A = []
st = [0]
s = np.array(st)
Af = []
it = []
for i in range(Gen0):
it.append(i)
#gen = 0
if gen == 0:
print('Generation-%d STARTED'%gen)
for i in range(Gen0):
Airfoil.append(airfoil(0,i))
Airfoil[i].ctrlPoints()
Airfoil[i].bspline()
Airfoil[i].write()
Airfoil[i].savefig()
Airfoil[i].show(gen, i)
#Airfoil[i].camber(gen, i)
def run(i):
Airfoil[i].cfd()
print(Airfoil[i].cost)
#np.savetxt('../../cost-%d'%i, Airfoil[i].cost)
y = Pool(5)
#y.starmap(run, zip(itertools.repeat(Airfoil), it))
y.map(run, range(Gen0))
#import the name of the airfoils from the webtry program #Generate a new airfoil using constructor for every specie and evaluate cost #!Rename the airfoil to airfoil.txt for evaluation! #make a new folder for every airfoil imported with sub folders for generation and species #save the plot of every generation and specie in their respective folder. #only for upper array(the same can be repeated for lower array.) #subtract Y values of corresponding elements and compute distance #Minimize the inverse of the distance b/w points #write code for choosing which x values to subrract from (possibility to add interpolation values) #Apply same IWO GA to minimize (Decide on the number of generations and other constants based on experimentation.) #from web_try import airfoils from airfoil_Class import airfoil airfoils = 's1210.dat' Airfoil = airfoil(0, 1) Airfoil.ctrlPoints() Airfoil.bspline() #Airfoil.write() #Airfoil.savefig() #Airfoil.show(0, 1) Airfoil.error(airfoils) print(airfoils)
def run(number):
af = loaded_af[number]
for i in range(Gen0):
gen = 0
s[0] = 0
Airfoil.append(airfoil(0, i))
Airfoil[i].ctrlPoints()
Airfoil[i].bspline()
Airfoil[i].write()
#Airfoil[i].savefig()
#Airfoil[i].show(gen, i)
#Airfoil[i].camber(gen, i)
for i in range(Gen0):
#Airfoil[i].savefig()
#Airfoil[i].xFoil()
#Airfoil[i].cfd()
try:
Airfoil[i].error(af)
gen = 1
except IndexError:
gen = maxIt
except ValueError:
gen = maxIt
#print(Airfoil[i].cost)
if __name__ == "__main__":
while gen < maxIt:
sigma = (((maxIt - float(gen - 1)) / maxIt)**
exponent) * (sigma_initial - sigma_final) + sigma_final
#print('SIGMA')
#print(sigma)
Airfoil.sort(key=lambda Airfoil: Airfoil.cost, reverse=True)
for i in range(len(Airfoil)):
#print(Airfoil[i].cost)
pass
del Airfoil[nPop:]
for i in range(len(Airfoil)):
#print(Airfoil[i].cost)
pass
for k in range(nPop):
Airfoil[k].copy(gen, s[0])
Airfoil[k].copy_Results(gen, s[0])
#Airfoil[k].show(gen, s[0])
#Airfoil[k].camber(gen, s[0])
s[0] += 1
for x in range(len(Airfoil)):
reproduction(Airfoil, gen, sigma, x, s, af)
Airfoil.sort(key=lambda x: x.cost, reverse=True)
gen += 1
s[0] = 0
if gen == maxIt:
final_cost.append(Airfoil[0].cost)
print('%s Done' % name)
def run(number):
af = loaded_af[number]
name = loaded_af[number]
#print(name)
os.mkdir('../fitting/%s' % name)
os.chdir('../fitting/%s' % name)
#os.mkdir('Plots')
#os.mkdir('Camber')
os.mkdir('error')
t.sleep(2)
Airfoil.clear()
for i in range(Gen0):
gen = 0
s[0] = 0
Airfoil.append(airfoil(0, i))
Airfoil[i].ctrlPoints()
Airfoil[i].bspline()
Airfoil[i].write()
#Airfoil[i].savefig()
#Airfoil[i].show(gen, i)
#Airfoil[i].camber(gen, i)
for i in range(Gen0):
#Airfoil[i].savefig()
#Airfoil[i].xFoil()
#Airfoil[i].cfd()
try:
Airfoil[i].error(af)
gen = 1
except IndexError:
gen = maxIt
except ValueError:
gen = maxIt
#print(Airfoil[i].cost)
if __name__ == "__main__":
while gen < maxIt:
sigma = (((maxIt - float(gen - 1)) / maxIt)**
exponent) * (sigma_initial - sigma_final) + sigma_final
#print('SIGMA')
#print(sigma)
Airfoil.sort(key=lambda Airfoil: Airfoil.cost, reverse=True)
for i in range(len(Airfoil)):
#print(Airfoil[i].cost)
pass
del Airfoil[nPop:]
for i in range(len(Airfoil)):
#print(Airfoil[i].cost)
pass
for k in range(nPop):
Airfoil[k].copy(gen, s[0])
Airfoil[k].copy_Results(gen, s[0])
#Airfoil[k].show(gen, s[0])
#Airfoil[k].camber(gen, s[0])
s[0] += 1
for x in range(len(Airfoil)):
reproduction(Airfoil, gen, sigma, x, s, af)
Airfoil.sort(key=lambda x: x.cost, reverse=True)
gen += 1
s[0] = 0
if gen == maxIt:
final_cost.append(Airfoil[0].cost)
c.append(Airfoil[0].cost)
np.savetxt('Airfoil-Cost.txt', c, fmt='%s')
c.clear()
print('%s Done' % name)
os.chdir('../../optimisation_code')
np.savetxt('Airfoil-Cost.txt', final_cost, fmt='%s')