I have a NumPy array:
[[ 0. 1. 2. 3. 4.]
[ 7. 8. 9. 10. 4.]
[ 14. 15. 16. 17. 4.]
[ 1. 20. 21. 22. 23.]
[ 27. 28. 1. 20. 29.]]
which I want to quickly find the coordinates of specific values and avoid Python loops on the array. For example the number 4 is on:
row 0 and col 4
row 1 and col 4
row 2 and col 4
and a search function should return a tuple:
((0,4),(1,4),(2,4))
Can this be done directly via NunmPy's functions?
If a is your array, then you could use:
ii = np.nonzero(a == 4)
or
ii = np.where(a == 4)
If you really want a tuple, you can convert from the tuple of arrays to the tuple of tuples, but the return value from the numpy functions is convient for then doing other operations on your array.
Conversion to a tuple for the OP's specification:
tuple(zip(*ii))
a = numpy.array([[ 0., 1., 2., 3., 4.],
[ 7., 8., 9., 10., 4.],
[ 14., 15., 16., 17., 4.],
[ 1., 20., 21., 22., 23.],
[ 27., 28., 1., 20., 29.]])
print numpy.argwhere(a == 4.)
prints
[[0 4]
[1 4]
[2 4]]
The usual caveats for floating point comparisons apply.
np.argwhere is not suitable for indexing arrays. For this purpose use np.where(a) instead."
.where