# Using Gammapy#

To use Gammapy you need a basic knowledge of Python, Numpy, Astropy, as well as matplotlib for plotting. Many standard gamma-ray analyses can be done with few lines of configuration and code, so you can get pretty far by copy and pasting and adapting the working examples from the Gammapy documentation. But eventually, if you want to script more complex analyses, or inspect analysis results or intermediate analysis products, you need to acquire a basic to intermediate Python skill level.

## Jupyter notebooks#

To learn more about Gammapy, and also for interactive data analysis in general, we recommend you use Jupyter notebooks. Assuming you have followed the steps above to install Gammapy and activate the conda environment, you can start JupyterLab like this:

\$ jupyter lab

If you haven’t used Jupyter before, try typing print("Hello Jupyter") in the first input cell, and use the keyboard shortcut SHIFT + ENTER to execute it.

## Python#

Gammapy is a Python package, so you can of course import and use it from Python:

\$ python
Python 3.6.0 | packaged by conda-forge | (default, Feb 10 2017, 07:08:35)
[GCC 4.2.1 Compatible Apple LLVM 7.3.0 (clang-703.0.31)] on darwin
>>> from gammapy.stats import CashCountsStatistic
>>> CashCountsStatistic(n_on=10, mu_bkg=4.2).sqrt_ts
2.397918129147546

## IPython#

IPython is nicer to use for interactive analysis:

\$ ipython
Python 3.6.0 | packaged by conda-forge | (default, Feb 10 2017, 07:08:35)
IPython 6.5.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: from gammapy.stats import CashCountsStatistic

In [2]: CashCountsStatistic(n_on=10, mu_bkg=4.2).sqrt_ts
Out[2]: array([2.39791813])

For example you can use ? to look up help for any Gammapy function, class or method from IPython:

In [3]: CashCountsStatistic?

Of course, you can also use the Gammapy online docs if you prefer, clicking in links (i.e. gammapy.stats.CashCountsStatistic) or using search docs field in the upper left.

As an example, here’s how you can create gammapy.data.DataStore and gammapy.data.EventList objects and start exploring H.E.S.S. data:

from gammapy.data import DataStore
data_store = DataStore.from_dir('\$GAMMAPY_DATA/hess-dl3-dr1/')
events = data_store.obs(obs_id=23523).events
print(events)
EventList
---------
<BLANKLINE>
Instrument       : H.E.S.S. Phase I
Telescope        : HESS
Obs. ID          : 23523
<BLANKLINE>
Number of events : 7613
Event rate       : 4.513 1 / s
<BLANKLINE>
Time start       : 53343.92234009259
Time stop        : 53343.94186555556
<BLANKLINE>
Min. energy      : 2.44e-01 TeV
Max. energy      : 1.01e+02 TeV
Median energy    : 9.53e-01 TeV
<BLANKLINE>
Max. offset      : 58.0 deg

Try to make your first plot using the gammapy.data.EventList.peek helper method:

import matplotlib.pyplot as plt
events.peek()
plt.savefig("events.png")

## Python scripts#

Another common way to use Gammapy is to write a Python script. Try it and put the following code into a file called example.py:

"""Example Python script using Gammapy"""
from gammapy.data import DataStore
data_store = DataStore.from_dir('\$GAMMAPY_DATA/hess-dl3-dr1/')
events = data_store.obs(obs_id=23523).events
print(events.energy.mean())
4.418007850646973 TeV

You can run it with Python:

\$ python example.py
4.418007850646973 TeV

If you want to continue with interactive data or results analysis after running some Python code, use IPython like this:

\$ ipython -i example.py

For examples how to run Gammapy analyses from Python scripts, see Survey Map Script.