python 快速求解最大特征值，只求最大特征值

2024年4月27日 123次阅读 来源: 颹蕭蕭 
import numpy as np
from time import clock
from scipy.linalg import eigh as largest_eigh
from scipy.sparse.linalg.eigen.arpack import eigsh as largest_eigsh

np.set_printoptions(suppress=True)
np.random.seed(0)
N=5000
k=1
X = np.random.random((N,N)) - 0.5
X = np.dot(X, X.T) #create a symmetric matrix

# Benchmark the dense routine
start = clock()
evals_large, evecs_large = largest_eigh(X, eigvals=(N-k,N-1))
elapsed = (clock() - start)
print ("eigh elapsed time: ", elapsed)

# Benchmark the sparse routine
start = clock()
evals_large_sparse, evecs_large_sparse = largest_eigsh(X, k, which='LM')
elapsed = (clock() - start)
print ("eigsh elapsed time: ", elapsed)

输出：

eigh elapsed time:  12.561862699999999
eigsh elapsed time:  2.3652462000000014

可见，对于 5000 维的对称矩阵，求解其最大特征值只需 2 秒

    原文作者：颹蕭蕭
    原文地址: https://blog.csdn.net/itnerd/article/details/109774318
    本文转自网络文章，转载此文章仅为分享知识，如有侵权，请联系博主进行删除。
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