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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 4.13 was released on January 8, 2021.
It contains a few minor documentation updates, a version number update to coincide with CIAO version 4.13.0,
and infrastructure changes to migrate from Travis-CI to GitHub Actions for testing.
This version is compatible with Python 3.6, 3.7 and 3.8.
It is available for use outside of `CIAO `_, and can be installed with conda, pip,
or built from source.
Check the complete `4.13.0 Release Notes `_ and
the `Sherpa 4.13 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 new `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
-------------
Please follow the Digital Object Identifier (DOI) for information on how to cite Sherpa.
Release Notes
-------------
Release Notes for the previous version of Sherpa:
* `4.12.2 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 `_