scale correlate

utils.py

def scale(X):
    m = X.mean(0, keepdims=True)
    s = X.std(0, keepdims=True)
    s[s == 0] = 1  # avoid nan
    X -= m
    X /= s
    return X


def correlate(X, Y):
    if X.ndim == 1:
        X = X[:, None]
    if Y.ndim == 1:
        Y = Y[:, None]
    out = np.zeros(max([Y.shape[1], X.shape[1]]))
    X = X - X.mean(0)
    Y = Y - Y.mean(0)

    SX2 = (X ** 2).sum(0) ** 0.5
    SY2 = (Y ** 2).sum(0) ** 0.5
    SXY = (X * Y).sum(0)
    valid = (SX2 != 0) & (SY2 != 0)
    out[valid] = SXY[valid] / (SX2[valid] * SY2[valid])
    return out