INFO:root:Namespace(input_file='data/bimodal.npy', output_dir='outputs/1125', architecture='k-jumps', number_of_states=34, 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: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.8940098816394584
        x: [ 8.652e+00 -8.489e+00 ...  2.557e-01  4.653e-02]
      nit: 71
      jac: [-2.665e-07  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 7533
     njev: 81
 hess_inv: <92x92 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 1 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.8809403688057924
        x: [ 9.858e+00 -1.223e+01 ...  3.268e-01  2.223e-01]
      nit: 103
      jac: [-2.220e-07  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 10881
     njev: 117
 hess_inv: <92x92 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 2 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.8943812692331408
        x: [ 5.004e+00 -7.299e+00 ...  1.902e-01  2.138e-01]
      nit: 74
      jac: [-1.132e-05  4.530e-06 ...  0.000e+00  0.000e+00]
     nfev: 7440
     njev: 80
 hess_inv: <92x92 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 3 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.893873120784538
        x: [ 6.032e+00 -8.285e+00 ...  2.795e-01  8.747e-01]
      nit: 58
      jac: [-4.796e-06  5.773e-07 ...  0.000e+00  0.000e+00]
     nfev: 6045
     njev: 65
 hess_inv: <92x92 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 4 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.883598576478745
        x: [ 6.888e+00 -7.290e+00 ...  9.062e-01  7.676e-01]
      nit: 96
      jac: [-2.665e-06  7.105e-07 ...  0.000e+00  0.000e+00]
     nfev: 10788
     njev: 116
 hess_inv: <92x92 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 5 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.8812826845459414
        x: [ 6.494e+00 -7.362e+00 ...  6.048e-01  7.227e-01]
      nit: 69
      jac: [-1.821e-06  9.770e-07 ...  0.000e+00  0.000e+00]
     nfev: 7254
     njev: 78
 hess_inv: <92x92 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 6 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.880494761291934
        x: [ 8.683e+00 -8.270e+00 ...  2.519e-01  9.685e-01]
      nit: 75
      jac: [-5.329e-07  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 8277
     njev: 89
 hess_inv: <92x92 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 7 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.8598757233742207
        x: [ 7.523e+00 -7.312e+00 ...  5.510e-01  8.300e-01]
      nit: 89
      jac: [-3.064e-06  3.553e-07 ...  0.000e+00  0.000e+00]
     nfev: 10323
     njev: 111
 hess_inv: <92x92 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 8 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.880592718463
        x: [ 1.109e+01 -1.181e+01 ...  9.026e-01  7.924e-01]
      nit: 68
      jac: [-4.441e-08  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 7347
     njev: 79
 hess_inv: <92x92 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 9 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.882306620960091
        x: [ 7.454e+00 -7.314e+00 ...  4.885e-01  6.689e-02]
      nit: 113
      jac: [-2.132e-06  3.553e-07 ...  0.000e+00  0.000e+00]
     nfev: 12276
     njev: 132
 hess_inv: <92x92 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.
