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Sherpa: Modeling and Fitting in Python
==========================================
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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.
Sherpa 4.17.1 was released on May 13, 2025. It includes improvements to
plotting, several bug fixes, infrastructure and documentation updates.
This version is compatible with Python 3.10 - 3.13. It is available for use outside of `CIAO `_, and can be installed with conda, pip,
or built from source.
Check the complete `4.17.1 Release Notes `_ and
the `Sherpa 4.17.1 documentation `_ pages.
Information on recent releases and
citation information is available using the `Digital Object
Identifier (DOI) `_.
Install Sherpa
---------------
Check `How to Install Sherpa? `_ for installation.
There is a set of `Notebooks `_ with examples of Sherpa in Python.
See the `quick guide to modeling and fitting in Sherpa `_ for a simple introduction to Sherpa’s capabilities.
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
-------------
The new paper describing Sherpa was published in the `Astrophysical
Journal Supplement Series `_ in 2024. It
has been posted on `archives.
`_
Please follow the Digital Object Identifier (DOI) for information
on how to cite Sherpa.
Release Notes
-------------
Release Notes for the previous version of Sherpa:
* `4.17.0 Release Notes `_
* `4.16.1 Release Notes `_
* `4.16.0 Release Notes `_
* `4.15.1 Release Notes `_
* `4.15.0 Release Notes `_
* `4.14.1 Release Notes `_
* `4.14.0 Release Notes `_
* `4.13.1 Release Notes `_
* `4.13.0 Release Notes `_
* `4.12.2 Release Notes `_
* `4.12.1 Release Notes `_
* `4.12.0 Release Notes `_
* `4.11.1 Release Notes `_
* `4.11.0 Release Notes `_
* `4.10.2 Release Notes `_
* `4.10.1 Release Notes `_
* `4.10.0 Release Notes `_
* `4.9.1 Release Notes `_
* `4.9.0 Release Notes `_
* `4.8.2 Release Notes `_
* `4.8.1 Release Notes `_
* `4.8.0 Release Notes `_