Python篇(二)：matplotlib中pyplot的使用简介

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Python提供了类似于MATLAB的2D绘图库，在使用时会发现编译通过但图片show不出来的情况。如

from numpy import arraya = array([1,2,3,4])from matplotlib import pyplotpyplot.plot(a,3*a)

此时只需要增加如下语句即可show出图片

pyplot.show()

example_1

import matplotlib.pyplot as pltfrom numpy import *plt.close('all')pi = 3.1415926x = linspace(0, 2*pi, 50)y = sin(x)z = cos(x)plt.plot(x, y, 'g-o', label='sin')plt.plot(x, z, 'r-^', label='cos')# plt.legend(['sin', 'cos'])plt.legend()plt.axis([0, 7, -1.2, 1.2])plt.xlabel('radians', fontsize='large')plt.ylabel('amplitude', fontsize='large')plt.title('eg title')plt.grid()

example_2 子图

import numpy as npimport matplotlib.pyplot as pltdef f(t):    return np.exp(-t) * np.cos(2*np.pi*t)t1 = np.arange(0.0, 5.0, 0.1)t2 = np.arange(0.0, 5.0, 0.02)plt.figure(1)plt.subplot(211)plt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')plt.subplot(212)plt.plot(t2, np.cos(2*np.pi*t2), 'r--')plt.show()

example_3 图上加文字注释

import numpy as npimport matplotlib.pyplot as pltmu, sigma = 100, 15x = mu + sigma * np.random.randn(10000)# the histogram of the datan, bins, patches = plt.hist(x, 50, normed=1, facecolor='g', alpha=0.75)plt.xlabel('Smarts')plt.ylabel('Probability')plt.title('Histogram of IQ')plt.text(60, .025, r'$\mu=100,\ \sigma=15$')plt.axis([40, 160, 0, 0.03])plt.grid(True)plt.show()

example_4 箭头标注

import numpy as npimport matplotlib.pyplot as pltax = plt.subplot(111)t = np.arange(0.0, 5.0, 0.01)s = np.cos(2*np.pi*t)line, = plt.plot(t, s, lw=2)plt.annotate('local max', xy=(2, 1), xytext=(3, 1.5),            arrowprops=dict(facecolor='black', shrink=0.05),            )plt.ylim(-2,2)plt.show()

example_5 散点图

from matplotlib import pyplotfrom numpy.random import randx = rand(200)y = rand(200)size = rand(200) * 30color = rand(200)pyplot.scatter(x, y, size, color)pyplot.colorbar()pyplot.show()

example_6读文本数据绘图

# -*- coding:utf-8 -*-import sysimport numpy as npimport matplotlib.pyplot as pltreload(sys)sys.setdefaultencoding('utf-8')np.set_printoptions(precision=2, suppress=True)data = np.genfromtxt("JANAF_CH4.txt",                  delimiter="\t", # TAB 分隔                  skiprows=1,     # 忽略首行                  names=True,     # 读入属性                  missing_values="INFINITE",  # 缺失值                  filling_values=np.inf)      # 填充缺失值for row in data[:7]:    print "{}\t{}".format(row['TK'], row['Cp'])print "...\t..."p = plt.plot(data['TK'], data['Cp'], 'kx')t = plt.title("JANAF data for Methane $CH_4$")a = plt.axis([0, 6000, 30, 120])x = plt.xlabel("Temperature (K)")y = plt.ylabel(r"$C_p$ ($\frac{kJ}{kg K}$)")plt.show()

数据来源：http://kinetics.nist.gov/janaf/html/C-067.txt

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