Я создавал проект по оптимизации формы самолета для минимального сопротивления, и столкнулся с двумя проблемами: одна возникает с примененным ограничением, и я получил следующую ошибку
File "/home/name/Desktop/x1ac3opt.py", line 202, in <module>
top.setup()
File "/usr/local/lib/python2.7/dist-packages/openmdao/core/problem.py", line 498, in setup
connections = self._setup_connections(params_dict, unknowns_dict)
File "/usr/local/lib/python2.7/dist-packages/openmdao/core/problem.py", line 197, in _setup_connections
connections = self.root._get_explicit_connections()
File "/usr/local/lib/python2.7/dist-packages/openmdao/core/group.py", line 685, in _get_explicit_connections
(src, tgt, tgt))
NameError: Source 'p.Sp1' cannot be connected to target 'con.Sp1': 'con.Sp1' does not exist.
и это происходит с ограничениями, указанными в `
File "/home/name/Desktop/x1ac3opt.py", line 63, in solve_nonlinear
unknowns['Cdi'] = (324/((7750)*(m.pi)*(((Sp1+Sp2+Sp3+Sp4+Sp5)**2)/(Sp1*(Rc+Tc1)/2+Sp2*(Tc1+Tc2)/2+Sp3*(Tc2+Tc3)/2+Sp4*(Tc3+Tc4)/2+Sp5*(Tc4+Tc5)/2))))
File "/usr/local/lib/python2.7/dist-packages/openmdao/core/vec_wrapper.py", line 435, in __setitem__
self._dat[name].set(value)
File "/usr/local/lib/python2.7/dist-packages/openmdao/core/vec_wrapper.py", line 313, in _set_scalar
self.val[0] = value
ValueError: setting an array element with a sequence.
`
есть идеи о том, почему это происходит?
РЕДАКТИРОВАТЬ: вот весь код
`# Для печати используйте этот импорт, если вы используете Python 2.x из будущего import print_function
импортировать математику как m
из openmdao.api импортировать IndepVarComp, Component, Problem, Group, ExecComp, ScipyOptimizer, SqliteRecorder
class Outershell (Компонент): "" "Компонент, содержащий Outershell." ""
def __init__(self):
super(Outershell, self).__init__()
self.add_param('Sp1', val=23) #Sec1Span
self.add_param('Sp2', val=13) #Sec2Span
self.add_param('Sp3', val=20) #Sec3Span
self.add_param('Sp4', val=35) #Sec4Span
self.add_param('Sp5', val=35) #Sec5Span
self.add_param('Sw1', val=60) #Sec1Sweep
self.add_param('Sw2', val=60) #Sec2sweep
self.add_param('Sw3', val=50) #Sec3sweep
self.add_param('Sw4', val=37) #Sec4sweep
self.add_param('Sw5', val=35) #Sec5sweep
self.add_param('Rc', val=130) #Sec1RC
self.add_param('Tc1', val=90) #Sec1TC
self.add_param('Tc2', val=66) #Sec2TC
self.add_param('Tc3', val=42) #Sec3TC
self.add_param('Tc4', val=24) #Sec4TC
self.add_param('Tc5', val=10) #Sec5TC
self.add_output('Cdi', shape=1) #Objective output as low as possible
def solve_nonlinear(self, params, unknowns, resids):
#0.0324 and 0.775 are the squared Cl and the oswald efficiency number in the case that I can find a way to add in those values to the optimization problem
Sp1 = params['Sp1']
Sp2 = params['Sp2']
Sp3 = params['Sp3']
Sp4 = params['Sp4']
Sp5 = params['Sp5']
Sw1 = params['Sw1']
Sw2 = params['Sw2']
Sw3 = params['Sw3']
Sw4 = params['Sw4']
Sw5 = params['Sw5']
Rc = params['Rc']
Tc1 = params['Tc1']
Tc2 = params['Tc2']
Tc3 = params['Tc3']
Tc4 = params['Tc4']
Tc5 = params['Tc5']
unknowns['Cdi'] = (324/((7750)*(m.pi)*(((Sp1+Sp2+Sp3+Sp4+Sp5)**2)/(Sp1*(Rc+Tc1)/2+Sp2*(Tc1+Tc2)/2+Sp3*(Tc2+Tc3)/2+Sp4*(Tc3+Tc4)/2+Sp5*(Tc4+Tc5)/2))))
def linearize(self, params, unknowns, resids):
Sp1 = params['Sp1']
Sp2 = params['Sp2']
Sp3 = params['Sp3']
Sp4 = params['Sp4']
Sp5 = params['Sp5']
sw1 = params['Sw1']
sw2 = params['Sw2']
sw3 = params['Sw3']
sw4 = params['Sw4']
sw5 = params['Sw5']
Rc = params['Rc']
Tc1 = params['Tc1']
Tc2 = params['Tc2']
Tc3 = params['Tc3']
Tc4 = params['Tc4']
Tc5 = params['Tc5']
J ={}
J['Cdi', 'Sp1']=unknowns['Cdi']/Sp1
J['Cdi', 'Sp2']=unknowns['Cdi']/Sp2
J['Cdi', 'Sp3']=unknowns['Cdi']/Sp3
J['Cdi', 'Sp4']=unknowns['Cdi']/Sp4
J['Cdi', 'Sp5']=unknowns['Cdi']/Sp5
J['Cdi', 'Sw1']=unknowns['Cdi']/sw1
J['Cdi', 'Sw2']=unknowns['Cdi']/sw2
J['Cdi', 'Sw3']=unknowns['Cdi']/sw3
J['Cdi', 'Sw4']=unknowns['Cdi']/sw4
J['Cdi', 'Sw5']=unknowns['Cdi']/sw5
J['Cdi', 'Tc1']=unknowns['Cdi']/Tc1
J['Cdi', 'Tc2']=unknowns['Cdi']/Tc2
J['Cdi', 'Tc3']=unknowns['Cdi']/Tc3
J['Cdi', 'Tc4']=unknowns['Cdi']/Tc4
J['Cdi', 'Tc5']=unknowns['Cdi']/Tc5
J['Cdi', 'Rc']=unknowns['Cdi']/Rc
if __name__ == "__main__":
top = Problem()
root = top.root = Group()
root.add('p1', IndepVarComp('Sp1', 23))
root.add('p2', IndepVarComp('Sp2', 13))
root.add('p3', IndepVarComp('Sp3', 20))
root.add('p4', IndepVarComp('Sp4', 35))
root.add('p5', IndepVarComp('Sp5', 35))
root.add('p6', IndepVarComp('Sw1', 60))
root.add('p7', IndepVarComp('Sw2', 60))
root.add('p8', IndepVarComp('Sw3', 50))
root.add('p9', IndepVarComp('Sw4', 37))
root.add('p10', IndepVarComp('Sw5', 35))
root.add('p11', IndepVarComp('Tc1', 90))
root.add('p12', IndepVarComp('Tc2', 66))
root.add('p13', IndepVarComp('Tc3', 42))
root.add('p14', IndepVarComp('Tc4', 24))
root.add('p15', IndepVarComp('Tc5', 10))
root.add('p16', IndepVarComp('Rc', 130))
root.add('p', Outershell())
root.add('con', ExecComp('L = (15067/100000000)/(Sp1(Rc+Tc1)/2+Sp2(Tc1+Tc2)/2+Sp3(Tc2+Tc3)/2+Sp4(Tc3+Tc4)/2+Sp5(Tc4+Tc5)/2)'))
#Cl=0.18 rho = 0.000737 v**2 = 810471.67 Area = ... 597.31762079
root.connect('p1.Sp1', 'p.Sp1')
root.connect('p2.Sp2', 'p.Sp2')
root.connect('p3.Sp3', 'p.Sp3')
root.connect('p4.Sp4', 'p.Sp4')
root.connect('p5.Sp5', 'p.Sp5')
root.connect('p6.Sw1', 'p.Sw1')
root.connect('p7.Sw2', 'p.Sw2')
root.connect('p8.Sw3', 'p.Sw3')
root.connect('p9.Sw4', 'p.Sw4')
root.connect('p10.Sw5', 'p.Sw5')
root.connect('p11.Tc1', 'p.Tc1')
root.connect('p12.Tc2', 'p.Tc2')
root.connect('p13.Tc3', 'p.Tc3')
root.connect('p14.Tc4', 'p.Tc4')
root.connect('p15.Tc5', 'p.Tc5')
root.connect('p16.Rc', 'p.Rc')
root.connect('p.Sp1', 'con.Sp1')
root.connect('p.Sp2', 'con.Sp2')
root.connect('p.Sp3', 'con.Sp3')
root.connect('p.Sp4', 'con.Sp4')
root.connect('p.Sp5', 'con.Sp5')
root.connect('p.Sw1', 'con.Sw1')
root.connect('p.Sw2', 'con.Sw2')
root.connect('p.Sw3', 'con.Sw3')
root.connect('p.Sw4', 'con.Sw4')
root.connect('p.Sw5', 'con.Sw5')
root.connect('p.Tc1', 'con.Tc1')
root.connect('p.Tc2', 'con.Tc2')
root.connect('p.Tc3', 'con.Tc3')
root.connect('p.Tc4', 'con.Tc4')
root.connect('p.Tc5', 'con.Tc5')
root.connect('p.Rc', 'con.Rc')
top.driver = ScipyOptimizer()
top.driver.options['optimizer'] = 'COBYLA'
top.driver.add_desvar('p1.Sp1', lower=13, upper=33)
top.driver.add_desvar('p2.Sp2', lower=3, upper=23)
top.driver.add_desvar('p3.Sp3', lower=10, upper=30)
top.driver.add_desvar('p4.Sp4', lower=25, upper=45)
top.driver.add_desvar('p5.Sp5', lower=25, upper=45)
top.driver.add_desvar('p6.Sw1', lower=55, upper=65)
top.driver.add_desvar('p7.Sw2', lower=55, upper=65)
top.driver.add_desvar('p8.Sw3', lower=45, upper=55)
top.driver.add_desvar('p9.Sw4', lower=32, upper=42)
top.driver.add_desvar('p10.Sw5', lower=30, upper=40)
top.driver.add_desvar('p11.Tc1', lower=80, upper=100)
top.driver.add_desvar('p12.Tc2', lower=56, upper=76)
top.driver.add_desvar('p13.Tc3', lower=37, upper=45)
top.driver.add_desvar('p14.Tc4', lower=19, upper=29)
top.driver.add_desvar('p15.Tc5', lower=5, upper=15)
top.driver.add_objective('p.Cdi')
top.driver.add_constraint('con.L', lower=220000, upper=240000)
recorder = SqliteRecorder('Outershell')
recorder.options['record_params'] = True
recorder.options['record_metadata'] = True
top.driver.add_recorder(recorder)
top.setup()
top.run()
top.cleanup() # this closes all recorders
print('\n')
print('Minimum of %f found at: ' % (top['p.Cdi']))
print('\n')
print('Lift produced is: %f ' % (top['con.L']))
print('SP1 = %f' % (top['p.Sp1']))
print('\n')
print('SP2 = %f' % (top['p.Sp2']))
print('\n')
print('SP3 = %f' % (top['p.Sp3']))
print('\n')
print('SP4 = %f' % (top['p.Sp4']))
print('\n')
print('SP5 = %f' % (top['p.Sp5']))
print('\n')
print('SW1 = %f' % (top['p.Sw1']))
print('\n')
print('SW2 = %f' % (top['p.Sw2']))
print('\n')
print('SW3 = %f' % (top['p.Sw3']))
print('\n')
print('SW4 = %f' % (top['p.Sw4']))
print('\n')
print('SW5 = %f' % (top['p.Sw5']))
print('\n')
print('Rc = %f' % (top['p.Rc']))
print('\n')
print('TC1 = %f' % (top['p.Tc1']))
print('\n')
print('TC2 = %f' % (top['p.Tc2']))
print('\n')
print('TC3 = %f' % (top['p.Tc3']))
print('\n')
print('TC4 = %f' % (top['p.Tc4']))
print('\n')
print('TC5 = %f' % (top['p.Tc5']))
print('\n')
`
