optimize_mup 実行例
help出力 optimize_mup.py --help
Warning in tkprogvars.py: Environment variable tkProg_Root is not given
tkProg_Root is speculated from the script path [D:\git\tkProg\sphinx\tkProg\docs\source\electrical\optimize_mup\optimize_mup.py]
time at startup: 26/03/21 18:11:35
Read application configuration from [optimize_mup_arg_config.xlsx]
Read fitting configuration from [optimize_mup_fit_config.xlsx]
get_list_from_cells(): len(cells)= 15
get_list_from_cells(): len(cells[0])= 10
Read_sheet_list: len(datalist)= 10
Read_sheet_list: len(datalist[0])= 14
Open logfile [D:\git\tkProg\sphinx\tkProg\docs\source\electrical\optimize_mup\Hall-T-out.txt]
Information in tkutils.set_exception(): Set excption handler sys.excepthook
#========================================================
# optimize_mu_pi
#========================================================
Check infile parameter:
Input file [Hall-T.xlsx] is given.
Paramter file is set to [D:\git\tkProg\sphinx\tkProg\docs\source\electrical\optimize_mup\Hall-T.in].
Update parameters from command line arguments
#==============================================
Found the argument [--help] for help:
#==============================================
time at startup: 26/03/21 18:11:35
time at end: 26/03/21 18:11:35
Elapsed time from startup to end: 0.0774911 sec
Usage: python optimize_mup.py [--help=val] [--mode=[init|inf|lasso|sim|scan|mapping|sampling|fit|plot|plot_mu_N|plot_history|mlr|error]] [--infile=path] [--xlabel=int|str] [--ylabel=int|str] [--sample=val] [--ix_sort=val] [--Tmin=val] [--Tmax=val] [--Nmin=val] [--Nmax=val] [--trainfile=val] [--outfile=path] [--fitfile=path] [--datafile=path] [--fitfile_template=filename] [--input_template=path] [--converted_file=path] [--fhisotry=[0|1]] [--ffitfiles=[0|1]] [--x_scale=val] [--y_scale=[|log]] [--method=[nelder-mead|cg|bfgs|pso|ga|sa|so|so:test|so:ga:gpr:cg]] [--jac=[3-points|2-points|func]] [--nmaxiter=int(>1)] [--nmaxcall=int(>1)] [--tol=val] [--xatol=val] [--interval=val] [--print_interval=val] [--fmax_record=val] [--ncal_error=val] [--target_var=val] [--x0=val] [--x1=val] [--nx=val] [--dx=val] [--surrogate_model=[gp]] [--surrogate_method=[cg|L-BFGS-B|nelder-mead]] [--initialize_method=[random|ga|simplex]] [--surrogate_scores=[mean|min|max|sigma|-sigma]] [--nmax_surrogate_trial=int] [--nparents=int] [--ga_nmaxiter=int] [--nmaxdata=int] [--mutation_rate=val] [--test_data_ratio=val] [--l1_ratio=val] [--alpha=val] [--use_cv=val] [--cv=val] [--nsample=val] [--fmin_max_mlr=val] [--kvariance=val] [--n_restarts_optimizer=int] [--seed=val] [--score_mode=val] [--max_num_probes=val] [--num_rand_basis=val] [--hidden_layer_sizes="n1,n2,3" etc] [--max_iter_mlp=int] [--use_tkplt=[0|1]] [--fplot=[0|1]] [--fmax_plot=val] [--graphupdateinterval=val] [--plot_interval=val] [--fontsize=val] [--legend_fontsize=val] [--ix_plot=val] [--run=[0|1]] [--daemon=[0|1]] [--nohup=[0|1]] [VB] [sigma0] [Eop] [p1] [a1] [p2] [a2] [p3] [a3] [p4] [a4] [p5] [a5] [#1 arg: file1: val] [#2 arg: file2: val] [#3 arg: file3: val] [#4 arg: file4: val] [#5 arg: file5: val]
Options:
--help=val (def=0) (type=str)
help
--mode=[init|inf|lasso|sim|scan|mapping|sampling|fit|plot|plot_mu_N|plot_history|mlr|error] (def=fit) (type=str)
task mode
--infile=path (def=Hall-T.xlsx) (type=str)
measured IV Excel/parameter .in file
--xlabel=int|str (def=T) (type=str)
index or label name (regexp) for x values
--ylabel=int|str (def=mu) (type=str)
index or label name (regexp) for y values
--sample=val (def=) (type=str)
sample
--ix_sort=val (def=) (type=int|str)
index iof x_data to sort data_list
--Tmin=val (def=0) (type=float)
Tmin
--Tmax=val (def=1000) (type=float)
Tmax
--Nmin=val (def=0) (type=float)
Nmin
--Nmax=val (def=1e+23) (type=float)
Nmax
--trainfile=val (def=fit_db.xlsx) (type=str)
Training history file (.xlsx) for MLR
--outfile=path (def=input-repeat.xlsx) (type=str)
Input reapeal Excel file
--fitfile=path (def=mu-fit.xlsx) (type=str)
Fitting result (.xlsx) file
--datafile=path (def=mu.xlsx) (type=str)
input/calculated data .xlsx file
--fitfile_template=filename (def={filebody}_parameters.csv) (type=str)
Template string to make fitting parameter file
--input_template=path (def=) (type=str)
mode=convert: Input template path
--converted_file=path (def=) (type=str)
mode=convert: Output converted file
--fhisotry=[0|1] (def=1) (type=int)
flag to save hisotry file
--ffitfiles=[0|1] (def=0) (type=int)
flag to save fit files
--x_scale=val (def=) (type=str)
x scale to plot [blank|log]
--y_scale=[|log] (def=) (type=str)
Y scale to fit
--method=[nelder-mead|cg|bfgs|pso|ga|sa|so|so:test|so:ga:gpr:cg] (def=nelder-mead) (type=str)
optimization algorism
--jac=[3-points|2-points|func] (def=3-points) (type=str)
first differential
--nmaxiter=int(>1) (def=1000) (type=int)
maximum interation number for optimization
--nmaxcall=int(>1) (def=10000) (type=int)
maximum number for function calls
--tol=val (def=1e-05) (type=float)
eps for optimization
--xatol=val (def=0.0001) (type=float)
eps for parameter change for optimization
--interval=val (def=50) (type=int)
interval
--print_interval=val (def=5) (type=int)
print interval
--fmax_record=val (def=2000) (type=float)
max fmin to record to file
--ncal_error=val (def=11) (type=int)
# of mesh for error probability function
--target_var=val (def=0) (type=str|int)
target_var
--x0=val (def=) (type=float|str)
x0
--x1=val (def=) (type=float|str)
x1
--nx=val (def=5) (type=int)
nx
--dx=val (def=1e-05) (type=float)
dx for numerical differentiation in mode=fit1
--surrogate_model=[gp] (def=gpr) (type=str)
Surrogate model
--surrogate_method=[cg|L-BFGS-B|nelder-mead] (def=cg) (type=str)
Minimize algorism for surrogate optimization
--initialize_method=[random|ga|simplex] (def=simplex) (type=str)
Generation algorism for initial parameters
--surrogate_scores=[mean|min|max|sigma|-sigma] (def=max) (type=str)
GP score to minimize
--nmax_surrogate_trial=int (def=5) (type=int)
Max trials for cases x are not updated
--nparents=int (def=5) (type=int)
Number of parents in initial parameters
--ga_nmaxiter=int (def=3) (type=int)
# of GA iteration to generate initial parameters
--nmaxdata=int (def=20) (type=int)
Maximum number of data used for surrogate optimization
--mutation_rate=val (def=0.01) (type=float)
Mutation rate for genetic algorism
--test_data_ratio=val (def=0.2) (type=float)
Ratio of test data
--l1_ratio=val (def=0.5) (type=float)
L1 reguralization parameter ratio
--alpha=val (def=0) (type=float)
L2 reguralization parameter
--use_cv=val (def=0) (type=int)
flag to use CV
--cv=val (def=) (type=int|str)
# of cross validation
--nsample=val (def=100) (type=int)
nsample
--fmin_max_mlr=val (def=60) (type=float)
Max value of fmin for MLR
--kvariance=val (def=6) (type=float)
Multiplier of variance for error estimation
--n_restarts_optimizer=int (def=50) (type=int)
# of maximum interation to optimize hyper parameters in GA
--seed=val (def=) (type=int|str)
seed
--score_mode=val (def=EI) (type=int)
score_mode
--max_num_probes=val (def=1) (type=int)
max_num_probes
--num_rand_basis=val (def=400) (type=int)
num_rand_basis
--hidden_layer_sizes="n1,n2,3" etc (def=3,3,3) (type=str)
Number of perceptrons and layers seprated by comma
--max_iter_mlp=int (def=1000) (type=int)
Number of max iteration for mlp regression
--use_tkplt=[0|1] (def=0) (type=int)
flag to use tkplot
--fplot=[0|1] (def=1) (type=int)
flag to plot graph
--fmax_plot=val (def=10) (type=float)
max fmin to plot
--graphupdateinterval=val (def=10) (type=int)
graphupdateinterval
--plot_interval=val (def=5) (type=int)
plot interval
--fontsize=val (def=16) (type=int)
fontsize
--legend_fontsize=val (def=12) (type=int)
legend_fontsize
--ix_plot=val (def=) (type=int|str)
index of x_data to plot as x-axis
--run=[0|1] (def=1) (type=int)
flag to run external app
--daemon=[0|1] (def=0) (type=int)
daemonize the process
--nohup=[0|1] (def=0) (type=int)
flag to ignore HUP signal
VB (def=0) (type=float)
fitting parameter
sigma0 (def=0) (type=float)
fitting parameter
Eop (def=0.0446) (type=float)
fitting parameter
p1 (def=0) (type=float)
fitting parameter
a1 (def=1) (type=float)
fitting parameter
p2 (def=-0.5) (type=float)
fitting parameter
a2 (def=0) (type=float)
fitting parameter
p3 (def=0.5) (type=float)
fitting parameter
a3 (def=0) (type=float)
fitting parameter
p4 (def=-1) (type=float)
fitting parameter
a4 (def=0) (type=float)
fitting parameter
p5 (def=1) (type=float)
fitting parameter
a5 (def=0) (type=float)
fitting parameter
#1 arg: file1: val (def=) (type=str)
file1
#2 arg: file2: val (def=) (type=str)
file2
#3 arg: file3: val (def=) (type=str)
file3
#4 arg: file4: val (def=) (type=str)
file4
#5 arg: file5: val (def=) (type=str)
file5
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