我要說的第一件事就是不要用eigh
來測試正定性,因爲eigh
假設輸入是厄米特。這可能就是你認爲你參考的answer不起作用的原因。
我不喜歡那個答案,因爲它有一個迭代(並且,我不明白它的例子),也不是other answer有它不答應給你最好的正定矩陣,即,根據Frobenius範數(元素的平方和)最接近輸入的那個。 (我絕對不知道你在你的問題的代碼是應該做的。)
我喜歡這個matlab實現海厄姆的1988年紙:https://www.mathworks.com/matlabcentral/fileexchange/42885-nearestspd所以我把它移植到Python:
from numpy import linalg as la
def nearestPD(A):
"""Find the nearest positive-definite matrix to input
A Python/Numpy port of John D'Errico's `nearestSPD` MATLAB code [1], which
credits [2].
[1] https://www.mathworks.com/matlabcentral/fileexchange/42885-nearestspd
[2] N.J. Higham, "Computing a nearest symmetric positive semidefinite
matrix" (1988): https://doi.org/10.1016/0024-3795(88)90223-6
"""
B = (A + A.T)/2
_, s, V = la.svd(B)
H = np.dot(V.T, np.dot(np.diag(s), V))
A2 = (B + H)/2
A3 = (A2 + A2.T)/2
if isPD(A3):
return A3
spacing = np.spacing(la.norm(A))
# The above is different from [1]. It appears that MATLAB's `chol` Cholesky
# decomposition will accept matrixes with exactly 0-eigenvalue, whereas
# Numpy's will not. So where [1] uses `eps(mineig)` (where `eps` is Matlab
# for `np.spacing`), we use the above definition. CAVEAT: our `spacing`
# will be much larger than [1]'s `eps(mineig)`, since `mineig` is usually on
# the order of 1e-16, and `eps(1e-16)` is on the order of 1e-34, whereas
# `spacing` will, for Gaussian random matrixes of small dimension, be on
# othe order of 1e-16. In practice, both ways converge, as the unit test
# below suggests.
I = np.eye(A.shape[0])
k = 1
while not isPD(A3):
mineig = np.min(np.real(la.eigvals(A3)))
A3 += I * (-mineig * k**2 + spacing)
k += 1
return A3
def isPD(B):
"""Returns true when input is positive-definite, via Cholesky"""
try:
_ = la.cholesky(B)
return True
except la.LinAlgError:
return False
if __name__ == '__main__':
import numpy as np
for i in xrange(10):
for j in xrange(2, 100):
A = np.random.randn(j, j)
B = nearestPD(A)
assert(isPD(B))
print('unit test passed!')
除了找到最接近的正定矩陣之外,上述庫包括isPD
,它使用Cholesky分解來確定矩陣是否是正定的。這樣,您不需要任何容差 - 任何想要正確定位的函數都會運行Cholesky,所以它是確定正定性的絕對最佳方式。
它還具有在端部具有基於蒙特卡羅的單元測試。如果你把它放在posdef.py
並運行python posdef.py
,它會運行一個單元測試,在我的筆記本電腦上傳遞一秒鐘。然後在你的代碼,你可以import posdef
,並呼籲posdef.nearestPD
或posdef.isPD
。
的代碼也是一個Gist如果你做到這一點。
嘿,我的答案解決了這個問題?如果這樣你能接受它,所以我們可以關閉這個問題?或者,如果沒有,請說明還有什麼問題?謝謝! –