2018-08-14 03:49:00 by wst
python小技巧
git clone https://github.com/tracyone/program_font && cd program_font && ./install.sh
转自:https://www.cnblogs.com/arkenstone/p/6411055.html
__author__ = 'Katherine'
from matplotlib.font_manager import FontManager
import subprocess
fm = FontManager()
mat_fonts = set(f.name for f in fm.ttflist)
output = subprocess.check_output(
'fc-list :lang=zh -f "%{family}\n"', shell=True)
output = output.decode('utf-8')
# print '*' * 10, '系统可用的中文字体', '*' * 10
# print output
zh_fonts = set(f.split(',', 1)[0] for f in output.split('\n'))
available = mat_fonts & zh_fonts
print('*' * 10, '可用的字体', '*' * 10)
for f in available:
print(f)
输出为(每个人可能不一样, 可有可能为空):
********** 可用的字体 **********
Droid Sans Fallback
HanaMinA
若没有可用字体,则执行以下步骤安装字体:
首先需要安装中文字体
git clone https://github.com/tracyone/program_font && cd program_font && ./install.sh
git clone这一步有时非常慢,后来我直接下载完放到了百度云上(链接: https://pan.baidu.com/s/1kD_9mNDm4yVNSx_PIvkRKw 提取码: f978 复制这段内容后打开百度网盘手机App,操作更方便哦)
如果没有sudo权限,这一步会报错,修改install.sh文件为:
#!/bin/bash
# author:tracyone,tracyone@live.cn
if [[ `uname` == 'Darwin' ]]; then
# MacOS
font_dir="$HOME/Library/Fonts/"
else
# Linux
font_dir="${HOME}/.fonts/"
mkdir -p $font_dir
# sudo mkdir -p /usr/share/fonts/MyFonts
# find . -regextype posix-egrep -iregex '.*\.tt[cf]$' -exec sudo cp {} /usr/share/fonts/MyFonts \;
fi
echo "Install start..."
find . -regextype posix-egrep -iregex '.*\.tt[cf]$' -exec cp {} ${font_dir} \;
#sudo fc-cache -f -v
echo "Install finish..."
然后再次执行安装动作:
./install.sh
清除缓存,这一步很关键,一定要执行
rm -rf ~/.cache/matplotlib/*
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from scipy import stats
# 虽然代码中没有用到此包,画3d图时依然要引入
from mpl_toolkits.mplot3d import Axes3D
mpl.rcParams['axes.unicode_minus'] = False
# 可通过前面代码查看可用字体,然后找个可用放这里
mpl.rcParams['font.sans-serif'] = 'HanaMinA'
if __name__ == "__main__":
x1, x2 = np.mgrid[-5:5:51j, -5:5:51j]
x = np.stack((x1, x2), axis=2)
fig = plt.figure(figsize=(9, 8), facecolor='w')
sigma = (np.identity(2), np.diag((3, 3)), np.diag((2, 5)), np.array(((2, 1), (2, 5))))
for i in np.arange(4):
ax = fig.add_subplot(2, 2, i + 1, projection='3d')
norm = stats.multivariate_normal((0, 0), sigma[i])
y = norm.pdf(x)
ax.plot_surface(x1, x2, y, cmap=plt.cm.Accent, rstride=1, cstride=1, alpha=0.9, lw=0.5)
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
plt.suptitle(u"二元高斯分布方差比较", fontsize=18)
plt.tight_layout(1.5)
plt.show()