This article mainly introduces the method of creating symmetric matrices in Python, and analyzes the related operating skills of Python based on the numpy module to implement matrix operations in the form of examples. Friends in need can refer to the following
The examples in this article describe Python Methods for creating symmetric matrices. Share it with everyone for your reference, the details are as follows:
Symmetric (real symmetric) matrix is:
step 1: Create a square matrix
>>> import numpy as np >>> X = np.random.rand(5**2).reshape(5, 5) >>> X array([[ 0.26984148, 0.25408384, 0.12428487, 0.0194565 , 0.91287708], [ 0.31837673, 0.35493156, 0.74336268, 0.31810561, 0.04409245], [ 0.06644445, 0.8967897 , 0.10990936, 0.05036292, 0.72581982], [ 0.94758512, 0.21375975, 0.36781736, 0.1633904 , 0.36070709], [ 0.53263787, 0.18380491, 0.0225521 , 0.91239367, 0.75521585]])
step 2: Keep its upper triangle part
>>> X = np.triu(X) # 保留其上三角部分 >>> X array([[ 0.26984148, 0.25408384, 0.12428487, 0.0194565 , 0.91287708], [ 0. , 0.35493156, 0.74336268, 0.31810561, 0.04409245], [ 0. , 0. , 0.10990936, 0.05036292, 0.72581982], [ 0. , 0. , 0. , 0.1633904 , 0.36070709], [ 0. , 0. , 0. , 0. , 0.75521585]])
step 3: "Copy" the upper triangle to the lower triangle
>>> X += X.T - np.diag(X.diagonal()) >>> X array([[ 0.26984148, 0.25408384, 0.12428487, 0.0194565 , 0.91287708], [ 0.25408384, 0.35493156, 0.74336268, 0.31810561, 0.04409245], [ 0.12428487, 0.74336268, 0.10990936, 0.05036292, 0.72581982], [ 0.0194565 , 0.31810561, 0.05036292, 0.1633904 , 0.36070709], [ 0.91287708, 0.04409245, 0.72581982, 0.36070709, 0.75521585]])
Note , subtract the elements on the diagonal once.Because the upper trianglecov
and the lower trianglecov.T
will add the elements on the main diagonal twice when adding.
step 4: Test
>>> X.T == X array([[ True, True, True, True, True], [ True, True, True, True, True], [ True, True, True, True, True], [ True, True, True, True, True], [ True, True, True, True, True]], dtype=bool)
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