.. include:: references.txt .. _tutorials: Tutorial notebooks ================== 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 and download the tutorial notebooks and example datasets. The setup steps are described in :ref:`getting-started`. Once Gammapy installed, remember that you can always use ``gammapy info`` to check your setup. .. _tutorials_notebooks: Notebooks --------- .. toctree:: :hidden: notebooks/first_steps.ipynb notebooks/intro_maps.ipynb notebooks/cta_1dc_introduction.ipynb notebooks/cta_data_analysis.ipynb notebooks/analysis_3d.ipynb notebooks/analysis_3d_joint.ipynb notebooks/simulate_3d.ipynb notebooks/hess.ipynb notebooks/detect_ts.ipynb notebooks/image_fitting_with_sherpa.ipynb notebooks/spectrum_analysis.ipynb notebooks/spectrum_fitting_with_sherpa.ipynb notebooks/sed_fitting_gammacat_fermi.ipynb notebooks/fermi_lat.ipynb notebooks/light_curve.ipynb notebooks/cta_sensitivity.ipynb notebooks/spectrum_simulation.ipynb notebooks/image_analysis.ipynb For a quick introduction to Gammapy, go here: - `First steps with Gammapy `__ | *first_steps.ipynb* - `Introduction to gammapy.maps `__ | *intro_maps.ipynb* Interested to do a first analysis of simulated CTA data? - `CTA first data challenge (1DC) with Gammapy `__ | *cta_1dc_introduction.ipynb* - `CTA data analysis with Gammapy `__ | *cta_data_analysis.ipynb* To get started with H.E.S.S. data analysis see here: - `H.E.S.S. with Gammapy `__ | *hess.ipynb* 3-dimensional cube analysis: - `3D analysis `__ | *analysis_3d.ipynb* - `Joint 3D analysis `__ | *analysis_3d_joint.ipynb* - `3D simulation and fitting `__ | *simulate_3d.ipynb* - `Fermi-LAT data with Gammapy `__ | *fermi_lat.ipynb* 2-dimensional sky image analysis: - `Source detection with Gammapy `__ (Fermi-LAT data example) | *detect_ts.ipynb* - `CTA 2D source fitting with Gammapy `__ (DC 1 example) | *image_analysis.ipynb* - `CTA 2D source fitting with Sherpa `__ | *image_fitting_with_sherpa.ipynb* 1-dimensional spectral analysis: - `Spectral simulation with Gammapy `__ | *spectrum_simulation.ipynb* - `Spectral analysis with Gammapy `__ (H.E.S.S. data example) | *spectrum_analysis.ipynb* - `Fitting Gammapy spectra with sherpa `__ | *spectrum_fitting_with_sherpa.ipynb* - `Flux point fitting with Gammapy `__ | *sed_fitting_gammacat_fermi.ipynb* Time-dependent analysis: - `Light curves `__ | *light_curve.ipynb* Sensitivity: - `Compute the CTA sensitivity `__ | *cta_sensitivity.ipynb* .. _tutorials_extras: Extra topics ------------ .. toctree:: :hidden: notebooks/hgps.ipynb notebooks/source_population_model.ipynb notebooks/cwt.ipynb notebooks/astro_dark_matter.ipynb notebooks/background_model.ipynb notebooks/mcmc_sampling.ipynb notebooks/pulsar_analysis.ipynb These notebooks contain examples on some more specialised functionality in Gammapy. - `H.E.S.S. Galactic plane survey (HGPS) data `__ | *hgps.ipynb* - `Astrophysical source population modeling with Gammapy `__ | *source_population_model.ipynb* - `Continuous wavelet transform on gamma-ray images `__ | *cwt.ipynb* - `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* .. _tutorials_basics: Basics ------ Gammapy is a Python package built on `Numpy`_ and `Astropy`_, so to use it effectively, you have to learn the basics. To make plots you have to learn a bit of `matplotlib`_. We plan to add a very simple to use high-level interface to Gammapy where you just have to adjust a config file, but that isn't available yet. Here are some great hands-on tutorials to get started quickly: - Python: `A Whirlwind tour of Python `__ - IPython, Jupyter, Numpy, matplotlib: `Python data science handbook `__ - Astropy: `Astropy Hands-On Tutorial `__