画图案例分享

案例 1

from scipy.misc import derivative
from scipy.integrate import quad
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.stats import norm
import warnings

plt.style.use('ggplot')
np.random.seed(37)
warnings.filterwarnings('ignore')
import matplotlib
plt.rcParams['font.sans-serif']=['Songti SC'] #用来正常显示中文标签
# 或者是下面这个，宋体和仿宋字体，都可以用。
#plt.rcParams['font.sans-serif']=['STFangsong'] #用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号


x = np.arange(-2.5, 2.5, 0.1)
y_pdf = norm.pdf(x)
y_cdf = norm.cdf(x)

y_cdf = np.array([tup[0] for tup in [quad(norm.pdf, a, b) for a, b in [(a, b) for a, b in zip(x, x[1:len(x)])]]] + [0]).cumsum()
y_pdf = derivative(norm.cdf, x, dx=1e-6)

fig, ax = plt.subplots(1, 2, figsize=(20, 6),facecolor="white")

_ = ax[0].plot(x, y_pdf, color='black',linewidth=3.0)
#_ = ax[1].plot(x, y_cdf, color='b')
ax[0].set_facecolor('white') # 设置背景颜色
ax[0].axvline(x=0.0, color="black", linestyle="-", linewidth=3,ymin=0., ymax=0.66)
#ax[0].arrow(-4,0,8,0,color="black",linewidth=3)
ax[0].set_ylim(0,0.6)

################################################
for side in ['bottom','right','top','left']:
    ax[0].spines[side].set_visible(False)
for side in ['bottom','right','top','left']:
    ax[1].spines[side].set_visible(False)
################################################

xmin, xmax = ax[0].get_xlim() 
ymin, ymax = ax[0].get_ylim()

dps = fig.dpi_scale_trans.inverted()
bbox = ax[0].get_window_extent().transformed(dps)
width, height = bbox.width, bbox.height
# manual arrowhead width and length
hw = 1./20.*(ymax-ymin) 
hl = 1./20.*(xmax-xmin)
lw = 2.0 # axis line width
ohg = 0.3 # arrow overhang
 
# compute matching arrowhead length and width
yhw = hw/(ymax-ymin)*(xmax-xmin)* height/width 
yhl = hl/(xmax-xmin)*(ymax-ymin)* width/height
 
# draw x and y axis
ax[0].arrow(xmin, 0, xmax-xmin+0.2, 0., fc='k', ec='k', lw = lw, 
         head_width=hw, head_length=hl, color="black",
         length_includes_head= False, clip_on = False) 

ax[0].text(0,-0.05,"$\mu$",size=18)
ax[0].text(-2.8,0.5,"$p(x)$",size=18)
ax[0].text(3,-0.05,"$x$",size=18)
ax[0].set_xticks([])
ax[0].set_yticks([])
_ = ax[0].set_title('($a$)'+' 正态密度函数',y=-0.2,fontsize=18) # 标题放下面


_ = ax[1].plot(x, y_cdf, color='black',linewidth=3.0)
ax[1].set_facecolor('white') # 设置背景颜色
ax[1].axvline(x=0.0, color="black", linestyle="-", linewidth=3,ymin=0., ymax=0.66)
ax[1].axhline(y=1.0, color="black", linestyle="-", linewidth=3,xmin=0.05,xmax=0.9,ls="--")
#ax[1].arrow(-4,0,8,0,color="black",linewidth=3)
ax[1].set_ylim(0,1.5)

# get width and height of axes object to compute 
# matching arrowhead length and width
dps = fig.dpi_scale_trans.inverted()
bbox = ax[1].get_window_extent().transformed(dps)
width, height = bbox.width, bbox.height

xmin, xmax = ax[1].get_xlim() 
ymin, ymax = ax[1].get_ylim()
# manual arrowhead width and length
hw = 1./20.*(ymax-ymin) 
hl = 1./20.*(xmax-xmin)
lw = 2.0 # axis line width
ohg = 0.3 # arrow overhang
 
# compute matching arrowhead length and width
yhw = hw/(ymax-ymin)*(xmax-xmin)* height/width 
yhl = hl/(xmax-xmin)*(ymax-ymin)* width/height
 
# draw x and y axis
ax[1].arrow(xmin, 0, xmax-xmin, 0., fc='k', ec='k', lw = lw, 
         head_width=hw, head_length=hl, 
         length_includes_head= False, clip_on = False) 

ax[1].text(0,-0.1,"$\mu$",size=18)
ax[1].text(-2.8,1.28,"$F(x)$",size=18)
ax[1].text(3,-0.1,"$x$",size=18)
ax[1].text(-0.2,0.9,"$1$",size=18)
ax[1].set_xticks([])
ax[1].set_yticks([])
_ = ax[1].set_title('($b$)'+' 正态分布函数',y=-0.2,fontsize=18) # 标题放下面

plt.savefig("./重绘/13.png",dpi=500,bbox_inches='tight')

结果如下
在这里插入图片描述

注意点1

其中有一个易错的点需要注意
在这里插入图片描述

################################################
for side in ['bottom','right','top','left']:
    ax[0].spines[side].set_visible(False)
for side in ['bottom','right','top','left']:
    ax[1].spines[side].set_visible(False)
################################################

这部分代码是一定要加上的，否则这个图像就变成了下面的这个结果
在这里插入图片描述这个x轴就像长了一个奇怪的东西一样，需要注意

注意点2

保存图片时，一定要记得用bbox_inches的参数

plt.savefig("./重绘/13.png",dpi=500,bbox_inches='tight')

如果不用这个参数，图片下面的标题就没有了，意外的被丢掉了，需要注意

案例2

%matplotlib inline
from scipy.stats import norm
import numpy as np
import matplotlib.pyplot as plt
import warnings
plt.style.use('ggplot')
np.random.seed(37)
warnings.filterwarnings('ignore')

plt.rcParams['font.sans-serif']=['Songti SC'] #用来正常显示中文标签

plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号

fig, ax = plt.subplots(1, 2, figsize=(20, 6),facecolor="white")
ax[0].set_facecolor('white') # 设置背景颜色

################################################
for side in ['bottom','right','top','left']:
    ax[0].spines[side].set_visible(False)
for side in ['bottom','right','top','left']:
    ax[1].spines[side].set_visible(False)
################################################

# draw x and y axis
ax[0].arrow(-4, 0, 12, 0., fc='k', ec='k', lw = 2.0, 
         head_width=0.021931753100282243, head_length=0.66, color="black",
         length_includes_head= False, clip_on = False)
# draw x and y axis
# draw x and y axis
ax[0].arrow(0, 0, 0, 0.5, fc='k', ec='k', lw = 2.0,
        head_width=0.3,head_length=0.05,color="black",
         length_includes_head= False, clip_on = False)

means = [0.0, 3.0, 2.0]
cnt=0
for mean in means:
    if(cnt ==0):
        x = np.linspace(-3.3,3.3,100)
        ax[0].plot(x, norm.pdf(x,loc=mean),c="b",linewidth=3.0)
    if(cnt ==1):
        x = np.linspace(-1.5,7.5,100)
        ax[0].plot(x, norm.pdf(x,loc=mean),c="g",linewidth=3.0)
        ax[0].axvline(x=3.0, color="black", linestyle="-", linewidth=2,ymin=0.07, ymax=0.71)
    if(cnt ==2):
        x = np.linspace(-1.5,5.5,100)
        ax[0].plot(x, norm.pdf(x,loc=mean),c="r",linewidth=3.0)
        ax[0].axvline(x=2.0, color="black", linestyle="-", linewidth=2,ymin=0.07, ymax=0.71)
    cnt+=1
# ax[0].set_yticks([])
# ax[0].set_xticks([])
ax[0].text(0,-0.05,"$\mu_{2}$",size=18)
ax[0].text(2.0,-0.05,"$\mu_{1}$",size=18)
ax[0].text(3.0,-0.05,"$\mu_{3}$",size=18)
ax[0].text(0.35,0.5,"$\mathrm{p(x)}$",size=18)
ax[0].text(8.5,-0.05,"$x$",size=18)
ax[0].set_xticks([])
ax[0].set_yticks([])

ax[1].set_facecolor('white') # 设置背景颜色




# draw x and y axis
ax[1].arrow(-4, 0, 12, 0., fc='k', ec='k', lw = 2.0, 
         head_width=0.021931753100282243, head_length=0.66, color="black",
         length_includes_head= False, clip_on = False)
# draw x and y axis
# draw x and y axis
ax[1].arrow(0, 0, 0, 0.55, fc='k', ec='k', lw = 2.0,
        head_width=0.3,head_length=0.05,color="black",
         length_includes_head= False, clip_on = False)

cnt=0

x = np.linspace(-3.3,7.3,100)
ax[1].plot(x, norm.pdf(x,loc=2,scale=1.0),c="r",linewidth=3.0)

x = np.linspace(-3.3,7.3,100)
ax[1].plot(x, norm.pdf(x,loc=2,scale=2.0),c="b",linewidth=3.0)

x = np.linspace(-3.3,8.0,100)
ax[1].plot(x, norm.pdf(x,loc=2,scale=0.7),c="g",linewidth=3.0)

ax[1].axvline(x=2.0, color="black", linestyle="-", linewidth=1,ymin=0.07, ymax=1.0)

ax[1].text(0,-0.05,"0",size=18)
ax[1].text(8.5,-0.05,"$x$",size=18)
ax[1].text(0,0.62,"$\mathrm{p(x)}$",size=18)
ax[1].text(2.1,0.63,"$x=\mu$",size=18)
ax[1].text(2.4,0.53,"$\sigma=0.7$",size=18,color="g")
ax[1].text(3.0,0.25,"$\sigma=1$",size=18,color="r")
ax[1].text(5.0,0.1,"$\sigma=2$",size=18,color="b")
ax[1].set_xticks([])
ax[1].set_yticks([])


plt.savefig("./重绘/14.png",dpi=500,bbox_inches='tight')

结果如下
在这里插入图片描述
除了这个坐标轴有点丑，其余的都还行的