Reputation: 437
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?
Upvotes: 9
Views: 18803
Reputation: 671
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]]
You should use numpy.diagflat(flatted_input, k=0)
, to Create a two-dimensional array with the flattened input as a diagonal
example
In [1]: flatted_input = [12, 4, 2, 1]
In [2]: np.diagflat(flatted_input)
Out [2]: array([[12, 0, 0, 0],
[0, 4, 0, 0],
[0, 0, 2, 0],
[0, 0, 0, 1]])
Upvotes: 4
Reputation: 571
Use numpy's diag function:
numpy.diag(i)
From the documentation:
Extract a diagonal or construct a diagonal array.
Upvotes: 12