pastas.solver.LeastSquares.misfit#

LeastSquares.misfit(p, noise, weights=None, callback=None, returnseparate=False)#

This method is called by all solvers to obtain a series that are minimized in the optimization process. It handles the application of the weights, a noisemodel and other optimization options.

Parameters
  • p (array_like) – array_like object with the values as floats representing the model parameters.

  • noise (Boolean) –

  • weights (pandas.Series, optional) – pandas Series by which the residual or noise series are multiplied. Typically values between 0 and 1.

  • callback (ufunc, optional) – function that is called after each iteration. the parameters are provided to the func. E.g. “callback(parameters)”

  • returnseparate (bool, optional) – return residuals, noise, noiseweights

Returns

rv – residuals array (if noise=False) or noise array (if noise=True)

Return type

array_like