INFO:root:Namespace(input_file='data/far_gaussian.npy', output_dir='outputs/1138', architecture='k-jumps', number_of_states=16, log_f='trainig_log', no_mean=1, threads=1, fit='d', training_opt=[10, 500, 100], opt_options=[1e-06, 1e-06, 15000.0, 10.0], k=1, l=7)
INFO:root:Best Optimization Result for iteration 0 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 5.335e-02  6.860e-01 ...  2.661e-01  6.632e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 39
     njev: 1
 hess_inv: <38x38 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: [ 1.742e-01  9.071e-01 ...  9.185e-01  2.124e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 39
     njev: 1
 hess_inv: <38x38 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: [ 3.038e-01  3.520e-01 ...  7.450e-01  4.875e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 39
     njev: 1
 hess_inv: <38x38 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: [ 2.661e-01  5.353e-01 ...  4.608e-01  6.361e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 39
     njev: 1
 hess_inv: <38x38 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: [ 1.717e-01  7.452e-01 ...  5.354e-01  4.001e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 39
     njev: 1
 hess_inv: <38x38 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: [ 3.863e-01  3.781e-01 ...  8.979e-01  8.585e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 39
     njev: 1
 hess_inv: <38x38 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: [ 7.149e-01  9.406e-01 ...  7.942e-01  1.954e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 39
     njev: 1
 hess_inv: <38x38 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: [ 4.224e-01  8.420e-01 ...  1.111e-01  5.460e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 39
     njev: 1
 hess_inv: <38x38 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: [ 4.622e-01  9.311e-01 ...  9.631e-01  6.015e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 39
     njev: 1
 hess_inv: <38x38 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: [ 8.104e-02  4.531e-01 ...  7.079e-01  7.628e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 39
     njev: 1
 hess_inv: <38x38 LbfgsInvHessProduct with dtype=float64>
WARNING:matplotlib.legend:No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
