jax.scipy.optimize.OptimizeResults#
- class jax.scipy.optimize.OptimizeResults(x: Array, success: bool | Array, status: int | Array, fun: Array, jac: Array, hess_inv: Array | None, nfev: int | Array, njev: int | Array, nit: int | Array)[source]#
Object holding optimization results.
- Parameters:
x – final solution.
success –
Trueif 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
funAlias for field number 3
hess_invAlias for field number 5
jacAlias for field number 4
nfevAlias for field number 6
nitAlias for field number 8
njevAlias for field number 7
statusAlias for field number 2
successAlias for field number 1
xAlias for field number 0