Partial Covariance

pcov.py

def pcov(data, I=None, corrcoef=False, rowvar=True):
    '''
    Partial covariance
    
    Stephan Kuschel, 2019
    https://gist.github.com/skuschel/9cd745c4b47ad579481b1ade6115250a
    '''
    import numpy as np
    if I is None:
        I = np.mean(data, axis=0 if rowvar else 1)
    I = np.atleast_2d(I)
    c = np.cov(data, I, rowvar=rowvar)
    cov = c[:-1, :-1]
    ret = cov - np.outer(c[-1, :-1], c[:-1, -1]) / c[-1,-1]
    if corrcoef:
        s = np.sqrt(np.diag(ret))
        ret /= np.outer(s,s)
    return ret