AstropyFitter1D

class glue.core.fitters.AstropyFitter1D(**params)

Bases: glue.core.fitters.BaseFitter1D

A base class for wrapping astropy.modeling.

Subclasses must override model_cls fitting_cls to point to the desired Astropy model and fitter classes.

In addition, they should override label with a better label, and parameter_guesses() to generate initial guesses

Attributes Summary

fitting_cls	class to fit the model
label	UI Label
model_cls	class describing the model
param_names	Built-in mutable sequence.

Methods Summary

fit(x, y, dy, constraints)	Fit the model to data.
parameter_guesses(x, y, dy)	Provide initial guesses for each model parameter.
predict(fit_result, x)	Evaluate the model at a set of locations.
summarize(fit_result, x, y[, dy])	Return a textual summary of the fit.

Attributes Documentation

fitting_cls = None

class to fit the model

label = 'Base Astropy Fitter'

UI Label

model_cls = None

class describing the model

param_names

list of parameter names that support restrictions

Methods Documentation

fit(x, y, dy, constraints)

Fit the model to data.

This must be overriden by a subclass.

Parameters

• x (numpy.ndarray) – The x values of the data

• y (numpy.ndarray) – The y values of the data

• dy (numpy.ndarray) – 1 sigma uncertainties on each datum (optional)

• constraints – The current value of the constraints property

• options – kwargs for model hyperparameters.

Returns

An object representing the fit result.

parameter_guesses(x, y, dy)

Provide initial guesses for each model parameter.

The base implementation does nothing, and should be overridden

Parameters

• x (numpy.ndarray) – X - values of the data

• y (numpy.ndarray) – Y - values of the data

• dy (numpy.ndarray) – uncertainties on Y(assumed to be 1 sigma)

Returns

A dict mapping {parameter_name: value guess} for each parameter

predict(fit_result, x)

Evaluate the model at a set of locations.

This must be overridden in a subclass.

Parameters

• fit_result – The result from the fit method

• x (numpy.ndarray) – Locations to evaluate model at

Returns

model(x)

Return type

numpy.ndarray

summarize(fit_result, x, y, dy=None)

Return a textual summary of the fit.

Parameters

• fit_result – The return value from fit()

• x – The x values passed to fit()

Returns

A description of the fit result

Return type

str