The default behavior for adding and solving with noisemodels has changed from Pastas 1.5. Find more information here

LeastSquares#

class LeastSquares(pcov=None, nfev=None, **kwargs)[source]#

Solver based on Scipy’s least_squares method [Virtanen et al., 2020].

Notes

This class is the default solve method called by the pastas Model solve method. All kwargs provided to the Model.solve() method are forwarded to the solver. From there, they are forwarded to Scipy least_squares solver.

Examples

>>> ml.solve(solver=ps.LeastSquares())

References

https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.least_squares.html

Parameters

Methods#

__init__

ci_block_response

Method to calculate the confidence interval for the block response.

ci_contribution

Method to calculate the confidence interval for the contribution.

ci_simulation

Method to calculate the confidence interval for the simulation.

ci_step_response

Method to calculate the confidence interval for the step response.

get_parameter_sample

Method to obtain a parameter sets for monte carlo analyses.

misfit

This method is called by all solvers to obtain a series that are minimized in the optimization process.

objfunction

prediction_interval

Method to calculate the prediction interval for the simulation.

set_model

Method to set the Pastas Model instance.

solve

to_dict