def obj_func(xdict):
global dia
global tsr
global solidity
global Cp
global dens
global velf
global funcs
Vars = xdict['xvars']
x = xdict['xvars']
y = xdict['yvars']
funcs = {}
veleff = np.zeros_like(x)
power_turb = np.zeros_like(x)
for i in range(np.size(x)):
xp = np.delete(x,i)
yp = np.delete(y,i)
diap = np.delete(dia,i)
tsrp = np.delete(tsr,i)
solidityp = np.delete(solidity,i)
veleff[i] = overlap(xp,yp,diap,tsrp,solidityp,x[i],y[i],dia[i],velf,True,False)
power_turb[i] = powerval(Cp,dens,veleff[i],dia[i])
# print i+1
power = np.sum(power_turb)
print power
funcs['obj'] = (-1.0*power)
sep = sep_func(np.append(x,y))
funcs['sep'] = sep
funcs['veleff'] = veleff
funcs['power_turb'] = power_turb
fail = False
return funcs, fail
spacing = 5 # turbine grid spacing in diameters
# Set up position arrays
points = np.linspace(spacing*turb_dia,nRows*spacing*turb_dia,nRows)
xpoints, ypoints = np.meshgrid(points, points)
xt = np.ndarray.flatten(xpoints)
yt = np.ndarray.flatten(ypoints)
dia = np.ones_like(xt)*turb_dia
tsr = np.ones_like(xt)*4.0
solidity = np.ones_like(xt)*0.25
Cp = 0.4
dens = 1.225
velf = 15.
power_iso = powerval(Cp,dens,velf,turb_dia)
x0 = xt
y0 = yt
area = 2
xlow = points[0]-spacing*area
xupp = points[-1]+spacing*area
ylow = points[0]-spacing*area
yupp = points[-1]+spacing*area
optProb = Optimization('VAWT_Power', obj_func)
optProb.addObj('obj')
n = np.size(x0)
optProb.addVarGroup('xvars', n, 'c', lower=xlow, upper=xupp, value=x0)
optProb.addVarGroup('yvars', n, 'c', lower=ylow, upper=yupp, value=y0)
