python Matplotlib 学习笔记(1)

1.绘制简单曲线

import numpy as npimport sysimport matplotlib.pyplot as pltfunc = np.poly1d(np.array([1, 2, 3, 4]).astype(float))func1 = func.deriv(m=1)x = np.linspace(-10, 10, 30)y = func(x)y1 = func1(x)plt.plot(x, y, 'ro', x, y1, 'g--')plt.xlabel('x')plt.ylabel('y')plt.show()

2.绘制子图

# -*- coding:utf-8 -*-import numpy as npimport matplotlib.pyplot as pltfunc = np.poly1d(np.array([1, 2, 3, 4]).astype(float))x = np.linspace(-10, 10, 30)y = func(x)func1 = func.deriv(m=1)y1 = func1(x)func2 = func.deriv(m=2)y2 = func2(x)plt.subplot(311)# 三行一列，从第一个图开始显示plt.plot(x, y, 'r-')plt.title("Polynomial")plt.subplot(312)plt.plot(x, y1, 'b^')plt.title("First Derivative")plt.subplot(313)plt.plot(x, y2, 'go')plt.title("Second Derivative")plt.xlabel('x')plt.ylabel('y')plt.subplots_adjust(hspace=1)# 每个图之间所空的距离plt.show()

import numpy as npimport matplotlib.pyplot as pltmean = 0sigma = 1x=mean+sigma*np.random.randn(10000)fig,(ax0,ax1) = plt.subplots(nrows=2,figsize=(9,6))# 第二个参数是柱子宽一些还是窄一些，越大越窄越密ax0.hist(x,40,normed=1,histtype='bar',facecolor='yellowgreen',alpha=0.75)# pdf概率分布图，一万个数落在某个区间内的数有多少个ax0.set_title('pdf')ax1.hist(x, 20, normed = 1,histtype='bar',facecolor='pink',alpha=0.75,cumulative=True,rwidth=0.8)# cdf累计概率函数，cumulative累计。比如需要统计小于5的数的概率ax1.set_title("cdf")fig.subplots_adjust(hspace=0.4)plt.show()