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commented out skopt in optimizers

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titusquah
2020-07-14 17:16:48 -06:00
parent 159a5c8140
commit cab58fda25
2 changed files with 32 additions and 31 deletions
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29
.idea/workspace.xml generated
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@@ -2,15 +2,8 @@
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<change afterPath="$PROJECT_DIR$/docs/Examples/iterative_fitter.py" afterDir="false" />
<change afterPath="$PROJECT_DIR$/llepe/objectives.py" afterDir="false" />
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<option name="SHOW_DIALOG" value="false" /> <option name="SHOW_DIALOG" value="false" />
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@@ -269,7 +262,14 @@
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<updated>1594739749122</updated> <updated>1594739749122</updated>
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@@ -293,7 +293,8 @@
<MESSAGE value="Edited parity plot to allow color to represent 3rd dimension. Still need to improve colorbar axis name." /> <MESSAGE value="Edited parity plot to allow color to represent 3rd dimension. Still need to improve colorbar axis name." />
<MESSAGE value="updated to LLEPE" /> <MESSAGE value="updated to LLEPE" />
<MESSAGE value="fixed setup file by changing LLEPE to llepe" /> <MESSAGE value="fixed setup file by changing LLEPE to llepe" />
<option name="LAST_COMMIT_MESSAGE" value="fixed setup file by changing LLEPE to llepe" /> <MESSAGE value="added example file to do iterative optimization" />
<option name="LAST_COMMIT_MESSAGE" value="added example file to do iterative optimization" />
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@@ -313,11 +314,11 @@
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@@ -367,11 +368,11 @@
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34
llepe/optimizers.py
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@@ -1,6 +1,6 @@
import scipy.optimize as scipy_opt import scipy.optimize as scipy_opt
from scipy.optimize import minimize from scipy.optimize import minimize
import skopt # import skopt
def dual_anneal_optimizer(objective, x_guess): def dual_anneal_optimizer(objective, x_guess):
bounds = [(1e-1, 1e1)] * len(x_guess) bounds = [(1e-1, 1e1)] * len(x_guess)
@@ -21,19 +21,19 @@ def diff_evo_optimizer(objective, x_guess):
return est_parameters, res.fun return est_parameters, res.fun
def forest_lbfgsb_optimizer(objective, x_guess): # def forest_lbfgsb_optimizer(objective, x_guess):
x_guess = list(x_guess) # x_guess = list(x_guess)
bounds = [(1e-1, 1e1)]*len(x_guess) # bounds = [(1e-1, 1e1)]*len(x_guess)
bounds[1] = (1e-1, 2) # bounds[1] = (1e-1, 2)
res = skopt.forest_minimize(objective, # res = skopt.forest_minimize(objective,
bounds, # bounds,
random_state=1, # random_state=1,
acq_func='LCB', # acq_func='LCB',
n_random_starts=30, # n_random_starts=30,
x0=x_guess, # x0=x_guess,
xi=1e-4) # xi=1e-4)
x_guess = res.x # x_guess = res.x
optimizer_kwargs = {"method": 'l-bfgs-b', # optimizer_kwargs = {"method": 'l-bfgs-b',
"bounds": bounds} # "bounds": bounds}
res = minimize(objective, x_guess, **optimizer_kwargs) # res = minimize(objective, x_guess, **optimizer_kwargs)
return res.x, res.fun # return res.x, res.fun