Question

我很难理解下面代码中的函数 rhs（u，m，r）是如何接收参数 m 和 r 。从代码中可以看出，函数 rhs 在函数 euler_step（u，rhs，dt）中被调用，但是参数 m < / strong>和 r 作为参数传递给函数 euler_step ，也不是全局变量。所以，有人可以向我解释参数 m 和 u 是如何到达函数 rhs 。

# model parameters: mpo = 100. # initial mass of the rocket propellant in kg ms = 50. # mass of the rocket shell in kg g = 9.81 # gravity in m s^{-2} rho = 1.091 # average air density in kg/m^{3} rad = 0.5 # radius of the maximum cross sectional area of the rocket in m A = numpy.pi*(rad**2)# maximum cross sectional area of the rocket in m^{2} v_e = 325. # the exhaust speed in m/s C_D = 0.15 # drag coefficient rt = 20.0 # propellant burn rate in kg/s dtp = 5.0 # time interval to empty the propellant in s ### set initial conditions ### h0 = 0.0 # start at the zero height [m] v0 = 0.0 # initial speed [m/s] def rhs(u, m, r): """Returns the right-hand side of the phugoid system of equations. Parameters ---------- u : array of float array containing the solution at time n. mp: float mass of the propellant at time t mp_rate: float propellant burn rate Returns ------- dudt : array of float array containing the RHS given u. """ print("[m,r]",[m,r]) [h,v] = u.copy() return numpy.array( [ v, -g + pow((ms+m),-1)*(r*v_e - 0.5*rho*v*abs(v)*A*C_D) ] ) def euler_step(u, rhs, dt): """Returns the solution at the next time-step using Euler's method. Parameters ---------- u : array of float solution at the previous time-step. rhs : function function to compute the right hand-side of the system of equation. dt : float time-increment. Returns ------- u_n_plus_1 : array of float approximate solution at the next time step. """ return u + dt * rhs(u, m, r) if __name__ == "__main__": T = 17.0 # final time dt = 0.1 # time increment t = numpy.arange(0.0, T, dt) # time discretization N = len(t) # number of time-steps # initialize the array containing the solution for each time-step u = numpy.zeros((N, 2)) u[0] = numpy.array([h0, v0]) # fill 1st element with initial values rate = numpy.zeros(N) mp = numpy.zeros(N) Np = int(((N)/(T))*dtp) # number of time-steps with propellant burn rate[0:Np] = rt # propellant burn rate in kg/s mp[0:Np] = mpo - rt*t[0:Np] # time loop - Euler method for n in range(1,N-1): r = rate[n] m = mp[n] print("[R,M]",[r,m]) u[n+1] = euler_step(u[n], rhs, dt)

提前致谢。

Answer 1

m和n 是全局变量。

这可能令人困惑，因为__main__似乎是一个功能，但事实并非如此。 if __name__ == "__main__" ....正在全局范围内运行。

Answer 2

他们是全局变量。在Python中，if，while和for执行而非创建单独的变量范围，因此在第一个变量范围之前，它们仍然在全局/模块范围内分配值调用euler_step：

if __name__ == "__main__":  # does not start a new variable scope
    ...

    for n in range(1,N-1):  # does not start one either
        # thus these variables are set in global scope.
        r = rate[n]
        m = mp[n]

        # and euler_step is invoked only here, thus it will see
        # r and m being set.
        u[n+1] = euler_step(u[n], rhs, dt)

另见Short Description of the Scoping Rules?。

Answer 3

var figlet = require('figlet'); function art(dataToArt, callback) { var arry[]; figlet(dataToArt, function(err, data) { if (err) { console.log('Something went wrong...'); console.dir(err); return callback(''); } arry[0] = data; callback(arry); }); figlet(dataToArt, function(err, data) { if (err) { console.log('Something went wrong...'); console.dir(err); return callback(''); } arry[1] = data; callback(arry); }); } art('Hello World', function (data){ console.log(data); });和m在模块级别的脚本底部附近定义：

因此they are available to all functions within the module：

以下是块：模块，函数体和类定义。范围定义块内名称的可见性。如果在块中定义了局部变量，则其范围包括该变量块。如果定义发生在功能块中，则范围会扩展包含在定义的块中的任何块，除非包含 block为名称引入了不同的绑定...当名称是在代码块中使用它，使用最近的封闭解析范围。

在python中通过函数传递变量的问题

3 个答案: