and runs a recent OS, your best bet is probably our "Virtual machine":https://hallaweb.jlab.org/data_reduc/AnaWork2018/VirtualBox/ since the environment is completely set up and configured for the workshop exercises. See the download directory for "detailed instructions":https://hallaweb.jlab.org/data_reduc/AnaWork2018/VirtualBox/Instructions.txt.

If you feel comfortable installing software on your system and/or you already have much of the required software available, option 2. may be for you. You can find some guidance here:

* "JLab 2018 Software Carpentry Workshop Setup Instructions":https://kevin-vilbig.github.io/2018-05-21-JLAB/ (covers @bash@, @git@ and @Python@, even for Windows)

* [[ROOT Installation Guide|ROOT Installation Guide]]

* "Hall C Analyzer Installation Guide":https://hallcweb.jlab.org/wiki/index.php/ROOT_Analyzer/Git

Please start well in advance of the workshop.

Connecting to @ifarm@ or some other remote system (_e.g._ your office desktop) requires an @ssh@ client with X forwarding and an X server. On @ifarm@, do

<pre>

ifarm> source /apps/root/6.12.06/setroot_CUE

</pre>

to set up ROOT as well as a Python3 environment that has all the required packages. Unfortuantely, performance will be slow because @ifarm@ is a busy system that you share with many other users. As mentioned, do this as a last resort.

Please contact Ole Hansen (ole@jlab.org) with questions.