| import numpy as np | |
| from scipy import signal | |
| from .base import VHRMethod | |
| class LGI(VHRMethod): | |
| methodName = 'LGI' | |
| def __init__(self, **kwargs): | |
| super(LGI, self).__init__(**kwargs) | |
| def apply(self, X): | |
| #M = np.mean(X, axis=1) | |
| #M = M[:, np.newaxis] | |
| #Xzero = X - M # zero mean (row) | |
| U,_,_ = np.linalg.svd(X) | |
| S = U[:,0].reshape(1,-1) # array 2D shape (1,3) | |
| P = np.identity(3) - np.matmul(S.T,S) | |
| Y = np.dot(P,X) | |
| bvp = Y[1,:] | |
| return bvp |