This is my participation 11 The fourth of the yuegengwen challenge 28 God , Check out the activity details ：2021 One last more challenge

Review

stay Python About drawing ,Mlab Provide open source matplotlib modular , You can not only draw a line chart 、 Histogram 、 Scatter diagram and other conventional diagrams , It also supports drawing quantity field diagram 、 spectrum 、 Picture of violin 、 Special drawings such as box drawing , Examples of previous articles can be found at .

• specgram() Method to draw spectrum diagram for amplitude spectrum ：matplotlib Plot the spectrum

• boxplot() Methods draw a box diagram for data distribution ：matplotlib Draw a box diagram

• quiver() Methods to draw the quantity field diagram for electromagnetic field analysis ：matplotlib Plot the quantity field

• violinplot() Draw and display data distribution and probability ：matplotlib Draw a picture of the violin

We often pay attention to the weather forecast in our daily life , When the season changes , The announcer will explain the air flow . During the weather forecast , Meteorological experts will draw the air flow according to the streamline map , To predict the local weather .

In this issue , We will learn matplotlib.pyplot.streamplot() Method related attribute learning ,let's go~

1. Streamline diagram Overview

• What is a flow chart ？

  • Streamline diagram is drawn by a combination of streamline and arrow , To represent the operation of the streamline in a certain period of time 、
  • The arrow on the streamline chart indicates the flow direction , The shape on the streamline indicates the flow intensity
  • Streamline diagram can be divided into airflow diagram 、 Isoanemometry 、 Elevation map, etc
  • The flow lines in the flow line diagram can be merged 、 Convergence 、 Split cross , But it can't cross

• Streamline diagram application scenario

  • Streamline diagrams are usually used to study wind speed in meteorology 、 airflow 、 The flow direction of the ocean current
  • Flow chart is an important chart for wind field analysis , The dilute density of the streamline is directly proportional to the wind speed

• Method of obtaining streamline diagram

  import matplotlib.pyplot as plt 
  plt.streamplot(x,y,u,v)
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2. Streamline properties

• Set streamline density

  • keyword ：density
  • The default value is ：1
  • The value type is ： Floating point or tuple
  • Control streamline density , When density=1 when , The grid will be divided into 30*30 grid
  • For setting the density in each direction , Tuples can be used (x,y)

• Set the streamline width

  • keyword ：linewidth
  • The value type is ： Floating point or two-dimensional array
  • Use a two-dimensional array , You can change the line width of the streamline on the mesh
  • The shape of the array must match u、v identical

• Set streamline color

  • keyword ：color
  • Values can be ：
    • English words for color ： Like green "g"
    • Abbreviations of words indicating color, such as ： Red "r", yellow "y"
    • RGB Format ： Hexadecimal format, such as "#88c999";(r,g,b) Tuple form
    • You can go to the color list
  • When using cmap when , You need to color Set as a two-dimensional array , Otherwise it will not work

• Set streamline scaling

  • keyword ：norm
  • The default is to stretch the streamline to （0,1）
  • Use... Only when the color is an array

• Set streamline color system

  • keyword ：cmap
  • The value form is ： color table _r
  • Available values commonly used are ：'Accent', 'Accent_r', 'Blues', 'Blues_r', 'BrBG', 'BrBG_r', 'BuGn', 'BuGn_r', 'BuPu', 'BuPu_r', 'CMRmap', 'CMRmap_r', 'Dark2', 'Dark2_r', 'GnBu', 'GnBu_r', 'Greens'

3. To draw a streamline diagram

• Import matplotlib.pyplot class

import matplotlib.pyplot as plt
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• call numpy library arange()、random()、randint() Wait until you're ready x,y,u,v data

  • x,y: One dimensional array / Two dimensional array
  • u,v: Two dimensional array
  • When it is a two-dimensional array , Can pass np.meshgrid(x,y),np.mgrid() establish

  x = np.arange(1,10)
  y = np.arange(1,10)
  
  u,v = np.meshgrid(np.sin(x),np.sin(y))
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• call pyplot.streamplot() Draw a streamline diagram

plt.streamplot(x,y,u,v,density=[0.5,1])
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• call pyplot.show() The rendering shows a streamline

plt.show()
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• Set up linewidth、color、cmap Property to draw a flow chart

plt.streamplot(x,y,u,v,density=[0.5,1],color=u,cmap="Accent_r",linewidth=3)
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4. A profound

We learned about the attributes related to drawing streamline diagram , Let's practice the starting point data of the control flow line

• call np.mgrid[] Definition x,y Two dimensional data
• call pyplot.streamplot() Method to draw a streamline diagram
• call pyplot.plot() Methods draw a line chart , Use marker Attribute tags

y,x= np.mgrid[-3:3:100j, -3:3:100j]
u = -1-x**2+y
v = 1+x-y**2

seed_points = np.array([[-2, -1, 0, 1, 2, -1], [-2, -1, 0, 1, 2, 2]])
plt.streamplot(x,y,u,v,density=0.6,color=u,cmap="autumn",linewidth=1,start_points=seed_points.T)
plt.plot(seed_points[0],seed_points[1],"^",color="b")

plt.show()
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summary

In this issue , We are right. matplotlib.pyplot Provide streamplot() Methods to draw streamline graph and learn related attributes . Flowcharts are usually used in meteorology , Study the change of air flow .

The above is the content of this issue , Welcome big guys to praise and comment , See you next time ~