我已设置以下代码以读取.graphml文件,执行计算(特征值),然后绘制结果。这是我到目前为止的代码:
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()
但图表上没有显示网格线或轴。我需要使用其他plt.grid()
以外的东西吗?
答案 0 :(得分:4)
这可能会有所帮助 - 我一直在发现,摆脱一般的pyplot命令是一种更有效的方法,可以使事情按预期工作。 Pyplot本质上是面向对象调用的一个重要包装器。我写了一些应该是等价的东西:
import matplotlib.pyplot as plt
# ... your other code here
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()