INFO:root:Namespace(input_file='data/bimodal.npy', output_dir='outputs/1041', architecture='k-jumps', number_of_states=50, 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: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.822860101371701
        x: [ 7.662e+00 -9.543e+00 ...  1.921e-01  5.481e-01]
      nit: 101
      jac: [-4.219e-06  4.441e-08 ...  0.000e+00  0.000e+00]
     nfev: 16588
     njev: 116
 hess_inv: <142x142 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: 3.8247149294364364
        x: [ 7.079e+00 -8.600e+00 ...  7.391e-01  3.971e-01]
      nit: 77
      jac: [-5.773e-06  1.776e-07 ...  0.000e+00  0.000e+00]
     nfev: 13728
     njev: 96
 hess_inv: <142x142 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: 3.8234976517159156
        x: [ 7.384e+00 -8.367e+00 ...  5.621e-01  9.744e-01]
      nit: 89
      jac: [-5.151e-06  1.776e-07 ...  0.000e+00  0.000e+00]
     nfev: 14729
     njev: 103
 hess_inv: <142x142 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: 3.8235745947376585
        x: [ 6.623e+00 -7.598e+00 ...  5.376e-01  8.327e-01]
      nit: 89
      jac: [-1.177e-05  6.661e-07 ...  0.000e+00  0.000e+00]
     nfev: 14157
     njev: 99
 hess_inv: <142x142 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: 3.823686823750626
        x: [ 1.056e+01 -1.192e+01 ...  4.242e-01  4.663e-02]
      nit: 82
      jac: [-1.776e-07  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 13442
     njev: 94
 hess_inv: <142x142 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: 3.8234999645068144
        x: [ 8.864e+00 -1.192e+01 ...  9.570e-02  9.780e-01]
      nit: 88
      jac: [-1.155e-06  0.000e+00 ...  0.000e+00  0.000e+00]
     nfev: 15444
     njev: 108
 hess_inv: <142x142 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: 3.824771730993696
        x: [ 8.433e+00 -8.086e+00 ...  1.858e-02  1.384e-01]
      nit: 73
      jac: [-1.288e-06  8.882e-08 ...  0.000e+00  0.000e+00]
     nfev: 11869
     njev: 83
 hess_inv: <142x142 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: 3.8207128914753072
        x: [ 7.046e+00 -8.183e+00 ...  7.938e-01  6.636e-01]
      nit: 84
      jac: [-3.597e-06  3.109e-07 ...  0.000e+00  0.000e+00]
     nfev: 13871
     njev: 97
 hess_inv: <142x142 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: 3.824283737034551
        x: [ 7.406e+00 -8.094e+00 ...  8.346e-01  1.231e-01]
      nit: 136
      jac: [-5.018e-06  1.776e-07 ...  0.000e+00  0.000e+00]
     nfev: 23166
     njev: 162
 hess_inv: <142x142 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: 3.8240532644423157
        x: [ 6.078e+00 -6.686e+00 ...  1.368e-01  5.074e-03]
      nit: 75
      jac: [-2.149e-05  2.798e-06 ...  0.000e+00  0.000e+00]
     nfev: 12870
     njev: 90
 hess_inv: <142x142 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.
