Python equivalent to R poly() function?

Question

I\'m trying to understand how to replicate the poly() function in R using scikit-learn (or other module).

For example, let\'s say I have a vector in R:

a         


        

Answer 1

The answer by K. A. Buhr is full and complete.

The R poly function also calculates interactions of different degrees of the members. That's why I was looking for the R poly equivalent.
sklearn.preprocessing.PolynomialFeatures Seems to provide such, you can do the np.linalg.qr(X)[0][:,1:] step after to get the orthogonal matrix.

Something like this:

import numpy as np
import pprint
import sklearn.preprocessing
PP = pprint.PrettyPrinter(indent=4)

MATRIX = np.array([[ 4,  2],[ 2,  3],[ 7,  4]])
poly = sklearn.preprocessing.PolynomialFeatures(2)
PP.pprint(MATRIX)
X = poly.fit_transform(MATRIX)
PP.pprint(X)

Results in:

array([[4, 2],
       [2, 3],
       [7, 4]])
array([[ 1.,  4.,  2., 16.,  8.,  4.],
       [ 1.,  2.,  3.,  4.,  6.,  9.],
       [ 1.,  7.,  4., 49., 28., 16.]])