A quiver plot is a type of plot that displays arrows with directional components U and V at the Cartesian coordinates specified by X and Y.
We can easily create a quiver plot in Matplotlib by using the quiver() function, which uses the following syntax:
quiver(x, y, u, v)
where:
- x: The x-coordinates of the arrow locations
- y: The y-coordinates of the arrow locations
- u: The x components of the arrow vectors
- v: The y components of the arrow vectors
This tutorial provides several examples of how to use this function in practice.
Example 1: Quiver Plot with One Arrow
The following code shows how to display a quiver plot with just one arrow:
import matplotlib.pyplot as plt #define plots fig, ax = plt.subplots() #define coordinates and directions x = 0 y = 0 u = 15 v = 3 #create quiver plot ax.quiver(x, y, u, v) #display quiver plot plt.show()
Example 2: Quiver Plot with Two Arrows
The following code shows how to display a quiver plot with two arrows:
import matplotlib.pyplot as plt #define plots fig, ax = plt.subplots() #define coordinates and directions x = [0, 0] y = [0, 0] u = [0, 1] v = [-2, 0] #create quiver plot ax.quiver(x, y, u, v, scale = 10) #display quiver plot plt.show()
Note that the scale argument scales the arrows to be longer, which makes them easier to view on the plot.
Example 3: Quiver Plot with a Mesh Grid
The following code shows how to display a quiver plot using a mesh grid:
import matplotlib.pyplot as plt import numpy as np #define plots fig, ax = plt.subplots() #define coordinates and directions x,y = np.meshgrid(np.arange(-2, 2, .1), np.arange(-2, 2, .1)) z = x*np.exp(-x**2 - y**2) v, u = np.gradient(z, .1, .1) #create quiver plot ax.quiver(x, y, u, v) #display quiver plot plt.show()
You can find the complete documentation for the quiver() function here.