If I have a numpy array with objects such as the following:
array(['Ana', 'Charlie', 'Andrew'], dtype=object)
And I want to map each object to all objects in the array so I obtain the following output:
array(['Ana', 'Ana'],['Ana','Charlie'],['Ana', 'Andrew'],
['Charlie','ana'], ['Charlie','Charlie'],['Charlie','Andrew'], ['Andrew','ana'],['Andrew', 'Charlie'], ['Andrew','Andrew'], dtype=object).
how can I use numpy to map each object to all objects in the same array?
Thanks so much.
You are searching for the cartesian product of the two arrays.
numpy.transpose() should do the trick:
x = array(['Ana', 'Charlie', 'Andrew'], dtype=object)
numpy.transpose([numpy.tile(x, len(x)), numpy.repeat(x, len(x))])
Python lists are generally more suited when dealing with strings. Looks like you want the cartesian product:
from itertools import product
l = ['Ana', 'Charlie', 'Andrew']
list(map(list, product(l,l)))
[['Ana', 'Ana'],
['Ana', 'Charlie'],
['Ana', 'Andrew'],
['Charlie', 'Ana'],
['Charlie', 'Charlie'],
['Charlie', 'Andrew'],
['Andrew', 'Ana'],
['Andrew', 'Charlie'],
['Andrew', 'Andrew']]
The following code taking advantage of list comprehension should work fine.
import numpy as np
a=np.array(['Ana', 'Charlie', 'Andrew'], dtype=object)
b=np.array([[i,j] for i in a for j in a], dtype=object)
