%matplotlib inline

import matplotlib as mpl

import  matplotlib.pyplot as plt

import numpy as np

import pandas as pd

house = pd.read_csv('./housing.csv')  # 读取数据，数据文件存放在c根目录下盘可直接这样访问，如果放在文件夹里。可像平常一样加上目录名称

house.describe().loc[['min', 'std', 'max', 'mean'], ['RM', 'MEDV']].round(2)  求均值方差等

for i in range(4):

print (house.iloc[:, i].corr(house.iloc[:, i+4]).round(2))  #  可得到相关系数

fig, axes = plt.subplots(1, 4, figsize = (16, 4))

for n in range(4):

axes[n].scatter(house.iloc[:, n],house.iloc[:, n+4])  ## 这里开始画图

fig, ax = plt.subplots()

ax.plot(x, y1, color = "blue", label = "y(x)")

ax.plot(x, y2, color = "red", label = "y'(x)")

ax.set_xlabel("xxxxx")

ax.set_ylabel("yyyyy")

ax.legend()    # 基本画线图

fig, ax = plt.subplots()

ax.scatter(x, y1, color = "blue", label = "y(x)")

ax.scatter(x, y2, color = "red", label = "y'(x)")

ax.set_xlabel("xxxxx")

ax.set_ylabel("yyyyy")

ax.legend()  #基本画点图

fig, axes = plt.subplots(2, 2, figsize = (10,4))

for i in range(2):

for j in range(2):

axes[i, j].scatter(house.loc[:, 'RM'],house.loc[:, 'RM'])

fig, axes = plt.subplots(figsize = (16, 8))

axes.plot(x, np.zeros_like(x), color = 'black')

axes.plot([0, 0], [0, 5], lw = 0.5, ls = '--', color = 'red')

axes.plot([0, 0], [1, 10], lw = '', color = 'green')

axes.set_ylim(4, 15)

axes.set_xlim(-1, 1)

fig, ax = plt.subplots(figsize = (10,4))

ax.plot(x, y1, lw = 1.5, color = 'blue', label = 'Sy(x)s')

ax.plot(x, y2, lw = 1.5, color = 'red', label = 'Sy(x)s')

ax.plot(x, y2, lw = 1.5, color = 'green', label = 'Sy''(x)s')

ax.plot(x, np.zeros_like(x), lw = 0.5, color = 'black')

ax.plot([-3.33, -3.33], [0, (-3,33)**3 + 5*(-3.33)*2 + 10], ls = '--', lw = 0.5, color = 'black')

ax.plot([0, 0], [0, 10], lw = 0.5, ls = '--', color = 'black')

ax.plot([0], [10], lw = 0.5, marker = 'o', color = 'blue')

ax.plot([-3.33], [(-3.33)**3 + 5*(-3.33)**2 + 10], lw = 0.5, marker = 'o', color = 'blue')

fig = plt.figure(figsize = (8, 2.5), facecolor = "#f1f1f1")

left, bottom, width, height = 0.1, 0.1, 0.8, 0.8

ax = fig.add_axes((left, bottom, width, height), facecolor = "#e1e1e1")

x = np.linspace(-2, 2, 1000)

y1 = np.cos(40*x)

y2 = np.exp(-x*2)

ax.plot(x, y1*y2)

ax.plot(x, y2, 'g')

ax.plot(x, -y2, 'g')

ax.set_xlabel("x")

ax.set_ylabel("y")

fig.savefig("graph.png", dpi = 100, facecolor = "#f1f1f1")

fig.savefig("graph.pdf", dpi = 300, facecolor = "#f1f1f1")

x = np.linspace(-3, 3, 25)

y1 = x**3 + 3*x**2 + 10

y2 = -1.5*x**3 + 10*x*2 - 1.5

fig, ax = plt.subplots(1, 2, figsize = (20, 5))

ax[0].plot(x, y1)

ax[0].plot(x, y2)

ax[1].step(x, y1)

ax[1].step(x, y2)

ax[1].set_xlabel('ddfdfdf')

fig.savefig('./xxxpng')

fignum = 0

x = np.linspace(-3, 3, 25)

y1 = x**3 + 3*x**2 + 10

y2 = -1.5*x**3 + 10*x*2 - 1.5

fig, ax = plt.subplots()

ax.plot(x, y1)

ax.plot(x, y2)

def hide_label(fig, ax):

global fignum

ax.set_xtickets([])

ax.set_yticks([])

ax.xaxis.set

fig, ax = plt.subplots(figsize = (10,4))

width = 6/50.0

ax.bar(x - width/2, y1, width = width, color = "blue")

ax.bar(x - width/2, y2, width = width, color = "green")

fig, ax = plt.subplots(figsize = (10,4))

ax.fill_between(x, y1, y2)

ax.plot(x, y1, color = 'green', lw = 5)

fig, ax = plt.subplots(figsize = (10,4))

ax.hist(y2, bins = 30)

ax.hist(y1, bins = 30)

fig, ax = plt.subplots(figsize = (10,4))

ax.errorbar(x, y2, yerr = y1, fmt = 'o-')

ax.plot(x, y1, color = 'red')

ax.plot(x, y2, color = 'black', lw = 5)

fig, ax = plt.subplots(figsize = (10,4))

x = np.linspace(0, 5, 50)

ax.scatter(x, -1 + x + 0.25*x**2 + 2*np.random.rand(len(x)))

ax.scatter(x, np.sqrt(x) + 2*np.random.rand(len(x)))

s.plot(kind = 'bar')

s.plot(kind = 'pie')  # 画饼状图

import matplotlib.pyplot as  plt

%matplotlib inline

def sigmoid(x):

    return 1/(1+np.exp(-x))

x = np.arange(-5.0, 5.0 ,0.1)

y = sigmoid(x)

plt.plot(x ,y)

plt.ylim(-0.1, 1.1)

plt.show()

a = np.array([[1, 2, 3], [4, 5, 6]])

b = np.array([[1 ,2], [3, 4], [5, 6]])

np.dot(a, b)

#X--------Y

W2 = np.array([[1, 2], [3, 4] ,[5, 6]])

W1 = np.array([[1, 2, 3], [4, 5, 6]])

W3 = np.array([[1, 2], [3, 4]])

b1 = np.array([1, 2, 3])

b2 = np.array([1, 2])

b3 = np.array([1, 2])

X = np.array([1.0, 2.0])

A1 = np.dot(X ,W1) + b1

A2 = np.dot(A1, W2) + b2

Y = np.dot(A2, W3) + b3

#and门

def and_gate(x1, x2):

    if (20*x1 + 20*x2 -30) > 0:

        return 1

    else:

        return 0

x1, x2 = 1, 1

and_gate(x1, x2)