pastas.solver.least_squares.LeastSquares.objfunction
====================================================

.. py:method:: pastas.solver.least_squares.LeastSquares.objfunction(p: pastas.typing.ArrayLike, noise: bool, weights: pandas.Series | None, initial: pastas.typing.ArrayLike, vary: pastas.typing.ArrayLike) -> pastas.typing.ArrayLike

   
   Objective function that is minimized by the least_squares solver.

   :param p: array_like object with the values as floats representing the model
             parameters.
   :type p: array_like
   :param noise: If True, minimizes the sum of squared noise computed by the NoiseModel.
   :type noise: Boolean
   :param weights: pandas Series by which the residual or noise series are
                   multiplied. Typically values between 0 and 1.
   :type weights: pandas.Series | None
   :param initial: array_like object with the initial parameter values.
   :type initial: array_like
   :param vary: array_like object with booleans indicating which parameters (p) are varied.
   :type vary: array_like
   :param callback: function that is called after each iteration. the parameters are
                    provided to the func.
   :type callback: ufunc















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