Fitting
Sherpa provides extensive facilities for modeling and
fitting data. The topics here range from basic fits using
source spectra and responses to more advanced areas, such as
simultaneous fits to multiple data sets, accounting for the
effects of pileup, and fitting spatial and grating data.
Before fitting ACIS spectral data sets with limited
pulse-height ranges, please read the CIAO caveat "Spectral analyses of ACIS data with a limited pulse-height range."
Spectral (1-D) Data
- Introduction to Fitting PHA Spectra (S-Lang or Python)
- Changing the grouping scheme of a data set within Sherpa (S-Lang or Python)
-
Introduction to Fitting ASCII Data with Errors: Single-Component Source Models
(S-Lang or Python)
- Simultaneously Fitting Two Data Sets (S-Lang or Python)
- Simulating 1-D Data: the Sherpa FAKE_PHA Command (S-Lang or Python)
- Simulating Chandra ACIS-S Spectra with Sherpa (S-Lang or Python)
- Fitting PHA Data with Multi-Component Source Models (S-Lang or Python)
- Calculating Uncertainties by Simulating Flux Distributions (S-Lang or Python)
- Independent Background Responses (S-Lang or Python)
- Using A Pileup Model (S-Lang or Python)
- Sherpa User Models (S-Lang or Python)
- Sherpa Table Models (S-Lang or Python)
Grating Data
Users interested in conducting wavelength analysis are
encouraged to learn the
limitations associated with
the set_analysis
command (S-Lang or Python help)
before doing so with the information contained in
these threads.
- Fitting Grating Data (S-Lang or Python)
- Fitting Multiple Orders of HRC-S/LETG Data (S-Lang or Python)
- Measuring Line Parameters with an HETG/ACIS-S Spectrum (S-Lang or Python)
- Measuring Line Parameters with an LETG/ACIS-S Spectrum (S-Lang or Python)
Generic Data
These threads involve data analysis which is not
specific to X-ray spectral or spatial modeling,
therefore they can be followed using simple ASCII files
as input, or other non-X-ray data.
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