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Sherpa: Modeling and Fitting in Python

Sherpa is a modeling and fitting application for Python. It contains a powerful language for combining simple models into complex expressions that can be fit to the data using a variety of statistics and optimization methods. It is easily extensible to include user models, statistics and optimization methods.

What’s new in Sherpa 4.11.0

Sherpa 4.11.0 released on February 20, 2019 provides improvements to the optimization routines and statistics, and includes several bug fixes. This release supports Python 2.7, 3.5-3.7. Support for Python 2.7 is being deprecated and may be dropped in future releases.

This release also provides support for XSPEC 12.10.1 (patch ‘a’ or later) in addition to versions 12.10.0 (included in the CIAO 4.11 release) and version 12.9.1.

Check the complete Release Notes.

Learn more on the Sherpa documentation pages.

Learn How to Install Sherpa?

What can you do with Sherpa?

  • Model generic 1D/2D (N-D) data arrays.
  • Fit 1D (multiple) data including: spectra, surface brightness profiles, light curves, arrays.
  • Fit 2D images/surfaces in Poisson/Gaussian regime.
  • Build complex model expressions.
  • Import, define and use your own models.
  • Simulate predicted data based on defined models.
  • Use appropriate statistics for modeling Poisson or Gaussian data
  • Use Classic Maximum Likelihood or Bayesian Framework.
  • Import, define the new statistics, with priors if required by analysis.
  • Visualize a parameter space with simulations or using 1D/2D cuts of the parameter space
  • Calculate confidence levels on the best fit model parameters
  • Use a robust optimization method for the fit: Levenberg-Marquardt, Nelder-Mead Simplex or Monte Carlo/Differential Evolution.
  • Sherpa supports wcs, responses, psf, convolution.
  • Use Sherpa as part of astropy.modeling with Sherpa Bridge to Astropy - SABA

Citing Sherpa

Please follow the Digital Object Identifier (DOI) <https://doi.org/10.5281/zenodo.593753> for information on how to cite Sherpa.