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Python matplotlib画曲线例题解析

2020-02-15 21:19:58
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这篇文章主要介绍了Python matplotlib画曲线例题解析,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下

初学者,练习以下片段:

代码1:用 一元一次函数 画直线

import matplotlib.pyplot as pltimport numpy as npx = np.linspace(-2, 2, 50)print(x)y = 2*x + 1plt.plot(x, y)ax = plt.gca()ax.spines['bottom'].set_position(('data',0))ax.spines['left'].set_position(('data',0))plt.show()

代码2:用 一元二次函数 画抛物线

import matplotlib.pyplot as pltimport numpy as npx = np.linspace(-4, 6, 50)print(type(x))print(x)y = x**2 - x*2+1plt.plot(x, y)plt.show()

代码3:用反比例函数 画曲线

import matplotlib.pyplot as pltimport numpy as npx = np.linspace(-11, 11, 110)print(x)y =10/xplt.plot(x, y)ax = plt.gca()ax.spines['bottom'].set_position(('data',0))ax.spines['left'].set_position(('data',0))plt.show()

代码4:子坐标系的应用

import matplotlib.pyplot as pltfig = plt.figure()ax1 = fig.add_subplot(221)ax2 = fig.add_subplot(222)ax3 = fig.add_subplot(224)ax1.set(xlim=[0.5, 4.5], ylim=[-2, 8], title='Axes Show',    ylabel='Y', xlabel='X')plt.show()

代码5:子坐标系的应用

import matplotlib.pyplot as pltfig = plt.figure()fig,axes=plt.subplots(nrows=2, ncols=2)axes[0,0].set(xlim=[0.5, 4.5], ylim=[-2, 8], title='Axes Show',    ylabel='Y', xlabel='X')axes[0,1].set(title='Upper Right') axes[1,0].set(title='Lower Left') axes[1,1].set(title='Lower Right')

代码6:用已知少量坐标值画曲线

import matplotlib.pyplot as pltplt.plot([1, 2, 3, 4], [10, 20, 25, 30], color='lightblue', linewidth=3)plt.xlim(0.5, 4.5)plt.show()

代码7:画离散点

mport matplotlib.pyplot as pltimport numpy as npx = np.arange(10)y = np.random.randn(10)print(y)plt.scatter(x, y, color='red', marker='+')plt.show()

代码8:画出正弦曲线

import numpy as npimport matplotlib.pyplot as pltx=np.arange(-2*np.pi,2*np.pi,0.01)y=np.sin(x)plt.plot(x,y)ax = plt.gca()ax.spines['bottom'].set_position(('data',0))ax.spines['left'].set_position(('data',0))plt.xticks([-np.pi*2,-np.pi*3/2,-np.pi, -np.pi/2, 0, np.pi/2, np.pi,np.pi*3/2,np.pi*2],[r'$-2/pi$',r'$-/frac{3}{2} /pi$',r'$-/pi$',r'$-/frac{1}{2}/pi$', r'0', r'$/frac{1}{2}/pi$','$/pi$',r'$/frac{3}{2}/pi$',r'$2 /pi$'])plt.show()            
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