def objfunc(x):
inputs = {'sma':{'x-':x[0], 'y-':x[1], 'x+':x[2], 'y+':x[3]},
'linear':{'x-':x[4], 'y-':x[5], 'x+':x[6], 'y+':x[7]}}
DataFile = open('opt_data.txt','a')
for x_i in x:
DataFile.write( '\t %.5f' % (x_i) )
DataFile.close()
# print inputs
outputs = run(inputs = inputs, parameters = [eng])
k_nadir = 0
k_utopia = 514.486
normalized_theta = 1 + outputs['theta']/(math.pi/2.)
normalized_k = (abs(outputs['k']) - k_nadir)/(k_utopia - k_nadir)
f = 0.9*normalized_theta + 0.1*normalized_k
DataFile = open('opt_data.txt','a')
DataFile.write( '\t %.5f \t %.5f \t %.5f' % (outputs['theta'], outputs['k'], f) )
DataFile.write('\n')
DataFile.close()
# f = x[0] + x[1] + x[2] + x[3] + x[4] + x[5] + x[6] + x[7]
fail = 0
g = []
return f,g,fail
def objfunc_BFGS(x):
inputs = {'sma':{'x-':x[0], 'y-':x[1], 'x+':x[2], 'y+':x[3]},
'linear':{'x-':x[4], 'y-':x[5], 'x+':x[6], 'y+':x[7]}}
DataFile = open('opt_data.txt','a')
for x_i in x:
DataFile.write( '\t %.5f' % (x_i) )
DataFile.close()
# print inputs
outputs = run(inputs = inputs, parameters = [eng])
f = outputs['theta']
# print f
DataFile = open('opt_data.txt','a')
DataFile.write( '\t %.5f' % (f) )
DataFile.write('\n')
DataFile.close()
return f