.. include:: ../references.txt .. _spectrum: ******************************* spectrum - 1D spectrum analysis ******************************* .. currentmodule:: gammapy.spectrum Introduction ============ `gammapy.spectrum` holds functions and classes related to 1D region based spectral analysis. This includes also simulation tools. The basic of 1D spectral analysis are explained in `this `__ talk. A good reference for the forward-folding on-off likelihood fitting methods is Section 7.5 "Spectra and Light Curves" in [Naurois2012]_, in publications usually the reference [Piron2001]_ is used. A standard reference for the unfolding method is [Albert2007]_. Getting Started =============== The following code snippet demonstrates how to load an observation stored in OGIP format and fit a spectral model. .. code-block:: python from gammapy.spectrum import SpectrumObservation, SpectrumFit from gammapy.spectrum.models import PowerLaw filename = '$GAMMAPY_DATA/joint-crab/spectra/hess/pha_obs23523.fits' obs = SpectrumObservation.read(filename) model = PowerLaw( index=2, amplitude='1e-12 cm-2 s-1 TeV-1', reference='1 TeV', ) fit = SpectrumFit(obs_list=[obs], model=model) fit.run() print(fit.result[0]) It will print the following output to the console: .. code-block:: text Fit result info --------------- Model: PowerLaw Parameters: name value error unit min max --------- --------- --------- --------------- --------- --- index 2.791e+00 1.456e-01 nan nan amplitude 5.030e-11 6.251e-12 1 / (cm2 s TeV) nan nan reference 1.000e+00 0.000e+00 TeV 0.000e+00 nan Covariance: name index amplitude reference --------- --------------------- ---------------------- --------- index 0.021213640646334082 5.788340722422449e-13 0.0 amplitude 5.788340722422449e-13 3.9079614123597625e-23 0.0 reference 0.0 0.0 0.0 Statistic: 41.756 (wstat) Fit Range: [8.79922544e+08 1.00000000e+11] keV Using `gammapy.spectrum` ======================== For more advanced use cases please go to the tutorial notebooks: * :gp-notebook:`spectrum_simulation` - simulate and fit 1D spectra using pre-defined or a user-defined model. * :gp-notebook:`spectrum_analysis` - spectral analysis starting from event lists and field-of-view IRFs. The following pages describe ``gammapy.spectrum`` in more detail: .. toctree:: :maxdepth: 1 fitting Reference/API ============= .. automodapi:: gammapy.spectrum :no-inheritance-diagram: :include-all-objects: .. automodapi:: gammapy.spectrum.models :no-inheritance-diagram: :include-all-objects: