INFO:root:Namespace(input_file='data/far_gaussian.npy', output_dir='outputs/1146', architecture='k-jumps', number_of_states=32, 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: [ 3.527e-01  1.013e-01 ...  8.574e-01  5.218e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 87
     njev: 1
 hess_inv: <86x86 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: [ 7.337e-01  4.764e-02 ...  2.682e-01  1.564e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 87
     njev: 1
 hess_inv: <86x86 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: [ 3.960e-01  5.540e-01 ...  9.912e-01  6.762e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 87
     njev: 1
 hess_inv: <86x86 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: [ 8.233e-01  5.139e-01 ...  7.228e-01  5.364e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 87
     njev: 1
 hess_inv: <86x86 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: [ 6.043e-01  8.937e-01 ...  9.850e-01  7.613e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 87
     njev: 1
 hess_inv: <86x86 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: [ 1.909e-01  6.804e-01 ...  8.507e-01  2.261e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 87
     njev: 1
 hess_inv: <86x86 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: [ 4.868e-01  2.927e-01 ...  7.766e-01  3.185e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 87
     njev: 1
 hess_inv: <86x86 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: [ 7.917e-01  1.721e-01 ...  1.068e-01  1.732e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 87
     njev: 1
 hess_inv: <86x86 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: [ 7.724e-01  4.986e-01 ...  9.970e-01  7.759e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 87
     njev: 1
 hess_inv: <86x86 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: [ 8.268e-01  4.066e-01 ...  8.075e-01  1.789e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 87
     njev: 1
 hess_inv: <86x86 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.
