Gridlines not showing up

Question

I've set up the following code to read in a .graphml file, preform a calculation (eigenvalues) and then plot the results. Here is the code I have so far:

import numpy as np
import networkx as nx
import matplotlib.pyplot as plt

# Read in the Data

G = nx.read_graphml("/home/user/DropBox_External_Datasets/JHU_Human_Brain/cat_brain_1.graphml")

nx.draw(G)
plt.savefig("test_graph.png")

Z = nx.to_numpy_matrix(G)

# Get Eigenvalues and Eigenvectors
# ----------------------------------------------------------------------------------
#
e_vals, e_vec = np.linalg.eigh(Z)

print("The eigenvalues of A are:", e_vals)
print("The size of the eigenvalues matrix is:", e_vals.shape)
# ----------------------------------------------------------------------------------

plt.plot(e_vals, 'g^')
plt.ylabel('Eigenvalues')
# plt.axis([-30, 300, -15, 30]) # Optimal settings for Rhesus data
# plt.axis([-0.07, 1, -0.2, 1.2])  # range to zoom in on cluster of points in Rhesus data

plt.grid(b=True, which='major', color='b', linestyle='-')
plt.show()

But no gridlines or axes show up on the graph. Is there something other then plt.grid() that I need to use?

Answer 1

I have been finding that using the matplotlib object oriented API is a more robust way to make things work as expected. Pyplot is essentially a big wrapper for the object-oriented calls. I've written something that should be equivalent:

import matplotlib.pyplot as plt

# ... your other code here

# Using subplots
fig, ax = plt.subplots(ncols=1, nrows=1) # These arguments can be omitted for one
                                         # plot, I just include them for clarity
ax.plot(e_vals, 'g^')
ax.set_ylabel('Eigenvalues')

ax.grid(b=True, which='major', color='b', linestyle='-')

plt.show()