INFO:root:Namespace(input_file='data/far_gaussian.npy', output_dir='outputs/189', architecture='chain', number_of_states=10, log_f='trainig_log', no_mean=1, threads=1, fit='d', training_opt=[10, 500, 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: [ 5.639e-01  6.442e-01  2.120e-01  5.066e-01  2.878e-01
             8.356e-01  7.045e-02  9.578e-01  1.525e-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]
     nfev: 10
     njev: 1
 hess_inv: <9x9 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: [ 1.327e-01  4.244e-01  7.084e-01  7.280e-01  6.574e-01
             7.538e-01  1.876e-01  7.147e-01  4.569e-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]
     nfev: 10
     njev: 1
 hess_inv: <9x9 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: [ 5.921e-01  7.596e-01  5.128e-01  5.414e-01  5.797e-01
             4.832e-01  5.856e-01  3.862e-01  1.988e-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]
     nfev: 10
     njev: 1
 hess_inv: <9x9 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: [ 4.574e-01  3.372e-01  9.094e-01  8.456e-01  5.308e-01
             9.516e-02  3.183e-02  1.075e-01  4.405e-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]
     nfev: 10
     njev: 1
 hess_inv: <9x9 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: [ 1.732e-01  2.133e-01  3.256e-03  4.049e-01  5.459e-01
             3.995e-01  7.186e-01  3.688e-01  7.283e-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]
     nfev: 10
     njev: 1
 hess_inv: <9x9 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: [ 4.978e-01  1.781e-01  5.358e-01  7.616e-01  5.241e-01
             1.497e-01  9.861e-01  1.366e-01  1.854e-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]
     nfev: 10
     njev: 1
 hess_inv: <9x9 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: [ 8.034e-01  4.407e-02  5.797e-01  2.959e-01  4.960e-01
             9.138e-01  4.427e-01  5.026e-01  7.171e-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]
     nfev: 10
     njev: 1
 hess_inv: <9x9 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: [ 3.031e-01  9.658e-02  2.522e-01  2.909e-01  4.524e-01
             3.593e-01  5.831e-01  4.772e-02  1.704e-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]
     nfev: 10
     njev: 1
 hess_inv: <9x9 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: [ 4.206e-01  6.695e-01  8.649e-01  1.237e-01  5.252e-01
             5.092e-01  2.868e-01  9.786e-01  7.141e-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]
     nfev: 10
     njev: 1
 hess_inv: <9x9 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: [ 5.647e-01  9.399e-01  3.005e-01  3.583e-01  2.022e-01
             3.399e-01  1.243e-01  5.285e-01  3.775e-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]
     nfev: 10
     njev: 1
 hess_inv: <9x9 LbfgsInvHessProduct with dtype=float64>
