python - scipy.optimize.minimize 使用 L-BFGS-B 返回 ABNORMAL_TERMINATION_IN_LNSRCH

Question

我正在使用 scipy.optimize.minimize 来求解/计算 314 次仿射变换中的 3768 个变量，以将一个点云转换为另一个 eval_fun，首先我尝试使用 scipy.optimize.fmin_l_bfgs_b 和 approx_grad 来避免实现渐变，但它一直因 ABNORMAL_TERMINATION_IN_LNSRCH 而崩溃。然后我实现了梯度函数并开始使用最小化，它仍然崩溃并出现同样的错误。

res = minimize(eval_func,
               x0=np.array(M),
               method='L-BFGS-B',
               args=(scan_pts, scan_fce, scan_nrm, scan_mar, temp_pts, temp_fce, temp_nrm, temp_mar, alfa, beta, gama,edges),
               options={'iprint' : 99, 'maxiter' : 100}, jac=True)

这是完整的输出：

This problem is unconstrained.

 Line search cannot locate an adequate point after 20 function
  and gradient evaluations.  Previous x, f and g restored.
 Possible causes: 1 error in function or gradient evaluation;
                  2 rounding error dominate computation.
RUNNING THE L-BFGS-B CODE

           * * *

Machine precision = 2.220D-16
 N =         3768     M =           10

At X0         0 variables are exactly at the bounds

At iterate    0    f=  1.88129D-01    |proj g|=  9.98119D-01


ITERATION     1

---------------- CAUCHY entered-------------------
 There are            0   breakpoints 

 GCP found in this segment
Piece      1 --f1, f2 at start point  -9.3847D+02  9.3847D+02
Distance to the stationary point =   1.0000D+00

---------------- exit CAUCHY----------------------

        3768  variables are free at GCP            1

           * * *

Tit   = total number of iterations
Tnf   = total number of function evaluations
Tnint = total number of segments explored during Cauchy searches
Skip  = number of BFGS updates skipped
Nact  = number of active bounds at final generalized Cauchy point
Projg = norm of the final projected gradient
F     = final function value

           * * *

   N    Tit     Tnf  Tnint  Skip  Nact     Projg        F
 3768      1     21      1     0     0   9.981D-01   1.881D-01
  F =  0.18812870968000006     

ABNORMAL_TERMINATION_IN_LNSRCH                              

我尝试按照此处所述更改所有值： scipy.optimize.fmin_l_bfgs_b 返回 'ABNORMAL_TERMINATION_IN_LNSRCH'但它们都不起作用

我能做些什么？

标签： pythonoptimizationscipyminimize