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curvefit.core.core_model.Model

Base class for a curvefit model

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Arguments

  • param_set (curvefit.core.parameter.ParameterSet)
  • curve_fun (Callable): function from curvefit.core.functions for the parametric function to fit
  • loss_fun (Callable): function from curvefit.core.functions for the loss function

Attributes

  • self.data_inputs (curvefit.models.base.DataInputs): data inputs that have been converted during data fitting -- helper for the objective function

Methods

objective

Returns a function that can be called in a Solver that is the objective function given the current variables and data.

  • x (np.array): an array of variable values that can be converted to parameters, these will be the parameters that the objective function is evaluated at
  • data (Tuple[pd.DataFrame, DataSpecs]): the input data frame to be fit, and data specifications object

get_params

Wrapper for effects2params to convert the values of x (the variables) into parameters for the model.

  • x (np.array): an array of variable values that can be converted to parameters

predict

Create predictions given some variable values x and at some times t. Can optionally pass a different functional form as long as it is in the same family (e.g. Gaussian).

  • x (np.array): an array of variable values that can be converted to parameters
  • t (np.array): times to evaluate the function
  • predict_fun (Callable): function from curvefit.core.functions
  • is_multi_groups (bool): whether or not the model was fit on data for multiple groups

convert_inputs

Convert a data frame and specifications into inputs for the objective function of the model.

  • data (Tuple[pd.DataFrame, DataSpecs]): the input data frame to be fit, and data specifications object