:orphan: .. include:: ../references.txt .. _tutorials: ========= Tutorials ========= **Notice :** it is advised to first read :ref:`package_structure` of the User Guide before using the 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 :ref:`installation`) and download the tutorial notebooks and example datasets (see :ref:`getting-started`). Once Gammapy is 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`_. .. raw:: html
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Introduction ============ The following three tutorials show different ways of how to use Gammapy to perform a complete data analysis, from data selection to data reduction and finally modeling and fitting. The first tutorial is an overview on how to perform a standard analysis workflow using the high level interface in a configuration-driven approach, whilst the second deals with the same use-case using the low level API and showing what is happening *under-the-hood*. The third tutorial shows a glimpse of how to handle different basic data structures like event lists, source catalogs, sky maps, spectral models and flux points tables. .. raw:: html
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High level interface
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Low level API
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Data structures
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.. toctree:: :hidden: /tutorials/starting/analysis_1 /tutorials/starting/analysis_2 /tutorials/starting/overview Data exploration ================ These tutorials show how to perform data exploration with Gammapy, providing an introduction to the CTA, HAWC, H.E.S.S. and Fermi-LAT data and instrument response functions (IRFs). You will be able to explore and filter event lists according to different criteria, as well as to get a quick look of the multidimensional IRFs files. .. raw:: html
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CTA with Gammapy
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Fermi-LAT with Gammapy
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HAWC with Gammapy
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H.E.S.S. with Gammapy
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.. toctree:: :hidden: /tutorials/data/cta /tutorials/data/fermi_lat /tutorials/data/hawc /tutorials/data/hess Data analysis ============= The following set of tutorials are devoted to data analysis, and grouped according to the specific covered use cases in spectral analysis and flux fitting, image and cube analysis modelling and fitting, as well as time-dependent analysis with light-curves. 1D Spectral ----------- .. raw:: html
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Point source sensitivity
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Spectral analysis of extended sources
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Flux point fitting
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Spectral analysis
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Spectral analysis with the HLI
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Spectral analysis with energy-dependent directional cuts
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1D spectrum simulation
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.. toctree:: :hidden: /tutorials/analysis-1d/cta_sensitivity /tutorials/analysis-1d/extended_source_spectral_analysis /tutorials/analysis-1d/sed_fitting /tutorials/analysis-1d/spectral_analysis /tutorials/analysis-1d/spectral_analysis_hli /tutorials/analysis-1d/spectral_analysis_rad_max /tutorials/analysis-1d/spectrum_simulation 2D Image -------- .. raw:: html
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Source detection and significance maps
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2D map fitting
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Ring background map
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.. toctree:: :hidden: /tutorials/analysis-2d/detect /tutorials/analysis-2d/modeling_2D /tutorials/analysis-2d/ring_background 3D Cube ------- .. raw:: html
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3D detailed analysis
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Multi instrument joint 3D and 1D analysis
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Basic image exploration and fitting
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Morphological energy dependence estimation
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Event sampling
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Sample a source with energy-dependent temporal evolution
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Flux Profile Estimation
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3D map simulation
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.. toctree:: :hidden: /tutorials/analysis-3d/analysis_3d /tutorials/analysis-3d/analysis_mwl /tutorials/analysis-3d/cta_data_analysis /tutorials/analysis-3d/energy_dependent_estimation /tutorials/analysis-3d/event_sampling /tutorials/analysis-3d/event_sampling_nrg_depend_models /tutorials/analysis-3d/flux_profiles /tutorials/analysis-3d/simulate_3d Time ---- .. raw:: html
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.. only:: html .. image:: /tutorials/analysis-time/images/thumb/sphx_glr_Variability_estimation_thumb.png :alt: :ref:`sphx_glr_tutorials_analysis-time_Variability_estimation.py` .. raw:: html
Estimation of time variability in a lightcurve
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Light curves
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Light curves for flares
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Simulating and fitting a time varying source
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.. only:: html .. image:: /tutorials/analysis-time/images/thumb/sphx_glr_pulsar_analysis_thumb.png :alt: :ref:`sphx_glr_tutorials_analysis-time_pulsar_analysis.py` .. raw:: html
Pulsar analysis
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.. toctree:: :hidden: /tutorials/analysis-time/Variability_estimation /tutorials/analysis-time/light_curve /tutorials/analysis-time/light_curve_flare /tutorials/analysis-time/light_curve_simulation /tutorials/analysis-time/pulsar_analysis Package / API ============= The following tutorials demonstrate different dimensions of the Gammapy API or expose how to perform more specific use cases. .. raw:: html
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Dark matter spatial and spectral models
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Source catalogs
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Datasets - Reduced data, IRFs, models
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Fitting
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Using Gammapy IRFs
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Makers - Data reduction
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Maps
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Mask maps
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Modelling
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Models
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Observational clustering
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Priors
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.. toctree:: :hidden: /tutorials/api/astro_dark_matter /tutorials/api/catalog /tutorials/api/datasets /tutorials/api/fitting /tutorials/api/irfs /tutorials/api/makers /tutorials/api/maps /tutorials/api/mask_maps /tutorials/api/model_management /tutorials/api/models /tutorials/api/observation_clustering /tutorials/api/priors Scripts ======= For interactive use, IPython and Jupyter are great, and most Gammapy examples use those. However, for long-running, non-interactive tasks like data reduction or survey maps, you might prefer a Python script. The following example shows how to run Gammapy within a Python script. .. raw:: html
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Survey Map Script
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.. toctree:: :hidden: /tutorials/scripts/survey_map .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-gallery .. container:: sphx-glr-download sphx-glr-download-python :download:`Download all examples in Python source code: tutorials_python.zip ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download all examples in Jupyter notebooks: tutorials_jupyter.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_