INFO:root:Namespace(input_file='data/bimodal.npy', output_dir='outputs/355', architecture='escape_chain', number_of_states=6, log_f='trainig_log', no_mean=0, 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: [-1.500e+01 -1.446e+01 -1.278e+01 -1.215e+01  7.236e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 6
     njev: 1
 hess_inv: <5x5 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: [-1.500e+01 -1.500e+01 -1.423e+01 -1.132e+01  5.097e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 6
     njev: 1
 hess_inv: <5x5 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: [-1.500e+01 -1.500e+01 -1.452e+01 -1.108e+01  2.105e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 6
     njev: 1
 hess_inv: <5x5 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: [-1.500e+01 -1.500e+01 -1.500e+01 -1.101e+01  1.347e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 6
     njev: 1
 hess_inv: <5x5 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: [-1.500e+01 -1.496e+01 -1.227e+01 -1.148e+01  7.869e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 6
     njev: 1
 hess_inv: <5x5 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: [-1.500e+01 -1.500e+01 -1.232e+01 -1.117e+01  2.411e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 6
     njev: 1
 hess_inv: <5x5 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: [-1.500e+01 -1.500e+01 -1.425e+01 -1.114e+01  4.757e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 6
     njev: 1
 hess_inv: <5x5 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: [-1.500e+01 -1.500e+01 -1.500e+01 -1.094e+01  8.902e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 6
     njev: 1
 hess_inv: <5x5 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: [-1.500e+01 -1.500e+01 -1.321e+01 -1.081e+01  9.572e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 6
     njev: 1
 hess_inv: <5x5 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: [-1.500e+01 -1.500e+01 -1.309e+01 -1.053e+01  9.962e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00  0.000e+00  0.000e+00]
     nfev: 6
     njev: 1
 hess_inv: <5x5 LbfgsInvHessProduct with dtype=float64>
