Python scipy solve_ovp的数组维度错误

我试图用Scipy

solve_bvp

求解一个边值，第221页。代码是

from scipy.integrate import solve_bvp

def fun(x, y):    
    tmp = np.vstack(( np.cos(y[2]), np.sin(y[2]), y[3], (y[4]*np.cos(y[2])), 0 ))
    return tmp

def bc(ya, yb):
    tmp = np.array([   ya[0], ya[1], ya[3], yb[1], yb[2]+(np.pi/2) ])
    return tmp

x = np.linspace(0, 0.5, 400)
y = np.zeros((5, x.size))

sol = solve_bvp(fun, bc, x, y)

我犯了一个错误

ValueError: all the input array dimensions except for the concatenation axis must match exactly

有什么消息来源吗？一个简单的问题不会出错

def fun(x, y):
    tmp = np.vstack((y[1], -np.exp(y[0])))
    print (tmp)
    return tmp

def bc(ya, yb):
    tmp = np.array([ya[0], yb[0]])
    print (tmp)
    return tmp

x = np.linspace(0, 1, 5)

y_1 = np.zeros((2, x.size))

from scipy.integrate import solve_bvp
res_1 = solve_bvp(fun, bc, x, y_1)

问题在于

np.vstack（…，（y[4]*np.cos（y[2]））中的0）。它没有铸造到正确的尺寸

from scipy.integrate import solve_bvp

def fun(x, y):    
    tmp = np.vstack(( np.cos(y[2]), np.sin(y[2]), y[3], (y[4]*np.cos(y[2])), np.zeros(y[3].shape) ))
    return tmp

def bc(ya, yb):
    tmp = np.array([   ya[0], ya[1], ya[3], yb[1], yb[2]+(np.pi/2) ])
    return tmp

x = np.linspace(0, 0.5, 400)
y = np.zeros((5, x.size))

sol = solve_bvp(fun, bc, x, y)

运行时没有问题。
错误
error
应该给您一个
回溯
显示它发生的确切时间。但只有你能看到这一点；我们不能！