INFO:root:Namespace(input_file='data/far_gaussian.npy', output_dir='outputs/327', architecture='escape_chain', number_of_states=10, 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 -1.500e+01 -1.167e+01 -1.500e+01 -1.284e+01
            -1.042e+01 -9.414e+00 -1.000e+01  3.141e-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 1 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [-1.500e+01 -1.500e+01 -1.202e+01 -1.500e+01 -1.471e+01
            -1.026e+01 -9.102e+00 -1.011e+01  9.631e-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: [-1.500e+01 -1.500e+01 -1.281e+01 -1.210e+01 -1.266e+01
            -1.170e+01 -1.088e+01 -9.996e+00  8.208e-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: [-1.500e+01 -1.500e+01 -1.258e+01 -1.142e+01 -1.144e+01
            -1.093e+01 -1.064e+01 -9.445e+00  3.939e-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: [-1.500e+01 -1.500e+01 -1.258e+01 -1.209e+01 -1.208e+01
            -1.117e+01 -1.051e+01 -1.010e+01  6.127e-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 5 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [-1.500e+01 -1.500e+01 -1.209e+01 -1.190e+01 -1.228e+01
            -1.063e+01 -9.733e+00 -1.008e+01  9.684e-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: [-1.500e+01 -1.500e+01 -1.204e+01 -1.236e+01 -1.500e+01
            -1.052e+01 -9.262e+00 -1.005e+01  3.876e-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: [-1.500e+01 -1.500e+01 -1.228e+01 -1.500e+01 -1.144e+01
            -1.033e+01 -1.002e+01 -1.144e+01  7.274e-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: [-1.500e+01 -1.500e+01 -1.239e+01 -1.383e+01 -1.500e+01
            -1.118e+01 -1.001e+01 -1.074e+01  6.457e-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: [-1.500e+01 -1.500e+01 -1.249e+01 -1.281e+01 -1.500e+01
            -1.164e+01 -9.810e+00 -1.052e+01  1.600e-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>
