Question

我从here复制了一个片段并运行它，但没有获得所需的样式。

繁殖代码

#!/usr/bin/evn python

import numpy as np
import scipy.linalg
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt

# some 3-dim points
mean = np.array([0.0, 0.0, 0.0])
cov = np.array([[1.0, -0.5, 0.8], [-0.5, 1.1, 0.0], [0.8, 0.0, 1.0]])
data = np.random.multivariate_normal(mean, cov, 50)

# regular grid covering the domain of the data
X, Y = np.meshgrid(np.arange(-3.0, 3.0, 0.5), np.arange(-3.0, 3.0, 0.5))
XX = X.flatten()
YY = Y.flatten()

order = 1  # 1: linear, 2: quadratic
if order == 1:
    # best-fit linear plane
    A = np.c_[data[:, 0], data[:, 1], np.ones(data.shape[0])]
    C, _, _, _ = scipy.linalg.lstsq(A, data[:, 2])  # coefficients

    # evaluate it on grid
    Z = C[0] * X + C[1] * Y + C[2]

    # or expressed using matrix/vector product
    #Z = np.dot(np.c_[XX, YY, np.ones(XX.shape)], C).reshape(X.shape)

elif order == 2:
    # best-fit quadratic curve
    A = np.c_[np.ones(data.shape[0]), data[:, :2],
              np.prod(data[:, :2], axis=1), data[:, :2]**2]
    C, _, _, _ = scipy.linalg.lstsq(A, data[:, 2])

    # evaluate it on a grid
    Z = np.dot(np.c_[np.ones(XX.shape), XX, YY, XX * YY, XX**2, YY**2],
               C).reshape(X.shape)

# plot points and fitted surface
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.plot_surface(X, Y, Z, rstride=1, cstride=1, alpha=0.2)
ax.scatter(data[:, 0], data[:, 1], data[:, 2], c='r', s=50)
plt.xlabel('X')
plt.ylabel('Y')
ax.set_zlabel('Z')
ax.axis('equal')
ax.axis('tight')
plt.show()

实际结果

请参阅此link

预期结果

请参阅此link

这两种风格非常不同：网格颜色，线框，表面颜色等。这个图像的样式来自先前版本的matplotlib吗？如果是这样，我怎么能得到那种风格？

Matplotlib版本

操作系统：Linux Mint 18.3
Matplotlib版本：2.2.2
Matplotlib后端：Qt4Agg
Python版本：2.7.12

我在虚拟环境中通过pip安装了matplotlib。

Answer 1

在我的Python 3.5中，matplotlib 2.2.2安装plt.style.use（'classic'）似乎有效

Why matplotlib graphs and icons look different on two computers with the same OS?类似，但Q是关于图标的

我怎样才能获得所需的matplotlib 3d绘图样式？

1 个答案: