Python编程深度学习绘图库之matplotlib

matplotlib是python的一个开源的2d绘图库，它的原作者是john d. hunter，因为在设计上借鉴了matlab，所以成为matplotlib。和pillow一样是被广泛使用的绘图功能，而在深度学习相关的部分，matplotlib得宠的多。这篇文章将简单介绍一下如何安装以及使用它来画一些非常常见的统计图形。

概要信息

注意事项：由于python2支持到2020年，很多python库都开始主要支持python3了，matplotlib的主分支也已经是python3了。而这篇文章中为了简单，安装和demo代码依然是在python2.7上进行验证的。

安装

使用pip install即可直接安装。安装日志如下：

liumiaocn:tmp liumiao$ python -mpip install -u pip
requirement already up-to-date: pip in /usr/local/lib/python2.7/site-packages (10.0.1)
liumiaocn:tmp liumiao$
liumiaocn:tmp liumiao$ python -mpip install -u matplotlib
collecting matplotlib
 downloading https://files.pythonhosted.org/packages/61/38/d70e8bf77d5cb27d5f3595edd0b3978825063feadd023786d2591e393e6e/matplotlib-2.2.2-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (13.7mb)
  100% |████████████████████████████████| 13.7mb 2.1mb/s
collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 (from matplotlib)
 downloading https://files.pythonhosted.org/packages/6a/8a/718fd7d3458f9fab8e67186b00abdd345b639976bc7fb3ae722e1b026a50/pyparsing-2.2.0-py2.py3-none-any.whl (56kb)
  100% |████████████████████████████████| 61kb 5.8mb/s
collecting backports.functools-lru-cache (from matplotlib)
 downloading https://files.pythonhosted.org/packages/03/8e/2424c0e65c4a066e28f539364deee49b6451f8fcd4f718fefa50cc3dcf48/backports.functools_lru_cache-1.5-py2.py3-none-any.whl
collecting subprocess32 (from matplotlib)
 downloading https://files.pythonhosted.org/packages/fa/60/b50459f291cae6bc1d0ff711b75e5130684fd3949370fdba78f6c57c1903/subprocess32-3.5.2-cp27-cp27m-macosx_10_6_intel.whl
collecting pytz (from matplotlib)
 downloading https://files.pythonhosted.org/packages/dc/83/15f7833b70d3e067ca91467ca245bae0f6fe56ddc7451aa0dc5606b120f2/pytz-2018.4-py2.py3-none-any.whl (510kb)
  100% |████████████████████████████████| 512kb 8.9mb/s
requirement not upgraded as not directly required: six>=1.10 in /usr/local/lib/python2.7/site-packages (from matplotlib) (1.11.0)
collecting python-dateutil>=2.1 (from matplotlib)
 downloading https://files.pythonhosted.org/packages/cf/f5/af2b09c957ace60dcfac112b669c45c8c97e32f94aa8b56da4c6d1682825/python_dateutil-2.7.3-py2.py3-none-any.whl (211kb)
  100% |████████████████████████████████| 215kb 7.2mb/s
collecting kiwisolver>=1.0.1 (from matplotlib)
 downloading https://files.pythonhosted.org/packages/79/d8/94633718f3f77dcb638687a77ba199325a1cb158d2d4b00c9dc17f2b5c72/kiwisolver-1.0.1-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (110kb)
  100% |████████████████████████████████| 112kb 5.9mb/s
collecting cycler>=0.10 (from matplotlib)
 downloading https://files.pythonhosted.org/packages/f7/d2/e07d3ebb2bd7af696440ce7e754c59dd546ffe1bbe732c8ab68b9c834e61/cycler-0.10.0-py2.py3-none-any.whl
requirement not upgraded as not directly required: numpy>=1.7.1 in /usr/local/lib/python2.7/site-packages (from matplotlib) (1.14.5)
requirement not upgraded as not directly required: setuptools in /usr/local/lib/python2.7/site-packages (from kiwisolver>=1.0.1->matplotlib) (39.2.0)
installing collected packages: pyparsing, backports.functools-lru-cache, subprocess32, pytz, python-dateutil, kiwisolver, cycler, matplotlib
successfully installed backports.functools-lru-cache-1.5 cycler-0.10.0 kiwisolver-1.0.1 matplotlib-2.2.2 pyparsing-2.2.0 python-dateutil-2.7.3 pytz-2018.4 subprocess32-3.5.2
liumiaocn:tmp liumiao$

确认

liumiaocn:~ liumiao$ pip show matplotlib
name: matplotlib
version: 2.2.2
summary: python plotting package
home-page: http://matplotlib.org
author: john d. hunter, michael droettboom
author-email: [e-mail]
license: bsd
location: /usr/local/lib/python2.7/site-packages
requires: pyparsing, backports.functools-lru-cache, subprocess32, pytz, six, python-dateutil, kiwisolver, cycler, numpy
required-by:
liumiaocn:~ liumiao$

使用

正弦函数

我们使用numpy和matplotlib可以非常简单地就能够画出正弦的波形图，具体代码如下：

liumiaocn:plot liumiao$ cat plot-1.py
#!/usr/local/bin/python
import numpy as np
import matplotlib.pyplot as plot
print("y=sin(x): x with range fo -4pi to 4pi")
x=np.arange(-4*np.pi, 4*np.pi, 0.1)
y=np.sin(x)
#print sin
plot.plot(x,y)
plot.show()
liumiaocn:plot liumiao$

执行&结果确认

liumiaocn:plot liumiao$ python plot-1.py
y=sin(x): x with range fo -4pi to 4pi

直方图

最简单的直方图的做法，可以通过bar或者hist来创建

liumiaocn:plot liumiao$ cat plot-2.py
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(7)
y = (10,15,24,7,14,30,20)
plt.bar(x,y)
plt.show()
liumiaocn:plot liumiao$

饼图

使用pie函数创建饼图

liumiaocn:plot liumiao$ cat plot-3.py
#!/usr/local/bin/python
import matplotlib.pyplot as plt
dateinf = '06/01', '06/02', '06/03', '06/04', '06/05', '06/06', '06/07'
bugnums = [11,22,7,29,24,15,18]
plt.pie(bugnums, labels=dateinf)
plt.show()
liumiaocn:plot liumiao$

总结

以上就是这篇文章的全部内容了，希望本文的内容对大家的学习或者工作具有一定的参考学习价值，谢谢大家对服务器之家的支持。如果你想了解更多相关内容请查看下面相关链接

原文链接：https://blog.csdn.net/liumiaocn/article/details/80728030