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Python Matplotlib drawing streamline diagram

2022-02-01 16:26:03 Little cute in the circle of friends

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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 .

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 .

 Streamline diagram .png

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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image.png

  • 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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image.png

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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image.png

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 ~

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