Information in tkutils.set_exception(): Set excption handler sys.excepthook

#========================================================
#  single peak fit sample program
#========================================================

Check infile parameter:
  Input file [peaks.xlsx] is given.
  Paramter file is set to [D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks.in].

Update paramers from command line arguments
i=1 positional arg: error

Read configration file [D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks.in]
Read parameters from [D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks.in]
  alpha: 0
  bg_c0: 0
  bg_c1: 0
  converted_file: 
  cv: 
  daemon: 0
  datafile: peaks-cal.xlsx
  dx: 1e-05
  ffitfiles: 0
  fhistory: 1
  figsize: [8, 6]
  file1: error
  file2: 
  file3: 
  file4: 
  file5: 
  fitfile: peaks-fit.xlsx
  fitfile_template: {filebody}_parameters.csv
  fmax_plot: 10
  fmax_record: 2000
  fmin_max_mlr: 60
  fontsize: 16
  fplot: 1
  ga_nmaxiter: 3
  graphupdateinterval: 10
  help: 0
  hidden_layer_sizes: 3,3,3
  historyfile: D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks-history.xlsx
  I0: 1
  infile: peaks.xlsx
  initialize_method: simplex
  input_template: 
  interval: 50
  ix_plot: 
  ix_sort: 
  jac: 3-points
  kvariance: 6
  l1_ratio: 0.5
  legend_fontsize: 12
  logfile: D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks-out.txt
  max_iter_mlp: 1000
  max_num_probes: 1
  method: nelder-mead
  mode: fit
  mutation_rate: 0.01
  n_restarts_optimizer: 50
  ncal_error: 11
  Nmax: 1e+23
  nmax_surrogate_trial: 5
  nmaxcall: 10000
  nmaxdata: 20
  nmaxiter: 1000
  Nmin: 0
  nohup: 0
  nparents: 5
  nsample: 100
  num_rand_basis: 400
  nx: 5
  outfile: input-repeat.xlsx
  parameterfile: D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks.in
  plot_interval: 5
  print_interval: 5
  run: 1
  sample: 
  score_mode: EI
  seed: 
  surrogate_method: cg
  surrogate_model: gpr
  surrogate_scores: max
  target_var: 0
  test_data_ratio: 0.2
  Tmax: 1000
  Tmin: 0
  tol: 1e-05
  trainfile: fit_db.xlsx
  use_cv: 0
  use_tkplt: 0
  w: 0.5
  x0: 
  x1: 
  x_scale: 
  xatol: 0.0001
  xc: 0
  xlabel: 0
  y_scale: 
  ylabel: 1
infile: peaks.xlsx
parameterfile: D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks.in
stop file: D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\stop

Estimate errors for fitted parameters:
In tkminimize_func.read_parameters():
Read parameters from [D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks.in]
mode                 : error
fplot                : 1
fhistory             : 1
ffitfiles            : 0
stop path            : D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\stop
infile               : peaks.xlsx
outfile              : input-repeat.xlsx

config parameter file : D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks.in
fitting parameter file: D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks_parameters.csv
history file          : D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks-history.xlsx

Fitting configuration
  method  : nelder-mead
  jac     : 3-points
  tol     : 1e-05
  nmaxiter: 1000
  nmaxcall: 10000
  y_scale  : 
Fitting parameters red from [D:\git\tkProg\tkprog_COE\optimize\optimize_peakfit1\test\peaks_parameters.csv]:
   00:      bg_c0=     0.11091            (id=1) (linear=1) penality:        1 * (-1e+10 - 1e+10)
   01:      bg_c1=  0.00687364            (id=1) (linear=1) penality:        1 * (-1e+10 - 1e+10)
   02:         I0=     1.39069            (id=1) (linear=1) penality:        1 * (0 - 1e+10)
   03:         xc=    0.288756            (id=1) (linear=0) penality:        1 * (0 - 200)
   04:          w=    0.601388            (id=1) (linear=0) penality:        1 * (0.01 - 10)
Read input data from [peaks.xlsx]
minimize_func.read_input_data(): Read input data from [peaks.xlsx]
Save input data repeat to [input-repeat.xlsx]

Fitting parameters:
   00:      bg_c0=     0.11091            (id=1) (linear=1) penality:        1 * (-1e+10 - 1e+10)
   01:      bg_c1=  0.00687364            (id=1) (linear=1) penality:        1 * (-1e+10 - 1e+10)
   02:         I0=     1.39069            (id=1) (linear=1) penality:        1 * (0 - 1e+10)
   03:         xc=    0.288756            (id=1) (linear=0) penality:        1 * (0 - 200)
   04:          w=    0.601388            (id=1) (linear=0) penality:        1 * (0.01 - 10)

plot: 3 x 2 for 5 graphs

Calculate likelihood function for var#0/5 bg_c0=     0.11091 for 11 points
Error statistics for bg_c0:
  # of data   : 101
  mean        :  -7.1746e-06
  variance    :   0.00206984
  S2=sum(error^2):     0.209054
  xrange: -1e+10 - 1e+10
  S2=         101
  p0= 1.16984e-22
  S2_target=107

*** Warning in tkFit_mxy_flex.build_likelihood_func(): xlim_max=10000000000 is too large for nmax_iter=10
    nmaxiter is changed to 44, kstep is changed to 382.0

    calculate in xrange: 0.11091 - 0.122051 at S2=107.065
xlim_min=-10000000000

*** Warning in tkFit_mxy_flex.build_likelihood_func(): xlim_min=-10000000000 is too large for nmax_iter=10
    nmaxiter is changed to 55, kstep is changed to 115.0

    calculate in xrange: 0.0997686 - 0.11091 at S2=107.049
  Save to [error_bg_c0.xlsx]
Save to [error_bg_c0.xlsx]
  index at maximum p in p_list:10
  x_min_s at p(sigma):     0.106375
  x_max_s at p(sigma):     0.115431

Accuracy within one sigma:
000: bg_c0     :      0.11091 -0.004535 + 0.004521 in (    0.106375 -     0.115431)

Calculate likelihood function for var#1/5 bg_c1=  0.00687364 for 11 points
Error statistics for bg_c1:
  # of data   : 101
  mean        :  -7.1746e-06
  variance    :   0.00206984
  S2=sum(error^2):     0.209054
  xrange: -1e+10 - 1e+10
  S2=         101
  p0= 1.16984e-22
  S2_target=107

*** Warning in tkFit_mxy_flex.build_likelihood_func(): xlim_max=10000000000 is too large for nmax_iter=10
    nmaxiter is changed to 44, kstep is changed to 382.0

    calculate in xrange: 0.00687364 - 0.0140359 at S2=106.942
xlim_min=-10000000000

*** Warning in tkFit_mxy_flex.build_likelihood_func(): xlim_min=-10000000000 is too large for nmax_iter=10
    nmaxiter is changed to 55, kstep is changed to 115.0

    calculate in xrange: -0.000288635 - 0.00687364 at S2=106.948
  Save to [error_bg_c1.xlsx]
Save to [error_bg_c1.xlsx]
  index at maximum p in p_list:10
  x_min_s at p(sigma):   0.00393708
  x_max_s at p(sigma):   0.00981401

Accuracy within one sigma:
000: bg_c0     :      0.11091 -0.004535 + 0.004521 in (    0.106375 -     0.115431)
001: bg_c1     :   0.00687364 -0.002937 +  0.00294 in (  0.00393708 -   0.00981401)

Calculate likelihood function for var#2/5 I0=     1.39069 for 11 points
Error statistics for I0:
  # of data   : 101
  mean        :  -7.1746e-06
  variance    :   0.00206984
  S2=sum(error^2):     0.209054
  xrange: 0 - 1e+10
  S2=         101
  p0= 1.16984e-22
  S2_target=107

*** Warning in tkFit_mxy_flex.build_likelihood_func(): xlim_max=10000000000 is too large for nmax_iter=10
    nmaxiter is changed to 44, kstep is changed to 382.0

    calculate in xrange: 1.39069 - 1.41934 at S2=106.974
xlim_min=0
    calculate in xrange: 1.3619 - 1.39069 at S2=107.041
  Save to [error_I0.xlsx]
Save to [error_I0.xlsx]
  index at maximum p in p_list:10
  x_min_s at p(sigma):      1.37898
  x_max_s at p(sigma):      1.40242

Accuracy within one sigma:
000: bg_c0     :      0.11091 -0.004535 + 0.004521 in (    0.106375 -     0.115431)
001: bg_c1     :   0.00687364 -0.002937 +  0.00294 in (  0.00393708 -   0.00981401)
002: I0        :      1.39069 -0.01171 +  0.01173 in (     1.37898 -      1.40242)

Calculate likelihood function for var#3/5 xc=    0.288756 for 11 points
Error statistics for xc:
  # of data   : 101
  mean        :  -7.1746e-06
  variance    :   0.00206984
  S2=sum(error^2):     0.209054
  xrange: 0 - 200
  S2=         101
  p0= 1.16984e-22
  S2_target=107

*** Warning in tkFit_mxy_flex.build_likelihood_func(): xlim_max=200 is too large for nmax_iter=10
    nmaxiter is changed to 13, kstep is changed to 88.0

    calculate in xrange: 0.288756 - 0.300945 at S2=106.762
xlim_min=0
    calculate in xrange: 0.276348 - 0.288756 at S2=107.02
  Save to [error_xc.xlsx]
Save to [error_xc.xlsx]
  index at maximum p in p_list:10
  x_min_s at p(sigma):     0.283709
  x_max_s at p(sigma):     0.293846

Accuracy within one sigma:
000: bg_c0     :      0.11091 -0.004535 + 0.004521 in (    0.106375 -     0.115431)
001: bg_c1     :   0.00687364 -0.002937 +  0.00294 in (  0.00393708 -   0.00981401)
002: I0        :      1.39069 -0.01171 +  0.01173 in (     1.37898 -      1.40242)
003: xc        :     0.288756 -0.005047 + 0.005091 in (    0.283709 -     0.293846)

Calculate likelihood function for var#4/5 w=    0.601388 for 11 points
Error statistics for w:
  # of data   : 101
  mean        :  -7.1746e-06
  variance    :   0.00206984
  S2=sum(error^2):     0.209054
  xrange: 0.01 - 10
  S2=         101
  p0= 1.16984e-22
  S2_target=107

*** Warning in tkFit_mxy_flex.build_likelihood_func(): xlim_max=10 is too large for nmax_iter=10
    nmaxiter is changed to 7, kstep is changed to 38.0

    calculate in xrange: 0.601388 - 0.623416 at S2=114.147
xlim_min=0.01

*** Warning in tkFit_mxy_flex.build_likelihood_func(): xlim_min=0.01 is too large for nmax_iter=10
    nmaxiter is changed to 16, kstep is changed to 23.0

    calculate in xrange: 0.586834 - 0.601388 at S2=106.914
  Save to [error_w.xlsx]
Save to [error_w.xlsx]
  index at maximum p in p_list:10
  x_min_s at p(sigma):     0.595376
  x_max_s at p(sigma):     0.607408

Accuracy within one sigma:
000: bg_c0     :      0.11091 -0.004535 + 0.004521 in (    0.106375 -     0.115431)
001: bg_c1     :   0.00687364 -0.002937 +  0.00294 in (  0.00393708 -   0.00981401)
002: I0        :      1.39069 -0.01171 +  0.01173 in (     1.37898 -      1.40242)
003: xc        :     0.288756 -0.005047 + 0.005091 in (    0.283709 -     0.293846)
004: w         :     0.601388 -0.006012 +  0.00602 in (    0.595376 -     0.607408)
time at startup:24/11/19 12:21:40
time at end:24/11/19 12:21:42
Elapsed time from startup to end:    2.80777 sec

Warning in tkplotevent.on_click_default(): axis is not matched with line#11