# coding=utf-8
import numpy as np  # 数组相关的库
import matplotlib.pyplot as plt  # 绘图库

'''
绘制散点图，来分析映射关系
根据分布集合，来设置映射关系
'''


def scatterDiagram(result, trueResult):
    x = trueResult
    y = result
    plt.figure()
    plt.xlabel('正确结果')
    plt.ylabel('预测结果')
    plt.scatter(x, y)
    plt.show()
    return


def statisticsResult(result, trueResult, num):
    pos = [0]*(num+1)
    neu = [0]*(num+1)
    neg = [0]*(num+1)
    # print(len(trueResult))
    # print(len(result))
    for i in range(len(result)):
        if trueResult[i] == 1:
            # print(int(result[i] * 10))
            pos[int(result[i]*num)] += 1
        elif trueResult[i] == 0:
            # print(int(result[i] * 10))
            neu[int(result[i]*num)] += 1
        else:
            # print(int(result[i]*10))
            neg[int(result[i]*num)] += 1
    return pos, neu, neg


def chooseLeftAndRight(pos, neu, neg, num):
    left = []
    right = []
    sum = []
    for l in range(num):
        for r in range(l, num):
            correct = 0
            for n in range(0, l):
                correct += neg[n]
            for n in range(l, r):
                correct += neu[n]
            for p in range(r, num+1):
                correct += pos[p]
            print(correct)
            sum.append(correct)
            left.append(l*(1/num))
            right.append(r*(1/num))
    return left, right, sum


if __name__ == '__main__':
    result = [0.44289849564187256, 0.9994543029440242, 0.5, 0.003862980768790547, 0.0018132847554932496, 0.9999999853202581, 0.9999999999148357, 0.9283024859693915, 0.9694640952043556, 0.9921530764269413, 1.3856269909240382e-08, 3.7475676818221615e-05, 0.0034414558707704934, 0.6410811129560379, 0.005530817669478383, 0.2308227687892076, 0.0005001260743454639, 0.6850284624612241, 0.02932216070937299, 1.7459650714091168e-07, 0.9979482703954271, 0.9999688153466901, 0.9999899357367049, 0.9994967530781732, 0.5430371768713455, 0.9999771896730578, 0.5, 0.9999984674229085, 2.6063472937654097e-06, 0.9999999924438615, 0.8030018753187695, 0.9659564001246174, 0.8872673532536988, 0.3573267639153327, 2.3336967913678563e-09, 1.0, 0.17776066091169518, 0.43309191701502636, 0.9998381643065009, 0.999944673105809, 2.86381857583784e-06, 0.9998604170005331, 0.01183349036041692, 0.9999055713200303, 0.9999999999341862, 0.9999999991439801, 0.07541056796770917, 0.9996514170438561, 0.9999997275691622, 0.00736512520200705, 5.19925882347394e-08, 0.999999992909961, 1.0082525898513772e-05, 0.999249392442644, 0.9853318900617749, 0.9100251825587399, 0.9905665915688886, 1.0, 5.884185794169383e-08, 0.9976251476246372, 0.9917839958330102, 0.9355804438946592, 0.9933499385772394, 0.9999999900768314, 0.9610053754497138, 0.9994794580116703, 0.24365674236417634, 0.9905321022828223, 0.9999999982651218, 0.23291639384949903, 0.49908592321755063, 1.0, 0.006992121339346791, 0.04482008596013831, 0.9992433652252808, 0.6968527936519133, 0.9999956291887826, 0.02287352377028029, 0.9517256540066434, 0.22233640566910184, 0.993855193758131, 0.16873777721383776, 0.000723911506517072, 0.9999981468786109, 1.0, 0.9998676780392336, 0.999999953680664, 2.0572232806159718e-10, 0.6069104125276992, 9.182878951252693e-05, 0.19376814075017268, 0.0016587628923485642, 0.010733580952103305, 4.0047586841174265e-06, 0.9999999999999998, 6.807757949511828e-05, 0.9999908149513392, 6.297159667811858e-05, 0.9232491632764065, 0.023333469925352568, 0.9999999988370136, 0.999944673105809, 0.9999985938708414, 0.2034811692034214, 0, 0.9610053754497138, 0.7507499479521555, 0.99999999997938, 0.9999992420923676, 0.9999895642385699, 0.04656865488342876, 0.6120320073350595, 0.4140291688196127, 0.9999999875873028, 0.029221812328802277, 6.661338147750939e-16, 0.9999998257811621, 0.0037100733303953026, 0.947923003349979, 0.3887829210190785, 0.3886761035449403, 0.9979482703954271, 0.04692713947331284, 0.9483969170033487, 0.9999992404579656, 0.970240335635476, 0.9999997061829318, 0.9999999968288147, 1.0, 1.1799770432752155e-05, 0.5523309048204219, 0.9999999999999734, 0.9863737756865977, 0.09904122521795666, 0.9808472259046015, 0.9980659064643169, 2.832233164662412e-07, 0.6319521069306796, 0.9999849041199129, 0.15674129738443365, 1.4573036455356458e-07, 0.0, 1.0, 0.15276214211131822, 0.0003898073168964178, 0.0009241916938035333, 0.6122134643387672, 0, 0.020259958037386894, 0.9170040463715515, 0.7957051654091702, 0.6718373316747134, 0.98090276856446, 0.9977946176228458, 1.0, 5.556516136095979e-09, 0.9363854896679623, 0.9961407003035733, 3.078018062652177e-09, 0.999996013232739, 1.0614653855878231e-07, 0.9999907822541021, 8.362310178422483e-06, 0.7238856925145103, 0.9999972658101763, 0.9999999999999976, 0.5113605294999084, 0.9999999999708287, 5.907718758635383e-11, 0.44819886271383835, 0.9760717499879084, 7.767034287731178e-06, 0.9999999933453974, 0.994984542659386, 1.2188831863824134e-06, 0.3709462346096707, 0.2828702284006649, 0.9999999995562823, 0.029172706509800417, 0.0003579873151712265, 0.9968091985387287, 0.9974615196899552, 0.0008114303342175999, 0.9346142209630934, 0.9723988753941649, 0.0009045395271859435, 0.006549674304227038, 0.9999989409817449, 0.000331093361875312, 0.9999999766218061, 0.9992675618647203, 4.024588866946566e-06, 0.9967474052179305, 4.031911994883952e-05, 0.9999999999999816, 0.9974666594089072, 0.9999992440141376, 0.9999996409443305, 0.016046551867367587, 0.9999999999571789, 0.05480093472046277, 0.9031598709595414, 0.9999971062512366, 0.9999984674229085, 0.23039565859542055, 0, 2.0544943524214432e-10, 0.9999352403729784, 0.9999999999999976, 0.9999433724670025, 4.1419779173157423e-07, 0.9980153195354082, 2.995101086922247e-06, 0.9791092432740685, 0.06716661248343225, 0.004422597046692123, 0.0020883082441156553, 0.9999999916987324, 0.34290122563773295, 0.0006837713910744503, 0.9991718084321236, 0.9993500621041617, 0.999559113067915, 0.599204375932372, 0.9998832068007282, 0.9999999080493807, 0.011305924906836795, 0.9996738993543781, 0.0018286918378119799, 2.9229287537568815e-05, 0.999962407987585, 0.99999994550064, 0.9999999763950843, 0.0, 0.022711107206892733, 0.999951418919007, 0.9999996954105508, 0.9783593565342751, 0.9368444842584138, 0.9999881377839017, 0.38268007729150544, 0.9996920341556547, 0.14339133917605895, 0.9999999999999161, 0.2389281481503872, 0.00029567789774698205, 0.9930192571217952, 0.9999999999999982, 0.9999941863186846, 1.0, 1.1235001817766488e-09, 0.9988284685727385, 0.9644235500161203, 0.9999998837805917, 0.999998675124887, 0.994194044222611, 0.3436338558620602, 0.9999999996857447, 0.9997886977767412, 0.9999999999593698, 1.481593514540691e-09, 0.9248445913468868, 0.7964598101359046, 1.3103352415333447e-06, 0.15302414884964521, 0.9999999933453974, 0.016335819295127507, 0, 0.5523309048204219, 0.7622178593062368, 0.10055726043555879, 0.9674191905295051, 0.9996823656316063, 0.9999999892917545, 0.9999999999891649, 1.1723219993653444e-06, 0.9874908135313827, 0.04821486800244135, 0.5523309048204219, 4.864199099063882e-08, 5.449520942746311e-05, 0.9999999625381907, 0.9997250405644329, 0.21478365430997393, 0.9999999999999991, 0.9999993905221225, 0.8625410769431191, 0.9999999999999687, 0.999999980876095, 0.9998961048392541, 0.00017054406183247828, 0.9989442415675549, 0.9998676780392336, 3.882625732032352e-08, 2.0583756921155327e-11, 1.0, 0.9999999925648382, 0.999999865665448, 0.9999861005815229, 1.3612787334027487e-06, 0.9999999999671956, 0.0028613160063296617, 2.505911034234032e-10, 0.0009230825858388414, 0.9999999999973659, 0.595788872376107, 3.828482886270024e-07, 0.9992560813424222, 0, 1.3697376673671435e-05, 0.9999971062512366, 5.6612843354786335e-05, 0.020823526556763006, 0.9999972094061672, 0.9610053754497138, 0.9999999999767752, 0.859193787073717, 4.78806566376333e-05, 1.0, 0.185038275186863, 0.9660478273856509, 0.9999999042036126, 0.9998623601253036, 7.254490533348257e-05, 0.25720108049094403, 0.7216373433221379, 2.478165535890753e-06, 0.0003168446043271267, 0.002593513657011548, 0.9999999999999278, 0.9997420172251256, 0.9999999162375618, 0.04692713947331284, 0.007178015774584656, 0.8665014067143526, 0.9999995857712483, 0.9994778825291037, 1.500822491840026e-07, 0.01969335357566626, 6.113794376316761e-07, 0.46053834981254504, 3.0620176394435816e-08, 0.8720711748096923, 0.12418202673193313, 0.8009280585242499, 0.999997110153796, 2.0572232806159718e-10, 0.5523309048204219, 0.4508051430951394, 1.0, 0.9473684210526315, 0.9999975803573433, 0.9999990506545524, 0.014725850135930973, 0.9993368879764023, 0.953823491573082, 0.05676202237033168, 1.0, 0.028598014724776633, 0.37911418293999544, 0.00034559723054317093, 0.0024234433225954755, 0.004332139670448654, 0.6959494497086434, 0.9563129899633928, 0.999987848797263, 0.9113814454148117, 0.9911348047616025, 0.0010101377622706575, 4.6003068258082536e-06, 0.9999990239195767, 0.9999999405846851, 1.1933742882774823e-09, 0.9999974788166021, 0.20555129029473163, 0.9929743907711922, 0.9999999995179236, 0.999793117012515, 0.4472114115302761, 7.5876942642327805e-06, 7.585354893646645e-06, 1.0275285839966841e-06, 0.999825783726691, 0.15024038461538447, 0.7941662659807855, 0.9988721164780521, 0.9995913155952942, 0.00024979297402072387, 1.1106755684830993e-05, 2.1007292551056267e-06, 0.9999984700660977, 0.0009394686456301038, 0.5105620912628285, 0.3087519842552613, 0.0004177421947153537, 0.9999999999668094, 8.67949712102245e-10, 5.805611554943191e-06, 0.9977813742311384, 0.9999985607647208, 0.9999999901085109, 0.9995728252106235, 0.8132444513607092, 1.0500940732516284e-05, 1.593719639592095e-07, 0.9973099486418097, 4.439448919590916e-08, 0.05676202237033168, 0.999999995579254, 0.999999980876095, 0.9999976850036354, 0.9999998656340839, 8.979106347339894e-10, 2.876337112933669e-08, 0.0020827375185661356, 0.007876628850244649, 0.9962307531884399, 0.9999909186612562, 0.3867821084632096, 0.9999766307747745, 0.9998582218252355, 1.7289061211456236e-05, 0.9999955537874161, 0.9999999960734529, 2.946823001170884e-07, 0.9999999999999933, 0.999916882537637, 0.18491131266395433, 9.806904009201922e-06, 0.9419944633274272, 0.999999854123371, 0.009689279593511735, 0.9970853626273022, 0.999999945597109, 0.9998939842924776, 0.24377505731368176, 0.0006891121079887208, 0.9999980006114101, 1.0, 5.449520942746311e-05, 1.0, 0.2500000000000001, 0.005290041252500877, 1.0, 1.0, 0.9693992718537178, 0.004065775391759674, 0.7545291481509451, 0.999983576859936, 0.17417288022472965, 0.9455893956970222, 0.9574350820444539, 0.6817105692309999, 0.9999991333808554, 0.9998834192295495, 0.558905338071088, 0.6707650825960833, 0.05345663768805442, 0.40070003979515323, 0.005565546987337466, 0.42731651865958853, 0.9999997204414011, 0.9943816450762248, 2.6780716815055783e-05, 5.297875471654834e-10, 0.6758916470321636, 0.9999999347815896, 0.9999998797862968, 0.9999999999999971, 0.3054635585920267, 0.9999999999983944, 0.01739032834997789, 0.9919034966382607, 0.9999999446377472, 0.9999999998072877, 0.9368444842584138, 0.8795592431832002, 0.00013499787206394664, 0.999979993486341, 0.9999999999999989, 0.0040737163109280106, 0.9948202211681687, 0.35913211147891666, 0.9991329266873584, 0.11330291776529922, 0.9999999162375618, 0.9999999998863038, 0.998125084932503, 2.8171021071443647e-10, 0.3369565217391304, 0.9999999999991436, 0.9872245414599277, 0.9999999999787934, 0.9994902118724327, 0.9470568793834595, 0.0037100733303953026, 0.53053058386206, 0.9999999999988509, 0.999996691623679, 0.5581893068789348, 0.9999999999999889, 0.20001404138933998, 0.9999562331778828, 0.8885508466479617, 0.016351538521719555, 0.017116195003990198, 0.9989318167021377, 0.9999999999963349, 4.502522975236012e-06, 0.5523309048204219, 0.9999999650150381, 2.381840874199348e-06, 6.546385349359696e-07, 2.6399189187564787e-05, 0.1529326518234969, 0.8501508128250472, 3.4110485507832244e-05, 0.999998675124887, 0.8617676946238879, 0.9499961453398552, 0.8652931312208665, 0.0017344257914293504, 0.02894716586981505, 0.35499595844336784, 0.008800112218951162, 0.9999003999390195, 0.99350831599972, 8.129541484436231e-11, 0.05756570963244234, 7.904145340908997e-06, 0.04277112376681269, 7.013849329107202e-07, 0.0003508547741321033, 0.9999718799627758, 0.8927991945549613, 0.42333831754083306, 0.9798917189983021, 0.9874049413546728, 0.1483910103560978, 0.9999996142891243, 0.0003774028203590296, 0.9999999999999942, 0.0021417577788032105, 3.409147340682761e-05, 0.7146706271834455, 0.9808270026604654, 0.9998676780392336, 0.1032971653393322, 0.00182922072525471, 0.99997864780165, 0.9999999999952864, 6.107628010010302e-07, 0.9999822147376884, 0.6713347654065155, 2.25041656998215e-06, 0.8718043438368955, 0.8522890077717237, 0.20715209695346992, 0.9934958863342356, 0.9999999989079207, 0.8189042004763206, 0.9999999999973124, 0.05676202237033168, 0, 0.9999953700739949, 0.9203574876546878, 0.15439904322689924, 0.9148403844254749, 0.00039117413605560536, 1.0199634444485461e-05, 2.0885615509169675e-05, 0.7146706271834455, 0.2933467736370782, 0.999555754027738, 0.20915719822962542, 0.003353372652661335, 0.0516239033104583, 0.18887276802519837, 1.7920326871312398e-06, 0.1193925186754452, 0.9800814380761881, 0.05088713364015984, 0.8824689457267423, 0.00022248835526605948, 6.439293542825908e-15, 0.002531456997795556, 3.670200881211727e-05, 1.0, 0.9999880447426903, 0.10360940608555236, 0.33941423739439214, 0.5135860161798403, 0.9999999945276083, 0.9999999994268682, 0.9999999996656084, 1.2525536163821016e-12, 0.9413544382989606, 0.9965411661265625, 0.00014989310980439985, 0.999998675124887, 0.01785791123814151, 0.6307250257408122, 0.9852609624232342, 0.9942041652822797, 0.4152254097458863, 0.9999999379156509, 0.9999999998496805, 0.9999998692138332, 0.00016437759716936284, 0.999944673105809, 0.9999999969590692, 0.9999999622464425, 0.9994330396745699, 0.9518485416280148, 0.9999999933453974, 9.341799753315172e-05, 1.3199392390195186e-07, 0.0008783327779112726, 0.19452979735400444, 0.1234966007797601, 0.6129242094892682, 0.9999999880530165, 0.9999999983057404, 0.9999938731979137, 0.8224556540574018, 0.9999990967632939, 0.7360075004785299, 1.0, 0.999810931358567, 0.04052282625592418, 0.9999996374751527, 0.31652440950898586, 0.00011632889601187468, 0.9397457788630474, 0.9980152736884071, 4.272822482498384e-07, 0.9923507829770448, 1.3948737501823238e-05, 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-1, -1, -1, -1, 1, 1]
    scatterDiagram(result, trueResult)
    pos, neu, neg = statisticsResult(result, trueResult, 50)
    print(pos)
    print(neu)
    print(neg)
    left, right, sum = chooseLeftAndRight(pos, neu, neg, 50)
    for i in range(len(left)):
        print("左界:", round(left[i], 2), "右界:", round(right[i], 2), "正确结果数:", round(sum[i], 2))
    print("最大正确率：",max(sum))