- hyperspy.learn.orthomax.orthomax(A, gamma=1.0, tol=1.4901e-07, max_iter=256)
Calculate orthogonal rotations for a matrix of factors or loadings from PCA.
When gamma=1.0, this is known as varimax rotation, which finds a rotation matrix W that maximizes the variance of the squared components of A @ W. The rotation matrix preserves orthogonality of the components.
Taken from metpy.
B (numpy array) – Rotated data matrix
W (numpy array) – The unmixing matrix