How to create a three-dimensional line chart using Python and Matplotlib

1.0 Introduction

Three-dimensional image technology is one of the most advanced computer display technologies in the world. Any ordinary computer only needs to install a plug-in to present three-dimensional products in a web browser. It is not only lifelike, And it can dynamically display the product combination process, which is especially suitable for remote browsing.

The three-dimensional images are visually distinct and colorful, with strong visual impact, allowing viewers to stay in the scene for a long time and leaving a deep impression. The three-dimensional pictures give people a real and lifelike feeling, the characters are ready to be seen, and they have an immersive feeling, which has a high artistic appreciation value.

2.0 Three-dimensional drawing method and type

First, you need to install the Matplotlib library, you can use pip:

pip install matplotlib

Assume that the matplotlib tool package has been installed.

Use matplotlib.figure.Figure to create a plot frame:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

1. Line plots

Basic usage: ax.plot(x,y,z,label=' ')

The code is as follows:

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.add_subplot(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()

The effect is as follows:

2 , Scatter plots

Basic syntax:

ax.scatter(xs, ys, zs, s=20, c=None, depthshade=True, *args , *kwargs)

The code is roughly:

• xs,ys,zs: input data;

• s: size of scatter point

• c: color, if c = 'r’ it is red;

• depthshase: transparency, True is Transparent, the default is True, False is opaque

• *args and so on are expansion variables, such as maker = ‘o’, then the scatter result is the shape of ’o‘

Sample code:

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()

Effect:

##3. Wireframe plots

Basic Usage: ax.plot_wireframe(X, Y, Z, *args, **kwargs)

##X,Y,Z: Input data
rstride: Row step length
cstride: Column step length

• ##rcount: Upper limit of row number

• ccount: Upper limit of number of columns

• Sample code:

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
 
 
fig = plt.figure()
ax = fig.add_subplot(100, projection='3d')
 
# Grab some test data.
X, Y, Z = axes3d.get_test_data(0.12)
 
# Plot a basic wireframe.
ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
 
plt.show()

4. Tri-Surface plots

Basic usage: ax.plot_trisurf(*args, **kwargs)

ax.plot_trisurf(*args, **kwargs)

X,Y,Z:data

Other parameters are similar to surface-plot

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
 
 
n_radii = 8
n_angles = 36
 
radii = np.linspace(0.125, 1.0, n_radii)
angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
 
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
 
 
# points in the (x, y) plane.
x = np.append(0, (radii*np.cos(angles)).flatten())
y = np.append(0, (radii*np.sin(angles)).flatten())
 
 
z = np.sin(-x*y)
 
fig = plt.figure()
ax = fig.add_subplot(projection='3d')
 
ax.plot_trisurf(x, y, z, linewidth=0.2, antialiased=True)
 
plt.show()

Running rendering:

##5. Random scatter plot

Use scatter generates a random scatter plot.

Function definition:

#Function definition

matplotlib.pyplot.scatter(x, y,

s=None, #Scatter size array scalar

c=None, #Color sequence array, sequence

marker=None, #Point style
cmap=None, #colormap color style
norm=None, #Normalization Normalized color camp
vmin=None, vmax=None, #corresponding to the normalized range above
alpha=None, #transparency
linewidths=None, #linewidth
verts=None,
# edgecolors =None, #Edge color
data=None,
**kwargs
)


Sample code:

import numpy as np
import matplotlib.pyplot as plt
#定义坐标轴
fig4 = plt.figure()
ax4 = plt.axes(projection='3d')
 
#生成三维数据
xx = np.random.random(20)*10-5   #取100个随机数，范围在5~5之间
yy = np.random.random(20)*10-5
X, Y = np.meshgrid(xx, yy)
Z = np.sin(np.sqrt(X**2+Y**2))
 
#作图
ax4.scatter(X,Y,Z,alpha=0.3,c=np.random.random(400),s=np.random.randint(10,20,size=(20, 20)))     #生成散点.利用c控制颜色序列,s控制大小
 
plt.show()

Effect:

The above is the detailed content of How to create a three-dimensional line chart using Python and Matplotlib. For more information, please follow other related articles on the PHP Chinese website!