CODEWITHSUNDEEP
pythonlistnumpyunique
Pavel Pereverzev
Pavel Pereverzev

Reputation: 499

Finding ONLY Unique Coordinates in List

I have a list of coordinates like

list_cor = 
    [[4190091.4195999987, 7410226.618699998], 
    [4190033.2124999985, 7410220.0823], 
    [4190033.2124999985, 7410220.0823], 
    [4190035.7005000003, 7410208.670500003], 
    [4190033.2124999985, 7410220.0823], 
    [4190022.768599998, 7410217.844300002]]

I need to get only these values:

[[4190091.4195999987, 7410226.618699998], 
[4190035.7005000003, 7410208.670500003], 
[4190022.768599998, 7410217.844300002]]

Tried numpy.unique() but it adds this item [4190033.2124999985, 7410220.0823], which I don't need.

Upvotes: 7

Views: 10063

Answers (5)

Radhey
Radhey

Reputation: 81

Use numpy.unique with axis and return_counts parameters:

arr, uniq_cnt = np.unique(list_cor, axis=0, return_counts=True)
uniq_arr = arr[uniq_cnt==1]

Upvotes: 8

tobias_k
tobias_k

Reputation: 82949

For older version of numpy that don't have the return_counts parameter, you could help yourself with collections.Counter:

>>> list_cor = np.array(list_cor)  # assuming list_cor is a numpy array
>>> counts = collections.Counter(map(tuple, list_cor))
>>> counts_arr = np.array([counts[tuple(x)] for x in list_cor])
>>> list_cor[counts_arr == 1]
array([[ 4190091.4196,  7410226.6187],
       [ 4190035.7005,  7410208.6705],
       [ 4190022.7686,  7410217.8443]])

Upvotes: 1

00__00__00
00__00__00

Reputation: 5367

In simple pure python basic types:

# transform to tuples
list_cor=[tuple(c) for c in list_cor]
# transform back after using set to select unique elements only
list_cor_unique=[list(l) for l in list(set(list_cor))]
# create a copy
list_cor_more_than_once = [i for i in list_cor]
# drop all the elements appearing only once
[list_cor_more_than_once.remove(tuple(l)) for l in list_cor_unique if tuple(l) in list_cor]
# finally, keep the uniques not appearing more than once
list_cor_unique=[l for l in list_cor_unique if (tuple(l) in list_cor) and (not (tuple(l) in list_cor_more_than_once)) ]

Pros:

  • no external libraries

  • would work for higher dimension coordinates

Upvotes: 1

Brett Beatty
Brett Beatty

Reputation: 6003

I like using a dictionary to keep track of counts:

>>> counts = {}
>>> for coordinate in list_cor:
...     coordinate = tuple(coordinate) # so it can be hashed and used as dict key
...     counts.setdefault(coordinate, 0) # add coordinate to dict
...     counts[coordinate] += 1 # increment count for coordinate
...

You then have a dictionary that looks like this:

>>> counts
{(4190091.4195999987, 7410226.618699998): 1, (4190033.2124999985, 7410220.0823): 3, (4190035.7005000003, 7410208.670500003): 1, (4190022.768599998, 7410217.844300002): 1}

You can then use list comprehension to create a list of unique coordinates:

>>> [list(coordinate) for coordinate, count in counts.items() if count == 1]
[[4190091.4195999987, 7410226.618699998], [4190035.7005000003, 7410208.670500003], [4190022.768599998, 7410217.844300002]]

If you're fine leaving the coordinates as tuples, you can replace list(coordinate) with coordinate.

Upvotes: 1

B. M.
B. M.

Reputation: 18668

You're almost there : 

coords=[ x+1j*y for (x,y) in list_cor] # using complex; a way for grouping
uniques,counts=np.unique(coords,return_counts=True)
res=[ [x.real,x.imag] for x in uniques[counts==1] ] # ungroup

For :

[[4190022.7685999982, 7410217.8443000019],
 [4190035.7005000003, 7410208.6705000028],
 [4190091.4195999987, 7410226.6186999977]]

Upvotes: 2

Related Questions