'''
Created on Dec 2, 2017

@author: bob
'''
import numpy as np
A= np.arange(36)
print("original shape and array from arange\n",A.shape,"\n",A)
A=A.reshape((4,3,3))
print("\n\n reshaped from arange \n",A.shape,"\n",A)
B=A.reshape((-1,9))
print("\n\n new shape",B.shape ,"\narray \n",B)

C=np.arange(4)
print("original shape of label and array from arange\n",C.shape,"\n",C)
D=np.array([0,3,2,1,0,3,2,3,1,0,2,1,0])
print("original shape and array from arange\n",D.shape,"\n",D)
DR= D[:,None]
print("\n Use of None on array\n",DR.shape,"\n",DR)
OneHot= C==DR
print("\n one hot encoding before change to 0,1\n",OneHot)
# note what happens is that the DR array is expanded in the dimension (last ) that is 1 to match the 4 that is in C and then logical comparison is made )
print("\n one hot encoding \n",OneHot.astype(np.float32))