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Matplotlib.axes.Axes.streamplot() in Python
  • Last Updated : 19 Apr, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.streamplot() Function

The Axes.streamplot() function in axes module of matplotlib library is also used to draw streamlines of a vector flow..

Syntax: Axes.streamplot(axes, x, y, u, v, density=1, linewidth=None, color=None, cmap=None, norm=None, arrowsize=1, arrowstyle=’-|>’, minlength=0.1, transform=None, zorder=None, start_points=None, maxlength=4.0, integration_direction=’both’, *, data=None)

Parameters: This method accept the following parameters that are described below:

  • X, Y : These parameter are the x and y coordinates of the evenly spaced grid.
  • U, V: This parameter is the The number of rows and columns must match the length of y and x.
  • density : This parameter is used to controls the closeness of streamlines.
  • linewidth : This parameter is the width of the stream lines.
  • color : This parameter is the streamline color.
  • cmap : This parameter is used to plot streamlines and arrows.
  • norm : This parameter is used to normalize object used to scale luminance data to 0, 1.
  • arrowsize : This parameter is the scaling factor for the arrow size.
  • minlength : This parameter is the minimum length of streamline in axes coordinates..
  • maxlength : This parameter is the maximum length of streamline in axes coordinates.
  • zorder : This parameter is the zorder of the stream lines and arrows.

Returns:This method returns the following:



  • stream_container :This returns the StreamplotSet
    Container object with attributes

Below examples illustrate the matplotlib.axes.Axes.streamplot() function in matplotlib.axes:

Example 1:




# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
       
X, Y = np.meshgrid(np.arange(0, 2 * np.pi, .2),
                   np.arange(0, 2 * np.pi, .2))
U = np.cos(X**2)
V = np.sin(Y**2)
  
fig, ax = plt.subplots()
ax.streamplot(X, Y, U, V, density =[0.5, 1])
  
ax.set_title('matplotlib.axes.Axes.streamplot()\
 Example\n', fontsize = 14, fontweight ='bold')
plt.show()

Output:

Example 2:




# Implementation of matplotlib function
  
  
import matplotlib.pyplot as plt
import numpy as np
       
X, Y = np.meshgrid(np.arange(0, 2 * np.pi, .2),
                   np.arange(0, 2 * np.pi, .2))
U = np.cos(X**2)
V = np.sin(Y**2)
  
fig, (ax, ax1)= plt.subplots(nrows = 2, ncols = 1)
ax.streamplot(X, Y, U, V, density =[0.5, 1],
             color = V * U, linewidth = 2,
             cmap ='autumn')
val = np.array([[2, 1, 0, 1, 2, 1],
                [2, 10, 1, 2, 2]])
  
ax1.streamplot(X, Y, U, V, color = V * U, linewidth = 2,
               cmap ='autumn'
               start_points = val.T)
  
ax.set_title('matplotlib.axes.Axes.streamplot() \
Example\n', fontsize = 14, fontweight ='bold')
plt.show()

Output:

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