I am using Python with numpy to do linear algebra.
I performed numpy
SVD on a matrix to get the matrices U,i, and V. However the i matrix is expressed as a 1x4 matrix with 1 row. i.e.: [ 12.22151125 4.92815942 2.06380839 0.29766152]
.
How can I get numpy to express the i matrix as a diagonal matrix like so:
[[12.22151125, 0, 0, 0],[0,4.92815942, 0, 0],[0,0,2.06380839,0 ],[0,0,0,0.29766152]]
Code I am using:
A = np.matrix([[3, 4, 3, 1],[1,3,2,6],[2,4,1,5],[3,3,5,2]])
U, i, V = np.linalg.svd(A,full_matrices=True)
So I want i to be a full diagonal matrix. How an I do this?
Use numpy's diag function:
numpy.diag(i)
From the documentation:
Extract a diagonal or construct a diagonal array.
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