AstropyFitter1D¶
-
class
glue.core.fitters.
AstropyFitter1D
(**params)[source]¶ Bases:
glue.core.fitters.BaseFitter1D
A base class for wrapping
astropy.modeling
.Subclasses must override
model_cls
fitting_cls
to point to the desired Astropymodel
andfitter
classes.In addition, they should override
label
with a better label, andparameter_guesses()
to generate initial guessesAttributes Summary
class to fit the model
UI Label
class describing the model
list() -> new empty list list(iterable) -> new list initialized from iterable’s items
Methods Summary
fit
(self, x, y, dy, constraints)Fit the model to data.
parameter_guesses
(self, x, y, dy)Provide initial guesses for each model parameter.
predict
(self, fit_result, x)Evaluate the model at a set of locations.
summarize
(self, 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
[source]¶ list() -> new empty list list(iterable) -> new list initialized from iterable’s items
Methods Documentation
-
fit
(self, x, y, dy, constraints)[source]¶ Fit the model to data.
This must be overriden by a subclass.
- Parameters
x (
numpy.ndarray
) – The x values of the datay (
numpy.ndarray
) – The y values of the datady (
numpy.ndarray
) – 1 sigma uncertainties on each datum (optional)constraints – The current value of the
constraints
propertyoptions – kwargs for model hyperparameters.
- Returns
An object representing the fit result.
-
parameter_guesses
(self, x, y, dy)[source]¶ Provide initial guesses for each model parameter.
The base implementation does nothing, and should be overridden
- Parameters
x (
numpy.ndarray
) – X - values of the datay (
numpy.ndarray
) – Y - values of the datady (
numpy.ndarray
) – uncertainties on Y(assumed to be 1 sigma)
- Returns
A dict mapping
{parameter_name: value guess}
for each parameter
-
predict
(self, fit_result, x)[source]¶ 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
-