jax.scipy.optimize.OptimizeResults

class jax.scipy.optimize.OptimizeResults(x: jax.Array, success: bool | jax.Array, status: int | jax.Array, fun: jax.Array, jac: jax.Array, hess_inv: jax.Array | None, nfev: int | jax.Array, njev: int | jax.Array, nit: int | jax.Array)

Object holding optimization results.

Parameters:

• x – final solution.

• success – True if optimization succeeded.

• status – integer solver specific return code. 0 means converged (nominal), 1=max BFGS iters reached, 3=zoom failed, 4=saddle point reached, 5=max line search iters reached, -1=undefined

• fun – final function value.

• jac – final jacobian array.

• hess_inv – final inverse Hessian estimate.

• nfev – integer number of function calls used.

• njev – integer number of gradient evaluations.

• nit – integer number of iterations of the optimization algorithm.

__init__()

Methods

__init__()
count(value, /)	Return number of occurrences of value.
index(value[, start, stop])	Return first index of value.

Attributes

fun	Alias for field number 3
hess_inv	Alias for field number 5
jac	Alias for field number 4
nfev	Alias for field number 6
nit	Alias for field number 8
njev	Alias for field number 7
status	Alias for field number 2
success	Alias for field number 1
x	Alias for field number 0