用对数分块法去除噪声

Question

我感兴趣的是绘制一组点的概率分布，这些点是按幂律分布的。此外，我想使用对数装箱能够平滑大波动，特别是那些在尾部观察到的波动。我做了密码：

plt.figure()
plt.grid(True)
plt.loglog(x, y, 'bo')
plt.savefig('distribution.png', dpi=400)
plt.show()
plt.close()

其中x和y是包含数据的列表。我知道我应该用numpy.logspace，但我不知道怎么做

我附上图表的列表和图像：

图形：1

x=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 
20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 
38, 39, 40, 41, 44, 45, 46, 48, 50, 53, 54, 55, 56, 57, 58, 59, 63, 64, 
66, 71, 72, 73, 76, 79, 81, 84, 85, 86, 90, 95, 97, 99, 100, 101, 103, 
105, 114, 117, 118, 120, 122, 129, 141, 159, 166, 168, 172, 199, 201, 
206, 218, 226, 243, 260, 262, 263, 265, 273, 274, 278, 281, 292, 300, 
390, 404, 420, 443, 491, 849, 939, 1036, 1156, 1191, 1389, 1551, 1742, 
2082]

y=[0.0, 0.3508771929824561, 0.4259259259259261, 0.4400278940027895, 
0.439337474120083, 0.43933333333333335, 0.4165445665445665, 
0.4361247947454843, 0.4325877825877826, 0.4820728291316526, 
0.42828042328042315, 0.35761299632267374, 0.3491461529923068, 
0.4079423222280365, 0.43694194694194693, 0.34069215098626865, 
0.3449795896319961, 0.3633688071188071, 0.30852671293847767, 
0.4242381075714409, 0.20068791049183207, 0.24466260863319686, 
0.12237645395540135, 0.37624875124875123, 0.28918557997841887, 
0.25374977395437753, 0.4761346678013344, 0.41219336219336217, 
0.19267411510058569, 0.30895915678524377, 0.18104998922645982, 
0.2407892107892108, 0.23937740965604742, 0.3727204759813455, 
0.23712669683257917, 0.2567023619655199, 0.33474793703626654, 
0.3520767731294047, 0.2475947884643537, 0.3738888888888889, 
0.5274725274725275, 0.33489003749873314, 0.18518518518518517, 
0.15181358496575886, 0.3152953084067635, 0.17919413919413918, 
0.20858299108299105, 0.21746880570409982, 0.1915602105707053, 
0.2972972972972973, 0.18115942028985507, 0.25, 0.32707722385141735, 
0.33894302848575714, 0.21774193548387097, 0.34782608695652173, 
0.27608756290137165, 0.17296320127462694, 0.2727272727272727, 
0.2879728132387707, 0.06535947712418301, 0.083710407239819, 
0.28118393234672306, 0.1951219512195122, 0.09254361251031618, 
0.3062211259885678, 0.002663622526636225, 0.27311522048364156, 
0.0506558118498417, 0.1044776119402985, 0.06284153005464481, 
0.18588399720475193, 0.2129032258064516, 0.14903846153846154, 
0.021532091097308487, 0.3089430894308943, 0.301010101010101, 
0.3761904761904762, 0.10466269841269842, 0.07138047138047138, 
0.21709633649932158, 0.019401589527816735, 0.017575757575757574, 
0.15817805383022773, 0.025306629405371837, 0.20850040096230954, 
0.0001638001638001638, 0.04357084357084357, 0.09221213569039656, 
0.14047410008779632, 0.002560163850486431, 0.0031680440771349864, 
0.12334152334152335, 0.6428571428571429, 0.012745098039215686, 
0.0058073399287151255, 0.0012413644214162348, 0.013532269257460098, 
0.04368752313957793, 0.20265151515151514, 0.0018470281790196543, 
0.023099982366425676, 0.03265807243707796, 0.00695970695970696, 
0.003737745098039216, 0.009634076615208691, 0.024085079762277136, 
0.0062196422224854876, 0.030849549121974372, 0.01636020744931636, 
0.003922512815882666, 0.005677708965459911, 0.04833570605382686, 
0.014331723027375202]