nimble.calculate.meanNormalize

nimble.calculate.meanNormalize(values1, values2=None)

Subtract the vector mean from each element.

Normalization of values1 is calculated by subtracting the mean of values1 from each element. The mean of values1 is also subtracted from each element in values2, when applicable. This normalization is also known as “Centered” or “Centering”.

Examples

>>> lst1 = [[1], [2], [3], [4], [5]]
>>> X1 = nimble.data(lst1)
>>> meanNormalize(X1)
<Matrix 5pt x 1ft
       0
   ┌───────
 0 │ -2.000
 1 │ -1.000
 2 │  0.000
 3 │  1.000
 4 │  2.000
>
>>> lst2 = [[3], [2], [6]]
>>> X2 = nimble.data(lst2)
>>> norm1, norm2 = meanNormalize(X1, X2)
>>> norm2
<Matrix 3pt x 1ft
       0
   ┌───────
 0 │  0.000
 1 │ -1.000
 2 │  3.000
>