Just comparing the different ways.
Results:
> Shuffle cost comparison smallshuffle_lst: 0.001181483967229724shuffle_ar: 0.014688121969811618> Shuffle cost comparison mediumshuffle_lst: 0.572294642101042shuffle_ar: 0.3266364939045161> Shuffle cost comparison largeshuffle_lst: 26.5786890439922shuffle_ar: 6.284286553971469+cost -costbisectme: 0.004252934013493359 0.003071450046263635lexicon: 0.010936842067167163 0.009755358099937439compreh.: 0.0071560649666935205 0.005974580999463797arrayme: 0.03787591797299683 0.023187796003185213nplexicon: 0.022204622975550592 0.007516501005738974npbisect: 0.023507782025262713 0.008819660055451095+cost -costbisectme: 7.716002315981314 7.143707673880272lexicon: 22.17862514301669 21.606330500915647compreh.: 8.690494343056343 8.118199700955302arrayme: 1.5029839979251847 1.1763475040206686nplexicon: 2.0811527019832283 1.7545162080787122npbisect: 1.3076487149810418 0.9810122210765257+cost -costbisectme: 180.77819497592282 154.19950593193062arrayme: 22.476932613993995 16.192646060022525nplexicon: 41.74795828794595 35.46367173397448npbisect: 20.13856932707131 13.85428277309984Code:
import sysimport numpy as npfrom timeit import timeitfrom bisect import bisectfrom random import shuffledef shuffle_lst(): np.random.shuffle(lst)def shuffle_ar(): np.random.shuffle(ar)def bisectme(): np.random.shuffle(lst) lst.sort() i = bisect(lst, 0) return lst[i:] + lst[:i]def lexicon(): np.random.shuffle(lst) return sorted(lst, key=lambda x: (x < 0, x))def comprehension(): np.random.shuffle(lst) return sorted([i for i in lst if i > 0]) + sorted([i for i in lst if i < 0])def arrayme(): np.random.shuffle(ar) return np.concatenate([np.sort(ar[ar >= 0]), np.sort(ar[ar < 0])], axis=0)def nplexicon(): np.random.shuffle(ar) return ar[np.lexsort((ar, ar < 0))]def numpybisect(): np.random.shuffle(ar) ar.sort() i = ar.__abs__().argmin() return np.concatenate((ar[i:], ar[:i]))nloops = 1000lst = list(range(-10**1, 0, 1)) + list(range(10**1, -1, -1))ar = np.array(lst)print("> Shuffle cost comparison small")cost_shuffle_list_small = timeit(shuffle_lst, number=nloops)print("shuffle_lst:", cost_shuffle_list_small)cost_shuffle_array_small = timeit(shuffle_ar, number=nloops)print("shuffle_ar:", cost_shuffle_array_small)lst = list(range(-10**4, 0, 1)) + list(range(10**4, -1, -1))ar = np.array(lst)print("> Shuffle cost comparison medium")cost_shuffle_list_medium = timeit(shuffle_lst, number=nloops)print("shuffle_lst:", cost_shuffle_list_medium)cost_shuffle_array_medium = timeit(shuffle_ar, number=nloops)print("shuffle_ar:", cost_shuffle_array_medium)nloops = 100lst = list(range(-10**6, 0, 1)) + list(range(10**6, -1, -1))ar = np.array(lst)print("> Shuffle cost comparison large")cost_shuffle_list_large = timeit(shuffle_lst, number=nloops)print("shuffle_lst:", cost_shuffle_list_large)cost_shuffle_array_large = timeit(shuffle_ar, number=nloops)print("shuffle_ar:", cost_shuffle_array_large)print()nloops = 1000## With small lists/arrayslst = list(range(-10**1, 0, 1)) + list(range(10**1, -1, -1))ar = np.array(lst)print("\t\t\t\t\tw/o pen.\t\t\t\tw. pen.")foo = timeit(bisectme, number=nloops)print("bisectme:\t", foo, "\t", foo - cost_shuffle_list_small)foo = timeit(lexicon, number=nloops)print("lexicon:\t", foo, "\t", foo - cost_shuffle_list_small)foo = timeit(comprehension, number=nloops)print("compreh.:\t", foo, "\t", foo - cost_shuffle_list_small)foo = timeit(arrayme, number=nloops)print("arrayme:\t", foo, "\t", foo - cost_shuffle_array_small)foo = timeit(nplexicon, number=nloops)print("nplexicon:\t", foo, "\t", foo - cost_shuffle_array_small)foo = timeit(numpybisect, number=nloops)print("npbisect:\t", foo, "\t", foo - cost_shuffle_array_small)print()## With medium lists/arrayslst = list(range(-10**4, 0, 1)) + list(range(10**4, -1, -1))ar = np.array(lst)print("\t\t\t\t\tw/o cost\t\t\t\tw. cost")foo = timeit(bisectme, number=nloops)print("bisectme:\t", foo, "\t", foo - cost_shuffle_list_medium)foo = timeit(lexicon, number=nloops)print("lexicon:\t", foo, "\t", foo - cost_shuffle_list_medium)foo = timeit(comprehension, number=nloops)print("compreh.:\t", foo, "\t", foo - cost_shuffle_list_medium)foo = timeit(arrayme, number=nloops)print("arrayme:\t", foo, "\t", foo - cost_shuffle_array_medium)foo = timeit(nplexicon, number=nloops)print("nplexicon:\t", foo, "\t", foo - cost_shuffle_array_medium)foo = timeit(numpybisect, number=nloops)print("npbisect:\t", foo, "\t", foo - cost_shuffle_array_medium)print()## With large lists/arraysnloops = 100lst = list(range(-10**6, 0, 1)) + list(range(10**6, -1, -1))ar = np.array(lst)print("\t\t\t\t\tw/o cost\t\t\t\tw. cost")foo = timeit(bisectme, number=nloops)print("bisectme:\t", foo, "\t", foo - cost_shuffle_list_large)foo = timeit(arrayme, number=nloops)print("arrayme:\t", foo, "\t", foo - cost_shuffle_array_large)foo = timeit(nplexicon, number=nloops)print("nplexicon:\t", foo, "\t", foo - cost_shuffle_array_large)foo = timeit(numpybisect, number=nloops)print("npbisect:\t", foo, "\t", foo - cost_shuffle_array_large)print()