Core Module - Base Classes and Main Functions¶
This module holds the base level classes for the pymodelfit data fitting/modeling framework. This is seperated from the implementations of specific models, which can be found in the builtins module.
Class Inheritance Diagram¶
pymodelfit.core includes a number of classes that are primarily inteded to be subclassed by particular models. The relationship between these classes is shown in the below diagram.
Module Reference¶
Classes¶
| ModelTypeError(message) | This exception indicates a problem with the value of the input |
| ParametricModel | The superclass of all models with parameters. |
| AutoParamsMeta(name, bases, dct) | Metaclass used to auto-generate parameters from the FunctionModel.f() |
| InputCoordinateTransformer | This mixin class (i.e. |
| FunctionModel | A base class for models that use a single function to map a |
| CompositeModel([models, operation, ...]) | This model contains a group of FunctionModel objects joined by |
| FunctionModel1D | This class is the base for 1-dimensional models that are implemented as python functions. |
| FunctionModel1DAuto | A FunctionModel1D that infers the parameters from the f() |
| DatacentricModel1D | A FunctionModel1D that requires data to compute its value. |
| DatacentricModel1DAuto | A DatacentricModel1D that infers the parameters from the f() |
| CompositeModel1D(*args, **kwargs) | This model is a composite model of FunctionModel1D models with a few |
| FunctionModel2DScalar | This class is a FunctionModel that maps a two-dimensional input to a |
| FunctionModel2DScalarAuto | A FunctionModel2DScalar that has its parameters automatically |
| FunctionModel2DScalarDeformedRadial(rmodel) | A FunctionModel2DScalar with a profile that is flattened along an axis |
| FunctionModel2DScalarSeperable(rmodel[, ...]) | A FunctionModel2DScalar that is seperable and follows a radial and |
| CompositeModel2DScalar(*args, **kwargs) | This model is a composite model of FunctionModel2DScalar models. |
| ModelSequence(models[, extraparams, ...]) | A group of models with attached parameters that can be used to infer the parameter values at an arbitrary point in the space defined by the models. |
Functions¶
| register_model(model[, name, overwrite]) | Registers a model at the module package level for get_model_class() and :func`list_model`. |
| list_models([include, exclude, baseclass, ...]) | Lists the registered model objects in the package, possibly subject to constraints. |
| get_model_class(model[, baseclass]) | Returns the class object for the requested model in the model registry |
| get_model_instance(model[, baseclass, ...]) | Returns an instance of the supplied model - if the input is actually an instance of a model, the same instance will be passed in - otherwise, a new instance will be created. |
| offset_model(model[, offsetparname, offsetval]) | A convinience to generate a CompositeModel with an additive offset |
| scale_model(model[, scaleparname, scaleval]) | A convinience function to generate a CompositeModel with a scaling |
| scale_and_offset_model(model[, ...]) | A convinience function to generate a CompositeModel with a multiplicative |
| intersect_models(m1, m2[, bounds, nsample, ...]) | Determine the points where two models intersect. |