December 2017
Intermediate to advanced
386 pages
10h 42m
English
Content preview from SciPy Recipes
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How to do it…
In SciPy, we calculate the eigenvector and eigenvalue of a given matrix by using the eig function in scipy.linalg.
Using the following code, let us look at calculating the eigenvector and the corresponding eigenvalue of a given matrix:
- Initialize a matrix:
a = np.array([[1, 2], [3, 4]])
- Calculate the eigenvalue and eigenvector of the matrix:
la, v = linalg.eig(a)
- The output of the preceding code is:
print(la)[-0.37228132+0.j 5.37228132+0.j]print(v)[[-0.82456484 -0.41597356] [ 0.56576746 -0.90937671]]
Note that la is the eigenvalue and the v matrix is the eigenvector.
Let us cross-check the preceding output based on the intuition we laid out at the start of this section.
The eigenvector for a given matrix A satisfies the ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.