How to get a numpy array from multiple lists of the same length and sort along the axis?
I have a very simple question: how to get a numpy array from multiple lists of the same length and sort along the axis?
I'm looking for something like:
a = [1,1,2,3,4,5,6] b = [10,10,11,09,22,20,20] c = [100,100,111,090,220,200,200] d = np.asarray(a,b,c) print d >>>[[1,10,100],[1,10,100],[2,11,111].........[6,20,200]]
2nd question: And if this can be achieved, can I sort it along the axis (e.g. for List b values)?
3rd question: Can sorting be done on a range? eg. for values between b + 10 and b-10 when traversing list c for further sorting. as
[[1,11,111][1,10,122][1,09,126][1,11,154][1,11,191]
[1,20,110][1,25,122][1,21,154][1,21,155][1,21,184]]
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You can zip the array:
a = [1, 1, 2, 3, 4, 5, 6]
b = [10, 10, 11, 9, 22, 20, 20]
c = [100, 100, 111, 90, 220, 200, 200]
d = np.asarray(zip(a,b,c))
print(d)
[[ 1 10 100]
[ 1 10 100]
[ 2 11 111]
[ 3 9 90]
[ 4 22 220]
[ 5 20 200]
[ 6 20 200]]
print(d[np.argsort(d[:, 1])]) # a sorted copy
[[ 3 9 90]
[ 1 10 100]
[ 1 10 100]
[ 2 11 111]
[ 5 20 200]
[ 6 20 200]
[ 4 22 220]]
I don't know how you would do the inplace sort without doing something like:
d = np.asarray(zip(a,b,c))
d.dtype = [("0", int), ("1", int), ("2", int)]
d.shape = d.size
d.sort(order="1")
The presenter 0
will do octal 090
in python2 or invalid syntax in python3 so that I remove it.
You can also sort the zipped items before passing:
from operator import itemgetter
zipped = sorted(zip(a,b,c),key=itemgetter(1))
d = np.asarray(zipped)
print(d)
[[ 3 9 90]
[ 1 10 100]
[ 1 10 100]
[ 2 11 111]
[ 5 20 200]
[ 6 20 200]
[ 4 22 220]]
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You can use np.dstack
and np.lexsort
. for example if you want to sort based on an array b
(second axis) then then a
and then c
:
>>> d=np.dstack((a,b,c))[0]
>>> indices=np.lexsort((d[:,1],d[:,0],d[:,2]))
>>> d[indices]
array([[ 3, 9, 90],
[ 1, 10, 100],
[ 1, 10, 100],
[ 2, 11, 111],
[ 5, 20, 200],
[ 6, 20, 200],
[ 4, 22, 220]])
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