这并不容易。一种可能的变通方法如下：

• 根据您共享的参考图，我认为您的意思实际上是希望实现第二个z轴，而不是y轴。
• 3d图的axes对象仍然是单一的和共享的（出于必要性/明显的matplotlib 3d图限制），但是数据被绘制为相同的连续值尺度 *，但是轴刻度和标签被自定义覆盖以反映不同的值尺度 *。

例如，在一个示例中，

import numpy as np
import matplotlib.pyplot as plt

def f(x, y):
    return np.sin(np.sqrt(x ** 2 + y ** 2))

def g(x, y):
    return -np.cos(np.sqrt(x ** 2 + y ** 2))

x = np.linspace(-6, 6, 30)
y = np.linspace(-6, 6, 30)
X, Y = np.meshgrid(x, y)
Z = f(X, Y)
Z_new = g(X, Y)
offset = 5
Z_new_offset = Z_new + Z.max() + offset

fig = plt.figure(figsize=(16, 12))
ax = fig.add_subplot(111, projection="3d")

surf1 = ax.plot_surface(
    X, Y, Z, rstride=1, cstride=1, cmap="viridis", edgecolor="none", alpha=0.7
)

surf2 = ax.plot_surface(
    X,
    Y,
    Z_new_offset,
    rstride=1,
    cstride=1,
    cmap="plasma",
    edgecolor="none",
    alpha=0.7,
)

z_ticks_original = np.linspace(Z.min(), Z.max(), 5)

# Add custom tick labels and tick marks for the new plot on the left
z_ticks_new = np.linspace(Z_new_offset.min(), Z_new_offset.max(), 5)
for z_tick in z_ticks_new:
    ax.text(
        X.min() - 0.5,
        Y.min() - 2.5,
        z_tick + 0.25,
        f"{z_tick - (offset+1):.1f}",
        color="k",
        verticalalignment="center",
    )
    ax.plot(
        [X.min() - 0.5, X.min()],
        [Y.min() - 0.5, Y.min()],
        [z_tick, z_tick],
        color="k",
    )

ax.set_zticks(np.block([z_ticks_original, z_ticks_new]))

fig.canvas.draw()
labels = []
for lab, tick in zip(ax.get_zticklabels(), ax.get_zticks()):
    if float(tick) >= 1.0:
        lab.set_text("")
    labels += [lab]
ax.set_zticklabels(labels)

# Draw the left Z-axis line
ax.plot(
    [X.min() - 0.5] * 2,
    [Y.min() - 0.5] * 2,
    [z_ticks_new.min(), z_ticks_new.max()],
    color="k",
)

ax.set_xlabel("X")
ax.set_ylabel("Y")
ax.set_zlabel("Z")

cbar1 = fig.colorbar(
    surf1, ax=ax, pad=-0.075, orientation="vertical", shrink=0.5
)
cbar1.set_label("Z Values (primary z-axis)")
cbar2 = fig.colorbar(
    surf2,
    ax=ax,
    pad=0.12,
    orientation="vertical",
    shrink=0.5,
    ticks=z_ticks_original,
)
cbar2.set_label("Z Values (secondary z-axis)")

plt.show()

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