BaseSolver#

class BaseSolver(ml, pcov=None, nfev=None, obj_func=None, **kwargs)[source]#

All solver instances inherit from the BaseSolver class.

Parameters:
model#
Type:

pastas.Model instance

pcov#

Pandas DataFrame with the correlation between the optimized parameters.

Type:

pandas.DataFrame

pcor#

Based on pcov, cannot be parsed. Pandas DataFrame with the correlation between the optimized parameters.

Type:

pandas.DataFrame

nfev#

Number of times the model is called during optimization.

Type:

int

result#

The object returned by the minimization method that is used. It depends on the solver what is actually returned.

Type:

object

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.

prediction_interval

Method to calculate the prediction interval for the simulation.

to_dict