Sherpa: An Open Source Python Fitting Package
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2024
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866912030715281408 |
|---|---|
| author | Siemiginowska, Aneta Burke, Douglas Günther, Hans Moritz Lee, Nicholas P. McLaughlin, Warren Principe, David A. Cheer, Harlan Fruscione, Antonella Laurino, Omar McDowell, Jonathan Terrell, Marie |
| author_facet | Siemiginowska, Aneta Burke, Douglas Günther, Hans Moritz Lee, Nicholas P. McLaughlin, Warren Principe, David A. Cheer, Harlan Fruscione, Antonella Laurino, Omar McDowell, Jonathan Terrell, Marie |
| contents | We present an overview of Sherpa, an open source Python project, and discuss its development history, broad design concepts and capabilities. Sherpa contains powerful tools for combining parametric models into complex expressions that can be fit to data using a variety of statistics and optimization methods. It is easily extensible to include user-defined models, statistics, and optimization methods. It provides a high-level User Interface for interactive data-analysis, such as within a Jupyter notebook, and it can also be used as a library component, providing fitting and modeling capabilities to an application. We include a few examples of Sherpa applications to multiwavelength astronomical data. The code is available GitHub: https://github.com/sherpa/sherpa |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_10400 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Sherpa: An Open Source Python Fitting Package Siemiginowska, Aneta Burke, Douglas Günther, Hans Moritz Lee, Nicholas P. McLaughlin, Warren Principe, David A. Cheer, Harlan Fruscione, Antonella Laurino, Omar McDowell, Jonathan Terrell, Marie Instrumentation and Methods for Astrophysics High Energy Astrophysical Phenomena We present an overview of Sherpa, an open source Python project, and discuss its development history, broad design concepts and capabilities. Sherpa contains powerful tools for combining parametric models into complex expressions that can be fit to data using a variety of statistics and optimization methods. It is easily extensible to include user-defined models, statistics, and optimization methods. It provides a high-level User Interface for interactive data-analysis, such as within a Jupyter notebook, and it can also be used as a library component, providing fitting and modeling capabilities to an application. We include a few examples of Sherpa applications to multiwavelength astronomical data. The code is available GitHub: https://github.com/sherpa/sherpa |
| title | Sherpa: An Open Source Python Fitting Package |
| topic | Instrumentation and Methods for Astrophysics High Energy Astrophysical Phenomena |
| url | https://arxiv.org/abs/2409.10400 |