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Getting Started

Requirements

At least Python version 2.6 and ROOT with PyROOT enabled. matplotlib, numpy, PyTables, and PyYAML are optional.

Install

The easiest way to install rootpy is with pip. To install for all users:

sudo pip install rootpy

To install in your home directory:

pip install --user rootpy

If you have obtained a copy of rootpy yourself use the setup.py script to install. To install for all users:

sudo python setup.py install

To install in your home directory:

python setup.py install --user

To install the optional requirements (first download a source distribution if you haven't already):

pip install -U -r optional-requirements.txt

Getting the latest source

Clone the code from github with git:

git clone git://github.com/rootpy/rootpy.git

or checkout with svn:

svn checkout http://svn.github.com/rootpy/rootpy

Watch rootpy do tricks

Ever wish browsing through a ROOT file were as easy as navigating a filesystem in the shell? Try roosh:

$ roosh testfile.root
Welcome to the ROOSH terminal
type help for help
testfile.root > ls
dimensions  efficiencies  gaps  graphs  means  scales
dimensions > cd means/
means > ls
hist1  hist2  hist3  hist4

Ever wish that accessing objects in a ROOT file didn't involve so much writing? rootpy understands:

>>> from rootpy.io import File
>>> from rootpy.test import filename
>>> testfile = File(filename, 'read')             # File wraps ROOT.TFile
>>> for top, dirs, objects in testfile: print top # in analogy to os.walk
...

dimensions
scales
means
graphs
gaps
efficiencies
>>> hist = testfile.efficiencies.hist1            # no need for GetDirectory

Ever wish manipulating ROOT objects were more pythonic? rootpy does that:

>>> from rootpy.test import testfile
>>> hist = testfile.means.hist1
>>> list(hist)                                    # pythonic access to histogram contents
[204.0, 478.0, 771.0, 975.0, 947.0, 721.0, 431.0, 238.0, 94.0, 22.0, 6.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
>>> hist[0]                                       # bin indices start at 0
204.0
>>> hist[-1]                                      # ...support negative values
0.0
>>> hist[3:5]                                     # ...and can handle slicing
[975.0, 947.0]
>>> hist.xedges(-1)                               # added convenience methods
50.0
>>> hist += testfile.means.hist2                  # operators act like you'd expect