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Matplotlib.pyplot 三维绘图的实现示例

文锅儿   2020-07-28 我要评论

本文着重讲解了Matplotlib.pyplot 三维绘图的实现示例,文中通过代码实例讲解的非常细致,对大家的工作和学习具有一定的参考学习价值,需要的朋友们下面随着小编来一起学习学习吧

折线图

Axes3D.plot(xs,ys,*args,**kwargs)

Argument Description
xs, ys x, y coordinates of vertices
zs z value(s), either one for all points or one for each point.
zdir Which direction to use as z (‘x', ‘y' or ‘z') when plotting a 2D set.

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()

散点图

Axes3D.scatter(xs,ys,zs=0,zdir='z',s=20,c=None,depthshade=True,*args,**kwargs)

Argument Description
xs, ys Positions of data points.
zs Either an array of the same length as xs and ys or a single value to place all points in the same plane. Default is 0.
zdir Which direction to use as z (‘x', ‘y' or ‘z') when plotting a 2D set.
s Size in points^2. It is a scalar or an array of the same length as x and y.
c A color. c can be a single color format string, or a sequence of color specifications of length N, or a sequence of N numbers to be mapped to colors using the cmap and norm specified via kwargs (see below). Note that c should not be a single numeric RGB or RGBA sequence because that is indistinguishable from an array of values to be colormapped. c can be a 2-D array in which the rows are RGB or RGBA, however, including the case of a single row to specify the same color for all points.
depthshade Whether or not to shade the scatter markers to give the appearance of depth. Default is True.

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()

线框图

Axes3D.plot_wireframe(X,Y,Z,*args,**kwargs)

Argument Description
X, Y, Data values as 2D arrays
Z  
rstride Array row stride (step size), defaults to 1
cstride Array column stride (step size), defaults to 1
rcount Use at most this many rows, defaults to 50
ccount Use at most this many columns, defaults to 50

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()

表面图

Axes3D.plot_surface(X,Y,Z,*args,**kwargs)

Argument Description
X, Y, Z Data values as 2D arrays
rstride Array row stride (step size)
cstride Array column stride (step size)
rcount Use at most this many rows, defaults to 50
ccount Use at most this many columns, defaults to 50
color Color of the surface patches
cmap A colormap for the surface patches.
facecolors Face colors for the individual patches
norm An instance of Normalize to map values to colors
vmin Minimum value to map
vmax Maximum value to map
shade Whether to shade the facecolors

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import numpy as np
 
fig = plt.figure()
ax = fig.gca(projection='3d')
 
# Make data.
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X ** 2 + Y ** 2)
Z = np.sin(R)
 
# Plot the surface.
surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
            linewidth=0, antialiased=False)
 
# Customize the z axis.
ax.set_zlim(-1.01, 1.01)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))
 
# Add a color bar which maps values to colors.
fig.colorbar(surf, shrink=0.5, aspect=5)
 
plt.show()

柱状图

Axes3D.bar(left,height,zs=0,zdir='z',*args,**kwargs)

Argument Description
left The x coordinates of the left sides of the bars.
height The height of the bars.
zs Z coordinate of bars, if one value is specified they will all be placed at the same z.
zdir Which direction to use as z (‘x', ‘y' or ‘z') when plotting a 2D set.

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()

箭头图

Axes3D.quiver(*args,**kwargs)

Arguments:

X, Y, Z:
The x, y and z coordinates of the arrow locations (default is tail of arrow; see pivot kwarg)
U, V, W:
The x, y and z components of the arrow vectors

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
 
fig = plt.figure()
ax = fig.gca(projection='3d')
 
# Make the grid
x, y, z = np.meshgrid(np.arange(-0.8, 1, 0.2),
           np.arange(-0.8, 1, 0.2),
           np.arange(-0.8, 1, 0.8))
 
# Make the direction data for the arrows
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *
   np.sin(np.pi * z))
 
ax.quiver(x, y, z, u, v, w, length=0.1, normalize=True)
 
plt.show()

2D转3D图

from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt
 
fig = plt.figure()
ax = fig.gca(projection='3d')
 
# Plot a sin curve using the x and y axes.
x = np.linspace(0, 1, 100)
y = np.sin(x * 2 * np.pi) / 2 + 0.5
ax.plot(x, y, zs=0, zdir='z', label='curve in (x,y)')
 
# Plot scatterplot data (20 2D points per colour) on the x and z axes.
colors = ('r', 'g', 'b', 'k')
x = np.random.sample(20 * len(colors))
y = np.random.sample(20 * len(colors))
labels = np.random.randint(3, size=80)
 
# By using zdir='y', the y value of these points is fixed to the zs value 0
# and the (x,y) points are plotted on the x and z axes.
ax.scatter(x, y, zs=0, zdir='y', c=labels, label='points in (x,z)')
 
# Make legend, set axes limits and labels
ax.legend()
ax.set_xlim(0, 1)
ax.set_ylim(0, 1)
ax.set_zlim(0, 1)
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
 
# Customize the view angle so it's easier to see that the scatter points lie
# on the plane y=0
ax.view_init(elev=20., azim=-35)
 
plt.show()

文本图

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()

3D拼图

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d.axes3d import Axes3D, get_test_data
from matplotlib import cm
import numpy as np
 
# set up a figure twice as wide as it is tall
fig = plt.figure(figsize=plt.figaspect(0.5))
 
# ===============
# First subplot
# ===============
# set up the axes for the first plot
ax = fig.add_subplot(1, 2, 1, projection='3d')
 
# plot a 3D surface like in the example mplot3d/surface3d_demo
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X ** 2 + Y ** 2)
Z = np.sin(R)
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
            linewidth=0, antialiased=False)
ax.set_zlim(-1.01, 1.01)
fig.colorbar(surf, shrink=0.5, aspect=10)
 
# ===============
# Second subplot
# ===============
# set up the axes for the second plot
ax = fig.add_subplot(1, 2, 2, projection='3d')
 
# plot a 3D wireframe like in the example mplot3d/wire3d_demo
X, Y, Z = get_test_data(0.05)
ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
 
plt.show()


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