INFO:root:Namespace(input_file='data/bimodal.npy', output_dir='outputs/354', architecture='escape_chain', number_of_states=4, 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 -1.172e+01  2.049e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 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 -1.146e+01  4.895e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 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 -1.066e+01  9.581e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 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 -1.058e+01  5.970e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 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 -1.089e+01  5.369e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 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 -1.121e+01  2.311e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 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 -1.066e+01  5.779e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 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 -1.004e+01  8.283e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 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 -1.012e+01  4.768e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 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 -1.065e+01  7.496e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 LbfgsInvHessProduct with dtype=float64>
