INFO:root:Namespace(input_file='data/far_gaussian.npy', output_dir='outputs/1059', architecture='k-jumps', number_of_states=40, 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=5)
INFO:root:Best Optimization Result for iteration 0 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 46.05170185988091
        x: [ 4.900e-01  2.181e-01 ...  7.219e-01  4.852e-02]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 113
     njev: 1
 hess_inv: <112x112 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: [ 4.224e-01  2.868e-01 ...  9.612e-01  1.323e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 113
     njev: 1
 hess_inv: <112x112 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: [ 7.760e-01  4.678e-01 ...  9.379e-01  5.396e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 113
     njev: 1
 hess_inv: <112x112 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: [ 3.161e-02  1.913e-01 ...  8.590e-01  5.385e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 113
     njev: 1
 hess_inv: <112x112 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: [ 4.049e-01  9.532e-01 ...  9.724e-01  3.050e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 113
     njev: 1
 hess_inv: <112x112 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: [ 5.500e-01  1.329e-01 ...  8.739e-01  7.269e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 113
     njev: 1
 hess_inv: <112x112 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: [ 5.254e-01  8.024e-01 ...  7.310e-01  5.779e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 113
     njev: 1
 hess_inv: <112x112 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: [ 6.026e-01  4.308e-01 ...  8.969e-01  9.944e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 113
     njev: 1
 hess_inv: <112x112 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: [ 7.396e-01  6.843e-01 ...  3.630e-01  3.139e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 113
     njev: 1
 hess_inv: <112x112 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: [ 1.357e-01  6.174e-01 ...  7.118e-01  2.990e-01]
      nit: 0
      jac: [ 0.000e+00  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 113
     njev: 1
 hess_inv: <112x112 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.
