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This article introduces the relevant knowledge of "how to draw a variety of streamline charts in Python matplotlib". In the operation of actual cases, many people will encounter such a dilemma. Next, let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

Overview of flow charts what is a flow chart?

The streamline chart is drawn by a combination of streamline and arrowhead to show the operation of the streamline in a certain period of time.

The arrows on the streamline chart indicate the flow direction, and the shapes on the streamline indicate the flow intensity.

Flow chart can be divided into air flow chart, isoline, variable height map and so on.

The streamline in the streamline chart can be merged, converged and separated, but cannot be crossed.

Streamline chart application scenario

Flow charts are usually used in meteorology to study the flow direction of wind speed, air current and ocean current.

The flow chart is an important chart for wind field analysis, and the density of the streamline is proportional to the wind speed.

Get the streamline chart method import matplotlib.pyplot as plt plt.streamplot (x _ line y _ r _ r _ v) stream chart attribute sets the streamline chart density

Keyword: density

Default value is: 1

Value type: floating point or tuple

Control the density of the flow chart, when density=1, the grid will be divided into 30-30 grids

For setting the density in each direction, you can use a tuple (xPowery)

Set streamline width

Keyword: linewidth

The value type is: floating point or two-dimensional array

Using a two-dimensional array, you can change the linewidth of the streamline on the grid.

The shape of the array must be the same as u and v

Set streamline color

Keyword: color

The value can be:

English words for color: such as green "g"

Abbreviations for color words such as red "r" and yellow "y"

RGB format: hexadecimal format such as "# 88c999"; (rMagnegMagneb) tuple form

You can go to the color list

When using cmap, you need to set color to a two-dimensional array, otherwise it is invalid

Set streamline Zoom

Keyword: norm

The default is to stretch the streamline to (0recom 1)

Use only when the color is an array

Set streamline color system

Keyword: cmap

The form of value is: color table _ r

Available values are commonly used: 'Accent',' Accent_r', 'Blues',' Blues_r', 'BrBG',' BrBG_r', 'BuGn',' BuGn_r', 'BuPu',' BuPu_r', 'CMRmap',' Dark2', 'Dark2_r',' GnBu', 'GnBu_r',' Greens'

Steps to draw a streamline chart

Import matplotlib.pyplot CLA

Import matplotlib.pyplot as plt

Call the numpy libraries arange (), random (), randint (), etc., to prepare the data of XMagi, YJ, and v.

XBI y: one-dimensional array / two-dimensional array

UBI v: two-dimensional array

When it is a two-dimensional array, you can create it through np.meshgrid (XJO y), np.mgrid ()

X = np.arange (1mai 10) y = np.arange (1m 10) UBI v = np.meshgrid (np.sin (x), np.sin (y))

Call pyplot.streamplot () to draw a streamline chart

Plt.streamplot (x _ pencil _ y _ pr _ r _ v _ rec _ density = [0.5 ~ 1])

Call pyplot.show () to render to show the streamline chart

Plt.show ()

Set the attributes of linewidth, color, cmap to draw a streamline chart

Plt.streamplot (color=u,cmap= "Accent_r", linewidth=3)

Try a bull's knife

We have learned about the properties related to drawing a streamline chart. Let's actually manipulate the starting point data of the control streamline.

Call np.mgrid [] to define XBI y 2D data

Call the pyplot.streamplot () method to draw a streamline chart

Call the pyplot.plot () method to draw a line chart and use the marker attribute tag

Y np.mgrid x = np.mgrid [- 3 1+x-y**2 seed_points 3VR 100j] u =-1+x-y**2 seed_points = np.array ([[- 2,-1, 0, 1, 2,-1], [- 2,-1, 0, 1, 2, 2]) plt.streamplot Seed_points [1], "^", color= "b") plt.show ()

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