INFO:root:Namespace(input_file='data/bimodal.npy', output_dir='outputs/233', architecture='escape_chain', number_of_states=6, log_f='trainig_log', no_mean=0, threads=1, 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: 46.051701859880914
        x: [-1.500e+01 -1.500e+01 -1.466e+01 -1.095e+01  5.520e-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: 46.051701859880914
        x: [-1.500e+01 -1.500e+01 -1.209e+01 -1.162e+01  2.632e-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: 46.051701859880914
        x: [-1.500e+01 -1.500e+01 -1.463e+01 -1.059e+01  5.393e-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 3 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.051701859880914
        x: [-1.500e+01 -1.500e+01 -1.437e+01 -1.074e+01  4.331e-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: 46.051701859880914
        x: [-1.500e+01 -1.500e+01 -1.467e+01 -1.094e+01  7.714e-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: 46.051701859880914
        x: [-1.500e+01 -1.500e+01 -1.272e+01 -1.125e+01  3.253e-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: 46.051701859880914
        x: [-1.500e+01 -1.500e+01 -1.414e+01 -1.110e+01  7.326e-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: 46.051701859880914
        x: [-1.500e+01 -1.500e+01 -1.438e+01 -1.104e+01  1.538e-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: 46.051701859880914
        x: [-1.500e+01 -1.500e+01 -1.379e+01 -1.156e+01  8.062e-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: 46.051701859880914
        x: [-1.500e+01 -1.464e+01 -1.308e+01 -1.155e+01  4.775e-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>
