Python: Creating a 2D histogram from a numpy matrix

Question

I'm new to python.

I have a numpy matrix, of dimensions 42x42, with values in the range 0-996. I want to create a 2D histogram using this data. I've been looking at tutorials, but they all seem to show how to create 2D histograms from random data and not a numpy matrix.

So far, I have imported:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors

I'm not sure if these are correct imports, I'm just trying to pick up what I can from tutorials I see.

I have the numpy matrix M with all of the values in it (as described above). In the end, i want it to look something like this:

obviously, my data will be different, so my plot should look different. Can anyone give me a hand?

Edit: For my purposes, Hooked's example below, using matshow, is exactly what I'm looking for.

Answer 1

If you have the raw data from the counts, you could use plt.hexbin to create the plots for you (IMHO this is better than a square lattice): Adapted from the example of hexbin:

import numpy as np
import matplotlib.pyplot as plt

n = 100000
x = np.random.standard_normal(n)
y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
plt.hexbin(x,y)

plt.show()

If you already have the Z-values in a matrix as you mention, just use plt.imshow or plt.matshow:

XB = np.linspace(-1,1,20)
YB = np.linspace(-1,1,20)
X,Y = np.meshgrid(XB,YB)
Z = np.exp(-(X**2+Y**2))
plt.imshow(Z,interpolation='none')