Tutorials¶
This page lists the Gammapy tutorials that are available as Jupyter notebooks.
You can read them here, or execute them using a temporary cloud server in Binder.
To execute them locally, you have to first install Gammapy locally (see
Installation) and download the tutorial notebooks and example datasets (see
Getting Started). Once Gammapy installed, remember that you can always
use gammapy info to check your setup.
Gammapy is a Python package built on Numpy and Astropy, so to use it effectively, you have to learn the basics. Many good free resources are available, e.g. A Whirlwind tour of Python, the Python data science handbook and the Astropy Hands-On Tutorial.
Notebooks¶
Getting started
The following tutorials show the same 3D cube analysis of the Crab with the high level interface and with the lower level API:
First analysis | analysis_1.ipynb
Second analysis | analysis_2.ipynb
What data can I analyse?
CTA with Gammapy | cta.ipynb
H.E.S.S. with Gammapy | hess.ipynb
Fermi-LAT with Gammapy | fermi_lat.ipynb
Analyses
3-dim sky cube analysis
CTA data analysis with Gammapy | cta_data_analysis.ipynb
3D analysis | analysis_3d.ipynb
Multi instrument joint 3D and 1D analysis | analysis_mwl.ipynb
2-dim sky image analysis
2D map analysis | image_analysis.ipynb
Source detection | detect.ipynb
1-dim spectral analysis
Spectral analysis | spectrum_analysis.ipynb
Flux point fitting | sed_fitting.ipynb
Time-dependent analysis
Light curves | light_curve.ipynb
Light curves for flares | light_curve_flare.ipynb
Simulations, Sensitivity, Observability
3D map simulation | simulate_3d.ipynb
1D spectrum simulation | spectrum_simulation.ipynb
Point source sensitivity | cta_sensitivity.ipynb
Gammapy package
Overview | overview.ipynb
Maps | maps.ipynb
Modeling and Fitting | modeling.ipynb
Models Gallery | models.ipynb
Source catalogs | catalog.ipynb
Extra topics¶
These notebooks contain examples on some more specialised functionality in Gammapy.
Dark matter spatial and spectral models | astro_dark_matter.ipynb
Make template background model | background_model.ipynb
MCMC sampling of Gammapy models using the emcee package | mcmc_sampling.ipynb
Pulsar analysis with Gammapy | pulsar_analysis.ipynb