我想实现数据的2D表示,其中每行代表高斯分布的特征。我做了以下事情:
public ArrayList<ArrayList<Double>> getFeature( BufferedReader buffer1)
{ ArrayList<Double> arrList1 = new ArrayList<Double>();
ArrayList<ArrayList<Double>> arrList2 = new ArrayList<ArrayList<Double>>();
String[] strArr = getWords(buff1);
for(int j=0 ; j< strArr.length; j++){
for(int i =0 ;i < 50 ; i++){
arrList1.add(rand.nextGaussian());
}
arrList2.add(arrList1);
}
System.out.println("size of arrList2:"+ arrList2.size());
System.out.println(arrList2.toArray()[0]);
System.out.println(arrList2.toArray()[1]);
return arrList2;
}
当我编译并想要得到每行的值时,我得到了输出。谁能告诉我可能是什么原因?
预期输出为:
System.out.println(arrList2.toArray()[0]);
[0.08,1.1 .............,0.98]
尺寸为50的数组,其中填充了上述值。
以下是我们的输出。太大了
[0.46462618324716254,-0.7461971643031985,0.11198107553318244,-0.5445576195764561,-0.09170153174710902,1.0599085675813804,-0.5121868425685772,0.6578194527724543,0.07180836719554716,-0.8711795090831688,-1.1685999674955914,-0.8467566589850426,-0.9464559617558149,-0.25455126102711567,0.6880497852836619,0.05802417861623583,0.7605219159096197,0.5573206594413265, - 0.6464485036951102,0.9928577372480463,0.769468353755745,-1.0349221359588956,1.7475686681406222,0.7286721770852165,1.1938115793074722,0.05051321258899094,-1.5274223735062666,-0.10652710930319426,-2.1566969444968622,1.4572264331572156,-0.07630289414615696,0.2776127747056551,-0.3009457462994894,0.9554273666202241,-2.1190393953455047,0.4580572585843065,-0.6413109094169921,-0.4978755907488374,0.353842909950826 ,-1.257672808328245,-0.3236234929243931,-0.8899339209743886,0.347442395255124,-0.48611580230648704,1.219007569267497,-1.1789975566918134,-0.01825901882420379,-1.6486718275722763,-0.3 819056170192554,0.6042625214995715,0.33415986866928,-0.07450314651627132,1.1181610738837455,-0.44555621990204264,2.2166172691235473,-0.6944430028545253,1.7804248652436612,-0.3801297513557677,0.1603379135566103,0.4370378823762644,0.6537078245920281,-0.5909651262165042,-0.09079544840341715,-0.4588221391142408,0.3191257940850721,0.851481629251832,1.5836138371905788,-0.9214851789009444,-0.40274669796854634 ,0.33137905198405093,0.22048511721877453,-1.6107690385201552,-2.2293481002062734,-1.5862880920203761,-3.021081392986815,0.4806258491486294,-1.4404361309735374,-0.11292399203207835,-1.3927949945851505,-0.999380367686273,-0.34942295299214127,0.9614226886733961,-0.011646872308462626,-1.314757063583407,-0.5894619210755432,-0.018747975733725518,0.7847736709271301, -0.5673683910852766,0.4350772179247941,-2.310707468789298,-1.3594784507734978,-0.420522194159102,0.8723173566610757,0.08704331777378478,0.19156519877684638,1.13490819832362,2.26583242405 5537,0.08824246678795156,1.3416771872818614,2.0113403780125716,-0.6591827547030255,-2.1221005234426045,0.22388389358930083,-0.35281199160944976,1.57513125025632,-0.5543596830360817,0.24276349413614184,-0.6933647399153053,2.1733561712603406,-1.1295984403806556,0.978199373546278,1.4765841816237413,-0.23614652784978474,0.6860841664188477,1.724839793220621,0.09890307698728121,1.1759901942152857, - 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0.36987435658432716,-0.23254064940739874,0.4093041605249441,-0.22152432261151883,0.11956045271155907,0.817312179186691,-1.109714930373252,1.6919073761823942,-2.477322936459778,-0.8041619336754456,0.5354776432522204,-1.3994286642549634,0.7621208634646848,0.3168358861977863,0.5654315361895403,0.19188988525917902,-1.8959135432065441 ,-0.8883163800042816,-0.07396400493233038,-1.811056975930386,0.8323666750629728,0.16495843660377815,0.9180073204622988,-0.18482724669045245,-0.926597451803997,-0.37373162068547583,1.2 784981694766253,-0.9622089382124651,0.36846446000890226,1.7781522414929132,0.22598541140652853,0.0698645511906671,0.32437679311726797,-1.2473606786833797,-0.4098009718556575,0.04826245169132581,0.7412730519089504,-0.2550533401514563,-0.16038376756843503,-1.7248853346384536,-0.9996464058972109,-0.6041936215771648,0.7012791176135328,0.2634365350229634,1.6681642878727803,0.5006091547003853,0.8625317708776815, 0.1915138247321982,0.2611860227007197,1.1701209557262373,0.9057134706410637,-1.7953870540423091,1.2544035731509018,-0.8592198056076387,-0.7480509518320575,-1.4509156168191215,-0.6256261144134664,-0.3991019440510313,0.665093736894838,0.8193871205290613,0.3194454906105449,-0.7766590102568899,-0.4368566309637124,-0.5917671696216537,0.8311430693910862,-0.03873251937784431,0.12352685387320661, -1.3032763393594495,-1.3089664655879443,1.0600394162534208,-1.0448890523458283,0.06485611850874347,0.9952192969393494,0.7564433698789398,-0.129343789502 65682,-2.455965368428643,0.32562880194284605,1.0608150376407195,-0.5856546412601992,0.04459245589226094,-1.0485199770272802,0.171758532083598,-0.15219755725779346,0.22588623160615964,-0.8866303888277965,0.18071263060711168,-0.8101056664306856,0.40109990179114574,-1.2052661486349423,-0.7063493195672804,0.3790905532531173,0.6187801708754183,0.8973661967856524,-0.5094785611904082, - 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答案 0 :(得分:5)
您需要在外循环的每次迭代中重新初始化arrList1
:
for(int j = 0; j < strArr.length; j++){
arrList1 = new ArrayList<Double>();
for(int i = 0; i < 50; i++){
arrList1.add(rand.nextGaussian());
}
arrList2.add(arrList1);
}
否则你会继续添加相同的ArrayList
,这就是你获得巨大输出的原因。
答案 1 :(得分:2)
您在整个arrList1
使用相同的实例。
尝试:
for(int j=0 ; j< strArr.length; j++){
arrList1 = new ArrayList<Double>();
for(int i =0 ;i < 50 ; i++){
arrList1.add(rand.nextGaussian());
}
arrList2.add(arrList1);
}