3d图

3d图1

# coding=utf-8
import numpy as np
import matplotlib.pyplot as plt
import mpl_toolkits.mplot3d
a,b = np.mgrid[-2:2:20j,-2:2:20j]
#测试数据
c=a*np.exp(-a**2-b**2)
#三维图形
ax = plt.subplot(111, projection='3d')
ax.set_title('www.linuxidc.com - matplotlib Code Demo');
ax.plot_surface(a,b,c,rstride=2, cstride=1, cmap=plt.cm.Spectral)
#设置坐标轴标签
ax.set_xlabel('A')
ax.set_ylabel('B')
ax.set_zlabel('C')
plt.show()

3d图2

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()

3d图3

from matplotlib import pyplot as plt

import numpy as np

from mpl_toolkits.mplot3d import Axes3D

figure = plt.figure()

ax = Axes3D(figure)

X = np.arange(-10, 10, 0.25)

Y = np.arange(-10, 10, 0.25)

#网格化数据

X, Y = np.meshgrid(X, Y)

R = np.sqrt(X**2 + Y**2)

Z = np.cos(R)

ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap='rainbow')

plt.show()

3d图4

#coding=utf-8
#3D心形
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import matplotlib.pyplot as plt
import numpy as np
import matplotlib

#设置字体
myfont = matplotlib.font_manager.FontProperties(fname="ziti.TTF")#SIMLI.TTF与.py在同一目录下 字体文件库Windows一堆
matplotlib.rcParams['axes.unicode_minus'] = False

def heart_3d(x,y,z):
 return (x**2+(9/4)*y**2+z**2-1)**3-x**2*z**3-(9/80)*y**2*z**3


def plot_implicit(fn, bbox=(-1.5, 1.5)):
 xmin, xmax, ymin, ymax, zmin, zmax = bbox*3
 fig = plt.figure()
 ax = fig.add_subplot(111, projection='3d')
 A = np.linspace(xmin, xmax, 100) # resolution of the contour
 B = np.linspace(xmin, xmax, 40) # number of slices
 A1, A2 = np.meshgrid(A, A) # grid on which the contour is plotted

 for z in B: # plot contours in the XY plane
  X, Y = A1, A2
  Z = fn(X, Y, z)
  cset = ax.contour(X, Y, Z+z, [z], zdir='z', colors=('r',))
  # [z] defines the only level to plot
  # for this contour for this value of z

 for y in B: # plot contours in the XZ plane
  X, Z = A1, A2
  Y = fn(X, y, Z)
  cset = ax.contour(X, Y+y, Z, [y], zdir='y', colors=('red',))

 for x in B: # plot contours in the YZ plane
  Y, Z = A1, A2
  X = fn(x, Y, Z)
  cset = ax.contour(X+x, Y, Z, [x], zdir='x',colors=('red',))

 # must set plot limits because the contour will likely extend
 # way beyond the displayed level. Otherwise matplotlib extends the plot limits
 # to encompass all values in the contour.
 ax.set_zlim3d(zmin, zmax)
 ax.set_xlim3d(xmin, xmax)
 ax.set_ylim3d(ymin, ymax)
 #标题
 plt.title(u"这是一个标题",fontproperties=myfont)
 #取消坐标轴显示
 plt.axis('off')
 plt.show()

if __name__ == '__main__':
 plot_implicit(heart_3d)