1. #-*- coding: utf-8 -*-
  2. '''
  3. subplot(m,n,p):其中,m表示是图排成m行,n表示图排成n列,也就是整个figure中有n个图是排成一行的,一共m行,如果m=2就是表示2行图。p表示图所在的位置,p=1表示从左到右从上到下的第一个位置。
  4. np.random.uniform(0.5,1.0,n):获取 0.5~1.0之间n个随机数
  5. zip(x,y):将x和Y中的数据两两配对最后以列表返回
  6. plt.text(x+0.4, y+0.1, "%.2f"%y, ha="center"):指定文字出现在柱状图上的位置和内容
  7. x+0.4:文字显示横向增加0.4长度
  8. y+0.1:文字显示纵向增加0.1长度
  9. "%.2f"%y:应该显示的内容
  10. @author: soyo
  11. '''
  12. import matplotlib.pylab as plt
  13. import numpy as np
  14. plt.subplot(2,1,1)
  15. n=12
  16. x=np.arange(n)
  17. print x
  18. print x/float(n)
  19. print np.random.uniform(0.5,1.0,n)
  20. y1=(1-x/float(n))*np.random.uniform(0.5,1.0,n)
  21. y2=(1-x/float(n))*np.random.uniform(0.5,1.0,n)
  22. plt.bar(x,+y1,facecolor="red",edgecolor="grey")
  23. plt.bar(x,-y2,facecolor="lightblue",edgecolor="orange")
  24. print y1
  25. for x,y in zip(x,y1):
  26. plt.text(x+0.4, y+0.1, "%.2f"%y, ha="center")
  27. print (x,y)
  28. plt.ylim(-1.25,+1.25)
  29. plt.subplot(2,2,3)
  30. x=np.linspace(-np.pi,np.pi,300, endpoint=True)
  31. print x
  32. sin=np.sinc(x)
  33. cos=np.cos(x)
  34. plt.plot(x,cos,color="red",linewidth=2.7,linestyle="-")
  35. plt.plot(x,sin,color="blue",linewidth=4,linestyle="--")
  36. plt.xlim(x.min()*1.1,x.max()*1.1)
  37. plt.xticks([-np.pi,-np.pi/2,0,np.pi/2,np.pi],[r'$-\pi$',r'$-\pi/2$',r'$0$',r'$+\pi/2$',r'$+\pi$'])
  38. plt.ylim(cos.min()*1.1,cos.max()*1.1)
  39. # plt.yticks([-1,0,1],[r'$-1$',r'$0$',r'$+1$'])
  40. plt.yticks([-1,0,1])
  41.  
  42. plt.subplot(2,2,4)
  43. m=10
  44. z=np.random.uniform(5,9,6)
  45. plt.pie(z)
  46. plt.show()

结果:

  1. [ 0 1 2 3 4 5 6 7 8 9 10 11]
  2. [ 0. 0.08333333 0.16666667 0.25 0.33333333 0.41666667
  3. 0.5 0.58333333 0.66666667 0.75 0.83333333 0.91666667]
  4. [ 0.95962168 0.83510776 0.59960879 0.9103227 0.86161055 0.85219339
  5. 0.64341482 0.50396784 0.79940237 0.78113541 0.66371799 0.63459297]
  6. [ 0.65987664 0.87527832 0.79239077 0.61438775 0.44085434 0.38703261
  7. 0.40706581 0.2836271 0.25465063 0.20754596 0.124999 0.08099565]
  8. (0, 0.65987664052659789)
  9. (1, 0.87527832104794756)
  10. (2, 0.79239077290271298)
  11. (3, 0.61438775127130618)
  12. (4, 0.44085434356099779)
  13. (5, 0.3870326100974873)
  14. (6, 0.40706580998264275)
  15. (7, 0.2836271049672956)
  16. (8, 0.2546506260468242)
  17. (9, 0.20754596219057092)
  18. (10, 0.12499900221786377)
  19. (11, 0.080995646704109761)
  20. [-3.14159265 -3.12057866 -3.09956466 -3.07855066 -3.05753666 -3.03652267
  21. -3.01550867 -2.99449467 -2.97348067 -2.95246667 -2.93145268 -2.91043868
  22. -2.88942468 -2.86841068 -2.84739669 -2.82638269 -2.80536869 -2.78435469
  23. -2.7633407 -2.7423267 -2.7213127 -2.7002987 -2.6792847 -2.65827071
  24. -2.63725671 -2.61624271 -2.59522871 -2.57421472 -2.55320072 -2.53218672
  25. -2.51117272 -2.49015873 -2.46914473 -2.44813073 -2.42711673 -2.40610273
  26. -2.38508874 -2.36407474 -2.34306074 -2.32204674 -2.30103275 -2.28001875
  27. -2.25900475 -2.23799075 -2.21697676 -2.19596276 -2.17494876 -2.15393476
  28. -2.13292076 -2.11190677 -2.09089277 -2.06987877 -2.04886477 -2.02785078
  29. -2.00683678 -1.98582278 -1.96480878 -1.94379479 -1.92278079 -1.90176679
  30. -1.88075279 -1.85973879 -1.8387248 -1.8177108 -1.7966968 -1.7756828
  31. -1.75466881 -1.73365481 -1.71264081 -1.69162681 -1.67061282 -1.64959882
  32. -1.62858482 -1.60757082 -1.58655683 -1.56554283 -1.54452883 -1.52351483
  33. -1.50250083 -1.48148684 -1.46047284 -1.43945884 -1.41844484 -1.39743085
  34. -1.37641685 -1.35540285 -1.33438885 -1.31337486 -1.29236086 -1.27134686
  35. -1.25033286 -1.22931886 -1.20830487 -1.18729087 -1.16627687 -1.14526287
  36. -1.12424888 -1.10323488 -1.08222088 -1.06120688 -1.04019289 -1.01917889
  37. -0.99816489 -0.97715089 -0.95613689 -0.9351229 -0.9141089 -0.8930949
  38. -0.8720809 -0.85106691 -0.83005291 -0.80903891 -0.78802491 -0.76701092
  39. -0.74599692 -0.72498292 -0.70396892 -0.68295492 -0.66194093 -0.64092693
  40. -0.61991293 -0.59889893 -0.57788494 -0.55687094 -0.53585694 -0.51484294
  41. -0.49382895 -0.47281495 -0.45180095 -0.43078695 -0.40977295 -0.38875896
  42. -0.36774496 -0.34673096 -0.32571696 -0.30470297 -0.28368897 -0.26267497
  43. -0.24166097 -0.22064698 -0.19963298 -0.17861898 -0.15760498 -0.13659098
  44. -0.11557699 -0.09456299 -0.07354899 -0.05253499 -0.031521 -0.010507
  45. 0.010507 0.031521 0.05253499 0.07354899 0.09456299 0.11557699
  46. 0.13659098 0.15760498 0.17861898 0.19963298 0.22064698 0.24166097
  47. 0.26267497 0.28368897 0.30470297 0.32571696 0.34673096 0.36774496
  48. 0.38875896 0.40977295 0.43078695 0.45180095 0.47281495 0.49382895
  49. 0.51484294 0.53585694 0.55687094 0.57788494 0.59889893 0.61991293
  50. 0.64092693 0.66194093 0.68295492 0.70396892 0.72498292 0.74599692
  51. 0.76701092 0.78802491 0.80903891 0.83005291 0.85106691 0.8720809
  52. 0.8930949 0.9141089 0.9351229 0.95613689 0.97715089 0.99816489
  53. 1.01917889 1.04019289 1.06120688 1.08222088 1.10323488 1.12424888
  54. 1.14526287 1.16627687 1.18729087 1.20830487 1.22931886 1.25033286
  55. 1.27134686 1.29236086 1.31337486 1.33438885 1.35540285 1.37641685
  56. 1.39743085 1.41844484 1.43945884 1.46047284 1.48148684 1.50250083
  57. 1.52351483 1.54452883 1.56554283 1.58655683 1.60757082 1.62858482
  58. 1.64959882 1.67061282 1.69162681 1.71264081 1.73365481 1.75466881
  59. 1.7756828 1.7966968 1.8177108 1.8387248 1.85973879 1.88075279
  60. 1.90176679 1.92278079 1.94379479 1.96480878 1.98582278 2.00683678
  61. 2.02785078 2.04886477 2.06987877 2.09089277 2.11190677 2.13292076
  62. 2.15393476 2.17494876 2.19596276 2.21697676 2.23799075 2.25900475
  63. 2.28001875 2.30103275 2.32204674 2.34306074 2.36407474 2.38508874
  64. 2.40610273 2.42711673 2.44813073 2.46914473 2.49015873 2.51117272
  65. 2.53218672 2.55320072 2.57421472 2.59522871 2.61624271 2.63725671
  66. 2.65827071 2.6792847 2.7002987 2.7213127 2.7423267 2.7633407
  67. 2.78435469 2.80536869 2.82638269 2.84739669 2.86841068 2.88942468
  68. 2.91043868 2.93145268 2.95246667 2.97348067 2.99449467 3.01550867
  69. 3.03652267 3.05753666 3.07855066 3.09956466 3.12057866 3.14159265]

[ 0  1  2  3  4  5  6  7  8  9 10 11]
[ 0.          0.08333333  0.16666667  0.25        0.33333333  0.41666667
  0.5         0.58333333  0.66666667  0.75        0.83333333  0.91666667]
[ 0.95962168  0.83510776  0.59960879  0.9103227   0.86161055  0.85219339
  0.64341482  0.50396784  0.79940237  0.78113541  0.66371799  0.63459297]
[ 0.65987664  0.87527832  0.79239077  0.61438775  0.44085434  0.38703261
  0.40706581  0.2836271   0.25465063  0.20754596  0.124999    0.08099565]
(0, 0.65987664052659789)
(1, 0.87527832104794756)
(2, 0.79239077290271298)
(3, 0.61438775127130618)
(4, 0.44085434356099779)
(5, 0.3870326100974873)
(6, 0.40706580998264275)
(7, 0.2836271049672956)
(8, 0.2546506260468242)
(9, 0.20754596219057092)
(10, 0.12499900221786377)
(11, 0.080995646704109761)
[-3.14159265 -3.12057866 -3.09956466 -3.07855066 -3.05753666 -3.03652267
 -3.01550867 -2.99449467 -2.97348067 -2.95246667 -2.93145268 -2.91043868
 -2.88942468 -2.86841068 -2.84739669 -2.82638269 -2.80536869 -2.78435469
 -2.7633407  -2.7423267  -2.7213127  -2.7002987  -2.6792847  -2.65827071
 -2.63725671 -2.61624271 -2.59522871 -2.57421472 -2.55320072 -2.53218672
 -2.51117272 -2.49015873 -2.46914473 -2.44813073 -2.42711673 -2.40610273
 -2.38508874 -2.36407474 -2.34306074 -2.32204674 -2.30103275 -2.28001875
 -2.25900475 -2.23799075 -2.21697676 -2.19596276 -2.17494876 -2.15393476
 -2.13292076 -2.11190677 -2.09089277 -2.06987877 -2.04886477 -2.02785078
 -2.00683678 -1.98582278 -1.96480878 -1.94379479 -1.92278079 -1.90176679
 -1.88075279 -1.85973879 -1.8387248  -1.8177108  -1.7966968  -1.7756828
 -1.75466881 -1.73365481 -1.71264081 -1.69162681 -1.67061282 -1.64959882
 -1.62858482 -1.60757082 -1.58655683 -1.56554283 -1.54452883 -1.52351483
 -1.50250083 -1.48148684 -1.46047284 -1.43945884 -1.41844484 -1.39743085
 -1.37641685 -1.35540285 -1.33438885 -1.31337486 -1.29236086 -1.27134686
 -1.25033286 -1.22931886 -1.20830487 -1.18729087 -1.16627687 -1.14526287
 -1.12424888 -1.10323488 -1.08222088 -1.06120688 -1.04019289 -1.01917889
 -0.99816489 -0.97715089 -0.95613689 -0.9351229  -0.9141089  -0.8930949
 -0.8720809  -0.85106691 -0.83005291 -0.80903891 -0.78802491 -0.76701092
 -0.74599692 -0.72498292 -0.70396892 -0.68295492 -0.66194093 -0.64092693
 -0.61991293 -0.59889893 -0.57788494 -0.55687094 -0.53585694 -0.51484294
 -0.49382895 -0.47281495 -0.45180095 -0.43078695 -0.40977295 -0.38875896
 -0.36774496 -0.34673096 -0.32571696 -0.30470297 -0.28368897 -0.26267497
 -0.24166097 -0.22064698 -0.19963298 -0.17861898 -0.15760498 -0.13659098
 -0.11557699 -0.09456299 -0.07354899 -0.05253499 -0.031521   -0.010507
  0.010507    0.031521    0.05253499  0.07354899  0.09456299  0.11557699
  0.13659098  0.15760498  0.17861898  0.19963298  0.22064698  0.24166097
  0.26267497  0.28368897  0.30470297  0.32571696  0.34673096  0.36774496
  0.38875896  0.40977295  0.43078695  0.45180095  0.47281495  0.49382895
  0.51484294  0.53585694  0.55687094  0.57788494  0.59889893  0.61991293
  0.64092693  0.66194093  0.68295492  0.70396892  0.72498292  0.74599692
  0.76701092  0.78802491  0.80903891  0.83005291  0.85106691  0.8720809
  0.8930949   0.9141089   0.9351229   0.95613689  0.97715089  0.99816489
  1.01917889  1.04019289  1.06120688  1.08222088  1.10323488  1.12424888
  1.14526287  1.16627687  1.18729087  1.20830487  1.22931886  1.25033286
  1.27134686  1.29236086  1.31337486  1.33438885  1.35540285  1.37641685
  1.39743085  1.41844484  1.43945884  1.46047284  1.48148684  1.50250083
  1.52351483  1.54452883  1.56554283  1.58655683  1.60757082  1.62858482
  1.64959882  1.67061282  1.69162681  1.71264081  1.73365481  1.75466881
  1.7756828   1.7966968   1.8177108   1.8387248   1.85973879  1.88075279
  1.90176679  1.92278079  1.94379479  1.96480878  1.98582278  2.00683678
  2.02785078  2.04886477  2.06987877  2.09089277  2.11190677  2.13292076
  2.15393476  2.17494876  2.19596276  2.21697676  2.23799075  2.25900475
  2.28001875  2.30103275  2.32204674  2.34306074  2.36407474  2.38508874
  2.40610273  2.42711673  2.44813073  2.46914473  2.49015873  2.51117272
  2.53218672  2.55320072  2.57421472  2.59522871  2.61624271  2.63725671
  2.65827071  2.6792847   2.7002987   2.7213127   2.7423267   2.7633407
  2.78435469  2.80536869  2.82638269  2.84739669  2.86841068  2.88942468
  2.91043868  2.93145268  2.95246667  2.97348067  2.99449467  3.01550867
  3.03652267  3.05753666  3.07855066  3.09956466  3.12057866  3.14159265]

Python Matplotlib模块--pylab的更多相关文章

  1. Python Matplotlib模块--pyplot

    #-*- coding: utf- -*- ''' numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=No ...

  2. Windows python 安装 nNumpy、Scipy、matplotlib模块

    折腾了 很久,总结一些. 首先如果python 是64位,安装32位的numpy ,Scipy,或者matplotlib 模块. 会出现很多问题. 比如当你 在python 导入 Numpy 时,导入 ...

  3. python 爬虫与数据可视化--matplotlib模块应用

    一.数据分析的目的(利用大数据量数据分析,帮助人们做出战略决策) 二.什么是matplotlib? matplotlib: 最流行的Python底层绘图库,主要做数据可视化图表,名字取材于MATLAB ...

  4. 为python安装matplotlib模块

    matplotlib是python中强大的画图模块. 首先确保已经安装python,然后用pip来安装matplotlib模块. 进入到cmd窗口下,执行python -m pip install - ...

  5. Python使用matplotlib模块绘制多条折线图、散点图

    用matplotlib模块 #!usr/bin/env python #encoding:utf-8 ''' __Author__:沂水寒城 功能:折线图.散点图测试 ''' import rando ...

  6. windows_64下python下载安装Numpy、Scipy、matplotlib模块

    本文应用的python3.6.3及其对应的Numpy.Scipy.matplotlib计算模块的cp36版本,其中Numpy是需要MKL版本的Numpy,这是后续安装Scipy的需要(本机系统win7 ...

  7. windows下python安装Numpy、Scipy、matplotlib模块(转载)

    python下载链接     Numpy下载链接 python中Numpy包的安装及使用 Numpy包的安装 准备工作 Python安装 pip安装 将pip所在的文件夹添加到环境变量path路径中 ...

  8. python 1: 解决linux系统下python中的matplotlib模块内的pyplot输出图片不能显示中文的问题

    问题: 我在ubuntu14.04下用python中的matplotlib模块内的pyplot输出图片不能显示中文,怎么解决呢? 解决: 1.指定默认编码为UTF-8: 在python代码开头加入如下 ...

  9. Python使用pip安装matplotlib模块

    matplotlib是python中强大的画图模块. 首先确保已经安装python,然后用pip来安装matplotlib模块. 进入到cmd窗口下,建议执行python -m pip install ...

随机推荐

  1. Python学习之单继承与多继承

    继承 面向对象编程语言的一个主要功能就是“继承”. 继承是指这样一种能力:它可以使用现有类的所有功能,并在无需重新编写原来的类的情况下对这些功能进行扩展. (1) 单继承:python同时支持类的继承 ...

  2. LeetCode(62)Unique Paths

    题目 A robot is located at the top-left corner of a m x n grid (marked 'Start' in the diagram below). ...

  3. java-得到字符串中出现次数最最多的字符,并打印出字符以及出现次数

    最近面试总被面试到,整理出几种方式(有参考别人的部分) /** * java一个字符串中出现次数最多的字符以及次数 * @param args */ public static void main(S ...

  4. ROS 笔记 程序包/节点/topic

    官方教程: wiki.ros.org/cn/ROS/tutorials 程序包打创建于编译 创建程序包 在工作空间的src底下,输入如下命令: $ catkin_create_pkg 要创建的包名 依 ...

  5. NYOJ-1188并集与交集,STL的灵活运用!

    并集与交集 时间限制:1000 ms  |  内存限制:65535 KB 难度:2 描述 给你两个字符串的集合A和B,让你求这两个字符串集合的并集和交集,按字典序排序后输出. 然后又给出给出两个字符串 ...

  6. Codeforces Round #258 (Div. 2) D

    D. Count Good Substrings time limit per test 2 seconds memory limit per test 256 megabytes input sta ...

  7. Spring Boot Jpa 表名小写转大写

    今天在使用SpringBoot整合Hibernate后创建表,表名为小写,而在linux下,mysql的表名是区分大小写的,因此在我的数据表中,就出现了两个一样的表 act_id_user 和  AC ...

  8. 文件权限设置与http,php的关系

    在web服务器上的文件要使用什么权限比较好呢.我开始的时候直接都是777,后台安全部门的同事,通过漏洞把我管理的服务器给搞了.报告到我这里,我才意识到权限的设置不能马虎.环境采用nginx+php,一 ...

  9. Linux下汇编语言学习笔记30 ---

    这是17年暑假学习Linux汇编语言的笔记记录,参考书目为清华大学出版社 Jeff Duntemann著 梁晓辉译<汇编语言基于Linux环境>的书,喜欢看原版书的同学可以看<Ass ...

  10. MapReduce WordCount Combiner程序

    MapReduce WordCount Combiner程序 注意使用Combiner之后的累加情况是不同的: pom.xml <project xmlns="http://maven ...