风电场设计软件草稿

Question

我目前正在开发一个风电场设计软件，基本上，我必须分析某些风力涡轮机在另一个逆风上的发生率，以便计算出当下游涡轮“看到”流动时，风力的速度下降。

我已经整理了大部分的代码，它可以工作，但是这段代码的计算速度非常慢。

for wd in wind_direction_index:
        self.list_for_speed.append([])
        for ws in wind_speed_index:
            self.list_for_speed[wd].append([])
            wind_speed = self._wind_speeds[ws]
            #For every wind turbine, remember this list is still ordered from up to dow
            dummylist=copy.deepcopy(self.list_for_direction[wd])            
            for WT in dummylist:
                #Replace No deficit with 0
                if WT[6]=='NO_deficit':
                    WT[6]=[0.0]
                else:
                    pass
                #For every WT that causes a wake effect on current one
                for upWT in WT[3]:
                    #Define current turbine and rotating upwind turbine
                    for ready in dummylist:
                        if upWT[0]==ready[0]:
                            upWT[6]=ready[6]
                        else:
                            pass
                    current_turbine=WT
                    upwind_turbine=upWT
                    #Calculate wind speeds deficits in every current WT due to every upwind WT to it only if here are upwind WTS
                    if len(current_turbine[3])!=0:
                        self.calculate_deficits(current_turbine,upwind_turbine,wind_speed)
                    else:
                        pass
                #Now we have appended all deficits in current_turbine(6) Time to add them up, find the speed and replace
                #First, I square the list of deficits
                WT[6]=[i**2 for i in WT[6]]
                #Now, i add the squares of the deficits
                deficit_squared=sum(WT[6])
                #Take the square root
                deficit_current=sqrt(deficit_squared)
                #Finally calculate wind speed at the rotor
                U=wind_speed*(1-deficit_current)
                #And I replace the list of wind speed deficits with the wind speed at the rotor
                WT[6]=U
                _Ct=self.team.rna_analysts.get_Ct(U)
                #Save results to local wind speeds array
                self.local_wind_speeds[WT[0]][wd][ws]=[U,_Ct]
            self.list_for_speed[wd][ws].append(dummylist)

我知道这有点麻烦，但您可以或多或少地看到我的数据结构是如何安排的。我必须根据风向和风速计算每个涡轮机的风速“赤字”(由local_wind_speeds证明)。有人能发现如何使这段代码变得更快吗？

Answer 1

我怀疑copy.deepcopy花费了你很多时间，如果可能的话，尽量避免它。

另外，您只是在复制self.list_for_direction[wd]，是否有必要多次复制for ws in wind_speed_index？

我会尽我最大的努力猜出你想要达到的目标，但并不保证我的代码会做你想做的事情。在这里，除了self.list_for_speed[wd][ws].append(dummylist)之外，不再需要虚拟列表。除非以后真的需要self.list_for_speed，而且共享相同wd的对象是不同的对象，否则我担心您无法节省做这么多copy.deepcopy的时间。

让我感到困惑的是，您有嵌套的for WT in dummylist和for ready in dummylist。当第一个for-循环中的6是"NO_deficit"时，您可以更改WT循环。假设您在第一个for循环中的i-th迭代和第二个for-循环中的j-th迭代。如果是j>i，则ready[6]可能是"NO_deficit"。我想这不是你想要的。

def U_Ct(OBJ,WT6,wind_speed):
    if WT6 == 'NO_deficit':
        deficit_current = 0.0
    else:
        deficit_squared = sum([i**2 for i in WT6])
        deficit_current = sqrt(deficit_squared)
    U = wind_speed*(1-deficit_current)
    _Ct = OBJ.team.rna_analysts.get_Ct(U)
    return U,_Ct

def get_turbine(WT,upWT):
    '''  WT is a value in the dummylist
    upWT is the WT[3] where WT is from the dummylist
    '''
    if WT[6] == 'NO_deficit':
        WT[6] = [0.0]
    for ready in WT:
        if upWT[0] == ready[0]:
            upWT[6] = ready[6]
    current_turbine = WT
    upwind_turbine = upWT
    return current_turbine,upwind_turbine


for wd in wind_direction_index:
    for ws in wind_speed_index:
        dummylist = copy.deepcopy(self.list_for_direction[wd])
        self.list_for_speed[wd][ws].append(dummylist)
        wind_speed = self._wind_speeds[ws]
        for WT in self.list_for_direction[wd]:
            for upWT in WT[3]:
                current_turbine,upwind_turbine = get_turbine(WT,upWT)
                if len(current_turbine[3])!=0:
                    # What does this function do? It doesn't return anything
                    self.calculate_deficits(current_turbine,upwind_turbine,wind_speed)
            U,_Ct = U_Ct(self,WT[6],wind_speed)
            self.local_wind_speeds[WT[0]][wd][ws] = [U,_Ct]