python 3d绘图模块_Python绘制3D图形

3D图形在数据分析、数据建模、图形和图像处理等领域中都有着广泛的应用，下面将给大家介绍一下如何使用python进行3D图形的绘制，包括3D散点、3D表面、3D轮廓、3D直线（曲线）以及3D文字等的绘制。

准备工作：

python中绘制3D图形，依旧使用常用的绘图模块matplotlib，但需要安装mpl_toolkits工具包，安装方法如下：windows命令行进入到python安装目录下的Scripts文件夹下，执行： pip install --upgrade matplotlib即可；linux环境下直接执行该命令。

安装好这个模块后，即可调用mpl_tookits下的mplot3d类进行3D图形的绘制。

下面以实例进行说明。

1、3D表面形状的绘制

from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

import numpy as np

fig = plt.figure()

ax = fig.add_subplot(111, projection='3d')

# Make data

u = np.linspace(0, 2 * np.pi, 100)

v = np.linspace(0, np.pi, 100)

x = 10 * np.outer(np.cos(u), np.sin(v))

y = 10 * np.outer(np.sin(u), np.sin(v))

z = 10 * np.outer(np.ones(np.size(u)), np.cos(v))

# Plot the surface

ax.plot_surface(x, y, z, color='b')

plt.show()

球表面，结果如下：

2、3D直线（曲线）的绘制

import matplotlib as mpl

from mpl_toolkits.mplot3d import Axes3D

import numpy as np

import matplotlib.pyplot as plt

mpl.rcParams['legend.fontsize'] = 10

fig = plt.figure()

ax = fig.gca(projection='3d')

theta = np.linspace(-4 * np.pi, 4 * np.pi, 100)

z = np.linspace(-2, 2, 100)

r = z**2 + 1

x = r * np.sin(theta)

y = r * np.cos(theta)

ax.plot(x, y, z, label='parametric curve')

ax.legend()

plt.show()

这段代码用于绘制一个螺旋状3D曲线，结果如下：

3、绘制3D轮廓

from mpl_toolkits.mplot3d import axes3d

import matplotlib.pyplot as plt

from matplotlib import cm

fig = plt.figure()

ax = fig.gca(projection='3d')

X, Y, Z = axes3d.get_test_data(0.05)

cset = ax.contour(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)

cset = ax.contour(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)

cset = ax.contour(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)

ax.set_xlabel('X')

ax.set_xlim(-40, 40)

ax.set_ylabel('Y')

ax.set_ylim(-40, 40)

ax.set_zlabel('Z')

ax.set_zlim(-100, 100)

plt.show()

绘制结果如下：

4、绘制3D直方图

from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

import numpy as np

fig = plt.figure()

ax = fig.add_subplot(111, 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.

# Note: np.meshgrid gives arrays in (ny, nx) so we use 'F' to flatten xpos,

# ypos in column-major order. For numpy >= 1.7, we could instead call meshgrid

# with indexing='ij'.

xpos, ypos = np.meshgrid(xedges[:-1] + 0.25, yedges[:-1] + 0.25)

xpos = xpos.flatten('F')

ypos = ypos.flatten('F')

zpos = np.zeros_like(xpos)

# Construct arrays with the dimensions for the 16 bars.

dx = 0.5 * np.ones_like(zpos)

dy = dx.copy()

dz = hist.flatten()

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

plt.show()

绘制结果如下：

5、绘制3D网状线

from mpl_toolkits.mplot3d import axes3d

import matplotlib.pyplot as plt

fig = plt.figure()

ax = fig.add_subplot(111, projection='3d')

# Grab some test data.

X, Y, Z = axes3d.get_test_data(0.05)

# Plot a basic wireframe.

ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)

plt.show()

绘制结果如下：

6、绘制3D三角面片图

from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

import numpy as np

n_radii = 8

n_angles = 36

# Make radii and angles spaces (radius r=0 omitted to eliminate duplication).

radii = np.linspace(0.125, 1.0, n_radii)

angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)

# Repeat all angles for each radius.

angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)

# Convert polar (radii, angles) coords to cartesian (x, y) coords.

# (0, 0) is manually added at this stage, so there will be no duplicate

# points in the (x, y) plane.

x = np.append(0, (radii*np.cos(angles)).flatten())

y = np.append(0, (radii*np.sin(angles)).flatten())

# Compute z to make the pringle surface.

z = np.sin(-x*y)

fig = plt.figure()

ax = fig.gca(projection='3d')

ax.plot_trisurf(x, y, z, linewidth=0.2, antialiased=True)

plt.show(

绘制结果如下：

7、绘制3D散点图

from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

import numpy as np

def randrange(n, vmin, vmax):

'''''

Helper function to make an array of random numbers having shape (n, )

with each number distributed Uniform(vmin, vmax).

'''

return (vmax - vmin)*np.random.rand(n) + vmin

fig = plt.figure()

ax = fig.add_subplot(111, projection='3d')

n = 100

# For each set of style and range settings, plot n random points in the box

# defined by x in [23, 32], y in [0, 100], z in [zlow, zhigh].

for c, m, zlow, zhigh in [('r', 'o', -50, -25), ('b', '^', -30, -5)]:

xs = randrange(n, 23, 32)

ys = randrange(n, 0, 100)

zs = randrange(n, zlow, zhigh)

ax.scatter(xs, ys, zs, c=c, marker=m)

ax.set_xlabel('X Label')

ax.set_ylabel('Y Label')

ax.set_zlabel('Z Label')

plt.show()

绘制结果如下：

8、绘制3D文字

from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

fig = plt.figure()

ax = fig.gca(projection='3d')

# Demo 1: zdir

zdirs = (None, 'x', 'y', 'z', (1, 1, 0), (1, 1, 1))

xs = (1, 4, 4, 9, 4, 1)

ys = (2, 5, 8, 10, 1, 2)

zs = (10, 3, 8, 9, 1, 8)

for zdir, x, y, z in zip(zdirs, xs, ys, zs):

label = '(%d, %d, %d), dir=%s' % (x, y, z, zdir)

ax.text(x, y, z, label, zdir)

# Demo 2: color

ax.text(9, 0, 0, "red", color='red')

# Demo 3: text2D

# Placement 0, 0 would be the bottom left, 1, 1 would be the top right.

ax.text2D(0.05, 0.95, "2D Text", transform=ax.transAxes)

# Tweaking display region and labels

ax.set_xlim(0, 10)

ax.set_ylim(0, 10)

ax.set_zlim(0, 10)

ax.set_xlabel('X axis')

ax.set_ylabel('Y axis')

ax.set_zlabel('Z axis')

plt.show(

绘制结果如下：

9、3D条状图

from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

import numpy as np

fig = plt.figure()

ax = fig.add_subplot(111, projection='3d')

for c, z in zip(['r', 'g', 'b', 'y'], [30, 20, 10, 0]):

xs = np.arange(20)

ys = np.random.rand(20)

# You can provide either a single color or an array. To demonstrate this,

# the first bar of each set will be colored cyan.

cs = [c] * len(xs)

cs[0] = 'c'

ax.bar(xs, ys, zs=z, zdir='y', color=cs, alpha=0.8)

ax.set_xlabel('X')

ax.set_ylabel('Y')

ax.set_zlabel('Z')

plt.show()

绘制结果如下：

以上所述是小编给大家介绍的python绘制3D图形，希望对大家有所帮助，如果大家有任何疑问请给我留言，小编会及时回复大家的。在此也非常感谢大家对我们网站的支持

本文标题: Python绘制3D图形

本文地址: http://www.cppcns.com/jiaoben/python/226927.html

python 3d绘图模块_Python绘制3D图形相关推荐

python 3d绘图立方体_python绘制3D立方体
我想绘制一个平行六面体.其实我从python脚本开始画立方体为:python绘制3D立方体 import numpy as np from mpl_toolkits.mplot3d import Ax ...
python绘制3d动态模型_Python绘制3D图形
3D图形在数据分析.数据建模.图形和图像处理等领域中都有着广泛的应用,下面将给大家介绍一下如何使用python进行3D图形的绘制,包括3D散点.3D表面.3D轮廓.3D直线(曲线)以及3D文字等的绘制 ...
python 3d绘图范围_python – 在3D绘图中绘制所有三个轴上的分布轮廓
我在三维空间中有一堆点,并估计了这些点上的一些分布(也在3D空间中;使用 kernel density estimation虽然这与这个问题无关).我想将该分布的投影绘制为所有三个轴(x,y和z)上的 ...
3D绘图 WebGl引擎----ThreeJS 3D渲染引擎
3D绘图 WebGl引擎---->ThreeJS 3D渲染引擎是将OpenGl ES2.0d原来C语言的API和配置项迁移到了JavaScript中壹.基本图形语法 1.ThreeJs将原本 ...
python 3d绘图平面_python 用 matplotlib 在 3D 空间中绘制平面实例详解
#创建画布 fig = plt.figure(figsize=(12, 8), facecolor='lightyellow')#创建 3D 坐标系 ax = fig.gca(fc='whitesmo ...
python绘制四边螺旋线代_Python绘制3d螺旋曲线图实例代码
Line plots Axes3D.plot(xs, ys, *args, **kwargs) 绘制2D或3D数据参数描述 xs, ys X轴,Y轴坐标定点 zs Z值,每一个点的值都是1 zdi ...
matlab三维绘图poly,matplotlib绘制三维图形mplot3d(包含Mayavi.mlab模块)
http://blog.csdn.net/pipisorry/article/details/40008005 Matplotlib mplot3d 工具包简介 The mplot3d toolkit ...
Python数据分析10——使用Matplotlib绘制3D图
目录 3D立体图形 3D绘图 3D散点图 3D曲线图 3D平面图 3D立体图形绘制三维图像主要通过 mplot3d 模块实现. from matplotlib import pyplot as pl ...
python有多少个模块_python绘图模块有哪些
匿名用户 1级 2018-03-22 回答 urtle库是Python语言中一个很流行的绘制图像的函数库,想象一个小乌龟,在一个横轴为x.纵轴为y的坐标系原点,(0,0)位置开始,它根据一组函数指令的 ...

python 3d绘图模块_Python绘制3D图形

python 3d绘图模块_Python绘制3D图形相关推荐

最新文章

热门文章