numpy：在排序列表中，找到每个唯一值的第一个和最后一个索引

Question

Having a sorted list, how can anyone find (using numpy) the first and the last index for each unique value?

Example:

Initial sorted list:

>>> import numpy as np
>>> initial_list = np.array([1, 3, 2, 3, 0, 3, 0, 1, 0])
>>> initial_list.sort()

>>> initial_list
array([0, 0, 0, 1, 1, 2, 3, 3, 3])

The result of this would be:

first: [ 0, 0, 0, 3, 3, 5, 6, 6, 6 ]

last: [ 2, 2, 2, 4, 4, 5, 8, 8, 8 ]

Thank you in advance

Answer 1

Here's one approach leveraging the sorted nature of input data, making use of the very efficient NumPy array-slicing and other NumPy functions -

def start_stop_arr(initial_list):
    a = np.asarray(initial_list)
    mask = np.concatenate(([True], a[1:] != a[:-1], [True]))
    idx = np.flatnonzero(mask)
    l = np.diff(idx)
    start = np.repeat(idx[:-1], l)
    stop = np.repeat(idx[1:]-1, l)
    return start, stop

Further performance boost is possible with concatenated repetitions -

def start_stop_arr_concat_repeat(initial_list):
    a = np.asarray(initial_list)
    mask = np.concatenate(([True], a[1:] != a[:-1], [True]))
    idx = np.flatnonzero(mask)
    l = np.diff(idx)
    idx2 = np.concatenate((idx[:-1,None], (idx[1:,None]-1)),axis=1)
    ss = np.repeat(idx2, l, axis=0)
    return ss[:,0], ss[:,1]

Sample run -

In [38]: initial_list
Out[38]: array([0, 0, 0, 1, 1, 2, 3, 3, 3])

In [39]: start_stop_arr(initial_list)
Out[39]: (array([0, 0, 0, 3, 3, 5, 6, 6, 6]), array([2, 2, 2, 4, 4, 5, 8, 8, 8]))

Runtime test -

Other approach(es) -

# @Mohammed Elmahgiubi's soln
def reversed_app(initial_list): # input expected is a list
    reversed_initial_list = list(reversed(initial_list))
    first = [initial_list.index(i) for i in initial_list]
    last = list(reversed([(len(initial_list) - 
                           (reversed_initial_list.index(i) + 1)) 
                            for i in reversed_initial_list]))
    return first, last

def unique_app(a): # @B. M.'s soln
    _,ind1,inv1,cou1 = np.unique(a, return_index=True, return_inverse=True, 
                                 return_counts=True)
    return ind1[inv1],(ind1+cou1-1)[inv1]

Timings -

Case #1 : Smaller dataset

In [295]: initial_list = np.random.randint(0,1000,(10000))
     ...: initial_list.sort()

In [296]: input_list = initial_list.tolist()

In [297]: %timeit reversed_app(input_list)
1 loop, best of 3: 789 ms per loop

In [298]: %timeit unique_app(initial_list)
1000 loops, best of 3: 353 µs per loop

In [299]: %timeit start_stop_arr(initial_list)
10000 loops, best of 3: 96.3 µs per loop

Case #2 : Bigger dataset

In [438]: initial_list = np.random.randint(0,100000,(1000000))
     ...: initial_list.sort()

In [439]: %timeit unique_app(initial_list) # @B. M.'s soln
10 loops, best of 3: 53 ms per loop

In [440]: %timeit start_stop_arr(initial_list)
100 loops, best of 3: 9.64 ms per loop

In [441]: %timeit start_stop_arr_concat_repeat(initial_list)
100 loops, best of 3: 6.76 ms per loop

Answer 2

This is my approach:

initial_list = [0, 0, 0, 1, 1, 2, 3, 3, 3]
reversed_initial_list = list(reversed(initial_list))

first = [initial_list.index(i) for i in initial_list]
last = list(reversed([(len(initial_list) - (reversed_initial_list.index(i) + 1)) for i in reversed_initial_list]))

print("initial_list = {}\nfirst = {}\nlast = {}".format(initial_list, first, last))

results in :

initial_list = [0, 0, 0, 1, 1, 2, 3, 3, 3]
first = [0, 0, 0, 3, 3, 5, 6, 6, 6]
last = [2, 2, 2, 4, 4, 5, 8, 8, 8]

Answer 3

first = [np.min(np.where(initial_list==i)) for i in initial_list]
last = [np.max(np.where(initial_list==i)) for i in initial_list]

reference: Is there a Numpy function to return the first index of something in an array?

Answer 4

numpy.unique computes all the useful values for that :

a=np.array([0, 0, 0, 1, 1, 2, 3, 3, 3])
_,ind1,inv1,cou1 = np.unique(a, return_index=True, return_inverse=True, return_counts=True)

print(ind1[inv1],(ind1+cou1-1)[inv1])

#[0 0 0 3 3 5 6 6 6] [2 2 2 4 4 5 8 8 8]