How can we plot 2D math vectors with
matplotlib? Does anyone have an example or suggestion about that?
I have a couple of vectors stored as 2D
numpy arrays, and I would like to plot them as directed edges.
The vectors to be plotted are constructed as below:
import numpy as np # a list contains 3 vectors; # each list is constructed as the tail and the head of the vector a = np.array([[0, 0, 3, 2], [0, 0, 1, 1], [0, 0, 9, 9]])
I just added the plot of the final answer of
tcaswell for anyone interested in the output and want to plot 2d vectors with matplotlib:
The suggestion in the comments by halex is correct, you want to use quiver (doc), but you need to tweak the properties a bit.
import numpy as np import matplotlib.pyplot as plt soa = np.array([[0, 0, 3, 2], [0, 0, 1, 1], [0, 0, 9, 9]]) X, Y, U, V = zip(*soa) plt.figure() ax = plt.gca() ax.quiver(X, Y, U, V, angles='xy', scale_units='xy', scale=1) ax.set_xlim([-1, 10]) ax.set_ylim([-1, 10]) plt.draw() plt.show()
It's pretty straightforward. Hope this example helps.
import matplotlib.pyplot as plt import numpy as np x = np.random.normal(10,5,100) y = 3 + .5*x + np.random.normal(0,1,100) myvec = np.array([x,y]) plt.plot(myvec[0,],myvec[1,],'ro') plt.show()
To plot the arrays you can just slice them up into 1D vectors and plot them. I'd read the full documentation of matplotlib for all the different options. But you can treat a numpy vector as if it were a normal tuple for most of the examples.