INFO:root:Namespace(input_file='data/bimodal.npy', output_dir='outputs/409', architecture='escape_chain', number_of_states=4, log_f='trainig_log', no_mean=1, 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: [ 1.254e-02  7.414e-01  7.212e-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 1 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.051701859880914
        x: [ 3.964e-01  1.955e-01  6.180e-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: 46.051701859880914
        x: [ 2.082e-01  7.803e-01  6.752e-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 3 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.051701859880914
        x: [ 8.972e-01  4.608e-01  4.821e-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: 46.051701859880914
        x: [ 2.242e-01  2.274e-01  1.699e-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: 46.051701859880914
        x: [ 4.979e-02  8.221e-01  9.761e-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: 46.051701859880914
        x: [ 5.540e-01  3.153e-02  3.977e-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: 46.051701859880914
        x: [ 1.010e-02  8.800e-01  2.641e-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: 46.051701859880914
        x: [ 1.773e-01  2.954e-01  3.158e-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: 46.051701859880914
        x: [ 6.392e-01  2.728e-01  1.017e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00  0.000e+00]
     nfev: 4
     njev: 1
 hess_inv: <3x3 LbfgsInvHessProduct with dtype=float64>
