In this tutorial, we’ll try to understand how to plot a quiver plot in Python with the help of some examples.
What is a Quiver plot?
A quiver plot is basically a type of 2D plot which shows vector lines as arrows. These types of plots are used by Electrical engineers to visualize electrical potential and show stress gradients in Mechanical engineering.
We can plot a quiver plot in Python using axes.quiver
method in matplotlib.
Quiver Plot using matpltolib.Axes.quiver()
method
We can plot a Quiver plot in Python using the Axes.quiver
method within the matplotlib module. The following is the syntax –
Basic Syntax:
axes.quiver([x, y], u, v, [c], **kwargs)
Parameters:
- x: 1D or 2D array, sequence. The x coordinates of the arrow locations
- y: 1D or 2D array, sequence. The y coordinates of the arrow locations
- u: 1D or 2D array, sequence. The x components of the arrow vectors
- v: 1D or 2D array, sequence. The y components of the arrow vectors
- c: 1D or 2D array, sequence. The arrow colors
For more details, about the parameters, refer this.
Now let us try to understand the above method using some examples.
Example 1 – Quiver plot with a single arrow
import matplotlib.pyplot as plt import numpy as np #generating the figure and axes fig, ax = plt.subplots() #defining the parameters x = 0 y = 0 u = 1 v = 1 #plotting the Quiver plot ax.quiver(x,y,u,v) plt.show()
Output:

The steps followed in the above examples are:
- Import the modules
- create a figure and axes using
pyplot.subplots
(refer this). - Define the parameters
- Plot the Quiver plot using
axes.quiver
method (refer this).
Example 2 – Quiver plot with two arrows
import matplotlib.pyplot as plt import numpy as np #generating the figure and axes fig, ax = plt.subplots() #defining the parameters x = [0, -0.5] y = [0, 0.5] u = [1, 0] v = [1, -1] #plotting the Quiver plot ax.quiver(x,y,u,v) plt.show()
Output:

The steps followed in the above examples are:
- Import the modules
- create a figure and axes using
pyplot.subplots
(refer this). - Define the parameters
- Plot the Quiver plot using
axes.quiver
method (refer this).
Example 3 – Quiver plot using a meshgrid
import matplotlib.pyplot as plt import numpy as np #generating the figure and axes fig, ax = plt.subplots() #defining the parameters X = np.arange(0,2.2,0.2) Y = np.arange(0,2.2,0.2) x, y = np.meshgrid(X, Y) u = np.cos(x)*y v = np.sin(y)*y #plotting the Quiver plot ax.quiver(x,y,u,v) plt.show()
Output:

The steps followed in the above examples are:
- Import the modules
- create a figure and axes using
pyplot.subplots
- Define the parameters
- Plot the Quiver plot using
axes.quiver
method.
Example 4 – Quiver plot along with gradient
import matplotlib.pyplot as plt import numpy as np #generating the figure and axes fig, ax = plt.subplots() #defining the parameters x = np.arange(-2,2.2,0.2) y = np.arange(-2,2.2,0.2) X, Y = np.meshgrid(x, y) z = X*np.exp(-X**2 -Y**2) dx, dy = np.gradient(z) #plotting the Quiver plot ax.quiver(x,y,dx,dy) plt.show()
Output:

The steps followed in the above examples are:
- Import the modules
- create a figure and axes using
pyplot.subplots
- Define the parameters
- generate X,Y values using
numpy.arange
generate a meshgrid usingnumpy.meshgrid
Then create the respective dx and dy values usingnumpy.gradient
(refer this)
- generate X,Y values using
- Plot the Quiver plot using
axes.quiver
method
Example 5 – Quiver plot along with four vortices
import matplotlib.pyplot as plt import numpy as np #generating the figure and axes fig, ax = plt.subplots() #defining the parameters x = np.arange(0,2*np.pi+2*np.pi/20,2*np.pi/20) y = np.arange(0,2*np.pi+2*np.pi/20,2*np.pi/20) X,Y = np.meshgrid(x,y) u = np.sin(X)*np.cos(Y) v = -np.cos(X)*np.sin(Y) #plotting the Quiver plot ax.quiver(x,y,u,v) plt.show()
Output:

The steps followed in the above examples are:
- Import the modules
- create a figure and axes using
pyplot.subplots
- Define the parameters
- generate X,Y values using
numpy.arange
generate a meshgrid usingnumpy.meshgrid
Then create the respective u and v values.
- generate X,Y values using
- Plot the Quiver plot using
axes.quiver
method
Example 5 – Quiver plot with colour
import matplotlib.pyplot as plt import numpy as np #generating the figure and axes fig, ax = plt.subplots() #defining the parameters x = np.arange(0,2.2,0.2) y = np.arange(0,2.2,0.2) X, Y = np.meshgrid(x, y) u = np.cos(X)*Y v = np.sin(y)*Y n = -2 color_array = np.sqrt(((v-n)/2)**2 + ((u-n)/2)**2) #plotting the Quiver plot ax.quiver(x,y,u,v, color_array, alpha=0.8) plt.show()
Output:

The steps followed in the above examples are:
- Import the modules
- create a figure and axes using
pyplot.subplots
- Define the parameters
- generate X,Y values using
numpy.arange
generate a meshgrid usingnumpy.meshgrid
Then create the respective u and v values
- generate X,Y values using
- Plot the Quiver plot using
axes.quiver
method by adding a color array for colours.
Example 7 – Quiver plot in 3D
import matplotlib.pyplot as plt import numpy as np #generating the figure and axes ax = plt.figure().add_subplot(projection='3d') #defining the parameters X = np.arange(-0.8, 1, 0.2) Y = np.arange(-0.8, 1, 0.2) Z = np.arange(-0.8, 1, 0.8) x, y, z = np.meshgrid(X,Y,Z) u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z) v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z) w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) * np.sin(np.pi * z)) #plotting the Quiver plot ax.quiver(x, y, z, u, v, w, length=0.1, normalize=True) plt.show()
Output:

The steps followed in the above examples are:
- Import the modules
- Create an axes using
pyplot.figure.add_subplot(projection='3d')
for the 3D plot. - Define the parameters
- generate X,Y,Z values using
numpy.arange
generate a meshgrid usingnumpy.meshgrid
Then create the respective u,v and w values.
- generate X,Y,Z values using
- Plot the Quiver plot using
axes.quiver
method
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- How to Create a Contour Plot in Matplotlib
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