Defined a 1d array (or a 1d slice of a bigger array), like:
a=np.array([ 5, 12, 13])
if there some higher dimension array, like:
c1=np.array([[1, 2, 3], [ 5, 12, 13], [7, 8, 9]])
c2=np.array([[1, 2, 3], [ 5, 6, 7], [7, 8, 9]])
It turns out to be:
a in c1, a in c2
(True, True)
I would like that only the first condition, where a is consecutively contained as sub-array to be True. While a in c2 would give False.
Is there any function taking care of that?
You can use .tolist() and then call the functions normally:
>>> a=np.array([ 5, 12, 13])
>>> c1=np.array([[1, 2, 3], [ 5, 12, 13], [7, 8, 9]])
>>> c2=np.array([[1, 2, 3], [ 5, 6, 7], [7, 8, 9]])
>>> a.tolist() in c1.tolist(), a.tolist() in c2.tolist()
(True, False)
>>>
I think, this is what you want:
import numpy as np
a=np.array([ 5, 12, 13])
c1=np.array([[1, 2, 3], [5,12,13], [7, 8, 9]])
c2=np.array([[1, 2, 3], [5,6,7], [7, 8, 9]])
print any((a == x).all() for x in c1)
print any((a == x).all() for x in c2)
It outputs:
True
False
Edit: as moarningsun suggested, here a better version:
import numpy as np
a=np.array([ 5, 12, 13])
c1=np.array([[1, 2, 3], [5,12,13], [7, 8, 9]])
c2=np.array([[1, 2, 3], [5,6,7], [7, 8, 9]])
print np.any((a == c1).all(axis=1))
print np.any((a == c2).all(axis=1))
Truenot just accidentally true? If you change a toa=np.array([ 5, 12, 13])the output is(True, False)and should be(False, False).a in c1.T?