01 擬似乱数 - 数理生物学演習

擬似乱数¶

# 01-01. 擬似乱数列の生成
import random

for i in range(100):
    r = random.randrange(1, 1001)
    print(r)

シード¶

同じシード (seed)を与えると同じ乱数列が再現され，シミュレーションの再現性を確保できる．

# 01-02. シード
random.seed(1)
for i in range(100):
    r = random.randrange(1, 1001)
    print(r)

乱数生成：シーケンス¶

# 01-03. シーケンス操作 choice, choices
a_list = [23, 22, 32, 12, 31, 30, 3, 35, 26, 36]

# choice
print("# random.choice")
for i in range(30):
    r = random.choice(a_list)
    print(r)

# choices
weights = [0, 1, 1, 1, 1, 1, 1, 1, 1, 10]
print("# random.choices")
for i in range(30):
    r = random.choices(a_list, weights=weights, k=5)
    print(r)

# random.choice
31
36
35
26
3
36
23
35
12
3
3
32
30
26
30
22
35
26
22
32
26
3
30
35
23
35
23
31
36
36
# random.choices
[36, 36, 31, 30, 22]
[31, 36, 36, 26, 35]
[36, 35, 36, 36, 36]
[36, 35, 36, 36, 36]
[36, 12, 36, 31, 36]
[36, 35, 36, 36, 26]
[36, 26, 22, 36, 36]
[3, 36, 36, 36, 36]
[31, 32, 36, 36, 36]
[22, 36, 32, 36, 36]
[36, 3, 30, 36, 31]
[3, 31, 30, 36, 36]
[36, 3, 36, 36, 12]
[3, 35, 36, 30, 30]
[36, 36, 36, 26, 36]
[30, 26, 22, 36, 36]
[36, 26, 36, 36, 36]
[36, 36, 36, 22, 36]
[36, 36, 26, 36, 12]
[31, 22, 32, 32, 36]
[3, 12, 36, 12, 36]
[36, 36, 31, 36, 36]
[36, 36, 36, 36, 22]
[31, 32, 36, 36, 36]
[36, 36, 26, 36, 22]
[36, 26, 3, 12, 36]
[36, 36, 12, 26, 30]
[32, 35, 36, 36, 36]
[36, 36, 36, 32, 22]
[12, 12, 36, 30, 3]

# 01-04. シーケンス操作 sample
a_list = [23, 22, 32, 12, 31, 30, 3, 35, 26, 36]

# sample
print("# random.sample")
for i in range(30):
    r = random.sample(a_list, k=5)
    print(r)

# シャッフル
print("# random.sample シャッフル")
for i in range(30):
    r = random.sample(a_list, k=len(a_list))
    print(r)

# random.sample
[26, 31, 30, 32, 3]
[22, 31, 12, 3, 26]
[35, 32, 22, 26, 23]
[3, 22, 36, 35, 26]
[32, 30, 22, 31, 3]
[3, 22, 12, 31, 23]
[31, 30, 36, 35, 3]
[22, 35, 31, 23, 3]
[31, 23, 26, 35, 12]
[22, 23, 12, 36, 31]
[3, 32, 22, 12, 35]
[12, 32, 22, 36, 3]
[26, 31, 36, 30, 12]
[30, 22, 12, 36, 32]
[23, 36, 26, 3, 32]
[36, 30, 35, 12, 32]
[3, 22, 26, 32, 31]
[35, 22, 31, 26, 36]
[26, 35, 30, 32, 22]
[26, 12, 31, 22, 3]
[30, 22, 31, 23, 12]
[22, 30, 12, 35, 32]
[23, 30, 32, 35, 31]
[31, 12, 30, 23, 36]
[36, 22, 12, 26, 23]
[12, 3, 22, 32, 31]
[22, 36, 23, 30, 35]
[31, 30, 35, 12, 22]
[22, 26, 30, 23, 31]
[32, 36, 26, 22, 35]
# random.sample シャッフル
[31, 22, 36, 26, 3, 30, 23, 35, 12, 32]
[31, 3, 32, 23, 30, 22, 35, 26, 36, 12]
[26, 31, 35, 3, 36, 12, 23, 22, 32, 30]
[31, 35, 23, 3, 30, 12, 26, 36, 22, 32]
[36, 32, 26, 35, 3, 12, 31, 23, 30, 22]
[35, 23, 32, 31, 36, 3, 12, 30, 26, 22]
[30, 35, 26, 22, 36, 12, 32, 31, 3, 23]
[23, 22, 30, 26, 31, 3, 32, 35, 12, 36]
[32, 35, 22, 3, 23, 31, 12, 30, 36, 26]
[3, 12, 23, 26, 30, 36, 32, 22, 35, 31]
[26, 22, 31, 30, 23, 32, 3, 12, 35, 36]
[12, 3, 26, 36, 22, 32, 35, 23, 30, 31]
[22, 3, 26, 23, 30, 32, 31, 35, 36, 12]
[12, 26, 35, 31, 23, 30, 22, 36, 3, 32]
[31, 32, 12, 26, 3, 36, 30, 35, 22, 23]
[26, 30, 35, 12, 23, 22, 3, 36, 31, 32]
[23, 22, 36, 31, 32, 26, 35, 30, 3, 12]
[3, 26, 30, 36, 31, 32, 23, 12, 22, 35]
[30, 31, 3, 32, 36, 26, 12, 23, 22, 35]
[12, 26, 23, 32, 30, 31, 22, 36, 3, 35]
[32, 35, 12, 36, 31, 23, 26, 3, 22, 30]
[30, 22, 35, 36, 26, 32, 23, 3, 12, 31]
[31, 32, 22, 3, 36, 23, 26, 35, 12, 30]
[32, 35, 31, 12, 22, 3, 23, 30, 26, 36]
[22, 30, 36, 26, 12, 23, 35, 32, 31, 3]
[3, 31, 26, 22, 35, 36, 30, 12, 32, 23]
[22, 26, 30, 12, 31, 35, 23, 3, 36, 32]
[30, 12, 3, 31, 26, 22, 36, 35, 32, 23]
[31, 12, 23, 3, 36, 26, 32, 22, 35, 30]
[12, 22, 32, 3, 31, 36, 26, 35, 30, 23]

乱数生成：連続確率分布¶

# 01-05. 連続確率分布

# 一様分布 random
r_uniform_1_list = []
for i in range(100):
    r = random.random()
    r_uniform_1_list.append(r)
print("一様分布（0~1）", r_uniform_1_list)

# 一様分布 uniform
r_uniform_2_list = []
for i in range(100):
    r = random.uniform(5, 10)
    r_uniform_2_list.append(r)
print("一様分布（5~10）", r_uniform_2_list)

# 正規分布
r_gauss_list = []
for i in range(100):
    r = random.gauss(0, 1)
    r_gauss_list.append(r)
print("正規分布", r_gauss_list)

一様分布（0~1） [0.5265923229048832, 0.13861974163698576, 0.13809799323879335, 0.7157497662356598, 0.36108976833344886, 0.7513763114866316, 0.2404936039137613, 0.7181581423147705, 0.7184769263967773, 0.3054958810525106, 0.10638543387964139, 0.3970078551871341, 0.49236150032733617, 0.09997421469778434, 0.18676126036778584, 0.055343052815480465, 0.5975135715550439, 0.8888761233719161, 0.2165577909596218, 0.03471343587681974, 0.7039235944191828, 0.8149105587896851, 0.9641215867338897, 0.6131789568237019, 0.34244316565189636, 0.8378686180306556, 0.11806710521312225, 0.6926369381896267, 0.0952308492516365, 0.3997057470173988, 0.49502288140217887, 0.377894273032341, 0.16859757880447968, 0.2317173126022275, 0.8201499974998944, 0.46257580479248983, 0.5799327447235099, 0.2119070176161595, 0.7149350587865332, 0.33011725914726364, 0.5936185874860408, 0.9094870627958156, 0.9943934088859884, 0.04621794831314552, 0.797442711928691, 0.8575878253608825, 0.3195744372072056, 0.3831476259821177, 0.5802537596763331, 0.9188402309707125, 0.39992859333804187, 0.8800301687734118, 0.7585605282041756, 0.1522730797062255, 0.9136799203638493, 0.015181052589951283, 0.1451782500468748, 0.6648112128866874, 0.05711968663889244, 0.3794898856741835, 0.12997885852693347, 0.4628892738532562, 0.8399803437546011, 0.9060843513491861, 0.03546964032188504, 0.060851756668864554, 0.8406240353653226, 0.0428147832556115, 0.273590265071345, 0.11743671769283648, 0.09103770695709379, 0.027622889724836064, 0.6375130126648525, 0.7446142679398566, 0.6867713765586763, 0.8456227719182262, 0.6630161884986934, 0.38970192767534384, 0.6310630237160113, 0.9695948083687032, 0.6416033330232526, 0.24309173409213014, 0.0601840957099572, 0.9351659997400953, 0.5904954982942084, 0.3496147426104088, 0.6053527496610309, 0.5602575960634735, 0.5221717727865457, 0.06080464202945668, 0.3532275523761348, 0.4126500229395509, 0.199368340608838, 0.880105231228507, 0.4241197773808294, 0.6623856654024448, 0.7135464494458958, 0.7432830602725053, 0.7211152909126985, 0.7522085016390995]
一様分布（5~10） [6.257903470753821, 9.882018383464484, 5.7550487689193, 9.593236975496506, 9.272843876037815, 9.260821455899837, 5.26405627418767, 5.456090417219498, 9.06527901116161, 7.3458341323259395, 6.8512659556896285, 9.923437361146787, 5.2005896764482005, 7.657325269028024, 7.216748880753536, 5.641015615143388, 6.975941313929937, 8.53823702405251, 9.41157804601204, 5.123098557316717, 7.622547793015446, 5.451882975176292, 9.001967285775175, 5.428926397183523, 5.170966605085692, 6.921181010386443, 8.6630308725315, 6.566033465237238, 5.650024498265237, 8.972861110425859, 9.034596909475924, 9.27929899386286, 6.518722366320285, 7.124151805094868, 6.226949971271267, 7.7858874650825305, 6.650535833948739, 6.693316679795091, 8.918107092048682, 9.781480800201113, 7.920701596183792, 5.523439650599788, 8.262874663423052, 7.243058589240401, 9.940152785131566, 8.596907475739934, 9.173930532536044, 8.50643130094106, 7.678095028931959, 9.484091959140628, 9.158085323540046, 6.456629438071645, 5.7851594761004375, 6.8517593439384745, 7.605388362862929, 5.4869004491531435, 6.726896432279302, 7.8745283210599, 5.217873092759256, 9.074743382594146, 8.25558522841639, 6.568250857948819, 6.4916049062758425, 6.763080703939102, 6.626443481025715, 8.742568884793766, 7.505284287356263, 7.63064198649913, 5.743782494854583, 9.57209001208863, 6.627864643361668, 6.63782226194106, 5.344230698489165, 9.897057908758978, 7.398489209046295, 9.564423686421119, 9.638086212487417, 9.848760715891707, 9.078146438657564, 9.627216125956563, 9.61144661825029, 9.006838390830925, 5.6729060802134175, 7.618558611429203, 7.8780200650207455, 9.962487639930789, 8.919742749831263, 8.514581083274777, 8.733245184222193, 6.807888820417384, 9.711567789201084, 8.217504448076145, 7.012873042650083, 7.322857886488043, 9.898774636553663, 7.660641987157691, 5.838987679372441, 5.7417749706702494, 8.436210983288738, 7.8138776545750925]
正規分布 [0.5324375935904874, -0.3530779375782036, -1.3683741456475194, 0.8550825306685746, 0.43469013892015146, 0.14155661457278193, -0.7537828813773354, -0.22263462242443993, 0.6096537715636479, 0.48489767776433806, -0.8248452313401039, -0.9023965058382205, 0.34249730702473463, 0.18409849853991048, 0.8484820527112336, -1.1582125725053838, 0.9214086014444441, 1.7634074969742954, 0.9491413321949335, 0.13112646629094207, 0.9061431298592266, -1.2870797762586406, -0.4434220775745028, 2.0594570576366276, -1.6346161195291298, -1.157718860951095, 0.8228223320168564, -0.6567184327555143, -0.5651032811994183, -1.1194969459729216, 1.682237422911142, -0.6088058499271607, -0.27761469543636275, -1.8130900242341954, 0.7699729664826502, -0.008902331892990233, 0.49864433585385454, 1.5806230586981524, 0.15311291220500362, -1.1919806958263168, -1.0135889886150027, 0.08248995203401366, 1.32075594399839, -1.1988114571728905, -0.24668430582302578, -0.1450480958168968, 0.6574081580897599, -0.8913292640974034, 0.3116957216667728, 0.7838058354177626, -0.037866762244599075, -0.09803420161996611, 0.618793583055987, 0.5814126043641078, 1.2583567956103352, -1.0789656223169575, 1.2304906486400156, -0.22839071358666393, -1.1388952978780043, -0.5532281757233414, -1.2336128003688107, -0.2003717116136265, 1.0340562311015782, -2.2498212769594184, -1.1824327808803452, 0.7682248345284534, -0.30097882883050847, 0.7926079366310617, -1.327513684363958, -0.05272080362551487, -2.606046552863915, -0.8466556917182078, 0.7399065599766491, 1.215481411549136, 1.631408091907619, -0.05608163817060093, -0.8775564670832912, -0.3857148741498997, -1.9181306028911123, 1.3545970556258886, 1.177966182383311, -0.9098131673999311, 1.831576151410436, -1.3528606330079138, 0.5596126918649947, -0.8086752658193437, -1.7382947519171057, 0.3958475718858402, -1.1587062793401812, 1.1936940207218614, -0.8996917306991808, 0.10550901197176209, -0.47897015826125133, 0.1354140612230567, -0.6322787018890805, 0.8204726302534867, 0.6105451410390148, 0.06998263108965841, -0.12692339031175426, 1.9713229451563317]

ヒストグラム¶

# 01-06. 分布のプロット
import matplotlib.pyplot as plt

plt.hist(r_gauss_list)
plt.title("Gaussian distribution")

ループからの脱出：break文¶

for の範囲や条件分岐だけでは扱いにくいループ終了条件に対して break を使う．

# 01-07. ループの中断
for i in range(100):
    print(i)
    if i == 10:
        break
print("ループ終了")

# 01-08. ネストされたループの中断
for i in range(20):
    for j in range(20):
        print(i, ", ", j)
        if j == 5:
            break