perform varimax rotation in python using numpy

Question

I am working on principal component analysis of a matrix. I have already found the component matrix shown below

A = np.array([[-0.73465832 -0.24819766 -0.32045055]
              [-0.3728976   0.58628043 -0.63433607]
              [-0.72617152  0.53812819 -0.22846634]
              [ 0.34042864 -0.08063226 -0.80064174]
              [ 0.8804307   0.17166265  0.04381426]
              [-0.66313032  0.54576874  0.37964986]
              [ 0.286712    0.68305196  0.21769803]
              [ 0.94651412  0.14986739 -0.06825887]
              [ 0.40699665  0.73202276 -0.08462949]])

I need to perform varimax rotation in this component matrix but could not find the exact method and degree to rotate. Most of the examples are shown in R. However I need the method in python.

Asked By: Raj Subit

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Source

Answer 1

Wikipedia has an example in python here!

Lifting the example and tailoring it for numpy:

from numpy import eye, asarray, dot, sum, diag
from numpy.linalg import svd
def varimax(Phi, gamma = 1.0, q = 20, tol = 1e-6):
    p,k = Phi.shape
    R = eye(k)
    d=0
    for i in xrange(q):
        d_old = d
        Lambda = dot(Phi, R)
        u,s,vh = svd(dot(Phi.T,asarray(Lambda)**3 - (gamma/p) * dot(Lambda, diag(diag(dot(Lambda.T,Lambda))))))
        R = dot(u,vh)
        d = sum(s)
        if d_old!=0 and d/d_old < 1 + tol: break
    return dot(Phi, R)

Answered By: Steve Barnes

Answer 2

You can find a lot of examples with Python. Here is an example I found for Python using only numpy, on Wikipedia:

def varimax(Phi, gamma = 1, q = 20, tol = 1e-6):
    from numpy import eye, asarray, dot, sum, diag
    from numpy.linalg import svd
    p,k = Phi.shape
    R = eye(k)
    d=0
    for i in xrange(q):
        d_old = d
        Lambda = dot(Phi, R)
        u,s,vh = svd(dot(Phi.T,asarray(Lambda)**3 - (gamma/p) * dot(Lambda, diag(diag(dot(Lambda.T,Lambda))))))
        R = dot(u,vh)
        d = sum(s)
        if d/d_old < tol: break
    return dot(Phi, R)

Answered By: Sudip Kafle

Answer 3

I’ve looked up solutions for doing factor analysis in python on stack-overflow so many times, that I recently made my own package, fa-kit. Even though this is an old post, I’m throwing up this link in case there’s anybody else in the future that gets here via google.

Answered By: bmcmenamin

Answer 4

You can use advanced-pca. for more details click on https://pypi.org/project/advanced-pca/

Answered By: Arichandran R

perform varimax rotation in python using numpy

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