I am new to numpy and I am trying to avoid for-loops. My requirement is as below:
Input - decimal value (ex. 3)
Output - Binary numpy array ( = 00000 01000)
Another example :
Input = 6
Output = 00010 00000
Note: I do not want the binary representation of 3. I only need the index value of array = integer to be set.
Is there any standard library function in numpy? Something analogous to get_dummies function in pandas module.
Try this instead. This doesn't use any for loops and if you add some sanity checks it should work fine.
def oneOfK(label):
rows = label.shape[0];
rowsIndex=np.arange(rows,dtype="int")
oneKLabel = np.zeros((rows,10))
#oneKLabel = np.zeros((rows,np.max(label)+1))
oneKLabel[rowsIndex,label.astype(int)]=1
return oneKLabel
Are you looking for a standard function that does something like:
import numpy as np
def foo(d, len=10):
a = np.zeros(len)
a[len-d-1] = 1
return a
print foo(3) # [ 0. 0. 0. 0. 0. 0. 1. 0. 0. 0.]
print foo(6) # [ 0. 0. 0. 1. 0. 0. 0. 0. 0. 0.]
This is more of a comment with code than an answer. Just trying to be clear about what you're looking for, because I'm not sure this function exists as you specify.
np.zeros(len, dtype='bool'), this will give a boolean array.