FitResults

class sherpa.fit.FitResults(fit: Fit, results: tuple[bool, ndarray, float, str, dict[str, Any]], init_stat: float, param_warnings: str)[source] [edit on github]

Bases: NoNewAttributesAfterInit

The results of a fit.

This object contains the parameter values, information on the statistic and optimisation-method used, and other relevant information.

Changed in version 4.10.1: The covarerr attribute has been renamed to covar and now contains the covariance matrix estimated at the best-fit location, if provided by the optimiser.

Changed in version 4.17.1: The record_steps attribute has been added to the class. If the fit recorded the parameter values of each step in the optimization, this attribute will contain an array with the data.

Attributes Summary

`succeeded`	Was the fit successful (did it converge)?
`parnames`	The parameter names that were varied in the fit,
`parvals`	The parameter values, in the same order as `parnames`.
`istatval`	The statistic value at the start of the fit.
`statval`	The statistic value after the fit.
`dstatval`	The change in the statistic value (`istatval - statval`).
`numpoints`	The number of bins used in the fits.
`dof`	The number of degrees of freedom in the fit (the number of bins minus the number of free parameters).
`qval`	The Q-value (probability) that one would observe the reduced statistic value, or a larger value, if the assumed model is true and the current model parameters are the true parameter values.
`rstat`	The reduced statistic value (the `statval` field divided by `dof`).
`message`	A message about the results of the fit (e.g. if the fit was unable to converge).
`covar`	The covariance matrix from the best-fit location, if provided by the optimiser.
`nfev`	The number of model evaluations made during the fit.
`extra_output`	The `extra_output` field from the fit.
`record_steps`	A record of all steps taken during the fit, if requested with `record_steps=True`.
`modelvals`	The values of the best-fit model evaluated for the data.
`methodname`	The name of the optimisation method used (in lower case).
`itermethodname`	What iterated-fit scheme was used, if any.
`statname`	The name of the statistic function.
`datasets`	A sequence of the data set ids included in the results.

Methods Summary

format()

Return a string representation of the fit results.

Attributes Documentation

succeeded: bool: Was the fit successful (did it converge)?

parnames: tuple[str, ...]

The parameter names that were varied in the fit,

This is the thawed parameters in the model expression.

parvals: tuple[float, ...]: The parameter values, in the same order as parnames.

istatval: float: The statistic value at the start of the fit.

statval: float: The statistic value after the fit.

dstatval: float: The change in the statistic value (istatval - statval).

numpoints: int: The number of bins used in the fits.

dof: int: The number of degrees of freedom in the fit (the number of bins minus the number of free parameters).

qval: float | None

The Q-value (probability) that one would observe the reduced statistic value, or a larger value, if the assumed model is true and the current model parameters are the true parameter values.

This will be None if the value can not be calculated with the current statistic (e.g. the Cash statistic).

rstat: float | None

The reduced statistic value (the statval field divided by dof).

This is not calculated for all statistics.

message: str

A message about the results of the fit (e.g. if the fit was unable to converge).

The format and contents depend on the optimisation method.

covar: The covariance matrix from the best-fit location, if provided by the optimiser.

nfev: int: The number of model evaluations made during the fit.

extra_output: The extra_output field from the fit.

record_steps: None | dict: A record of all steps taken during the fit, if requested with record_steps=True.

modelvals: ndarray: The values of the best-fit model evaluated for the data.

methodname: str: The name of the optimisation method used (in lower case).

itermethodname: str | None: What iterated-fit scheme was used, if any.

statname: str: The name of the statistic function.

datasets: list[int | str] | None: A sequence of the data set ids included in the results.

Methods Documentation

format() → str[source] [edit on github]

Return a string representation of the fit results.

Returns:: txt – A multi-line representation of the fit results.
Return type:: str