Example 8: Composite Multiscale Cross-[Approximate] EntropyΒΆ

Import two signals of uniformly distributed pseudorandom integers in the range [1 8] and create a multiscale entropy object with the following parameters:

EnType = XApEn(), embedding dimension = 2, time delay = 2, radius distance threshold = 0.5.

X = EH.ExampleData('randintegers2');

Mobj = EH.MSobject('XApEn', m = 2, tau = 2, r = 0.5)

Mobj.Func
>>> <function EntropyHub._XApEn.XApEn(Sig, m=2, tau=1, r=None, Logx=2.71828)>

Mobj.Kwargs
>>> {'m': 2, 'tau': 2, 'r': 0.5}

Calculate the comsposite multiscale cross-approximate entropy over 3 temporal scales where the radius distance threshold value (r) specified by Mobj becomes scaled by the variance of the signal at each scale.

MSx, _ = EH.cXMSEn(X, Mobj, Scales = 3, RadNew = 1)
. . . . . . .

>>> MSx =
    array([1.089, 1.4746, 1.2932])