3

I want to slice an array of [x,y] coordinate pairs by x value in Python 3.x, in a similar way to the solution to this question but with coordinates rather than a 1d list.

For example for the (numpy) array of coordinates I want a function like:

coords = np.array([[1.5,10],[2.5,20],[3.5,30],[4.5,40],[5.5,50]])
def slice_coords_by_x(xmin, xmax, arr):
    *some function*
slice_coords_by_x(2, 4, arr)
>>>[[2.5,20],[3.5,30]]

Not overly fussy if the solution is inclusive or exclusive of xmin and xmax since i'll be using this over a large range of over 1000 or so.

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1
  • So you basically want to filter? Is it guaranteed that the x coordinates are ordered? Commented Jan 16, 2017 at 20:36

4 Answers 4

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2

Slice and create a mask with such min-max limits and thus select rows with boolean-indexing -

def slice_coords_by_x(arr, xmin, xmax):
    return arr[(arr[:,0] >= xmin) & (arr[:,0] <= xmax)]

Sample runs -

In [43]: arr
Out[43]: 
array([[  1.5,  10. ],
       [  2.5,  20. ],
       [  3.5,  30. ],
       [  4.5,  40. ],
       [  5.5,  50. ]])

In [44]: slice_coords_by_x(arr, xmin=2, xmax=4)
Out[44]: 
array([[  2.5,  20. ],
       [  3.5,  30. ]])

In [45]: slice_coords_by_x(arr, xmin=1, xmax=5)
Out[45]: 
array([[  1.5,  10. ],
       [  2.5,  20. ],
       [  3.5,  30. ],
       [  4.5,  40. ]])
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1 Comment

Appreciated all the answers thanks all- chose this one purely because it doesn't depend on another package and it retains the numpy array type over Python's own array
2

Without numpy, you could use bisect for this, to find insertion point. Note that the parameter is a list (I was adding None as second parameter as seen in here, but it's not useful).

import bisect

coords = [[1.5,10],[2.5,20],[3.5,30],[4.5,40],[5.5,50]]

def slice_coords_by_x(lower,upper,arr):
    l=bisect.bisect_left(arr,[lower])
    u=bisect.bisect_right(arr,[upper])
    return arr[l:u]

print(slice_coords_by_x(2,4,coords))

result:

[[2.5, 20], [3.5, 30]]

bisect requires that the list is sorted (which seems to be the case) or that won't work.

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7 Comments

Can't you simply use [lower] instead of [lower,None]? At least for bisect_left?
nope: TypeError: unorderable types: list() < int()
but [lower] is still a list.
given I query bisect.bisect_left(arr,[2.5,None]), I get TypeError: unorderable types: int() < NoneType()... With arr the one defined above.
Funny. So the answer I linked to telling to put None is just wrong. Wait: it must be python 2 only, as you were able to compare strings with ints, etc... not anymore in python 3.
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2

Unordered

If the given list of points are unordered, you can use a filter, and materialize with list:

def slice_coords_by_x(xmin,xmax,arr):
    return list(filter(lambda p: xmin < p[0] < xmax,arr))

You can evidently feed your sorted list to this as well, but it will take considerably more time than the next approach.

Sorted list

Given the points are sorted by x-coordinate, you can use the bisect package:

def slice_coords_by_x(xmin,xmax,arr):
    left = bisect.bisect_left(arr,[xmin])
    right = bisect.bisect_right(arr,[xmax])
    return arr[left:right]
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Comments

2

Shouldn't simply

def slice_coords_by_x(xmin, xmax, arr):
    return [i for i in arr if xmin <= i[0] and i[0] <= xmax]

do the trick? It's readable, fast and accessible.

This list can be sorted or even pass an array, but the approach should be accessible enough to be changed to any needs.

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6 Comments

if xmin <= i[0] and i[0] <= xmax => if xmin <= i[0] <= xmax is even better. Willem answer already covers that, though.
if xmin <= i[0] and i[0] <= xmax and if xmin <= i[0] <= xmax are actually one and the same thing.
probably, but the latter is more "pythonic".
Also I am not sure, that Willems answer is any kind of superior to mine. So why shouldn't I write a way easier to read and understand? PS.: I wrote the answer before Willem, I actually typed it as a comment before, deleted it, reformated it and saved it and I didn't saw Willems answer before.
You have to be more aggressive when answering ;)
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