smash.Optimize

class smash.Optimize(data=None)

Represents optimize optional results.

Attributes:

time_steppandas.DatetimeIndex

A list of length n containing the returned time steps.

rr_statesFortranDerivedTypeArray

A list of length n of RR_StatesDT for each time_step.

q_domainnumpy.ndarray

An array of shape (nrow, ncol, n) representing simulated discharges on the domain for each time_step.

internal_fluxesdict[str, numpy.ndarray]

A dictionary where keys are the names of the internal fluxes and the values are array of shape (nrow, ncol, n) representing an internal flux on the domain for each time_step.

control_vectornumpy.ndarray

An array of shape (k,) representing the control vector solution of the optimization (it can be transformed).

netNet

The trained neural network.

costfloat

Cost value.

n_iterint

Number of iterations performed.

projgnumpy.ndarray

Projected gradient value (infinity norm of the Jacobian matrix).

jobsfloat

Cost observation component value.

jregfloat

Cost regularization component value.

lcurve_wjregdict[str, Any]

A dictionary containing the wjreg lcurve data. The elements are:

wjreg_optfloat

The optimal wjreg value.

wjreg_approx: float

The approximative wjreg value evaluated with one optimization cycle only.

distancenumpy.ndarray

An array of shape (6,) representing the L-Curve distance for each optimization cycle (the maximum distance corresponds to the optimal wjreg).

costnumpy.ndarray

An array of shape (6,) representing the cost values for each optimization cycle.

jobsnumpy.ndarray

An array of shape (6,) representing the jobs values for each optimization cycle.

jregnumpy.ndarray

An array of shape (6,) representing the jreg values for each optimization cycle.

wjregnumpy.ndarray

An array of shape (6,) representing the wjreg values for each optimization cycle.

See also

smash.optimize

Model assimilation using numerical optimization algorithms.

Notes

The object’s available attributes depend on what is requested by the user during a call to optimize in return_options.