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Silviu Marian Udrescu 2020-06-20 19:30:25 -04:00 • committed by GitHub
parent 7a0d782d51
commit a96e7f321a
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10 changed files with 119 additions and 133 deletions
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19
Code/S_run_aifeynman.py
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@ -33,7 +33,8 @@ def run_AI_all(pathdir,filename,BF_try_time=60,BF_ops_file_type="14ops", polyfit
# load the data for different checks
data = np.loadtxt(pathdir+filename)
PA = get_atan(pathdir,"results/mystery_world_atan/",filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg)
'''
# Run bf and polyfit
PA = run_bf_polyfit(pathdir,pathdir,filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg)
@ -49,7 +50,7 @@ def run_AI_all(pathdir,filename,BF_try_time=60,BF_ops_file_type="14ops", polyfit
PA = get_sqrt(pathdir,"results/mystery_world_sqrt/",filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg)
PA = get_squared(pathdir,"results/mystery_world_squared/",filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg)
PA = get_tan(pathdir,"results/mystery_world_tan/",filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg)
'''
#############################################################################################################################
# check if the NN is trained. If it is not, train it on the data.
print("Checking for symmetry \n", filename)
@ -120,7 +121,8 @@ def run_AI_all(pathdir,filename,BF_try_time=60,BF_ops_file_type="14ops", polyfit
PA1 = run_AI_all(new_pathdir1,new_filename1,BF_try_time,BF_ops_file_type, polyfit_deg, NN_epochs, PA1_)
PA2_ = ParetoSet()
PA2 = run_AI_all(new_pathdir2,new_filename2,BF_try_time,BF_ops_file_type, polyfit_deg, NN_epochs, PA2_)
PA = combine_pareto(pathdir,filename,PA1,PA2,separability_plus_result[1],separability_plus_result[2],PA,"+")
combine_pareto_data = np.loadtxt(pathdir+filename)
PA = combine_pareto(combine_pareto_data,PA1,PA2,separability_plus_result[1],separability_plus_result[2],PA,"+")
return PA
elif idx_min == 5:
@ -129,7 +131,8 @@ def run_AI_all(pathdir,filename,BF_try_time=60,BF_ops_file_type="14ops", polyfit
PA1 = run_AI_all(new_pathdir1,new_filename1,BF_try_time,BF_ops_file_type, polyfit_deg, NN_epochs, PA1_)
PA2_ = ParetoSet()
PA2 = run_AI_all(new_pathdir2,new_filename2,BF_try_time,BF_ops_file_type, polyfit_deg, NN_epochs, PA2_)
PA = combine_pareto(pathdir,filename,PA1,PA2,separability_multiply_result[1],separability_multiply_result[2],PA,"*")
combine_pareto_data = np.loadtxt(pathdir+filename)
PA = combine_pareto(combine_pareto_data,PA1,PA2,separability_multiply_result[1],separability_multiply_result[2],PA,"*")
return PA
else:
return PA
@ -181,10 +184,11 @@ def run_aifeynman(pathdir,filename,BF_try_time,BF_ops_file_type, polyfit_deg=3,
PA_list = PA.get_pareto_points()
np.savetxt("results/solution_first_snap_%s.txt" %filename,PA_list,fmt="%s")
# Run gradient descent on the data one more time
# Run gradient descent on the data one more time
final_gd_data = np.loadtxt(pathdir+filename)
for i in range(len(PA_list)):
try:
gd_update = final_gd(pathdir,filename,PA_list[i][-1])
gd_update = final_gd(final_gd_data,PA_list[i][-1])
PA.add(Point(x=gd_update[1],y=gd_update[0],data=gd_update[2]))
except:
continue
@ -206,8 +210,9 @@ def run_aifeynman(pathdir,filename,BF_try_time,BF_ops_file_type, polyfit_deg=3,
# Try the found expressions on the test data
if DR_file=="" and test_data.size != 0:
test_errors = []
input_test_data = np.loadtxt(pathdir+filename+"_test")
for i in range(len(list_dt)):
test_errors = test_errors + [get_symbolic_expr_error(pathdir,filename+"_test",str(list_dt[i][-1]))]
test_errors = test_errors + [get_symbolic_expr_error(input_test_data,str(list_dt[i][-1]))]
test_errors = np.array(test_errors)
# Save all the data to file
save_data = np.column_stack((test_errors,log_err,log_err_all,list_dt))