Add info on the high level interface
@@ -25,6 +25,7 @@ the data flow and sub-package structure of Gammapy.
.. _overview_data:
+
Data access (DL3)
-----------------
@@ -106,6 +107,18 @@ see the `2D map analysis tutorial <./tutorials/image_analysis.html>`__.
Modeling and Fitting (DL4 -> DL5)
---------------------------------
+The second step is then typically to model and fit the datasets, either
+individually, or in a joint likelihood analysis, using the
+`~gammapy.datasets.Dataset`, `~gammapy.datasets.Datasets`,
+`~gammapy.modeling.Fit` and model classes (see :ref:`overview_modeling` below).
+
+You can specify your model using a YAML model specification, or write Python
+code to specify which spectral and spatial models to use and what their rough
+parameters are to start the fit (such as sky position and source extension, or
+approximate flux level). Methods to run global model fits are available, as well
+as methods to compute flux points or light curves, or run simple source
+detection algorithms.
+
Beyond `Dataset` objects, Gammapy provides numerous functionalities related
to data modeling and fitting, as well as data simulation.
@@ -137,11 +150,43 @@ High Level Analysis Interface
A convenient way to do this is to use the high level interface,
see :ref:`gammapy.analysis <analysis>`.
+To analyse data from CTA or existing IACTs, the usual workflow is to use the
+high-level interface in :ref:`gammapy.analysis <analysis>` as shown in the
+example `First analysis tutorial notebook <./tutorials/analysis_1.html>`__, i.e.
+to write a YAML config file, and then to use `~gammapy.analysis.AnalysisConfig`
+and `~gammapy.analysis.Analysis` to perform the data reduction from event lists
+and instrument response functions (IRFs) to a reduced data format called
+datasets, using either 3D cube analysis or 1D region-based spectral analysis.
+The IACT data distributed by instruments is called "data level 3" (DL3) and is
+given as FITS files, as shown in the `CTA with Gammapy <./tutorials/cta.html>`__
+and `H.E.S.S. with Gammapy <./tutorials/hess.html>`__ notebooks and explained in
+more detail in :ref:`overview_data` below. Then `~gammapy.analysis.Analysis`
+class is then used to compute intermediate reduced analysis files like counts
+and exposure maps or spectra, and reduced point spread function (PSF) or energy
+dispersion (EDISP) information, combined in container objects called datasets
+(see below).
+
+The analysis config file and `~gammapy.analysis.Analysis` class currently mostly
+scripts the data reduction up to the datasets level for the most common analysis
+cases. It might be extended in the future to become the "manager" or "driver"
+class for modeling or fitting as well, or that might remain the responsibility
+of the datasets, models and fit classes. Advanced users that need to run
+specialises analyses such as e.g. complex background modeling, or grouping of
+observations, have a second-level API available via dataset makers, that offer
+more flexibility. An example of this is shown in the `Second analysis tutorial
+notebook <./tutorials/analysis_2.html>`__.
+
.. _overview_other:
Other topics
------------
+Gammapy ships with a ``gammapy`` command line tool, that can be used to check
+your installation and show version information via ``gammapy info``, to download
+example datasets and tutorials via ``gammapy download`` or to bootstrap an
+analysis by creating a default config file via ``gammapy analysis``. To learn
+about the Gammapy command line tool, see :ref:`gammapy.scripts <CLI>`.
+
See :ref:`gammapy.catalog <catalog>`, :ref:`gammapy.astro <astro>`,
:ref:`gammapy.stats <stats>`,
:ref:`gammapy.scripts <CLI>` (``gammapy`` command line tool).
