实验内容

  1. 产生-1···1间隔为0.05的向量 $$ \\vec x $$
  2. 计算方程$$ y=x^2+3 $$
  3. 绘制函数$$ y=x^2+3 $$的函数图像
  4. 随机产生大小为30*30的随机矩阵$$ A $$
  5. 绘制箱形图
  6. 在矩阵$$ A $$中随机选择100个数据
  7. 用100个2-8之间的随机数替换矩阵A中的数据
  8. 重新绘制箱形图
  9. 取出异常值的点
  10. 矩阵归一化(标准化)

产生-1···1间隔为0.05的向量 $$ \vec x $$

1
2
3
import numpy as np
x=np.linspace(-1,1,41)
print("x的值为:\n",x)
1
2
3
4
5
x的值为:
 [-1. -0.95 -0.9  -0.85 -0.8  -0.75 -0.7  -0.65 -0.6  -0.55 -0.5  -0.45
 -0.4  -0.35 -0.3  -0.25 -0.2  -0.15 -0.1  -0.05  0. 0.05  0.1   0.15
  0.2   0.25  0.3   0.35  0.4   0.45  0.5   0.55  0.6   0.65  0.7   0.75
  0.8   0.85  0.9   0.95  1. ]

计算方程$$ y=x^2+3 $$

1
2
y=x*x+3
print("y的值为:\n",y)
1
2
3
4
5
6
y的值为:
 [ 4. 3.9025  3.81    3.7225  3.64    3.5625  3.49    3.4225  3.36
  3.3025  3.25    3.2025  3.16    3.1225  3.09    3.0625  3.04    3.0225
  3.01    3.0025  3. 3.0025  3.01    3.0225  3.04    3.0625  3.09
  3.1225  3.16    3.2025  3.25    3.3025  3.36    3.4225  3.49    3.5625
  3.64    3.7225  3.81    3.9025  4. ]

绘制函数$$ y=x^2+3 $$的函数图像

1
2
3
import matplotlib.pyplot as plt
plt.plot(x,y)
plt.show()

函数图象

随机产生大小为30*30的随机矩阵$$ A $$

1
2
A=np.random.random((30,30))
print("矩阵A的值如下:\n",A)
  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
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
矩阵A的值如下:
 [[  4.53616512e-01   8.61856377e-02   5.30296845e-01   2.40709187e-01
    3.80793044e-01   5.12444653e-01   7.76249207e-01   2.34136529e-01
    7.37731641e-01   5.32085033e-01   2.37284517e-01   5.43014312e-01
    2.55230539e-01   1.46512943e-01   5.11529807e-02   4.43609645e-01
    8.56999978e-02   1.40347620e-02   4.02022461e-02   1.90870830e-01
    3.49564773e-01   1.36749795e-02   1.55291591e-02   5.09445687e-01
    3.62207023e-01   7.20922722e-01   8.54771022e-01   6.61434389e-01
    4.86238090e-01   9.79529452e-01]
 [  8.05428682e-02   3.29047793e-01   6.43698673e-01   9.04277168e-01
    9.78384264e-01   3.37353494e-01   7.39358067e-01   3.55182658e-01
    9.89687095e-01   6.14935945e-01   6.52728677e-01   8.43784174e-01
    5.13862865e-01   9.99091787e-01   2.00922546e-01   5.76144358e-01
    2.56320016e-01   9.22332892e-01   3.08547956e-01   5.79930649e-01
    3.06355198e-01   2.61417887e-01   4.32863769e-01   4.31994524e-01
    4.83047584e-01   2.63712956e-01   8.35141356e-01   7.59380113e-01
    2.59410702e-02   3.29845339e-01]
 [  2.30571181e-01   4.26744408e-01   9.81635240e-02   7.26050569e-01
    9.63056915e-01   8.76546558e-01   9.08892112e-01   3.52611078e-01
    9.09544008e-01   6.62110762e-01   3.52487518e-01   6.94414615e-01
    4.20141358e-01   5.51120540e-01   5.02641235e-01   9.94162126e-01
    8.28955641e-01   1.58701251e-01   6.36350737e-01   9.10921055e-01
    2.07573003e-01   9.85773749e-01   3.10852943e-01   5.63833568e-01
    3.99233825e-01   7.07604940e-01   4.11989283e-01   2.11779969e-01
    2.43610690e-01   4.43425323e-01]
 [  9.99816333e-01   9.54144593e-01   9.27052004e-02   1.98800151e-01
    8.32015236e-01   3.43349579e-01   4.23569167e-01   3.93889508e-01
    7.36906066e-02   6.55602433e-02   5.05280247e-01   4.71164886e-01
    8.09818357e-01   3.85184812e-01   2.99313245e-01   9.17596868e-01
    8.19968098e-01   5.06040711e-01   1.63083626e-01   6.26927790e-01
    3.45427452e-01   4.51662512e-01   4.47094750e-01   7.28558869e-01
    5.29173761e-01   7.42919754e-01   7.75147259e-01   2.76066769e-01
    5.72056816e-01   4.06856582e-01]
 [  2.39926078e-01   9.42964547e-01   3.62383639e-01   1.16162214e-01
    9.34517505e-02   1.96429296e-01   5.81058059e-01   5.76398884e-01
    4.12430328e-01   5.14769968e-01   3.87464608e-02   6.16932645e-01
    3.74895218e-01   4.08285312e-01   8.98018119e-01   6.49249389e-01
    4.08645760e-01   6.07959661e-01   2.64660816e-01   7.15983366e-01
    7.61795316e-01   3.83236144e-01   9.32311048e-02   2.57465746e-01
    6.51411403e-01   3.91861222e-02   4.45628558e-01   6.89695145e-02
    3.32177995e-01   7.44112520e-01]
 [  6.43471306e-01   6.17741574e-01   1.55804821e-01   9.22755924e-01
    2.66214452e-01   5.46513450e-01   6.97813914e-01   9.27087146e-01
    9.36551648e-02   7.29070670e-01   9.42267932e-01   5.09140319e-01
    6.71722116e-01   5.03256039e-01   7.31127481e-01   8.97427376e-01
    5.02539040e-01   9.30951032e-01   4.86339289e-01   2.00832478e-01
    2.75863215e-01   9.49220128e-01   4.22106193e-01   4.14502322e-01
    5.10837783e-01   4.93701826e-02   1.06916975e-01   9.51495023e-01
    5.94213555e-01   6.89806343e-01]
 [  5.32218072e-02   6.02419805e-01   7.38856389e-01   9.98442237e-01
    1.56077273e-01   4.87020904e-02   3.09644991e-01   4.28412070e-01
    6.11152002e-01   2.49624942e-01   6.73371621e-01   8.84300346e-01
    3.64988087e-01   2.97069991e-01   8.91698891e-02   9.72148415e-01
    1.83263010e-01   4.77501078e-01   3.36176277e-01   7.34401939e-01
    1.50419950e-01   5.67514580e-01   2.14384487e-01   1.49284933e-01
    9.62571748e-01   6.98850409e-01   4.06660190e-01   2.66242175e-01
    1.97436047e-01   9.19230005e-02]
 [  4.92163478e-01   4.04041328e-02   8.97353508e-01   8.08023666e-01
    4.93427777e-01   5.14718018e-01   3.20256944e-01   8.87970629e-01
    1.35702605e-01   4.06703359e-01   8.20521000e-01   7.38040864e-01
    6.87990092e-01   3.12543181e-01   3.64128296e-02   1.48135257e-02
    1.27754601e-01   2.39116580e-01   9.76091465e-01   8.78382275e-01
    2.36204538e-01   9.35121634e-01   7.51336126e-01   9.92495197e-01
    9.21466098e-02   7.07920725e-01   2.91044917e-02   4.31194945e-01
    2.18753970e-01   1.63930148e-01]
 [  7.74691502e-02   6.74049501e-01   1.55214880e-01   2.11899380e-01
    3.78710508e-01   9.22175118e-01   6.02138278e-01   5.92256022e-01
    7.48140873e-01   2.35083541e-01   6.24699145e-01   8.34894787e-01
    3.82181188e-01   9.72445952e-01   1.20026772e-01   3.48326547e-01
    9.70255887e-01   2.43615320e-01   2.06208181e-01   5.44878636e-01
    3.05449030e-01   2.91951615e-01   5.46684064e-01   9.48980732e-01
    6.64767781e-01   5.67475644e-01   5.09257465e-01   3.56680706e-01
    7.22255973e-01   9.11089785e-01]
 [  3.21182533e-01   9.16638588e-01   6.76410717e-01   9.41517597e-01
    7.85639509e-01   8.48501654e-01   5.99196471e-01   1.58926672e-01
    4.34277230e-01   4.16950439e-01   2.51455848e-01   7.95457231e-01
    9.76156840e-02   1.74863285e-01   4.90367785e-02   6.05955463e-01
    9.26109633e-01   9.07404004e-02   8.77772522e-01   8.95524862e-01
    2.89990588e-01   8.86465212e-01   5.65386924e-01   5.22506072e-01
    8.04800048e-01   9.58401188e-01   8.76650733e-01   4.36407544e-01
    4.35897366e-01   4.21282791e-02]
 [  6.21116836e-01   8.07177698e-01   1.99283616e-01   7.16818426e-01
    6.30444834e-02   7.49011209e-01   2.21690981e-01   5.44367055e-01
    5.91085937e-01   5.14665559e-01   3.68442130e-02   5.86838238e-01
    1.21144411e-01   7.09006717e-01   8.11781165e-01   7.00584451e-01
    7.89617766e-01   4.06169539e-01   5.14643019e-02   4.44259476e-01
    6.31164737e-01   4.20459160e-01   9.42240139e-01   8.30847879e-01
    9.18140543e-01   3.81760300e-01   7.92373991e-01   2.31860280e-01
    9.46354518e-01   3.75202416e-01]
 [  5.50930948e-01   5.08670635e-01   4.12958665e-01   4.36796314e-01
    8.26977236e-01   7.04207320e-01   8.65431131e-01   2.77627445e-02
    1.01041029e-01   8.85477001e-01   6.80298595e-01   6.85517308e-01
    3.35492988e-01   9.82730241e-01   8.55022983e-01   5.92955204e-01
    8.71390552e-01   5.31295976e-01   3.51609401e-01   7.82383030e-01
    2.29179469e-01   6.63823281e-01   7.60393628e-01   1.15952071e-01
    5.77078024e-01   6.56804462e-01   4.49028121e-01   7.76892668e-01
    5.45501189e-01   1.88388244e-01]
 [  8.93321932e-01   5.06845012e-01   4.31313349e-01   7.21035303e-01
    7.75078545e-01   4.90340136e-01   6.64095207e-01   3.14882243e-01
    5.74882474e-01   8.54914351e-02   2.29522387e-01   9.65280601e-01
    9.67513077e-01   6.25049516e-01   2.26272879e-01   5.05133084e-01
    1.24498845e-01   6.63466349e-01   6.10403864e-01   2.94241823e-01
    8.65689955e-01   4.34987399e-01   8.28707010e-01   1.01292002e-01
    3.02191420e-01   5.35683842e-01   5.56497358e-01   9.00283773e-01
    5.96933997e-01   2.31266052e-01]
 [  2.00869929e-01   6.87700525e-01   7.90943405e-01   9.10485711e-01
    7.87919712e-01   2.03655881e-01   9.75773927e-01   1.72425760e-01
    4.62551856e-01   7.22217868e-01   4.66064643e-01   3.44048626e-01
    3.41570252e-02   9.58185691e-01   1.52693097e-01   8.75948809e-01
    4.46630485e-01   5.23765262e-02   2.08511371e-01   1.35768752e-01
    7.49602964e-01   7.75047315e-01   6.87546078e-01   7.06606352e-01
    9.85517606e-01   9.11915992e-01   7.66633068e-01   2.31048238e-02
    1.08736893e-01   5.58991586e-01]
 [  2.96840541e-01   6.01733831e-01   5.62589916e-01   1.27314644e-01
    1.13768259e-01   9.50645442e-01   9.53214950e-01   2.83338887e-01
    2.95641344e-01   9.93932973e-01   4.42558575e-01   3.17861786e-01
    3.51950557e-01   8.92850899e-01   5.81888813e-01   2.10892625e-01
    4.56231395e-01   7.60233098e-01   3.59024995e-01   8.14496584e-02
    8.08914162e-01   4.89421226e-01   4.29617282e-02   5.52092487e-01
    3.00890697e-01   4.28424067e-01   6.42356021e-01   8.21989997e-01
    4.47340679e-01   8.68804071e-01]
 [  7.51434264e-02   5.52199181e-01   9.19969731e-01   8.51645064e-01
    7.51345120e-01   8.77583973e-02   9.26237637e-01   2.19150644e-01
    4.08092718e-01   8.95639695e-01   7.72171088e-01   7.81289427e-01
    2.28178777e-01   9.30077181e-01   4.19585312e-01   2.44097381e-01
    3.28357999e-01   2.78507064e-01   2.50209896e-01   6.18202201e-01
    3.76463753e-01   1.50530003e-01   1.64497915e-02   7.64922531e-01
    4.33333915e-01   2.41891409e-01   8.71962571e-01   2.44459216e-01
    6.80981330e-01   7.93827145e-02]
 [  7.15641268e-01   1.08778058e-01   1.43065234e-01   6.06117137e-02
    3.52391605e-01   4.57280126e-01   5.97049130e-02   3.38956592e-01
    7.63581333e-02   3.50854759e-02   7.00528695e-01   2.95021393e-01
    4.90013140e-01   9.30788482e-02   7.12322005e-01   9.91398196e-01
    4.53065103e-01   4.56423547e-01   6.44709211e-01   7.95039261e-01
    2.63550937e-01   8.72979053e-01   6.02756601e-01   8.20349587e-01
    4.42687363e-01   4.15039370e-01   3.77932183e-01   6.99109985e-01
    4.09672573e-01   4.39442030e-01]
 [  8.69197298e-01   9.07443285e-01   5.19416725e-01   9.11409180e-01
    9.43908561e-01   6.97959165e-01   1.01214443e-02   4.07776022e-01
    3.18161837e-01   9.69083641e-01   4.17196181e-01   5.59609874e-01
    3.56169798e-01   1.98155329e-01   3.94955679e-01   9.30078279e-01
    5.78033741e-01   2.52016826e-01   2.46647276e-01   1.51569453e-01
    3.02141955e-01   4.64109118e-01   2.67262841e-01   1.24807089e-01
    4.47991317e-02   8.13420922e-01   9.58181195e-01   6.99010660e-01
    4.07442362e-01   2.28984931e-02]
 [  6.61338041e-01   2.12272427e-01   7.64864438e-01   7.55082985e-01
    3.48673856e-01   9.78532791e-01   5.92922844e-01   6.53760924e-01
    4.69817517e-01   2.56273368e-04   2.64391029e-01   7.92326472e-01
    1.29054694e-01   9.31478284e-01   4.72295157e-01   5.25253644e-01
    3.51249557e-01   1.48566635e-01   9.30453592e-02   2.07509038e-01
    6.33090819e-01   3.62103636e-01   3.21144254e-01   2.25883439e-01
    7.75169780e-01   7.62152905e-01   6.77181513e-01   1.64748671e-02
    6.12548462e-01   4.56932476e-02]
 [  3.20290004e-01   7.27256148e-01   5.45365434e-01   1.96168627e-01
    6.85802061e-01   5.23252138e-01   4.48142896e-01   3.19309597e-01
    5.48176968e-01   2.35829729e-02   9.82867574e-01   9.08310947e-01
    5.49149903e-01   4.15238294e-01   6.05819233e-01   8.65470202e-01
    1.11739451e-01   1.08267712e-01   4.98257156e-01   3.56629471e-01
    9.41341536e-03   3.05008479e-01   8.16168413e-01   9.48102040e-02
    7.50932676e-01   6.69112363e-01   1.83362938e-01   7.82888544e-01
    8.63846310e-01   2.34528133e-01]
 [  1.84891506e-01   4.51219830e-01   5.13826310e-01   3.55793464e-01
    2.45823661e-01   7.04971589e-01   8.95052295e-01   4.17752236e-01
    7.76837959e-01   5.91999492e-01   8.72210980e-01   4.44022284e-02
    5.42007566e-01   4.16450937e-02   8.53561806e-01   2.74497127e-01
    9.72187767e-02   5.99012242e-01   1.89006935e-01   5.77265135e-01
    7.65140750e-01   3.37124472e-01   6.83048394e-01   1.87602142e-01
    2.22835564e-01   9.20850308e-01   8.17093122e-01   8.72940746e-01
    6.96461233e-01   5.18271135e-01]
 [  9.02221159e-01   1.14513931e-01   9.66066075e-01   7.88829039e-01
    1.98595990e-01   2.21929682e-01   3.09277271e-01   8.87202801e-01
    1.08053652e-01   4.16926038e-01   7.48826302e-01   7.14149846e-01
    8.80779068e-01   8.57765275e-01   2.89985384e-02   2.25838293e-01
    4.17293200e-01   1.47195080e-01   3.58288761e-01   2.04777755e-01
    6.77519956e-01   7.86149744e-01   5.92319049e-01   5.99871573e-01
    3.43204099e-01   9.27673935e-01   3.19651902e-01   8.41224156e-01
    9.88279049e-02   6.43836841e-01]
 [  3.87612342e-01   1.70807796e-01   7.67897332e-01   2.24797633e-01
    5.06193819e-01   2.14355388e-01   6.12697997e-01   6.21282240e-01
    1.59679180e-02   3.25166938e-02   6.43530600e-01   1.88851400e-01
    4.15766705e-01   4.46564746e-01   2.16015097e-01   5.10646883e-01
    3.56884165e-01   8.01031596e-01   1.66534128e-02   6.66527471e-01
    2.42282043e-01   5.17458457e-01   5.50464819e-01   7.87807608e-01
    2.23473758e-02   2.20700509e-01   1.40911197e-01   9.91758577e-01
    2.06179273e-01   1.17518816e-01]
 [  6.58991469e-01   3.59322239e-01   6.93837890e-01   8.22961009e-01
    1.67662121e-01   9.72824073e-01   4.31251898e-01   3.43954893e-01
    3.99413215e-01   4.94253122e-01   3.44591218e-01   3.72417721e-01
    8.32728611e-01   8.50708346e-01   3.95309898e-01   9.97422750e-01
    4.87806927e-01   3.05109341e-01   1.07476215e-01   6.19426820e-01
    1.11747084e-01   4.63139395e-01   5.94526626e-01   2.06573180e-01
    2.69019255e-01   7.76018961e-01   4.45196546e-01   5.71212084e-01
    8.07842839e-01   8.10271267e-01]
 [  1.06867645e-01   4.57428917e-01   4.34235980e-01   7.53264849e-01
    4.67501894e-01   1.71249448e-01   4.83651170e-01   4.57952940e-01
    9.06379678e-01   8.05780125e-01   6.73169460e-01   2.02237933e-01
    8.81433640e-01   8.84452252e-01   5.67036598e-01   7.85603011e-01
    5.79736202e-01   7.25599159e-01   2.17162139e-02   6.43593946e-02
    9.50769118e-01   2.31827468e-01   4.56015424e-01   4.73970810e-01
    1.57328571e-02   7.21381541e-01   8.92268368e-01   1.93330371e-01
    6.89074614e-02   7.65966217e-01]
 [  7.82437644e-01   2.54459673e-01   9.02079728e-01   5.67139521e-01
    4.00032868e-02   6.48205549e-02   8.93877971e-01   6.69116279e-01
    7.95481194e-01   7.01110590e-01   9.52227287e-01   9.72121243e-01
    6.04902690e-01   2.27865967e-01   7.00373041e-01   9.93682670e-01
    9.27324035e-01   5.11124077e-02   6.53801527e-01   6.58840976e-01
    1.32423431e-01   9.34313383e-01   4.72065925e-01   3.85674209e-01
    1.68735899e-02   1.67336961e-01   7.87053695e-01   1.37380024e-01
    2.59411164e-01   4.45648754e-01]
 [  4.37207188e-01   9.76078648e-01   6.41505203e-02   6.91480284e-01
    9.41067905e-01   5.78125538e-01   3.51655903e-01   1.10825699e-01
    3.59069326e-01   4.85588840e-01   7.06675832e-02   9.69198366e-01
    1.01344795e-01   5.50283930e-02   6.46080615e-01   2.32338401e-01
    3.06876012e-02   3.44350700e-01   7.84279560e-01   1.80047561e-01
    8.27848957e-01   3.69625988e-01   9.99479285e-01   6.19765981e-01
    9.09865433e-01   2.14700309e-01   4.25524239e-01   8.77926018e-01
    1.91743005e-01   4.95813013e-02]
 [  8.01118976e-01   5.32619244e-01   6.82402234e-01   3.94839305e-01
    1.89424285e-01   3.50702685e-01   3.50710334e-01   1.83442752e-01
    3.83169199e-01   1.89545667e-01   5.66477118e-01   2.23782890e-01
    9.85683773e-01   2.26306415e-01   8.49209178e-01   4.46919780e-01
    8.48461459e-01   7.64945770e-01   3.81615683e-01   1.76282819e-01
    2.68170215e-01   4.94595789e-01   2.79779765e-01   2.57003998e-02
    2.02865152e-01   1.86914371e-01   6.93042554e-01   7.86875188e-01
    5.01200649e-01   6.40610938e-01]
 [  1.20922431e-01   6.68419768e-01   9.20904816e-01   6.85238938e-01
    1.66591278e-01   9.68874299e-01   7.86469826e-01   2.00759024e-01
    9.57520976e-01   7.14797232e-01   8.42330656e-02   1.91968081e-01
    9.22140887e-02   9.71800677e-02   3.58655119e-02   4.00498931e-01
    3.56510889e-01   4.96265343e-01   9.30854095e-01   6.40885803e-01
    2.43240043e-01   3.30122315e-01   3.86542719e-01   4.18976678e-01
    6.15132760e-01   3.71951212e-01   1.22695675e-01   9.78088830e-01
    3.77961648e-01   1.16711394e-02]
 [  1.44267261e-01   3.28952740e-01   5.49040368e-01   7.15072799e-01
    5.11284135e-01   4.23522401e-01   4.64180874e-01   9.44049553e-01
    6.59293044e-01   1.24652030e-02   8.60927647e-01   4.75932952e-01
    8.70098627e-01   9.24967149e-01   9.14747851e-01   1.42456714e-01
    7.22457496e-01   3.04584552e-01   4.45504562e-01   7.97074894e-01
    8.77306560e-01   9.88679647e-01   2.07693817e-01   3.33057365e-01
    8.10846347e-01   2.02307650e-01   1.92231409e-01   6.16916762e-01
    9.93207359e-02   2.59073134e-01]]

绘制箱形图

1
2
3
4
5
6
7
import pandas as pd
df=pd.DataFrame(A)
df.boxplot()
plt.ylabel('y')
plt.xlabel('x')
plt.title('$$A$$')
plt.show()

箱型图(1)

在矩阵$$ A $$中随机选择100个数据

1
2
3
4
5
6
# 先将B转化成一维数组 B与A共享一块内存
B=A.reshape(900,)
import random
C=random.sample(range(0,901),100) # 从0-900中随机生成不重复的数字
BB=B[C] # BB即为从A中取出的100个数组成的array
print("随机选择的数据如下:\n",BB)
 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
随机选择的数据如下:
 [ 0.69383789  0.90831095  0.6740495   0.95840119  0.69441462  0.91996973
  0.72138154  0.2160151   0.60213828  0.35688416  0.76494577  0.8199681
  0.35662947  0.18489151  0.9688743   0.98867965  0.65929304  0.48365117
  0.49626534  0.50604071  0.54436706  0.95222729  0.90744328  0.20750904
  0.93095103  0.22817878  0.75326485  0.80480005  0.23728452  0.14651294
  0.77689267  0.34395489  0.21227243  0.19743605  0.80981836  0.73804086
  0.39923382  0.64383684  0.42674441  0.21438449  0.26901926  0.59225602
  0.38567421  0.77683796  0.61040386  0.14426726  0.90889211  0.51941673
  0.17486329  0.09718007  0.46750189  0.34832655  0.37646375  0.04903678
  0.99947929  0.50325604  0.39941322  0.30927727  0.19087083  0.31816184
  0.8654702   0.99368267  0.04569325  0.20286515  0.16393015  0.76514075
  0.7621529   0.5929552   0.22070051  0.84378417  0.70420732  0.8691973
  0.22630641  0.02594107  0.17628282  0.7909434   0.94898073  0.79232647
  0.35932224  0.81178116  0.22283556  0.58105806  0.96606607  0.24664728
  0.1409112   0.94296455  0.1964293   0.98286757  0.02899854  0.24582366
  0.78687519  0.74901121  0.54668406  0.01367498  0.84920918  0.82199
  0.78427956  0.58683824  0.97609146  0.38654272]

用100个2-8之间的随机数替换矩阵A中的数据

1
2
3
D=[random.randint(2,8) for i in range(100)] # 生成范围在2-8之间的随机整数 100个
B[C]=D # 替换
print("替换后的矩阵A为:\n",A)
  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
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
替换后的矩阵A为:
 [[  4.53616512e-01   8.61856377e-02   5.30296845e-01   2.40709187e-01
    3.80793044e-01   5.12444653e-01   7.76249207e-01   2.34136529e-01
    7.37731641e-01   5.32085033e-01   4.00000000e+00   5.43014312e-01
    2.55230539e-01   6.00000000e+00   5.11529807e-02   4.43609645e-01
    8.56999978e-02   1.40347620e-02   4.02022461e-02   2.00000000e+00
    3.49564773e-01   7.00000000e+00   1.55291591e-02   5.09445687e-01
    3.62207023e-01   7.20922722e-01   8.54771022e-01   6.61434389e-01
    4.86238090e-01   9.79529452e-01]
 [  8.05428682e-02   3.29047793e-01   6.43698673e-01   9.04277168e-01
    9.78384264e-01   3.37353494e-01   7.39358067e-01   3.55182658e-01
    9.89687095e-01   6.14935945e-01   6.52728677e-01   7.00000000e+00
    5.13862865e-01   9.99091787e-01   2.00922546e-01   5.76144358e-01
    2.56320016e-01   9.22332892e-01   3.08547956e-01   5.79930649e-01
    3.06355198e-01   2.61417887e-01   4.32863769e-01   4.31994524e-01
    4.83047584e-01   2.63712956e-01   8.35141356e-01   7.59380113e-01
    7.00000000e+00   3.29845339e-01]
 [  2.30571181e-01   4.00000000e+00   9.81635240e-02   7.26050569e-01
    9.63056915e-01   8.76546558e-01   5.00000000e+00   3.52611078e-01
    9.09544008e-01   6.62110762e-01   3.52487518e-01   4.00000000e+00
    4.20141358e-01   5.51120540e-01   5.02641235e-01   9.94162126e-01
    8.28955641e-01   1.58701251e-01   6.36350737e-01   9.10921055e-01
    2.07573003e-01   9.85773749e-01   3.10852943e-01   5.63833568e-01
    8.00000000e+00   7.07604940e-01   4.11989283e-01   2.11779969e-01
    2.43610690e-01   4.43425323e-01]
 [  9.99816333e-01   9.54144593e-01   9.27052004e-02   1.98800151e-01
    8.32015236e-01   3.43349579e-01   4.23569167e-01   3.93889508e-01
    7.36906066e-02   6.55602433e-02   5.05280247e-01   4.71164886e-01
    3.00000000e+00   3.85184812e-01   2.99313245e-01   9.17596868e-01
    7.00000000e+00   5.00000000e+00   1.63083626e-01   6.26927790e-01
    3.45427452e-01   4.51662512e-01   4.47094750e-01   7.28558869e-01
    5.29173761e-01   7.42919754e-01   7.75147259e-01   2.76066769e-01
    5.72056816e-01   4.06856582e-01]
 [  2.39926078e-01   4.00000000e+00   3.62383639e-01   1.16162214e-01
    9.34517505e-02   8.00000000e+00   8.00000000e+00   5.76398884e-01
    4.12430328e-01   5.14769968e-01   3.87464608e-02   6.16932645e-01
    3.74895218e-01   4.08285312e-01   8.98018119e-01   6.49249389e-01
    4.08645760e-01   6.07959661e-01   2.64660816e-01   7.15983366e-01
    7.61795316e-01   3.83236144e-01   9.32311048e-02   2.57465746e-01
    6.51411403e-01   3.91861222e-02   4.45628558e-01   6.89695145e-02
    3.32177995e-01   7.44112520e-01]
 [  6.43471306e-01   6.17741574e-01   1.55804821e-01   9.22755924e-01
    2.66214452e-01   5.46513450e-01   6.97813914e-01   9.27087146e-01
    9.36551648e-02   7.29070670e-01   9.42267932e-01   5.09140319e-01
    6.71722116e-01   4.00000000e+00   7.31127481e-01   8.97427376e-01
    5.02539040e-01   6.00000000e+00   4.86339289e-01   2.00832478e-01
    2.75863215e-01   9.49220128e-01   4.22106193e-01   4.14502322e-01
    5.10837783e-01   4.93701826e-02   1.06916975e-01   9.51495023e-01
    5.94213555e-01   6.89806343e-01]
 [  5.32218072e-02   6.02419805e-01   7.38856389e-01   9.98442237e-01
    1.56077273e-01   4.87020904e-02   3.09644991e-01   4.28412070e-01
    6.11152002e-01   2.49624942e-01   6.73371621e-01   8.84300346e-01
    3.64988087e-01   2.97069991e-01   8.91698891e-02   9.72148415e-01
    1.83263010e-01   4.77501078e-01   3.36176277e-01   7.34401939e-01
    1.50419950e-01   5.67514580e-01   5.00000000e+00   1.49284933e-01
    9.62571748e-01   6.98850409e-01   4.06660190e-01   2.66242175e-01
    7.00000000e+00   9.19230005e-02]
 [  4.92163478e-01   4.04041328e-02   8.97353508e-01   8.08023666e-01
    4.93427777e-01   5.14718018e-01   3.20256944e-01   8.87970629e-01
    1.35702605e-01   4.06703359e-01   8.20521000e-01   5.00000000e+00
    6.87990092e-01   3.12543181e-01   3.64128296e-02   1.48135257e-02
    1.27754601e-01   2.39116580e-01   3.00000000e+00   8.78382275e-01
    2.36204538e-01   9.35121634e-01   7.51336126e-01   9.92495197e-01
    9.21466098e-02   7.07920725e-01   2.91044917e-02   4.31194945e-01
    2.18753970e-01   5.00000000e+00]
 [  7.74691502e-02   7.00000000e+00   1.55214880e-01   2.11899380e-01
    3.78710508e-01   9.22175118e-01   6.00000000e+00   3.00000000e+00
    7.48140873e-01   2.35083541e-01   6.24699145e-01   8.34894787e-01
    3.82181188e-01   9.72445952e-01   1.20026772e-01   7.00000000e+00
    9.70255887e-01   2.43615320e-01   2.06208181e-01   5.44878636e-01
    3.05449030e-01   2.91951615e-01   2.00000000e+00   4.00000000e+00
    6.64767781e-01   5.67475644e-01   5.09257465e-01   3.56680706e-01
    7.22255973e-01   9.11089785e-01]
 [  3.21182533e-01   9.16638588e-01   6.76410717e-01   9.41517597e-01
    7.85639509e-01   8.48501654e-01   5.99196471e-01   1.58926672e-01
    4.34277230e-01   4.16950439e-01   2.51455848e-01   7.95457231e-01
    9.76156840e-02   4.00000000e+00   5.00000000e+00   6.05955463e-01
    9.26109633e-01   9.07404004e-02   8.77772522e-01   8.95524862e-01
    2.89990588e-01   8.86465212e-01   5.65386924e-01   5.22506072e-01
    5.00000000e+00   8.00000000e+00   8.76650733e-01   4.36407544e-01
    4.35897366e-01   4.21282791e-02]
 [  6.21116836e-01   8.07177698e-01   1.99283616e-01   7.16818426e-01
    6.30444834e-02   2.00000000e+00   2.21690981e-01   4.00000000e+00
    5.91085937e-01   5.14665559e-01   3.68442130e-02   7.00000000e+00
    1.21144411e-01   7.09006717e-01   5.00000000e+00   7.00584451e-01
    7.89617766e-01   4.06169539e-01   5.14643019e-02   4.44259476e-01
    6.31164737e-01   4.20459160e-01   9.42240139e-01   8.30847879e-01
    9.18140543e-01   3.81760300e-01   7.92373991e-01   2.31860280e-01
    9.46354518e-01   3.75202416e-01]
 [  5.50930948e-01   5.08670635e-01   4.12958665e-01   4.36796314e-01
    8.26977236e-01   5.00000000e+00   8.65431131e-01   2.77627445e-02
    1.01041029e-01   8.85477001e-01   6.80298595e-01   6.85517308e-01
    3.35492988e-01   9.82730241e-01   8.55022983e-01   2.00000000e+00
    8.71390552e-01   5.31295976e-01   3.51609401e-01   7.82383030e-01
    2.29179469e-01   6.63823281e-01   7.60393628e-01   1.15952071e-01
    5.77078024e-01   6.56804462e-01   4.49028121e-01   4.00000000e+00
    5.45501189e-01   1.88388244e-01]
 [  8.93321932e-01   5.06845012e-01   4.31313349e-01   7.21035303e-01
    7.75078545e-01   4.90340136e-01   6.64095207e-01   3.14882243e-01
    5.74882474e-01   8.54914351e-02   2.29522387e-01   9.65280601e-01
    9.67513077e-01   6.25049516e-01   2.26272879e-01   5.05133084e-01
    1.24498845e-01   6.63466349e-01   5.00000000e+00   2.94241823e-01
    8.65689955e-01   4.34987399e-01   8.28707010e-01   1.01292002e-01
    3.02191420e-01   5.35683842e-01   5.56497358e-01   9.00283773e-01
    5.96933997e-01   2.31266052e-01]
 [  2.00869929e-01   6.87700525e-01   7.00000000e+00   9.10485711e-01
    7.87919712e-01   2.03655881e-01   9.75773927e-01   1.72425760e-01
    4.62551856e-01   7.22217868e-01   4.66064643e-01   3.44048626e-01
    3.41570252e-02   9.58185691e-01   1.52693097e-01   8.75948809e-01
    4.46630485e-01   5.23765262e-02   2.08511371e-01   1.35768752e-01
    7.49602964e-01   7.75047315e-01   6.87546078e-01   7.06606352e-01
    9.85517606e-01   9.11915992e-01   7.66633068e-01   2.31048238e-02
    1.08736893e-01   5.58991586e-01]
 [  2.96840541e-01   6.01733831e-01   5.62589916e-01   1.27314644e-01
    1.13768259e-01   9.50645442e-01   9.53214950e-01   2.83338887e-01
    2.95641344e-01   9.93932973e-01   4.42558575e-01   3.17861786e-01
    3.51950557e-01   8.92850899e-01   5.81888813e-01   2.10892625e-01
    4.56231395e-01   7.60233098e-01   3.59024995e-01   8.14496584e-02
    8.08914162e-01   4.89421226e-01   4.29617282e-02   5.52092487e-01
    3.00890697e-01   4.28424067e-01   6.42356021e-01   5.00000000e+00
    4.47340679e-01   8.68804071e-01]
 [  7.51434264e-02   5.52199181e-01   8.00000000e+00   8.51645064e-01
    7.51345120e-01   8.77583973e-02   9.26237637e-01   2.19150644e-01
    4.08092718e-01   8.95639695e-01   7.72171088e-01   7.81289427e-01
    7.00000000e+00   9.30077181e-01   4.19585312e-01   2.44097381e-01
    3.28357999e-01   2.78507064e-01   2.50209896e-01   6.18202201e-01
    6.00000000e+00   1.50530003e-01   1.64497915e-02   7.64922531e-01
    4.33333915e-01   2.41891409e-01   8.71962571e-01   2.44459216e-01
    6.80981330e-01   7.93827145e-02]
 [  7.15641268e-01   1.08778058e-01   1.43065234e-01   6.06117137e-02
    3.52391605e-01   4.57280126e-01   5.97049130e-02   3.38956592e-01
    7.63581333e-02   3.50854759e-02   7.00528695e-01   2.95021393e-01
    4.90013140e-01   9.30788482e-02   7.12322005e-01   9.91398196e-01
    4.53065103e-01   4.56423547e-01   6.44709211e-01   7.95039261e-01
    2.63550937e-01   8.72979053e-01   6.02756601e-01   8.20349587e-01
    4.42687363e-01   4.15039370e-01   3.77932183e-01   6.99109985e-01
    4.09672573e-01   4.39442030e-01]
 [  6.00000000e+00   8.00000000e+00   6.00000000e+00   9.11409180e-01
    9.43908561e-01   6.97959165e-01   1.01214443e-02   4.07776022e-01
    5.00000000e+00   9.69083641e-01   4.17196181e-01   5.59609874e-01
    3.56169798e-01   1.98155329e-01   3.94955679e-01   9.30078279e-01
    5.78033741e-01   2.52016826e-01   8.00000000e+00   1.51569453e-01
    3.02141955e-01   4.64109118e-01   2.67262841e-01   1.24807089e-01
    4.47991317e-02   8.13420922e-01   9.58181195e-01   6.99010660e-01
    4.07442362e-01   2.28984931e-02]
 [  6.61338041e-01   5.00000000e+00   7.64864438e-01   7.55082985e-01
    3.48673856e-01   9.78532791e-01   5.92922844e-01   6.53760924e-01
    4.69817517e-01   2.56273368e-04   2.64391029e-01   2.00000000e+00
    1.29054694e-01   9.31478284e-01   4.72295157e-01   5.25253644e-01
    3.51249557e-01   1.48566635e-01   9.30453592e-02   5.00000000e+00
    6.33090819e-01   3.62103636e-01   3.21144254e-01   2.25883439e-01
    7.75169780e-01   5.00000000e+00   6.77181513e-01   1.64748671e-02
    6.12548462e-01   4.00000000e+00]
 [  3.20290004e-01   7.27256148e-01   5.45365434e-01   1.96168627e-01
    6.85802061e-01   5.23252138e-01   4.48142896e-01   3.19309597e-01
    5.48176968e-01   2.35829729e-02   8.00000000e+00   7.00000000e+00
    5.49149903e-01   4.15238294e-01   6.05819233e-01   6.00000000e+00
    1.11739451e-01   1.08267712e-01   4.98257156e-01   6.00000000e+00
    9.41341536e-03   3.05008479e-01   8.16168413e-01   9.48102040e-02
    7.50932676e-01   6.69112363e-01   1.83362938e-01   7.82888544e-01
    8.63846310e-01   2.34528133e-01]
 [  6.00000000e+00   4.51219830e-01   5.13826310e-01   3.55793464e-01
    2.00000000e+00   7.04971589e-01   8.95052295e-01   4.17752236e-01
    4.00000000e+00   5.91999492e-01   8.72210980e-01   4.44022284e-02
    5.42007566e-01   4.16450937e-02   8.53561806e-01   2.74497127e-01
    9.72187767e-02   5.99012242e-01   1.89006935e-01   5.77265135e-01
    2.00000000e+00   3.37124472e-01   6.83048394e-01   1.87602142e-01
    7.00000000e+00   9.20850308e-01   8.17093122e-01   8.72940746e-01
    6.96461233e-01   5.18271135e-01]
 [  9.02221159e-01   1.14513931e-01   7.00000000e+00   7.88829039e-01
    1.98595990e-01   2.21929682e-01   5.00000000e+00   8.87202801e-01
    1.08053652e-01   4.16926038e-01   7.48826302e-01   7.14149846e-01
    8.80779068e-01   8.57765275e-01   4.00000000e+00   2.25838293e-01
    4.17293200e-01   1.47195080e-01   3.58288761e-01   2.04777755e-01
    6.77519956e-01   7.86149744e-01   5.92319049e-01   5.99871573e-01
    3.43204099e-01   9.27673935e-01   3.19651902e-01   8.41224156e-01
    9.88279049e-02   2.00000000e+00]
 [  3.87612342e-01   1.70807796e-01   7.67897332e-01   2.24797633e-01
    5.06193819e-01   2.14355388e-01   6.12697997e-01   6.21282240e-01
    1.59679180e-02   3.25166938e-02   6.43530600e-01   1.88851400e-01
    4.15766705e-01   4.46564746e-01   7.00000000e+00   5.10646883e-01
    5.00000000e+00   8.01031596e-01   1.66534128e-02   6.66527471e-01
    2.42282043e-01   5.17458457e-01   5.50464819e-01   7.87807608e-01
    2.23473758e-02   7.00000000e+00   6.00000000e+00   9.91758577e-01
    2.06179273e-01   1.17518816e-01]
 [  6.58991469e-01   5.00000000e+00   6.00000000e+00   8.22961009e-01
    1.67662121e-01   9.72824073e-01   4.31251898e-01   4.00000000e+00
    7.00000000e+00   4.94253122e-01   3.44591218e-01   3.72417721e-01
    8.32728611e-01   8.50708346e-01   3.95309898e-01   9.97422750e-01
    4.87806927e-01   3.05109341e-01   1.07476215e-01   6.19426820e-01
    1.11747084e-01   4.63139395e-01   5.94526626e-01   2.06573180e-01
    7.00000000e+00   7.76018961e-01   4.45196546e-01   5.71212084e-01
    8.07842839e-01   8.10271267e-01]
 [  1.06867645e-01   4.57428917e-01   4.34235980e-01   8.00000000e+00
    8.00000000e+00   1.71249448e-01   6.00000000e+00   4.57952940e-01
    9.06379678e-01   8.05780125e-01   6.73169460e-01   2.02237933e-01
    8.81433640e-01   8.84452252e-01   5.67036598e-01   7.85603011e-01
    5.79736202e-01   7.25599159e-01   2.17162139e-02   6.43593946e-02
    9.50769118e-01   2.31827468e-01   4.56015424e-01   4.73970810e-01
    1.57328571e-02   8.00000000e+00   8.92268368e-01   1.93330371e-01
    6.89074614e-02   7.65966217e-01]
 [  7.82437644e-01   2.54459673e-01   9.02079728e-01   5.67139521e-01
    4.00032868e-02   6.48205549e-02   8.93877971e-01   6.69116279e-01
    7.95481194e-01   7.01110590e-01   3.00000000e+00   9.72121243e-01
    6.04902690e-01   2.27865967e-01   7.00373041e-01   8.00000000e+00
    9.27324035e-01   5.11124077e-02   6.53801527e-01   6.58840976e-01
    1.32423431e-01   9.34313383e-01   4.72065925e-01   8.00000000e+00
    1.68735899e-02   1.67336961e-01   7.87053695e-01   1.37380024e-01
    2.59411164e-01   4.45648754e-01]
 [  4.37207188e-01   9.76078648e-01   6.41505203e-02   6.91480284e-01
    9.41067905e-01   5.78125538e-01   3.51655903e-01   1.10825699e-01
    3.59069326e-01   4.85588840e-01   7.06675832e-02   9.69198366e-01
    1.01344795e-01   5.50283930e-02   6.46080615e-01   2.32338401e-01
    3.06876012e-02   3.44350700e-01   5.00000000e+00   1.80047561e-01
    8.27848957e-01   3.69625988e-01   2.00000000e+00   6.19765981e-01
    9.09865433e-01   2.14700309e-01   4.25524239e-01   8.77926018e-01
    1.91743005e-01   4.95813013e-02]
 [  8.01118976e-01   5.32619244e-01   6.82402234e-01   3.94839305e-01
    1.89424285e-01   3.50702685e-01   3.50710334e-01   1.83442752e-01
    3.83169199e-01   1.89545667e-01   5.66477118e-01   2.23782890e-01
    9.85683773e-01   2.00000000e+00   5.00000000e+00   4.46919780e-01
    8.48461459e-01   8.00000000e+00   3.81615683e-01   6.00000000e+00
    2.68170215e-01   4.94595789e-01   2.79779765e-01   2.57003998e-02
    2.00000000e+00   1.86914371e-01   6.93042554e-01   8.00000000e+00
    5.01200649e-01   6.40610938e-01]
 [  1.20922431e-01   6.68419768e-01   9.20904816e-01   6.85238938e-01
    1.66591278e-01   2.00000000e+00   7.86469826e-01   2.00759024e-01
    9.57520976e-01   7.14797232e-01   8.42330656e-02   1.91968081e-01
    9.22140887e-02   4.00000000e+00   3.58655119e-02   4.00498931e-01
    3.56510889e-01   7.00000000e+00   9.30854095e-01   6.40885803e-01
    2.43240043e-01   3.30122315e-01   6.00000000e+00   4.18976678e-01
    6.15132760e-01   3.71951212e-01   1.22695675e-01   9.78088830e-01
    3.77961648e-01   1.16711394e-02]
 [  6.00000000e+00   3.28952740e-01   5.49040368e-01   7.15072799e-01
    5.11284135e-01   4.23522401e-01   4.64180874e-01   9.44049553e-01
    3.00000000e+00   1.24652030e-02   8.60927647e-01   4.75932952e-01
    8.70098627e-01   9.24967149e-01   9.14747851e-01   1.42456714e-01
    7.22457496e-01   3.04584552e-01   4.45504562e-01   7.97074894e-01
    8.77306560e-01   8.00000000e+00   2.07693817e-01   3.33057365e-01
    8.10846347e-01   2.02307650e-01   1.92231409e-01   6.16916762e-01
    9.93207359e-02   2.59073134e-01]]

重新绘制箱形图

1
2
3
4
5
6
df2=pd.DataFrame(A)
df.boxplot()
plt.ylabel('y')
plt.xlabel('x')
plt.title('$$A$$')
plt.show()

箱型图(2)

取出异常值的点

1
异常值的点就是图中用圈标记出的点

矩阵归一化(标准化)

1
2
3
4
5
print("标准化之前的矩阵A为:\n",A)
print("*"*100)
Amin,Amax=A.min(),A.max()
A=(A-Amin)/(Amax-Amin)
print("标准化后的矩阵A为:\n",A)
  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
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
标准化之前的矩阵A为:
 [[  4.53616512e-01   8.61856377e-02   5.30296845e-01   2.40709187e-01
    3.80793044e-01   5.12444653e-01   7.76249207e-01   2.34136529e-01
    7.37731641e-01   5.32085033e-01   4.00000000e+00   5.43014312e-01
    2.55230539e-01   6.00000000e+00   5.11529807e-02   4.43609645e-01
    8.56999978e-02   1.40347620e-02   4.02022461e-02   2.00000000e+00
    3.49564773e-01   7.00000000e+00   1.55291591e-02   5.09445687e-01
    3.62207023e-01   7.20922722e-01   8.54771022e-01   6.61434389e-01
    4.86238090e-01   9.79529452e-01]
 [  8.05428682e-02   3.29047793e-01   6.43698673e-01   9.04277168e-01
    9.78384264e-01   3.37353494e-01   7.39358067e-01   3.55182658e-01
    9.89687095e-01   6.14935945e-01   6.52728677e-01   7.00000000e+00
    5.13862865e-01   9.99091787e-01   2.00922546e-01   5.76144358e-01
    2.56320016e-01   9.22332892e-01   3.08547956e-01   5.79930649e-01
    3.06355198e-01   2.61417887e-01   4.32863769e-01   4.31994524e-01
    4.83047584e-01   2.63712956e-01   8.35141356e-01   7.59380113e-01
    7.00000000e+00   3.29845339e-01]
 [  2.30571181e-01   4.00000000e+00   9.81635240e-02   7.26050569e-01
    9.63056915e-01   8.76546558e-01   5.00000000e+00   3.52611078e-01
    9.09544008e-01   6.62110762e-01   3.52487518e-01   4.00000000e+00
    4.20141358e-01   5.51120540e-01   5.02641235e-01   9.94162126e-01
    8.28955641e-01   1.58701251e-01   6.36350737e-01   9.10921055e-01
    2.07573003e-01   9.85773749e-01   3.10852943e-01   5.63833568e-01
    8.00000000e+00   7.07604940e-01   4.11989283e-01   2.11779969e-01
    2.43610690e-01   4.43425323e-01]
 [  9.99816333e-01   9.54144593e-01   9.27052004e-02   1.98800151e-01
    8.32015236e-01   3.43349579e-01   4.23569167e-01   3.93889508e-01
    7.36906066e-02   6.55602433e-02   5.05280247e-01   4.71164886e-01
    3.00000000e+00   3.85184812e-01   2.99313245e-01   9.17596868e-01
    7.00000000e+00   5.00000000e+00   1.63083626e-01   6.26927790e-01
    3.45427452e-01   4.51662512e-01   4.47094750e-01   7.28558869e-01
    5.29173761e-01   7.42919754e-01   7.75147259e-01   2.76066769e-01
    5.72056816e-01   4.06856582e-01]
 [  2.39926078e-01   4.00000000e+00   3.62383639e-01   1.16162214e-01
    9.34517505e-02   8.00000000e+00   8.00000000e+00   5.76398884e-01
    4.12430328e-01   5.14769968e-01   3.87464608e-02   6.16932645e-01
    3.74895218e-01   4.08285312e-01   8.98018119e-01   6.49249389e-01
    4.08645760e-01   6.07959661e-01   2.64660816e-01   7.15983366e-01
    7.61795316e-01   3.83236144e-01   9.32311048e-02   2.57465746e-01
    6.51411403e-01   3.91861222e-02   4.45628558e-01   6.89695145e-02
    3.32177995e-01   7.44112520e-01]
 [  6.43471306e-01   6.17741574e-01   1.55804821e-01   9.22755924e-01
    2.66214452e-01   5.46513450e-01   6.97813914e-01   9.27087146e-01
    9.36551648e-02   7.29070670e-01   9.42267932e-01   5.09140319e-01
    6.71722116e-01   4.00000000e+00   7.31127481e-01   8.97427376e-01
    5.02539040e-01   6.00000000e+00   4.86339289e-01   2.00832478e-01
    2.75863215e-01   9.49220128e-01   4.22106193e-01   4.14502322e-01
    5.10837783e-01   4.93701826e-02   1.06916975e-01   9.51495023e-01
    5.94213555e-01   6.89806343e-01]
 [  5.32218072e-02   6.02419805e-01   7.38856389e-01   9.98442237e-01
    1.56077273e-01   4.87020904e-02   3.09644991e-01   4.28412070e-01
    6.11152002e-01   2.49624942e-01   6.73371621e-01   8.84300346e-01
    3.64988087e-01   2.97069991e-01   8.91698891e-02   9.72148415e-01
    1.83263010e-01   4.77501078e-01   3.36176277e-01   7.34401939e-01
    1.50419950e-01   5.67514580e-01   5.00000000e+00   1.49284933e-01
    9.62571748e-01   6.98850409e-01   4.06660190e-01   2.66242175e-01
    7.00000000e+00   9.19230005e-02]
 [  4.92163478e-01   4.04041328e-02   8.97353508e-01   8.08023666e-01
    4.93427777e-01   5.14718018e-01   3.20256944e-01   8.87970629e-01
    1.35702605e-01   4.06703359e-01   8.20521000e-01   5.00000000e+00
    6.87990092e-01   3.12543181e-01   3.64128296e-02   1.48135257e-02
    1.27754601e-01   2.39116580e-01   3.00000000e+00   8.78382275e-01
    2.36204538e-01   9.35121634e-01   7.51336126e-01   9.92495197e-01
    9.21466098e-02   7.07920725e-01   2.91044917e-02   4.31194945e-01
    2.18753970e-01   5.00000000e+00]
 [  7.74691502e-02   7.00000000e+00   1.55214880e-01   2.11899380e-01
    3.78710508e-01   9.22175118e-01   6.00000000e+00   3.00000000e+00
    7.48140873e-01   2.35083541e-01   6.24699145e-01   8.34894787e-01
    3.82181188e-01   9.72445952e-01   1.20026772e-01   7.00000000e+00
    9.70255887e-01   2.43615320e-01   2.06208181e-01   5.44878636e-01
    3.05449030e-01   2.91951615e-01   2.00000000e+00   4.00000000e+00
    6.64767781e-01   5.67475644e-01   5.09257465e-01   3.56680706e-01
    7.22255973e-01   9.11089785e-01]
 [  3.21182533e-01   9.16638588e-01   6.76410717e-01   9.41517597e-01
    7.85639509e-01   8.48501654e-01   5.99196471e-01   1.58926672e-01
    4.34277230e-01   4.16950439e-01   2.51455848e-01   7.95457231e-01
    9.76156840e-02   4.00000000e+00   5.00000000e+00   6.05955463e-01
    9.26109633e-01   9.07404004e-02   8.77772522e-01   8.95524862e-01
    2.89990588e-01   8.86465212e-01   5.65386924e-01   5.22506072e-01
    5.00000000e+00   8.00000000e+00   8.76650733e-01   4.36407544e-01
    4.35897366e-01   4.21282791e-02]
 [  6.21116836e-01   8.07177698e-01   1.99283616e-01   7.16818426e-01
    6.30444834e-02   2.00000000e+00   2.21690981e-01   4.00000000e+00
    5.91085937e-01   5.14665559e-01   3.68442130e-02   7.00000000e+00
    1.21144411e-01   7.09006717e-01   5.00000000e+00   7.00584451e-01
    7.89617766e-01   4.06169539e-01   5.14643019e-02   4.44259476e-01
    6.31164737e-01   4.20459160e-01   9.42240139e-01   8.30847879e-01
    9.18140543e-01   3.81760300e-01   7.92373991e-01   2.31860280e-01
    9.46354518e-01   3.75202416e-01]
 [  5.50930948e-01   5.08670635e-01   4.12958665e-01   4.36796314e-01
    8.26977236e-01   5.00000000e+00   8.65431131e-01   2.77627445e-02
    1.01041029e-01   8.85477001e-01   6.80298595e-01   6.85517308e-01
    3.35492988e-01   9.82730241e-01   8.55022983e-01   2.00000000e+00
    8.71390552e-01   5.31295976e-01   3.51609401e-01   7.82383030e-01
    2.29179469e-01   6.63823281e-01   7.60393628e-01   1.15952071e-01
    5.77078024e-01   6.56804462e-01   4.49028121e-01   4.00000000e+00
    5.45501189e-01   1.88388244e-01]
 [  8.93321932e-01   5.06845012e-01   4.31313349e-01   7.21035303e-01
    7.75078545e-01   4.90340136e-01   6.64095207e-01   3.14882243e-01
    5.74882474e-01   8.54914351e-02   2.29522387e-01   9.65280601e-01
    9.67513077e-01   6.25049516e-01   2.26272879e-01   5.05133084e-01
    1.24498845e-01   6.63466349e-01   5.00000000e+00   2.94241823e-01
    8.65689955e-01   4.34987399e-01   8.28707010e-01   1.01292002e-01
    3.02191420e-01   5.35683842e-01   5.56497358e-01   9.00283773e-01
    5.96933997e-01   2.31266052e-01]
 [  2.00869929e-01   6.87700525e-01   7.00000000e+00   9.10485711e-01
    7.87919712e-01   2.03655881e-01   9.75773927e-01   1.72425760e-01
    4.62551856e-01   7.22217868e-01   4.66064643e-01   3.44048626e-01
    3.41570252e-02   9.58185691e-01   1.52693097e-01   8.75948809e-01
    4.46630485e-01   5.23765262e-02   2.08511371e-01   1.35768752e-01
    7.49602964e-01   7.75047315e-01   6.87546078e-01   7.06606352e-01
    9.85517606e-01   9.11915992e-01   7.66633068e-01   2.31048238e-02
    1.08736893e-01   5.58991586e-01]
 [  2.96840541e-01   6.01733831e-01   5.62589916e-01   1.27314644e-01
    1.13768259e-01   9.50645442e-01   9.53214950e-01   2.83338887e-01
    2.95641344e-01   9.93932973e-01   4.42558575e-01   3.17861786e-01
    3.51950557e-01   8.92850899e-01   5.81888813e-01   2.10892625e-01
    4.56231395e-01   7.60233098e-01   3.59024995e-01   8.14496584e-02
    8.08914162e-01   4.89421226e-01   4.29617282e-02   5.52092487e-01
    3.00890697e-01   4.28424067e-01   6.42356021e-01   5.00000000e+00
    4.47340679e-01   8.68804071e-01]
 [  7.51434264e-02   5.52199181e-01   8.00000000e+00   8.51645064e-01
    7.51345120e-01   8.77583973e-02   9.26237637e-01   2.19150644e-01
    4.08092718e-01   8.95639695e-01   7.72171088e-01   7.81289427e-01
    7.00000000e+00   9.30077181e-01   4.19585312e-01   2.44097381e-01
    3.28357999e-01   2.78507064e-01   2.50209896e-01   6.18202201e-01
    6.00000000e+00   1.50530003e-01   1.64497915e-02   7.64922531e-01
    4.33333915e-01   2.41891409e-01   8.71962571e-01   2.44459216e-01
    6.80981330e-01   7.93827145e-02]
 [  7.15641268e-01   1.08778058e-01   1.43065234e-01   6.06117137e-02
    3.52391605e-01   4.57280126e-01   5.97049130e-02   3.38956592e-01
    7.63581333e-02   3.50854759e-02   7.00528695e-01   2.95021393e-01
    4.90013140e-01   9.30788482e-02   7.12322005e-01   9.91398196e-01
    4.53065103e-01   4.56423547e-01   6.44709211e-01   7.95039261e-01
    2.63550937e-01   8.72979053e-01   6.02756601e-01   8.20349587e-01
    4.42687363e-01   4.15039370e-01   3.77932183e-01   6.99109985e-01
    4.09672573e-01   4.39442030e-01]
 [  6.00000000e+00   8.00000000e+00   6.00000000e+00   9.11409180e-01
    9.43908561e-01   6.97959165e-01   1.01214443e-02   4.07776022e-01
    5.00000000e+00   9.69083641e-01   4.17196181e-01   5.59609874e-01
    3.56169798e-01   1.98155329e-01   3.94955679e-01   9.30078279e-01
    5.78033741e-01   2.52016826e-01   8.00000000e+00   1.51569453e-01
    3.02141955e-01   4.64109118e-01   2.67262841e-01   1.24807089e-01
    4.47991317e-02   8.13420922e-01   9.58181195e-01   6.99010660e-01
    4.07442362e-01   2.28984931e-02]
 [  6.61338041e-01   5.00000000e+00   7.64864438e-01   7.55082985e-01
    3.48673856e-01   9.78532791e-01   5.92922844e-01   6.53760924e-01
    4.69817517e-01   2.56273368e-04   2.64391029e-01   2.00000000e+00
    1.29054694e-01   9.31478284e-01   4.72295157e-01   5.25253644e-01
    3.51249557e-01   1.48566635e-01   9.30453592e-02   5.00000000e+00
    6.33090819e-01   3.62103636e-01   3.21144254e-01   2.25883439e-01
    7.75169780e-01   5.00000000e+00   6.77181513e-01   1.64748671e-02
    6.12548462e-01   4.00000000e+00]
 [  3.20290004e-01   7.27256148e-01   5.45365434e-01   1.96168627e-01
    6.85802061e-01   5.23252138e-01   4.48142896e-01   3.19309597e-01
    5.48176968e-01   2.35829729e-02   8.00000000e+00   7.00000000e+00
    5.49149903e-01   4.15238294e-01   6.05819233e-01   6.00000000e+00
    1.11739451e-01   1.08267712e-01   4.98257156e-01   6.00000000e+00
    9.41341536e-03   3.05008479e-01   8.16168413e-01   9.48102040e-02
    7.50932676e-01   6.69112363e-01   1.83362938e-01   7.82888544e-01
    8.63846310e-01   2.34528133e-01]
 [  6.00000000e+00   4.51219830e-01   5.13826310e-01   3.55793464e-01
    2.00000000e+00   7.04971589e-01   8.95052295e-01   4.17752236e-01
    4.00000000e+00   5.91999492e-01   8.72210980e-01   4.44022284e-02
    5.42007566e-01   4.16450937e-02   8.53561806e-01   2.74497127e-01
    9.72187767e-02   5.99012242e-01   1.89006935e-01   5.77265135e-01
    2.00000000e+00   3.37124472e-01   6.83048394e-01   1.87602142e-01
    7.00000000e+00   9.20850308e-01   8.17093122e-01   8.72940746e-01
    6.96461233e-01   5.18271135e-01]
 [  9.02221159e-01   1.14513931e-01   7.00000000e+00   7.88829039e-01
    1.98595990e-01   2.21929682e-01   5.00000000e+00   8.87202801e-01
    1.08053652e-01   4.16926038e-01   7.48826302e-01   7.14149846e-01
    8.80779068e-01   8.57765275e-01   4.00000000e+00   2.25838293e-01
    4.17293200e-01   1.47195080e-01   3.58288761e-01   2.04777755e-01
    6.77519956e-01   7.86149744e-01   5.92319049e-01   5.99871573e-01
    3.43204099e-01   9.27673935e-01   3.19651902e-01   8.41224156e-01
    9.88279049e-02   2.00000000e+00]
 [  3.87612342e-01   1.70807796e-01   7.67897332e-01   2.24797633e-01
    5.06193819e-01   2.14355388e-01   6.12697997e-01   6.21282240e-01
    1.59679180e-02   3.25166938e-02   6.43530600e-01   1.88851400e-01
    4.15766705e-01   4.46564746e-01   7.00000000e+00   5.10646883e-01
    5.00000000e+00   8.01031596e-01   1.66534128e-02   6.66527471e-01
    2.42282043e-01   5.17458457e-01   5.50464819e-01   7.87807608e-01
    2.23473758e-02   7.00000000e+00   6.00000000e+00   9.91758577e-01
    2.06179273e-01   1.17518816e-01]
 [  6.58991469e-01   5.00000000e+00   6.00000000e+00   8.22961009e-01
    1.67662121e-01   9.72824073e-01   4.31251898e-01   4.00000000e+00
    7.00000000e+00   4.94253122e-01   3.44591218e-01   3.72417721e-01
    8.32728611e-01   8.50708346e-01   3.95309898e-01   9.97422750e-01
    4.87806927e-01   3.05109341e-01   1.07476215e-01   6.19426820e-01
    1.11747084e-01   4.63139395e-01   5.94526626e-01   2.06573180e-01
    7.00000000e+00   7.76018961e-01   4.45196546e-01   5.71212084e-01
    8.07842839e-01   8.10271267e-01]
 [  1.06867645e-01   4.57428917e-01   4.34235980e-01   8.00000000e+00
    8.00000000e+00   1.71249448e-01   6.00000000e+00   4.57952940e-01
    9.06379678e-01   8.05780125e-01   6.73169460e-01   2.02237933e-01
    8.81433640e-01   8.84452252e-01   5.67036598e-01   7.85603011e-01
    5.79736202e-01   7.25599159e-01   2.17162139e-02   6.43593946e-02
    9.50769118e-01   2.31827468e-01   4.56015424e-01   4.73970810e-01
    1.57328571e-02   8.00000000e+00   8.92268368e-01   1.93330371e-01
    6.89074614e-02   7.65966217e-01]
 [  7.82437644e-01   2.54459673e-01   9.02079728e-01   5.67139521e-01
    4.00032868e-02   6.48205549e-02   8.93877971e-01   6.69116279e-01
    7.95481194e-01   7.01110590e-01   3.00000000e+00   9.72121243e-01
    6.04902690e-01   2.27865967e-01   7.00373041e-01   8.00000000e+00
    9.27324035e-01   5.11124077e-02   6.53801527e-01   6.58840976e-01
    1.32423431e-01   9.34313383e-01   4.72065925e-01   8.00000000e+00
    1.68735899e-02   1.67336961e-01   7.87053695e-01   1.37380024e-01
    2.59411164e-01   4.45648754e-01]
 [  4.37207188e-01   9.76078648e-01   6.41505203e-02   6.91480284e-01
    9.41067905e-01   5.78125538e-01   3.51655903e-01   1.10825699e-01
    3.59069326e-01   4.85588840e-01   7.06675832e-02   9.69198366e-01
    1.01344795e-01   5.50283930e-02   6.46080615e-01   2.32338401e-01
    3.06876012e-02   3.44350700e-01   5.00000000e+00   1.80047561e-01
    8.27848957e-01   3.69625988e-01   2.00000000e+00   6.19765981e-01
    9.09865433e-01   2.14700309e-01   4.25524239e-01   8.77926018e-01
    1.91743005e-01   4.95813013e-02]
 [  8.01118976e-01   5.32619244e-01   6.82402234e-01   3.94839305e-01
    1.89424285e-01   3.50702685e-01   3.50710334e-01   1.83442752e-01
    3.83169199e-01   1.89545667e-01   5.66477118e-01   2.23782890e-01
    9.85683773e-01   2.00000000e+00   5.00000000e+00   4.46919780e-01
    8.48461459e-01   8.00000000e+00   3.81615683e-01   6.00000000e+00
    2.68170215e-01   4.94595789e-01   2.79779765e-01   2.57003998e-02
    2.00000000e+00   1.86914371e-01   6.93042554e-01   8.00000000e+00
    5.01200649e-01   6.40610938e-01]
 [  1.20922431e-01   6.68419768e-01   9.20904816e-01   6.85238938e-01
    1.66591278e-01   2.00000000e+00   7.86469826e-01   2.00759024e-01
    9.57520976e-01   7.14797232e-01   8.42330656e-02   1.91968081e-01
    9.22140887e-02   4.00000000e+00   3.58655119e-02   4.00498931e-01
    3.56510889e-01   7.00000000e+00   9.30854095e-01   6.40885803e-01
    2.43240043e-01   3.30122315e-01   6.00000000e+00   4.18976678e-01
    6.15132760e-01   3.71951212e-01   1.22695675e-01   9.78088830e-01
    3.77961648e-01   1.16711394e-02]
 [  6.00000000e+00   3.28952740e-01   5.49040368e-01   7.15072799e-01
    5.11284135e-01   4.23522401e-01   4.64180874e-01   9.44049553e-01
    3.00000000e+00   1.24652030e-02   8.60927647e-01   4.75932952e-01
    8.70098627e-01   9.24967149e-01   9.14747851e-01   1.42456714e-01
    7.22457496e-01   3.04584552e-01   4.45504562e-01   7.97074894e-01
    8.77306560e-01   8.00000000e+00   2.07693817e-01   3.33057365e-01
    8.10846347e-01   2.02307650e-01   1.92231409e-01   6.16916762e-01
    9.93207359e-02   2.59073134e-01]]
****************************************************************************************************
标准化后的矩阵A为:
 [[ 0.05667185  0.01074151  0.06625719  0.03005758  0.04756862  0.0640256
   0.09700222  0.02923597  0.09218737  0.06648072  0.49998398  0.06784693
   0.0318728   0.74999199  0.00636229  0.05542095  0.01068081  0.00172237
   0.00499341  0.24997597  0.04366496  0.874996    0.00190917  0.06365072
   0.04524529  0.09008619  0.10681777  0.08264991  0.06074967  0.12241307]
 [ 0.01003615  0.04110026  0.08043288  0.11300623  0.12226992  0.0421385
   0.09239068  0.04436722  0.12368281  0.07683742  0.08156166  0.874996
   0.06420288  0.12485844  0.02508409  0.07198832  0.03200899  0.11526327
   0.03853769  0.07246162  0.03826359  0.03264625  0.05407767  0.05396901
   0.06035085  0.03293314  0.10436398  0.09489352  0.874996    0.04119995]
 [ 0.02879029  0.49998398  0.0122388   0.09072719  0.12035394  0.10953979
   0.62498799  0.04404576  0.11366461  0.08273446  0.04403032  0.49998398
   0.05248732  0.06886024  0.06280013  0.12424221  0.10359074  0.01980626
   0.07951436  0.11383674  0.02591542  0.12319363  0.03882583  0.07044942
   1. 0.08842142  0.05146827  0.02644131  0.03042028  0.05539791]
 [ 0.12494901  0.11923986  0.01155649  0.02481878  0.1039732   0.04288804
   0.05291581  0.04920573  0.00917959  0.00816326  0.06313002  0.05886546
   0.37497998  0.04811761  0.03738332  0.11467125  0.874996    0.62498799
   0.02035407  0.07833645  0.04314778  0.05642759  0.0558566   0.09104074
   0.0661168   0.09283591  0.09686448  0.03447742  0.07147736  0.05082667]
 [ 0.02995969  0.49998398  0.04526737  0.01448871  0.01164981  1. 1.
   0.07202013  0.05152341  0.06431627  0.00481143  0.07708702  0.04683137
   0.05100526  0.11222383  0.08112674  0.05105032  0.07596536  0.03305163
   0.08946875  0.09519543  0.04787402  0.01162223  0.03215221  0.081397
   0.00486639  0.05567332  0.00858943  0.04149154  0.09298501]
 [ 0.08040445  0.07718814  0.01944419  0.11531615  0.03324584  0.06828433
   0.0871975   0.11585757  0.01167524  0.09110472  0.11775523  0.06361254
   0.08393592  0.49998398  0.09136183  0.11214998  0.06278736  0.74999199
   0.06076232  0.02507283  0.03445197  0.11862428  0.05273293  0.05178241
   0.06382473  0.00613944  0.01333301  0.11890865  0.07424704  0.08619652]
 [ 0.0066209   0.07527285  0.09232797  0.12477724  0.01947825  0.00605592
   0.03867483  0.05352119  0.07636441  0.03117208  0.08414211  0.11050905
   0.04559294  0.0371029   0.01111456  0.12149041  0.02287657  0.05965751
   0.04199135  0.09177115  0.01877106  0.07090956  0.62498799  0.01862918
   0.12029329  0.08732706  0.05080212  0.0332493   0.874996    0.01145871]
 [ 0.06149037  0.00501864  0.11214075  0.10097416  0.06164841  0.06430978
   0.04000137  0.11096785  0.01693133  0.05080751  0.10253638  0.62498799
   0.08596948  0.03903711  0.00451971  0.00181971  0.0159378   0.02985849
   0.37497998  0.10976927  0.02949448  0.11686191  0.09388799  0.12403384
   0.01148666  0.08846089  0.00360614  0.05386906  0.02731309  0.62498799]
 [ 0.00965192  0.874996    0.01937045  0.02645624  0.04730829  0.11524355
   0.74999199  0.37497998  0.09348857  0.02935435  0.07805786  0.10433316
   0.04774214  0.1215276   0.01497179  0.874996    0.12125384  0.03042086
   0.02574481  0.06807998  0.03815032  0.03646309  0.24997597  0.49998398
   0.0830666   0.07090469  0.06362719  0.04455448  0.09025285  0.11385784]
 [ 0.04011707  0.11455146  0.08452201  0.11766143  0.09817605  0.10603407
   0.07486992  0.01983444  0.05425436  0.05208844  0.03140095  0.0994033
   0.01217032  0.49998398  0.62498799  0.07571482  0.11573538  0.01131088
   0.10969305  0.11191216  0.03621795  0.11077967  0.07064359  0.06528332
   0.62498799  1. 0.10955282  0.05452066  0.05445688  0.00523417]
 [ 0.07761006  0.10086841  0.02487921  0.08957314  0.00784878  0.24997597
   0.02768023  0.49998398  0.07385607  0.06430322  0.00457364  0.874996
   0.0151115   0.08859664  0.62498799  0.08754383  0.09867335  0.05074078
   0.00640121  0.05550218  0.07886608  0.05252704  0.11775176  0.10382728
   0.11473921  0.04768953  0.09901789  0.02895143  0.11826607  0.04686977]
 [ 0.06883654  0.06355383  0.05158945  0.05456925  0.10334343  0.62498799
   0.10815032  0.00343842  0.0125985   0.11065614  0.08500801  0.08566037
   0.04190593  0.12281318  0.10684926  0.24997597  0.10889527  0.06638209
   0.04392055  0.09776898  0.02861632  0.08294853  0.09502021  0.01446244
   0.07210503  0.08207115  0.05609828  0.49998398  0.0681578   0.02351725]
 [ 0.11163678  0.06332562  0.05388386  0.09010026  0.09685589  0.06126245
   0.08298253  0.03932951  0.07183058  0.01065474  0.02865918  0.12063191
   0.12091097  0.07810166  0.02825298  0.06311162  0.01553082  0.08290392
   0.62498799  0.03674937  0.10818268  0.05434313  0.10355966  0.01262987
   0.0377431   0.06693059  0.06953236  0.11250704  0.0745871   0.02887715]
 [ 0.02507751  0.08593328  0.874996    0.11378232  0.09846108  0.02542577
   0.12194361  0.02152188  0.0577888   0.09024809  0.05822791  0.04297542
   0.00423773  0.11974501  0.01905521  0.10946507  0.05579856  0.00651524
   0.02603272  0.0169396   0.09367134  0.09685198  0.08591398  0.08829659
   0.12316161  0.11396112  0.09580017  0.00285616  0.01356051  0.06984415]
 [ 0.03707422  0.0751871   0.07029396  0.01588281  0.01418945  0.11880245
   0.11912365  0.03538646  0.03692432  0.12421357  0.05528956  0.03970196
   0.04396319  0.1115779   0.0727064   0.02633039  0.05699872  0.09500015
   0.04484753  0.0101495   0.10108547  0.06114758  0.00533835  0.06898174
   0.03758051  0.05352269  0.08026504  0.62498799  0.05588734  0.10857195]
 [ 0.00936119  0.06899507  1. 0.10642701  0.09388911  0.01093812
   0.11575138  0.02736267  0.05098119  0.11192651  0.09649244  0.09763227
   0.874996    0.11623134  0.05241781  0.03048111  0.04101403  0.03478246
   0.0312452   0.07724572  0.74999199  0.01878482  0.00202425  0.09558634
   0.05413644  0.03020536  0.10896678  0.03052635  0.08509336  0.00989112]
 [ 0.08942599  0.01356566  0.01785169  0.00754467  0.04401833  0.05712981
   0.00743132  0.0423389   0.00951304  0.00435379  0.08753686  0.03684682
   0.06122157  0.01160319  0.08901107  0.12389671  0.05660292  0.05702274
   0.0805592   0.09935106  0.03291289  0.10909384  0.07531495  0.10251495
   0.05530566  0.05184955  0.047211    0.08735951  0.05117868  0.05489998]
 [ 0.74999199  1. 0.74999199  0.11389776  0.11796031  0.08721566
   0.00123319  0.0509416   0.62498799  0.1211073   0.05211916  0.06992144
   0.04449062  0.02473817  0.04933901  0.11623147  0.0722245   0.03147108
   1. 0.01891475  0.03773692  0.05798346  0.03337689  0.01556935
   0.00556804  0.10164884  0.11974445  0.0873471   0.05089989  0.00283037]
 [ 0.08263787  0.62498799  0.09557908  0.09435636  0.04355359  0.12228848
   0.07408569  0.0816907   0.05869704  0. 0.0330179   0.24997597
   0.01610032  0.11640648  0.05900675  0.06562677  0.04387557  0.01853939
   0.01159901  0.62498799  0.07910685  0.04523237  0.04011228  0.0282043
   0.09686729  0.62498799  0.08461837  0.00202739  0.07653898  0.49998398]
 [ 0.0400055   0.0908779   0.06814083  0.02448983  0.08569597  0.06537658
   0.05598762  0.03988294  0.06849228  0.00291593  1. 0.874996
   0.0686139   0.05187441  0.07569779  0.74999199  0.01393584  0.01350186
   0.0622521   0.74999199  0.00114468  0.03809525  0.10199228  0.01181962
   0.09383756  0.08360969  0.02288907  0.09783217  0.10795221  0.02928492]
 [ 0.74999199  0.05637225  0.06419831  0.04444357  0.24997597  0.08809224
   0.11185309  0.05218867  0.49998398  0.07397027  0.10899783  0.00551842
   0.06772108  0.00517377  0.10666661  0.0342812   0.0121207   0.07484689
   0.02359459  0.07212842  0.24997597  0.04210987  0.08535175  0.02341898
   0.874996    0.11507794  0.10210788  0.10908905  0.08702841  0.06475393]
 [ 0.11274922  0.01428266  0.874996    0.09857475  0.02479326  0.02771006
   0.62498799  0.11087187  0.0134751   0.05208539  0.09357425  0.08923956
   0.11006888  0.10719206  0.49998398  0.02819866  0.05213129  0.01836794
   0.04475549  0.025566    0.08466067  0.09823983  0.07401022  0.07495431
   0.04286985  0.11593092  0.03992573  0.10512435  0.01232185  0.24997597]
 [ 0.04842106  0.02131962  0.09595821  0.02806857  0.06324422  0.02676325
   0.07655767  0.07763073  0.00196402  0.00403268  0.08041187  0.02357515
   0.05194047  0.05579035  0.874996    0.06380087  0.62498799  0.10010012
   0.00204971  0.08328657  0.03025419  0.06465234  0.06877827  0.09844707
   0.00276148  0.874996    0.74999199  0.12394176  0.0257412   0.01465829]
 [ 0.08234454  0.62498799  0.74999199  0.10284139  0.0209264   0.12157487
   0.05387618  0.49998398  0.874996    0.06175158  0.04304325  0.04652167
   0.10406238  0.10630991  0.04938329  0.1246498   0.06094578  0.03810785
   0.01340292  0.0773988   0.0139368   0.05786224  0.07428617  0.02579044
   0.874996    0.09697344  0.05561932  0.07137176  0.10095155  0.10125512]
 [ 0.01332685  0.05714841  0.0542492   1. 1. 0.02137483
   0.74999199  0.05721392  0.11326905  0.10069371  0.08411684  0.02524852
   0.1101507   0.11052804  0.07084981  0.09817149  0.07243731  0.09067077
   0.00268258  0.00801315  0.11881791  0.02894733  0.05697172  0.05921621
   0.00193463  1. 0.11150508  0.02413504  0.00858167  0.09571681]
 [ 0.0977758   0.03177644  0.11273154  0.07086268  0.00496854  0.00807079
   0.11170629  0.08361018  0.0994063   0.0876096   0.37497998  0.12148701
   0.07558322  0.02845212  0.0875174   1. 0.11588718  0.00635722
   0.08169577  0.08232573  0.01652142  0.11676088  0.0589781   1.
   0.00207723  0.02088575  0.09835283  0.01714102  0.0323954   0.05567584]
 [ 0.05462061  0.1219817   0.00798704  0.08640577  0.11760522  0.07223597
   0.04392636  0.01382162  0.04485307  0.06066851  0.0088017   0.12112164
   0.01263647  0.00684673  0.08073063  0.0290112   0.00380404  0.04301318
   0.62498799  0.02247463  0.1034524   0.04617269  0.24997597  0.07744119
   0.11370479  0.02680636  0.0531602   0.10971223  0.02393661  0.00616583]
 [ 0.10011104  0.0665475   0.08527098  0.04932446  0.02364676  0.0438072
   0.04380816  0.02289904  0.04786565  0.02366193  0.07077987  0.02794172
   0.12318238  0.24997597  0.62498799  0.05583473  0.10602904  1.
   0.04767145  0.74999199  0.03349032  0.06179442  0.03494156  0.00318062
   0.24997597  0.02333301  0.08660106  1. 0.06262005  0.0800469 ]
 [ 0.01508375  0.08352311  0.11508475  0.08562558  0.02079254  0.24997597
   0.09827984  0.02506365  0.11966192  0.08932048  0.01049744  0.02396474
   0.0114951   0.49998398  0.0044513   0.05003193  0.04453325  0.874996
   0.11632845  0.08008126  0.03037394  0.04123458  0.74999199  0.05234173
   0.07686202  0.04646336  0.01530542  0.12223299  0.04721468  0.0014269 ]
 [ 0.74999199  0.04108837  0.06860021  0.08935493  0.06388053  0.05290996
   0.05799243  0.11797794  0.37497998  0.00152617  0.10758737  0.05946149
   0.10873378  0.11559256  0.11431511  0.01777562  0.09027804  0.03804225
   0.05565782  0.09960552  0.1096348   1. 0.02593052  0.04160147
   0.10132701  0.02525723  0.02399766  0.07708503  0.01238345  0.03235314]]