Python进阶之3D图形

news2024/9/21 16:41:28

Python进阶之3D图形

在数据可视化中，2D图形通常可以满足大多数需求。然而，对于一些复杂的数据或分析，3D图形可以提供更多的视角和洞察。在Python中，使用 Matplotlib 和 Plotly 等库可以轻松创建各种3D图形。本文将介绍如何使用这些工具绘制3D图形，并展示一些高级用法。

1. 使用Matplotlib绘制3D图形

Matplotlib 提供了一个 mplot3d 模块，用于创建3D图形。以下是一些常见的3D图形示例。

1.1 3D散点图

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

# 示例数据
np.random.seed(0)
x = np.random.rand(100)
y = np.random.rand(100)
z = np.random.rand(100)

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(x, y, z, c='blue', marker='o')

ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')
ax.set_title('3D Scatter Plot')

plt.show()

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1.2 3D曲面图

from mpl_toolkits.mplot3d import Axes3D

# 示例数据
x = np.linspace(-5, 5, 100)
y = np.linspace(-5, 5, 100)
x, y = np.meshgrid(x, y)
z = np.sin(np.sqrt(x**2 + y**2))

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(x, y, z, cmap='viridis')

ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')
ax.set_title('3D Surface Plot')

plt.show()

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1.3 3D柱状图

from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
ax = fig.add_subplot(projection='3d')
x, y = np.random.rand(2, 100) * 4
hist, xedges, yedges = np.histogram2d(x, y, bins=4, range=[[0, 4], [0, 4]])

# Construct arrays for the anchor positions of the 16 bars.
xpos, ypos = np.meshgrid(xedges[:-1] + 0.25, yedges[:-1] + 0.25, indexing="ij")
xpos = xpos.ravel()
ypos = ypos.ravel()
zpos = 0

# Construct arrays with the dimensions for the 16 bars.
dx = dy = 0.5 * np.ones_like(zpos)
dz = hist.ravel()

ax.bar3d(xpos, ypos, zpos, dx, dy, dz, zsort='average')

plt.show()

在这里插入图片描述

2. 使用Plotly绘制3D图形

Plotly 提供了更为交互的3D图形功能，可以使图表的操作更加灵活和动态。

2.1 3D散点图

import plotly.graph_objs as go
import plotly.offline as pyo

# 示例数据
trace = go.Scatter3d(
    x=np.random.rand(100),
    y=np.random.rand(100),
    z=np.random.rand(100),
    mode='markers',
    marker=dict(size=5, color='blue')
)

layout = go.Layout(
    title='3D Scatter Plot',
    scene=dict(
        xaxis_title='X Label',
        yaxis_title='Y Label',
        zaxis_title='Z Label'
    )
)

fig = go.Figure(data=[trace], layout=layout)
pyo.iplot(fig)

在这里插入图片描述

2.2 3D曲面图

import plotly.graph_objs as go
import plotly.offline as pyo

# 示例数据
x = np.linspace(-5, 5, 50)
y = np.linspace(-5, 5, 50)
x, y = np.meshgrid(x, y)
z = np.sin(np.sqrt(x**2 + y**2))

trace = go.Surface(
    z=z,
    x=x,
    y=y,
    colorscale='Viridis'
)

layout = go.Layout(
    title='3D Surface Plot',
    scene=dict(
        xaxis_title='X Label',
        yaxis_title='Y Label',
        zaxis_title='Z Label'
    )
)

fig = go.Figure(data=[trace], layout=layout)
pyo.iplot(fig)

在这里插入图片描述

2.3 3D网格图

import plotly.graph_objs as go
import plotly.offline as pyo

# 示例数据
x = np.arange(10)
y = np.arange(10)
x, y = np.meshgrid(x, y)
z = np.sin(x) + np.cos(y)

trace = go.Mesh3d(
    x=x.flatten(),
    y=y.flatten(),
    z=z.flatten(),
    i=[0, 1, 2],
    j=[1, 2, 3],
    k=[2, 3, 4],
    opacity=0.5
)

layout = go.Layout(
    title='3D Mesh Plot',
    scene=dict(
        xaxis_title='X Label',
        yaxis_title='Y Label',
        zaxis_title='Z Label'
    )
)

fig = go.Figure(data=[trace], layout=layout)
pyo.iplot(fig)