python Matplotlib 学习笔记(1)

import numpy as np
import sys
import matplotlib.pyplot as plt

func = 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()

# -*- coding:utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt

func = 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 np
import matplotlib.pyplot as plt
mean = 0
sigma = 1
x=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()