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Dakota_aiming.py
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Dakota_aiming.py
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from onekey_aiming import one_key_start
from sys import path
import numpy as np
def dakota_opt(**kwargs):
num_fns = kwargs['functions'] # equaling to one corresponds to the
x = kwargs['cv']
ASV = kwargs['asv']
retval = dict([])
from sys import path
folder=path[0]
num_bundle_2=num_bundle=16
r_height_2=r_height=24.0
r_diameter_2=r_diameter=16.0
bins=50
tower_h_2=tower_h=175.0
phi_1=phi=0.0
elevation_1=elevation=55.15
DNI_1=DNI=980.0
num_fp_2=num_fp=8
D0_2=D0=60.33
Model=one_key_start(folder,num_bundle,num_fp,r_height,r_diameter,bins,tower_h,phi,elevation,DNI,D0)
# initialization
C_aiming=np.zeros(num_bundle)
Exp=np.zeros(num_bundle)
A_f=np.zeros(num_bundle)
# flowpath 12
C_aiming_12_1=C_aiming[0]=0.7000000000000002
Exp_12_1=Exp[0]=1.5
A_f_12_1=A_f[0]=0.67
C_aiming_12_2=C_aiming[0]=0.7000000000000002
Exp_12_2=Exp[0]=1.5
A_f_12_2=A_f[0]=0.67
# flowpath 11
C_aiming_11_1=C_aiming[0]=0.7000000000000002
Exp_11_1=Exp[0]=1.5
A_f_11_1=A_f[0]=0.67
C_aiming_11_2=C_aiming[0]=0.7000000000000002
Exp_11_2=Exp[0]=1.5
A_f_11_2=A_f[0]=0.67
# flowpath 10
C_aiming_10_1=C_aiming[0]=0.7000000000000002
Exp_10_1=Exp[0]=1.5
A_f_10_1=A_f[0]=0.67
C_aiming_10_2=C_aiming[0]=0.7000000000000002
Exp_10_2=Exp[0]=1.5
A_f_10_2=A_f[0]=0.67
# flowpath 9
C_aiming_9_1=C_aiming[0]=0.7000000000000002
Exp_9_1=Exp[0]=1.5
A_f_9_1=A_f[0]=0.67
C_aiming_9_2=C_aiming[0]=0.7000000000000002
Exp_9_2=Exp[0]=1.5
A_f_9_2=A_f[0]=0.67
# flowpath 8
C_aiming_8_1=C_aiming[4]=0.8000000000000003
Exp_8_1=Exp[4]=1.5
A_f_8_1=A_f[4]=0.33
C_aiming_8_2=C_aiming[12]=0.9000000000000004
Exp_8_2=Exp[12]=7.5000000000e-01
A_f_8_2=A_f[12]=7.4500000000e-01
# flowpath 7
C_aiming_7_1=C_aiming[11]=0.8000000000000003
Exp_7_1=Exp[11]=1.5
A_f_7_1=A_f[11]=0.33
C_aiming_7_2=C_aiming[3]=0.9000000000000004
Exp_7_2=Exp[3]=7.5000000000e-01
A_f_7_2=A_f[3]=7.4500000000e-01
# flowpath 6
C_aiming_6_1=C_aiming[5]=0.6500000000000001
Exp_6_1=Exp[5]=1.5
A_f_6_1=A_f[5]=0.33
C_aiming_6_2=C_aiming[13]=1.0000000000000004
Exp_6_2=Exp[13]=1.5
A_f_6_2=A_f[13]=0.67
# flowpath 5
C_aiming_5_1=C_aiming[10]=0.6500000000000001
Exp_5_1=Exp[10]=1.5
A_f_5_1=A_f[10]=0.33
C_aiming_5_2=C_aiming[2]=1.0000000000000004
Exp_5_2=Exp[2]=1.5
A_f_5_2=A_f[2]=0.67
# flowpath 4
C_aiming_4_1=C_aiming[6]=0.7500000000000002
Exp_4_1=Exp[6]=1.5
A_f_4_1=A_f[6]=0.33
C_aiming_4_2=C_aiming[14]=0.8000000000000003
Exp_4_2=Exp[14]=1.5
A_f_4_2=A_f[14]=0.67
# flowpath 3
C_aiming_3_1=C_aiming[9]=0.7500000000000002
Exp_3_1=Exp[9]=1.5
A_f_3_1=A_f[9]=0.33
C_aiming_3_2=C_aiming[1]=0.8000000000000003
Exp_3_2=Exp[1]=1.5
A_f_3_2=A_f[1]=0.67
# flowpath 2
C_aiming_2_1=C_aiming[7]=0.8000000000000003
Exp_2_1=Exp[7]=1.5
A_f_2_1=A_f[7]=0.33
C_aiming_2_2=C_aiming[15]=0.7000000000000002
Exp_2_2=Exp[15]=1.5
A_f_2_2=A_f[15]=0.67
# flowpath 1
C_aiming_1_1=C_aiming[8]=0.8000000000000003
Exp_1_1=Exp[8]=1.5
A_f_1_1=A_f[8]=0.33
C_aiming_1_2=C_aiming[0]=0.7000000000000002
Exp_1_2=Exp[0]=1.5
A_f_1_2=A_f[0]=0.67
print C_aiming
print Exp
print A_f
aiming_results,eff_interception,Strt=Model.aiming_loop(C_aiming,Exp,A_f)
gx=aiming_results[2][15]
print aiming_results[2]
print eff_interception
f=[gx]
retval['fns'] = f
print f
return(retval)