The Fitting Module¶
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qexpy.fitting.fit(*args, **kwargs)[source]¶ Perform a fit to a data set
The fit function can be called on an XYDataSet object, or two arrays or MeasurementArray objects. QExPy provides 5 builtin fit models, which includes linear fit, quadratic fit, general polynomial fit, gaussian fit, and exponential fit. The user can also pass in a custom function they wish to fit their dataset on. For non-polynomial fit functions, the user would usually need to pass in an array of guesses for the parameters.
- Parameters
*args – An XYDataSet object or two arrays to be fitted.
- Keyword Arguments
model – the fit model given as the string or enum representation of a pre-set model or a custom callable function with parameters. Available pre-set models include: “linear”, “quadratic”, “polynomial”, “exponential”, “gaussian”
xrange (tuple|list) – a pair of numbers indicating the domain of the function
degrees (int) – the degree of the polynomial if polynomial fit were chosen
parguess (list) – initial guess for the parameters
parnames (list) – the names of each parameter
parunits (list) – the units for each parameter
dataset – the XYDataSet instance to fit on
xdata – the x-data of the fit
ydata – the y-data of the fit
xerr – the uncertainty on the xdata
yerr – the uncertainty on the ydata
- Returns
the result of the fit
- Return type
See also
The XYFitResult Class¶
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XYFitResult.dataset¶ The dataset used for this fit
- Type
dts.XYDataSet
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XYFitResult.fit_function¶ The function that fits to this data set
- Type
Callable
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XYFitResult.params¶ The fit parameters of the fit function
- Type
List[dt.ExperimentalValue]
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XYFitResult.residuals¶ The residuals of the fit
- Type
dts.ExperimentalValueArray
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XYFitResult.chi_squared¶ The goodness of fit represented as chi^2
- Type
dt.ExperimentalValue
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XYFitResult.ndof¶ The degree of freedom of this fit function
- Type
int
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XYFitResult.xrange¶ The xrange of the fit
- Type
tuple