在R3中显示两条曲线，前景和背景清晰

Question

我对这个基本问题表示歉意 - 我是 Python 新手。我试图在 R3 中显示两个交错的圆圈，但 python 无法正确显示谁在“前面”。我想要的是 Python 能够提供 Mathematica 所提供的功能，如下图所示： 代替 我使用的Python代码如下，它需要调整（不用担心视角——我可以稍后处理）。 非常感谢！

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

# Define the parametric equations for the circles
def circle_xy(t, h, k, r):
    x = h + r * np.cos(t)
    y = k + r * np.sin(t)
    z = 0 * np.ones_like(t)
    return x, y, z

def circle_yz(t, h, k, r):
    x = h + r * np.sin(t)
    y = 0 * np.ones_like(t)
    z = k + r * np.cos(t)
    return x, y, z

t = np.linspace(0, 2 * np.pi, 1000)

# Plotting
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

x1, y1, z1 = circle_xy(t, 0, 0, 1)
x2, y2, z2 = circle_yz(t, 1, 0, 1)

ax.plot(x1, y1, z1, label='unit circle centered at x=0, y=0 in the plane z=0',linewidth=3)
ax.plot(x2, y2, z2, label='unit circle centered at x=1, z=0 in the plane y=0',linewidth=3)

ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
ax.legend()

ax.view_init(30, 120)

plt.show()

我尝试了上面显示的代码。

Answer 1

Plotly 对此非常有用，它使得在 R3 中检查表面变得更容易，而在 matplotlib 中则更困难（允许在 HTML 输出中平移、旋转和缩放所有内容）

import numpy as np
import plotly.graph_objects as go

# Define the parametric equations for the circles
def circle_xy(t, h, k, r):
    x = h + r * np.cos(t)
    y = k + r * np.sin(t)
    z = 0 * np.ones_like(t)
    return x, y, z

def circle_yz(t, h, k, r):
    x = h + r * np.sin(t)
    y = 0 * np.ones_like(t)
    z = k + r * np.cos(t)
    return x, y, z

t = np.linspace(0, 2 * np.pi, 1000)

x1, y1, z1 = circle_xy(t, 0, 0, 1)
x2, y2, z2 = circle_yz(t, 1, 0, 1)

# Create the 3D plot in plotly
fig = go.Figure()

# Add circles to the plot
fig.add_trace(go.Scatter3d(x=x1, y=y1, z=z1, mode='lines', name='unit circle centered at x=0, y=0 in the plane z=0', line=dict(width=3)))
fig.add_trace(go.Scatter3d(x=x2, y=y2, z=z2, mode='lines', name='unit circle centered at x=1, z=0 in the plane y=0', line=dict(width=3)))

# Setting the axis labels
fig.update_layout(scene=dict(xaxis_title='X', yaxis_title='Y', zaxis_title='Z'))

# Display the

情节 图.show()