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()
