python 绘制3D图案例分享

这篇文章主要介绍了python 绘制3D图案例分享，文章围绕主题展开详细的内容介绍，具有一定的参考价值，需要的小伙伴可以参考一下，希望对你的学习有所帮助

1.散点图

代码

# This import registers the 3D projection, but is otherwise unused. from mpl_toolkits.mplot3d import Axes3D  # noqa: F401 unused import import matplotlib.pyplot as plt import numpy as np # Fixing random state for reproducibility np.random.seed(19680801) 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 m, zlow, zhigh in [('o', -50, -25), ('^', -30, -5)]: xs = randrange(n, 23, 32) ys = randrange(n, 0, 100) zs = randrange(n, zlow, zhigh) ax.scatter(xs, ys, zs, marker=m) ax.set_xlabel('X Label') ax.set_ylabel('Y Label') ax.set_zlabel('Z Label') plt.show()

输出：

输入的数据格式

这个输入的三个维度要求是三列长度一致的数据，可以理解为3个length相等的list。
用上面的scatter或者下面这段直接plot也可以。

fig = plt.figure() ax = fig.gca(projection='3d') ax.plot(h, z, t, '.', alpha=0.5) plt.show()

输出：

2.三维表面 surface

代码

x = [12.7, 12.8, 12.9] y = [1, 2, 3, 4] temp = pd.DataFrame([[7,7,9,9],[2,3,4,5],[1,6,8,7]]).T X,Y = np.meshgrid(x,y)  # 形成网格化的数据 temp = np.array(temp) fig = plt.figure(figsize=(16, 16)) ax = fig.gca(projection='3d') ax.plot_surface(Y,X,temp,rcount=1, cmap=cm.plasma, linewidth=1, antialiased=False,alpha=0.5) #cm.plasma ax.set_xlabel('zone', color='b', fontsize=20) ax.set_ylabel('h2o', color='g', fontsize=20) ax.set_zlabel('Temperature', color='r', fontsize=20)

output:

输入的数据格式

这里x和y原本都是一维list，通过np.meshgrid可以将其形成4X3的二维数据，如下图所示：

而第三维，得是4X3的2维的数据，才能进行画图

scatter + surface图形展示

3. 三维瀑布图waterfall

代码

from matplotlib.collections import PolyCollection import matplotlib.pyplot as plt from matplotlib import colors as mcolors import numpy as np axes=plt.axes(projection="3d") def colors(arg): return mcolors.to_rgba(arg, alpha=0.6) verts = [] z1 = [1, 2, 3, 4] x1 = np.arange(0, 10, 0.4) for z in z1: y1 = np.random.rand(len(x1)) y1[0], y1[-1] = 0, 0 verts.append(list(zip(x1, y1))) # print(verts) poly = PolyCollection(verts, facecolors=[colors('r'), colors('g'), colors('b'), colors('y')]) poly.set_alpha(0.7) axes.add_collection3d(poly, zs=z1, zdir='y') axes.set_xlabel('X') axes.set_xlim3d(0, 10) axes.set_ylabel('Y') axes.set_ylim3d(-1, 4) axes.set_zlabel('Z') axes.set_zlim3d(0, 1) axes.set_title("3D Waterfall plot") plt.show()

输出：

输入的数据格式

这个的输入我还没有完全搞懂，导致我自己暂时不能复现到其他数据，等以后懂了再回来补充。

4. 3d wireframe

code

from mpl_toolkits.mplot3d import axes3d import matplotlib.pyplot as plt fig, (ax1, ax2) = plt.subplots( 2, 1, figsize=(8, 12), subplot_kw={'projection': '3d'}) # Get the test data X, Y, Z = axes3d.get_test_data(0.05) # Give the first plot only wireframes of the type y = c ax1.plot_wireframe(X, Y, Z, rstride=10, cstride=0) ax1.set_title("Column (x) stride set to 0") # Give the second plot only wireframes of the type x = c ax2.plot_wireframe(X, Y, Z, rstride=0, cstride=10) ax2.set_title("Row (y) stride set to 0") plt.tight_layout() plt.show()

output: