diff --git a/README.md b/README.md
index 37bcb85170c148361142a5ae9fc8ad7c44d26efc..f75ef97deaefb0e2d68112ad2ebf084d913c2d77 100644
--- a/README.md
+++ b/README.md
@@ -172,7 +172,7 @@ nAUC aWallace2 0.999118 [0.996141 , 1.000000]
The clustering based on the cutoff 0.007 seems robust to data subsampling, as the three estimated nAUC are quite high (e.g. > 0.75).
However, the same clustering seems less robust to data perturbation, as the 2.5% CI are quite small for the silhouette and the first Wallace coefficient, e.g. < 0.4.
-**Searching for optimal clustering**
+**Searching for optimal clustering(s)**
An optimal MST-based clustering can be defined by the cutoff value that maximizes the different estimated statistics.
By considering every branch length from the minimum spanning tree in _data.graphml_ (see above) as a putative cutoff, _MSTclust_ can be used to display in standard output these statistics in a convenient tab-delimited format (option `-t`):
@@ -180,18 +180,37 @@ By considering every branch length from the minimum spanning tree in _data.graph
grep "data" data.graphml | awk -F '[<>]' '{print$3}' | sort -g | uniq |
while read c ; do MSTclust -i data.d -o out -c $c -L 2038 -B 9 -t ; done 2>/dev/null
```
-After observing the different outputted statistics (not shown), it seems that an optimal clustering can be obtained using
-0.016691213 as cutoff.
+After observing the different outputted statistics (not shown), it seems that an optimal clustering can be obtained using a cutoff between 0.010060363 (approx. 20/2038) and 0.048804782 (approx. 100/2038).
+_MSTclust_ can be used again to display the statistics associated to the clustering built from each of these cutoff:
+```bash
+for i in {20..100}
+do
+ c=0$(bc<<<"scale=9;$i/2038"); MSTclust -i data.d -o out -c $c -L 2038 -B 9 -t ;
+done 2>/dev/null
+```
+This second set of tab-delimited statistics (not shown) demonstrates that using 0.03581943 as cutoff yields an optimal MST-based clustering (i.e. that maximizes all statistics derived from data perturbation and subsampling analyses).
This can be summarized using the following command line:
```bash
-MSTclust -i data.d -o clust -c 0.016691213 -L 2038 -B 9 -t 2>&1 | tail -2
+MSTclust -i data.d -o clust -c 0.03581943 -L 2038 -B 9 -t 2>&1 | tail -2
+```
+This will output:
+```
+n c k silhouette noise silhouette [low avg up] noise aWallace1 [low avg up] noise aWallace2 [low avg up] nAUC silhouette [low avg up] nAUC aWallace1 [low avg up] nAUC aWallace2 [low avg up]
+413 0.035819430 2 0.889605 0.851100 0.892771 0.923340 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 0.747542 0.894428 0.952076 1.000000 1.000000 1.000000 1.000000 0.997500 1.000000
+```
+
+Of note, previous analyses also show that the cutoff value 0.016192345 leads to a clear local optimum between 0.009813542 (20/2038) and 0.049067713 (100/2048).
+In consequence, the corresponding MST-based clustering can be also considered if the number of classes obtained from the optimal one (i.e. _k_ = 2, see above) is found to be too small.
+This second clustering can be summarized using the following command line:
+```bash
+MSTclust -i data.d -o clust -c 0.016192345 -L 2038 -B 9 -t 2>&1 | tail -2
```
This will output:
```
n c k silhouette noise silhouette [low avg up] noise aWallace1 [low avg up] noise aWallace2 [low avg up] nAUC silhouette [low avg up] nAUC aWallace1 [low avg up] nAUC aWallace2 [low avg up]
-413 0.016691213 3 0.829778 0.763112 0.838848 0.918818 0.444911 0.977796 1.000000 0.998107 0.999338 1.000000 0.825384 0.899548 0.938995 1.000000 1.000000 1.000000 0.828055 0.978866 1.000000
+413 0.016192345 4 0.822087 0.739681 0.828704 0.904527 0.998107 0.993513 1.000000 1.000000 1.000000 1.000000 0.869052 0.903598 0.936799 1.000000 1.000000 1.000000 0.775950 0.970570 1.000000
```
-Details of the corresponding clustering (3 classes) is written into file _clust.txt_ (available in _example/_).
+Details of the corresponding clustering (_k_ = 4 classes) is written into file _clust.txt_ (available in _example/_).
A silhouette plot can be easily drawn using the output of the following command line on _clust.txt_:
```bash
grep -F " s=" clust.txt | sed 's/ s=//' | sed 1d
diff --git a/example/clust.txt b/example/clust.txt
index b50479b2eec7aaf70efc22b44c884267fe30029e..c3d93201ede0a7bc77efee72fd59662f437efc01 100644
--- a/example/clust.txt
+++ b/example/clust.txt
@@ -1,423 +1,425 @@
# n=413
-# c=0.01669121
-# k=3
-# s=0.82977824
+# c=0.01619235
+# k=4
+# s=0.82208711
-## cluster_1 n=402 s=0.83278240
-143 s=0.89825432
-85 s=0.89815314
-37 s=0.89815145
-74 s=0.89811303
-343 s=0.89792441
-86 s=0.89785800
-396 s=0.89541756
-298 s=0.89456357
-124 s=0.89423503
-378 s=0.89408981
-98 s=0.89394730
-170 s=0.89390835
-41 s=0.89390809
-334 s=0.88770005
-322 s=0.88763977
-336 s=0.88760053
-169 s=0.88760047
-401 s=0.88760031
-157 s=0.88759993
-151 s=0.88601817
-235 s=0.88600377
-340 s=0.88598133
-226 s=0.88586892
-144 s=0.88553706
-405 s=0.88528186
-181 s=0.88523413
-191 s=0.88509641
-253 s=0.88508710
-296 s=0.88505816
-16 s=0.88505004
-408 s=0.88498494
-282 s=0.88494903
-7 s=0.88491086
-276 s=0.88491082
-66 s=0.88487400
-208 s=0.88481098
-237 s=0.88480514
-39 s=0.88430297
-153 s=0.88411530
-72 s=0.88264892
-126 s=0.88204060
-140 s=0.88143228
-252 s=0.88136205
-67 s=0.88128918
-158 s=0.88121773
-99 s=0.88118281
-73 s=0.88118281
-163 s=0.88118193
-185 s=0.88114746
-200 s=0.88111037
-15 s=0.88111037
-12 s=0.88111037
-393 s=0.88103797
-115 s=0.87568758
-364 s=0.87532500
-407 s=0.87514509
-338 s=0.87511094
-177 s=0.87507125
-192 s=0.87499870
-283 s=0.87499782
-173 s=0.87485384
-387 s=0.87481860
-374 s=0.87478150
-194 s=0.87478082
-178 s=0.87470751
-161 s=0.87359261
-76 s=0.87357888
-132 s=0.87351307
-345 s=0.87316932
-399 s=0.87313918
-81 s=0.87310261
-375 s=0.87307435
-92 s=0.87303104
-274 s=0.87255919
-6 s=0.87249452
-230 s=0.87245748
-55 s=0.87244258
-409 s=0.87242326
-406 s=0.87242326
-370 s=0.87241431
-128 s=0.87241266
-206 s=0.87241252
-290 s=0.87238702
-127 s=0.87237623
-391 s=0.87234363
-344 s=0.87231243
-278 s=0.87231170
-272 s=0.87228193
-201 s=0.87227681
-245 s=0.87226769
-295 s=0.87223913
-82 s=0.87223112
-121 s=0.87220443
-137 s=0.87220420
-232 s=0.87220357
-270 s=0.87216656
-52 s=0.87216656
-31 s=0.87215535
-179 s=0.87209883
-10 s=0.87209628
-231 s=0.87209521
-175 s=0.87203458
-47 s=0.87178727
-17 s=0.87163787
-382 s=0.87161931
-347 s=0.87110186
-389 s=0.87105454
-83 s=0.87090626
-164 s=0.86998089
-101 s=0.86978062
-119 s=0.86978012
-404 s=0.86969943
-113 s=0.86969838
-400 s=0.86917035
-380 s=0.86910031
-168 s=0.86902814
-166 s=0.86892374
-381 s=0.86892243
-352 s=0.86888720
-139 s=0.86885197
-155 s=0.86885189
-109 s=0.86878288
-122 s=0.86878133
-183 s=0.86871211
-159 s=0.86871209
-104 s=0.86871080
-216 s=0.86857762
-196 s=0.86823079
-297 s=0.86703724
-330 s=0.86660966
-78 s=0.86657057
-331 s=0.86548614
-266 s=0.86373299
-149 s=0.86322457
-142 s=0.86272856
-49 s=0.86269319
-42 s=0.86262110
-213 s=0.86258008
-280 s=0.86254361
-267 s=0.86241688
-293 s=0.86233045
-165 s=0.86222207
-285 s=0.86195927
-152 s=0.86155977
-138 s=0.86118748
-333 s=0.86111735
-383 s=0.86111599
-277 s=0.86110932
-46 s=0.86079404
-79 s=0.86057596
-148 s=0.86021880
-33 s=0.86019292
-367 s=0.86017428
-281 s=0.86013522
-392 s=0.86011796
-359 s=0.86011254
-243 s=0.86004086
-335 s=0.85996651
-18 s=0.85996132
-105 s=0.85996084
-365 s=0.85993197
-112 s=0.85989825
-372 s=0.85988819
-339 s=0.85988819
-264 s=0.85987062
-90 s=0.85982600
-304 s=0.85976483
-302 s=0.85971821
-180 s=0.85971797
-221 s=0.85968328
-217 s=0.85957884
-204 s=0.85954408
-291 s=0.85950954
-96 s=0.85940198
-107 s=0.85901557
-110 s=0.85876651
-286 s=0.85858493
-244 s=0.85829192
-303 s=0.85822478
-64 s=0.85815688
-68 s=0.85814321
-254 s=0.85806914
-141 s=0.85801638
-354 s=0.85779538
-97 s=0.85777240
-114 s=0.85763390
-398 s=0.85756234
-388 s=0.85750140
-84 s=0.85697218
-203 s=0.85695166
-133 s=0.85679821
-123 s=0.85672995
-265 s=0.85163380
-225 s=0.85161286
-316 s=0.85142122
-25 s=0.85142112
-301 s=0.85139621
-320 s=0.85138558
-269 s=0.85138553
-321 s=0.85137460
-262 s=0.85074922
-260 s=0.85058498
-14 s=0.85051893
-215 s=0.85051385
-70 s=0.85044842
-58 s=0.85044842
-40 s=0.85044412
-385 s=0.85023382
-182 s=0.85012973
-292 s=0.85009299
-284 s=0.84988056
-329 s=0.84984652
-54 s=0.84984591
-8 s=0.84938597
-299 s=0.84929314
-195 s=0.84927013
-59 s=0.84893027
-273 s=0.84882479
-38 s=0.84879064
-75 s=0.84867535
-60 s=0.84864384
-246 s=0.84853303
-50 s=0.84850404
-162 s=0.84836231
-100 s=0.84832772
-44 s=0.84829549
-186 s=0.84816327
-210 s=0.84803842
-188 s=0.84800315
-56 s=0.84797376
-35 s=0.84794210
-207 s=0.84792141
-348 s=0.84790449
-289 s=0.84788846
-51 s=0.84743654
-11 s=0.84729519
-20 s=0.84675544
-350 s=0.84646689
-271 s=0.84576159
-69 s=0.84552037
-279 s=0.84541764
-361 s=0.84528200
-116 s=0.84524732
-147 s=0.84524613
-351 s=0.84517876
-187 s=0.84516535
-222 s=0.84510934
-288 s=0.84510903
-236 s=0.84489492
-174 s=0.84486905
-341 s=0.84003932
-323 s=0.83997345
-256 s=0.83990112
-318 s=0.83989680
-319 s=0.83986228
-317 s=0.83986228
-314 s=0.83977109
-184 s=0.83976077
-403 s=0.83965524
-229 s=0.83956283
-71 s=0.83955506
-250 s=0.83953735
-197 s=0.83875174
-306 s=0.83872536
-108 s=0.83865536
-263 s=0.83841422
-189 s=0.83824859
-145 s=0.83792224
-275 s=0.83786784
-120 s=0.83756081
-355 s=0.83753576
-287 s=0.83753495
-211 s=0.83750092
-346 s=0.83744383
-369 s=0.83742965
-356 s=0.83729554
-373 s=0.83671387
-62 s=0.83593853
-368 s=0.83589778
-88 s=0.83586696
-223 s=0.83508608
-77 s=0.83481174
-353 s=0.83475770
-357 s=0.83465939
-402 s=0.83458450
-134 s=0.83411138
-363 s=0.83383968
-160 s=0.83380661
-305 s=0.83353679
-255 s=0.83350269
-146 s=0.83343447
-219 s=0.83335839
-309 s=0.82905428
-313 s=0.82894967
-315 s=0.82868625
-308 s=0.82868625
-251 s=0.82852992
-248 s=0.82846167
-247 s=0.82846130
-23 s=0.82844604
-3 s=0.82837868
-257 s=0.82837739
-342 s=0.82833741
-312 s=0.82813618
-130 s=0.82800002
-234 s=0.82799453
-167 s=0.82796398
-36 s=0.82772334
-233 s=0.82765762
-48 s=0.82762442
-95 s=0.82708935
-227 s=0.82667815
-156 s=0.82643620
-61 s=0.82594375
-94 s=0.82594231
-397 s=0.82581265
-242 s=0.82547137
-371 s=0.82508870
-80 s=0.82477636
-193 s=0.82473934
-117 s=0.82429320
-135 s=0.82415146
-240 s=0.82407542
-258 s=0.82407338
-238 s=0.82400528
-205 s=0.82394608
-228 s=0.82362416
-45 s=0.82336730
-202 s=0.82224984
-63 s=0.82126097
-310 s=0.81835772
-307 s=0.81803689
-311 s=0.81792943
-214 s=0.81767199
-199 s=0.81741562
-241 s=0.81567181
-65 s=0.81544331
-172 s=0.81543692
-218 s=0.81543690
-377 s=0.81490001
-220 s=0.81486646
-395 s=0.81479891
-249 s=0.81458737
-13 s=0.81405246
-106 s=0.81374803
-22 s=0.81373053
-360 s=0.81322170
-136 s=0.81288298
-261 s=0.81287908
-102 s=0.81284974
-111 s=0.81275787
-198 s=0.81228949
-358 s=0.81159486
-259 s=0.81098264
-386 s=0.81075611
-24 s=0.80936262
-171 s=0.80639256
-154 s=0.80452136
-93 s=0.80445272
-376 s=0.80415445
-87 s=0.80411933
-190 s=0.80376578
-150 s=0.80154019
-212 s=0.80110144
-294 s=0.79617692
-125 s=0.79520744
-57 s=0.79316846
-89 s=0.79304017
-103 s=0.79234143
-384 s=0.79126037
-129 s=0.79106778
-43 s=0.78935000
-414 s=0.78534625
-91 s=0.78394775
-53 s=0.78361285
-366 s=0.78159332
-394 s=0.78097067
-379 s=0.77968901
-390 s=0.76884389
-26 s=0.74811280
-4 s=0.71702322
-131 s=0.69890047
-328 s=0.68702138
-30 s=0.68701967
-209 s=0.68670817
-2 s=0.66485392
-239 s=0.64841072
-411 s=0.62230583
-337 s=0.61921847
-176 s=0.61921768
-412 s=0.61529783
-325 s=0.51759181
-362 s=0.50438460
-27 s=0.47275294
-413 s=0.38401053
-349 s=0.37688457
-327 s=0.33924291
-332 s=0.31875402
-34 s=0.31348939
-32 s=0.30576043
-224 s=0.30412398
-118 s=0.27288434
+## cluster_1 n=2 s=0.97512282
+28 s=0.97527463
+21 s=0.97497102
-## cluster_2 n=5 s=0.82793797
-326 s=0.85681704
-1 s=0.83456644
-19 s=0.82185474
-410 s=0.81560084
-9 s=0.81085080
+## cluster_2 n=5 s=0.82492473
+326 s=0.85318993
+1 s=0.83225636
+19 s=0.81857605
+410 s=0.81212073
+9 s=0.80848059
-## cluster_3 n=6 s=0.63003300
-29 s=0.72546691
-324 s=0.72546498
-300 s=0.68082799
-268 s=0.61902163
-28 s=0.51521003
-21 s=0.51420649
+## cluster_3 n=402 s=0.82230651
+343 s=0.89160886
+143 s=0.89140390
+85 s=0.89129591
+37 s=0.89129410
+86 s=0.89125321
+74 s=0.89125309
+396 s=0.88968601
+298 s=0.88767608
+124 s=0.88732608
+378 s=0.88717137
+98 s=0.88701955
+170 s=0.88697805
+41 s=0.88697795
+334 s=0.88026518
+322 s=0.88018911
+169 s=0.88014720
+401 s=0.88014703
+336 s=0.88014689
+157 s=0.88014682
+151 s=0.87845998
+235 s=0.87843625
+340 s=0.87842069
+237 s=0.87838037
+226 s=0.87830083
+144 s=0.87794716
+405 s=0.87767503
+181 s=0.87762414
+208 s=0.87748017
+191 s=0.87747729
+253 s=0.87746736
+296 s=0.87743650
+16 s=0.87742785
+408 s=0.87735842
+282 s=0.87732013
+7 s=0.87727943
+276 s=0.87727939
+66 s=0.87724013
+153 s=0.87665634
+39 s=0.87651322
+72 s=0.87509538
+126 s=0.87444809
+140 s=0.87380062
+252 s=0.87372568
+393 s=0.87368855
+67 s=0.87364831
+158 s=0.87357226
+99 s=0.87353490
+73 s=0.87353490
+163 s=0.87353416
+185 s=0.87349747
+200 s=0.87345800
+15 s=0.87345800
+12 s=0.87345800
+115 s=0.86756724
+364 s=0.86718077
+407 s=0.86698890
+338 s=0.86695252
+177 s=0.86691045
+192 s=0.86683316
+283 s=0.86683242
+173 s=0.86667883
+387 s=0.86664108
+374 s=0.86660156
+194 s=0.86660125
+178 s=0.86652315
+76 s=0.86532017
+132 s=0.86525068
+161 s=0.86521048
+345 s=0.86487452
+399 s=0.86485237
+81 s=0.86481320
+375 s=0.86478331
+92 s=0.86473675
+55 s=0.86444480
+370 s=0.86432039
+272 s=0.86427449
+274 s=0.86423450
+6 s=0.86416560
+230 s=0.86412530
+409 s=0.86408969
+406 s=0.86408969
+128 s=0.86407839
+206 s=0.86407824
+290 s=0.86405087
+127 s=0.86403959
+175 s=0.86401164
+391 s=0.86400465
+10 s=0.86398240
+344 s=0.86397161
+278 s=0.86397084
+201 s=0.86393368
+245 s=0.86392395
+295 s=0.86389353
+82 s=0.86388499
+137 s=0.86385611
+121 s=0.86385593
+232 s=0.86385565
+270 s=0.86381622
+52 s=0.86381622
+179 s=0.86374386
+231 s=0.86374021
+31 s=0.86367791
+17 s=0.86349490
+47 s=0.86328542
+347 s=0.86255479
+389 s=0.86250432
+83 s=0.86234599
+119 s=0.86185095
+101 s=0.86184569
+382 s=0.86175311
+164 s=0.86173260
+404 s=0.86143349
+113 s=0.86143237
+400 s=0.86087085
+380 s=0.86079636
+168 s=0.86071962
+166 s=0.86060838
+381 s=0.86060720
+216 s=0.86057523
+352 s=0.86056973
+139 s=0.86053227
+155 s=0.86053218
+109 s=0.86045880
+122 s=0.86045715
+183 s=0.86038354
+159 s=0.86038352
+104 s=0.86038214
+330 s=0.85893703
+78 s=0.85889613
+297 s=0.85847904
+196 s=0.85840290
+331 s=0.85682767
+266 s=0.85511650
+149 s=0.85442097
+142 s=0.85389258
+49 s=0.85385516
+42 s=0.85377866
+213 s=0.85373500
+280 s=0.85369617
+267 s=0.85358959
+293 s=0.85346907
+165 s=0.85335394
+285 s=0.85265204
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+138 s=0.85225276
+333 s=0.85217811
+383 s=0.85217667
+46 s=0.85183377
+79 s=0.85160188
+367 s=0.85142954
+281 s=0.85138848
+148 s=0.85122173
+335 s=0.85120900
+18 s=0.85120371
+33 s=0.85119395
+392 s=0.85111440
+359 s=0.85110817
+304 s=0.85110115
+152 s=0.85107995
+96 s=0.85107945
+243 s=0.85103210
+302 s=0.85094517
+180 s=0.85094515
+365 s=0.85091644
+221 s=0.85090828
+112 s=0.85088054
+372 s=0.85086984
+339 s=0.85086984
+264 s=0.85085045
+105 s=0.85081227
+90 s=0.85080365
+217 s=0.85079731
+204 s=0.85076038
+291 s=0.85072323
+68 s=0.85034890
+107 s=0.84980618
+286 s=0.84961369
+254 s=0.84954910
+110 s=0.84954063
+303 s=0.84935834
+64 s=0.84928619
+141 s=0.84913668
+244 s=0.84903503
+388 s=0.84895880
+354 s=0.84891336
+97 s=0.84887767
+114 s=0.84873028
+398 s=0.84865470
+203 s=0.84836477
+84 s=0.84802763
+133 s=0.84784279
+123 s=0.84777026
+25 s=0.84238841
+316 s=0.84225892
+265 s=0.84223657
+321 s=0.84222193
+269 s=0.84222153
+320 s=0.84222134
+225 s=0.84219882
+301 s=0.84196892
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+14 s=0.84103623
+215 s=0.84103083
+70 s=0.84096125
+58 s=0.84096125
+40 s=0.84095667
+292 s=0.84084928
+385 s=0.84073279
+182 s=0.84062210
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+54 s=0.84032051
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+195 s=0.83972039
+59 s=0.83934678
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+38 s=0.83919781
+75 s=0.83907546
+60 s=0.83904219
+50 s=0.83889352
+186 s=0.83880057
+162 s=0.83874255
+100 s=0.83870601
+44 s=0.83867149
+207 s=0.83854380
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+56 s=0.83832960
+35 s=0.83829593
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+8 s=0.83815255
+51 s=0.83814662
+11 s=0.83799667
+20 s=0.83689180
+350 s=0.83686538
+236 s=0.83649065
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+69 s=0.83599471
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+147 s=0.83570355
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+256 s=0.82988848
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+71 s=0.82952130
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+3 s=0.81779600
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+36 s=0.81710025
+48 s=0.81699524
+95 s=0.81685470
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+80 s=0.81568314
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+61 s=0.81521064
+94 s=0.81520941
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+45 s=0.81232121
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+63 s=0.81039113
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+199 s=0.80660864
+214 s=0.80658360
+102 s=0.80586197
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+111 s=0.80449699
+172 s=0.80436514
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+65 s=0.80421937
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+377 s=0.80364304
+395 s=0.80353608
+13 s=0.80274394
+106 s=0.80242130
+22 s=0.80224430
+358 s=0.80220616
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+386 s=0.80132683
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+136 s=0.79997909
+261 s=0.79997492
+198 s=0.79888024
+24 s=0.79536729
+171 s=0.79477821
+154 s=0.79279477
+93 s=0.79272170
+376 s=0.79240552
+87 s=0.79236830
+190 s=0.79183167
+150 s=0.79151894
+212 s=0.78746722
+294 s=0.78442669
+125 s=0.78324566
+89 s=0.78128069
+57 s=0.78092666
+103 s=0.78005033
+129 s=0.77902301
+414 s=0.77786644
+43 s=0.77721935
+384 s=0.77714127
+91 s=0.77183302
+53 s=0.77097384
+366 s=0.76900200
+394 s=0.76800691
+379 s=0.76717126
+390 s=0.75607288
+26 s=0.73076499
+4 s=0.70052798
+131 s=0.69234411
+328 s=0.66492841
+30 s=0.66492712
+209 s=0.66459363
+2 s=0.64459617
+239 s=0.62723115
+337 s=0.59603123
+176 s=0.59603102
+411 s=0.59107296
+412 s=0.58286278
+325 s=0.48589761
+362 s=0.47283060
+27 s=0.44478974
+413 s=0.32883026
+349 s=0.32738178
+327 s=0.28979633
+32 s=0.27198102
+332 s=0.27104993
+34 s=0.26617569
+224 s=0.25943749
+118 s=0.25281028
+
+## cluster_4 n=4 s=0.71997276
+29 s=0.77528778
+324 s=0.77528653
+300 s=0.69240573
+268 s=0.63691100
diff --git a/example/plot.png b/example/plot.png
index 52427e8542c7741ec89d1e1ce2137ad5830c9b7e..2bf127400371f30715a7c107b6af6592a745c595 100644
Binary files a/example/plot.png and b/example/plot.png differ