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curvefit.solvers.solvers.Solver

Solver base class that fits a Model

In order to fit a curvefit.models.base.Model, you must first define a Solver and assign the model to the solver. The reason for this is that there might be multiple ways that you could solve a particular model.

Arguments

  • model_instance (curvefit.models.base.Model): the model instance that will be solved

Methods

fit

Fit the solver to some data using self.model_instance.

  • data (Tuple[pd.DataFrame, DataSpecs]): the input data frame to be fit, and data specifications object
  • options (None | Options): an optional Options object that has fit specifications for the underlying solver; overrides the options that have already been set

predict

Create predictions based on the optimal values estimated by the solver.

  • **kwargs: keyword arguments passed to self.model_instance.predict()

set_options

Set a dictionary of options that will be used in the optimization.

set_model_instance

Attach a new model instance.

detach_model_instance

Detach the current model instance.

get_model_instance

Get the current model instance.