Reputation: 26039
I have a list of tuples like this:
listOfTuples = [(0, 1), (0, 2), (3, 1)]
and an array that could look like this:
myArray = np.array([-2, 9, 5])
Furthermore, I have an array with Boolean expressions which I created like this:
dummyArray = np.array([0, 1, 0.6])
myBooleanArray = dummyArray < 1
myBooleanArray
therefore looks like this:
array([True, False, True], dtype=bool)
Now I would like to extract values from listOfTuples
and myArray
based on myBooleanArray
. For myArray
it is straight forward and I can just use:
myArray[myBooleanArray]
which gives me the desired output
[-2 5]
However, when I use
listOfTuples[myBooleanArray]
I receive
TypeError: only integer arrays with one element can be converted to an index
A workaround would be to convert this list to an array first by doing:
np.array(listOfTuples)[myBooleanArray]
which yields
[[0 1]
[3 1]]
Is there any smarter way of doing this? My desired output would be
[(0, 1), (3, 1)]
Upvotes: 6
Views: 3629
Reputation: 107347
Python list object, unlike Numpy array, doesn't support boolean indexing directly. For that you could use itertools.compress
function:
>>> from itertools import compress
>>> list(compress(listOfTuples,bool_array))
[(0, 1), (3, 1)]
Note that one of the advantages of compress
along side its functional structure which can be very useful in many cases, is that it returns a generator and its very memory efficient in cases where you have a very large list object to filter.
If you want you can also to loop over the result if you wish to process the items one by one instead of converting the whole object to a list:
for item in compress(listOfTuples,bool_array):
#do stuff
Upvotes: 7
Reputation: 5347
The answer by Kasra is the best this is just an alternate
In [30]: [i[0] for i in list(zip(listOfTuples,bools)) if i[1] == True ]
Out[30]: [(0, 1), (3, 1)]
Upvotes: 2