INFO:root:Namespace(input_file='data/far_gaussian.npy', output_dir='outputs/263', architecture='combined', number_of_states=6, log_f='trainig_log', no_mean=1, threads=20, fit='d', training_opt=[10, 1000, 100], opt_options=[1e-06, 1e-06, 15000.0, 10.0])
INFO:root:Best Optimization Result for iteration 0 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 7.870e-01  2.944e-01  1.308e-01  9.568e-01  8.565e-01
             3.208e-01  6.422e-01  8.406e-01  5.774e-01  4.574e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00
             0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 11
     njev: 1
 hess_inv: <10x10 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 1 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 2.279e-01  6.064e-02  4.474e-01  7.951e-01  8.740e-01
             7.336e-02  7.264e-02  6.667e-01  3.165e-01  8.674e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00
             0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 11
     njev: 1
 hess_inv: <10x10 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 2 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 3.304e-01  1.064e-01  7.897e-01  2.061e-01  9.959e-01
             8.548e-01  3.139e-01  8.440e-02  1.486e-02  5.732e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00
             0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 11
     njev: 1
 hess_inv: <10x10 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 3 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 1.724e-01  8.652e-03  1.654e-01  4.764e-01  6.648e-01
             9.194e-02  4.575e-01  8.505e-02  3.554e-01  4.548e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00
             0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 11
     njev: 1
 hess_inv: <10x10 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 4 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 7.662e-02  7.453e-01  8.211e-02  9.132e-01  1.776e-01
             7.644e-01  4.044e-02  3.148e-01  5.793e-02  1.900e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00
             0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 11
     njev: 1
 hess_inv: <10x10 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 5 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 9.971e-01  6.995e-01  9.678e-02  9.266e-02  6.787e-01
             4.235e-01  8.337e-01  2.807e-01  8.245e-01  8.443e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00
             0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 11
     njev: 1
 hess_inv: <10x10 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 6 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 5.279e-02  2.524e-01  5.270e-02  9.497e-01  2.756e-01
             5.726e-01  9.259e-01  3.143e-01  2.993e-01  3.461e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00
             0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 11
     njev: 1
 hess_inv: <10x10 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 7 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 4.350e-01  5.367e-01  9.375e-02  8.906e-01  8.381e-01
             5.629e-01  1.182e-01  3.379e-01  2.102e-01  3.875e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00
             0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 11
     njev: 1
 hess_inv: <10x10 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 8 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 2.794e-01  2.778e-01  1.932e-01  1.562e-01  8.080e-01
             5.114e-01  6.450e-01  9.060e-01  1.781e-01  9.732e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00
             0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 11
     njev: 1
 hess_inv: <10x10 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 9 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 5.854e-01  5.466e-01  2.128e-01  9.640e-01  9.025e-01
             2.802e-01  4.149e-02  6.003e-01  7.647e-01  5.012e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00
             0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 11
     njev: 1
 hess_inv: <10x10 LbfgsInvHessProduct with dtype=float64>
