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| Paper: |
Advanced Python Scripting Using Sherpa |
| Volume: |
442, Astronomical Data Analysis Software and Systems XX (ADASSXX) |
| Page: |
687 |
| Authors: |
Refsdal, R.; Doe, S.; Nguyen, D.; Siemiginowska, A.; Burke, D.; Evans, J.; Evans, I. |
| Abstract: |
Sherpa is a general purpose modeling and fitting application written in Python. The dynamism of Python allows Sherpa to be a powerful and
extensible software package ready for the modern challenges of data analysis.
Primarily developed for the Chandra Interactive Analysis of Observations (CIAO)
package, it provides a flexible
environment for resolving spectral and image properties, analyzing time series,
and modeling generic types of data. Complex model expressions are supported
using Sherpa's general purpose definition syntax. Sherpa's
parameterized data modeling is achieved using robust optimization methods
implementing the forward fitting technique. Sherpa includes functions to
calculate goodness–of–fit and parameter confidence limits. CPU intensive
routines are written in C++/FORTRAN. But since all other data structures are
contained in Python modules, users can easily add their own data structures,
models, statistics or optimization methods to Sherpa. We will introduce a
scripted example that highlights Sherpa's ability to estimate energy and
photon flux errors using simulations. The draws from these simulations,
accessible as NumPy ndarrays, can be sampled from uni–variate and multi–variate
normal distributions and can be binned and visualized with simple high level
functions. We will demonstrate how Sherpa can be extended with
user–defined model and statistic classes written in Python. Sherpa's open
design even allows users to incorporate prior statistics derived from the source
model. |
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