I need to find if a numpy array is inside other numpy array, but it seems to work different to python lists. I tried to search this question in numpy documentation and internet, but not answer. This is an example:
import numpy as np
m1=np.array([[1,2,3],[5,3,4]])
m2=np.array([5,4,3])
m2 in m1
True
m3=[[1,2,3],[5,3,4]]
m4=[5,4,3]
m4 in m3
False
In numpy I obtain True but with Python lists I obtain False. Is there any numpy function to make this work?
Thanks.
To get the same behavior as in for lists, you could do something like this:
any(np.all(row == m2) for row in m1)
That does the loop over rows in python, which isn't ideal, but it should work.
To understand what's going on with the numpy in, here's a description of the semantics of in from Robert Kern on the numpy mailing list:
It dates back to Numeric's semantics for bool(some_array), which would be True if any of the elements were nonzero. Just like any other iterable container in Python,
x in ywill essentially dofor row in y: if x == row: return True return FalseIterate along the first axis of y and compare by boolean equality. In Numeric/numpy's case, this comparison is broadcasted. So that's why [3,6,4] works, because there is one row where 3 is in the first column. [4,2,345] doesn't work because the 4 and the 2 are not in those columns.
Probably, this should be considered a mistake during the transition to numpy's semantics of having bool(some_array) raise an exception.
scalar in arrayshould probably work as-is for an ND array, but there are several different possible semantics forarray in arraythat should be explicitly spelled out, much like bool(some_array).
m3 = [[1, 2, 3], [5, 4, 3]]in place ofm3 = [[1, 2, 3], [5, 3, 4]].