基于二进制值的Python 3D绘图

Question

我有一个脚本，它创建一个带有XYZ值的dict。下面的判据包括x处的值，从-2到2，y从0到2。

my_dict = {
-2:{0:1,1:1,2:0},
-1:{0:3,1:1,2:0},
 0:{0:6,1:1,2:9},
 1:{0:-2,1:1,2:2},
 2:{0:1,1:1,2:6}}

现在，我不知道如何在此基础上创建3D图。我知道matplotlib库，但我不确定如何生成Z-Data。我试着写一个函数，让我的Z数据在网格中，但它不起作用。这就是我到目前为止得到的：

    x = np.arange(-2, 2, 1)
    y = np.arange(0, 2, 1)

    X, Y = np.meshgrid(x, y)
    Z = f(X,Y) #HERE, the function f is what I am searching for.

    fig = plt.figure()
    ax = plt.axes(projection='3d')
    ax.contour3D(X, Y, Z, 50, cmap='binary')
    ax.set_xlabel('x')
    ax.set_ylabel('y')
    ax.set_zlabel('z')

有没有任何麻木或蟒蛇的方法来做到这一点？

Answer 1

这就是你要找的吗？

my_dict = {
-2:{0:1,1:1,2:0},
-1:{0:3,1:1,2:0},
 0:{0:6,1:1,2:9},
 1:{0:-2,1:1,2:2},
 2:{0:1,1:1,2:6}}

x = np.arange(-2, 3, 1)
y = np.arange(0, 3, 1)
X, Y = np.meshgrid(x, y)


def f(x, y):
    z = np.zeros(X.reshape(-1).shape)  # Create an "empty" tensor that matches the "flattened" meshgrid
    c = 0  # To index over our "z"
    for i in y:
        for j in x:
            z[c] = my_dict[j][i]  # Fill the empty tensor with its corresponding values from the dictionary (depending on x and y)
            c += 1
    z = z.reshape(X.shape)  # Reshape it back to match meshgrid's shape
    return z


Z = f(x, y)
fig = plt.figure()
ax = plt.axes(projection='3d')
ax.contour3D(X, Y, Z, 50, cmap='binary')
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z')
plt.show()

Answer 2

我相信你可以通过以下方式访问你的字典中的正确值：

Z = mydict[x][y]