Quickstart Guide

This page walks through the steps to setup and perform a basic analysis of two dark matter targets, the “Segue 1” and “Draco” dwarf spheroidal galaxies.

Getting input data

First, you will need get Fermi-LAT data to analyze. In particular you will need:

  • An event list, a so-called ‘FT1’ file with event data.
  • The correspond spacecraft pointing history file: the so-called ‘FT2’ file.
  • A ‘livetime’ htype cube of the amout of time each direction in the sky was at a particular direction with respect to the LAT instrument boresight.

Running the example notebook

First, download the configuration files and python notebook for this analysis

$ curl -OL https://raw.githubusercontent.com/fermiPy/fermipy-extras/master/data/dmpipe_example.tar.gz
$ tar zxvf dmpipe_example.tar.gz
$ cd dmpipe_example
$ curl -OL https://raw.githubusercontent.com/fermiPy/fermipy-extras/master/notebooks/dSphs.ipynb

Now you need to do two things to set up to run the example notebook

  • Point the dmksy package at the target “Roster” you just downloaded. .. code-block:: bash

    $ export DMSKY_PATH=<current_dir>

  • Edit the ‘config/config_dSphs.yaml’ file so that the ‘evfile’, ‘ltcube’, and ‘scfile’ lines refer to the input data you set up above.

Now you can run the example notebook.

$ jupyter-notebook dSphs.ipynb

Running the analysis

Every step of the analysis, including the top-level script that runs the entire analysis, can be invoked directly from the UNIX command line:

$ dmpipe-pipeline --config config/master_dSphs.yaml

Extracting Analysis Results

The analysis pipeline produces a number of different outputs, including:

  • Combined plots of the DM interaction limits for the stacked analysis, as well as plots showing the results of the control tests. These are in the dSphs/results directory.
  • Indvidual plots of the SEDs and the DM interaction limits for each target in the analysis.
  • Detailed intermediate results allowing the user to preproduce any plot or to refit any ROI or reproduce any other step of the analysis chain in isolation.

Loading and running interactively

One can load the pipeline interactively in python, and see the current status of the analysis.

from dmpipe import Pipeline
configfile = 'config/master_dSphs.yaml'
pipe = Pipeline(linkname='dSphs')
pipe.preconfigure(configfile)
pipe.update_args(dict(config=configfile))

# look at the current state
pipe.print_status()

# Continue running analysis starting from the previously saved
# state
pipe.run()

Many other commands are demonstrated in the jupyter notebook example.