In [1]:
import numpy as np
import pandas as pd
from scipy.signal import argrelmax
In [2]:
#Read the CSV file and put it into pandas data frame
df = pd.read_csv('Polymers Plus Analytes_SNV_Reduced_SGSmoothed.csv', index_col=0)
In [3]:
#Take a quick look at the data
df
Out[3]:
200.1318
201.617
203.1022
204.5874
206.0726
207.5577
209.0429
210.5281
212.0133
213.4985
...
1986.816
1988.301
1989.786
1991.272
1992.757
1994.242
1995.727
1997.212
1998.698
2000.183
A1_C1
1.708752
1.775725
1.861025
1.941629
2.011954
2.046811
2.079291
2.112890
2.114177
2.114298
...
-0.665880
-0.656008
-0.649654
-0.641902
-0.642924
-0.636885
-0.630660
-0.626576
-0.600225
-0.613804
A1_C2
2.004295
2.006743
2.108492
2.173715
2.235133
2.287523
2.328738
2.376845
2.390796
2.400700
...
-0.708420
-0.705648
-0.697500
-0.696426
-0.689204
-0.689529
-0.689332
-0.694238
-0.690780
-0.703149
A1_C3
1.641548
1.719635
1.727123
1.780289
1.824746
1.873068
1.920712
1.953743
1.972046
1.972984
...
-0.440724
-0.441731
-0.436140
-0.433233
-0.429963
-0.419810
-0.415419
-0.413493
-0.422153
-0.422688
A1_Gly1
1.659481
1.716239
1.784938
1.847613
1.904956
1.948734
1.974711
2.006418
2.017988
2.022764
...
-0.786990
-0.788303
-0.793475
-0.792389
-0.792823
-0.793748
-0.801304
-0.803293
-0.822496
-0.826604
A1_Gly2
1.167688
1.225181
1.272517
1.320838
1.362455
1.399500
1.423343
1.449302
1.459464
1.450147
...
-1.018188
-1.009754
-1.005993
-1.001317
-1.002929
-1.002543
-1.013830
-1.013618
-1.043767
-1.012335
A1_Gly3
1.667580
1.727449
1.798728
1.832720
1.872614
1.895185
1.913762
1.931283
1.953513
1.951084
...
-1.052663
-1.058615
-1.056988
-1.057154
-1.060322
-1.060348
-1.056159
-1.058370
-1.055079
-1.065565
A1_HC1
1.213005
1.246412
1.294557
1.350900
1.414119
1.480618
1.557076
1.647480
1.727396
1.797848
...
-0.651136
-0.651901
-0.649899
-0.651513
-0.654322
-0.656268
-0.657652
-0.659916
-0.659924
-0.662043
A1_HC2
1.214321
1.250366
1.306477
1.366602
1.439891
1.518616
1.600351
1.688306
1.767251
1.833345
...
-0.669614
-0.669527
-0.670756
-0.671608
-0.673269
-0.674685
-0.675474
-0.675245
-0.672897
-0.681195
A1_HC3
1.144966
1.175299
1.241173
1.298419
1.366901
1.440046
1.517917
1.606259
1.688764
1.761680
...
-0.708548
-0.709161
-0.707377
-0.707572
-0.709099
-0.710288
-0.714087
-0.714551
-0.722282
-0.711487
A1_Ile1
2.080212
2.152591
2.180875
2.231400
2.285243
2.349542
2.394868
2.431752
2.461441
2.454932
...
-0.606310
-0.601787
-0.596811
-0.591758
-0.591364
-0.595460
-0.595208
-0.585713
-0.576605
-0.549335
A1_Ile2
2.497904
2.588654
2.629728
2.693445
2.737390
2.783184
2.818947
2.844160
2.851661
2.842934
...
-0.744714
-0.747692
-0.736922
-0.736229
-0.732720
-0.727792
-0.723185
-0.728081
-0.752789
-0.709134
A1_Ile3
1.843773
1.934465
1.953264
2.011428
2.056509
2.104142
2.151395
2.205697
2.227469
2.226187
...
-0.717272
-0.717951
-0.703682
-0.694608
-0.692060
-0.684847
-0.675930
-0.676181
-0.662299
-0.662334
A1_Phe1
1.213001
1.227603
1.308443
1.364954
1.419122
1.456064
1.493865
1.526027
1.546854
1.554699
...
-0.768946
-0.765989
-0.764601
-0.764101
-0.765451
-0.766235
-0.766378
-0.766339
-0.773450
-0.766635
A1_Phe2
1.428163
1.459969
1.539671
1.598359
1.651830
1.699517
1.735192
1.757098
1.778582
1.799640
...
-0.668539
-0.673312
-0.674053
-0.676834
-0.674994
-0.668920
-0.666232
-0.658654
-0.661206
-0.650613
A1_Phe3
1.563812
1.577121
1.645150
1.701708
1.759864
1.807987
1.856362
1.896501
1.917010
1.925464
...
-0.694087
-0.698959
-0.692347
-0.691738
-0.688455
-0.685409
-0.678736
-0.677610
-0.676467
-0.668454
A1_PP11
1.867184
1.822545
1.852295
1.855265
1.855054
1.881746
1.866032
1.863640
1.842072
1.836790
...
-0.915777
-0.900929
-0.890800
-0.894191
-0.898905
-0.905990
-0.923949
-0.930902
-0.939776
-0.921416
A1_PP12
2.822372
2.800852
2.812671
2.812050
2.812125
2.803801
2.804097
2.784388
2.759950
2.743271
...
-0.707583
-0.694670
-0.705081
-0.713193
-0.725592
-0.711798
-0.716706
-0.706635
-0.697382
-0.701405
A1_PP13
1.749527
1.770681
1.784955
1.804455
1.810886
1.809557
1.794373
1.792642
1.775503
1.767651
...
-0.957337
-0.947072
-0.937875
-0.924050
-0.921651
-0.920061
-0.924609
-0.928760
-0.946713
-0.932987
A1_SA1
1.417198
1.530497
1.589156
1.663126
1.706146
1.741557
1.774377
1.796937
1.811870
1.833364
...
-0.838260
-0.836762
-0.843309
-0.847092
-0.852731
-0.858477
-0.857943
-0.850889
-0.838261
-0.840517
A1_SA2
1.489096
1.634001
1.629703
1.687616
1.722893
1.766239
1.819158
1.856762
1.853006
1.853736
...
-0.859056
-0.863588
-0.861000
-0.855377
-0.858290
-0.855009
-0.853463
-0.858522
-0.863943
-0.881616
A1_SA3
1.688645
1.737642
1.822135
1.876374
1.927970
1.961163
1.995483
2.010958
2.028715
2.028709
...
-0.724410
-0.732390
-0.730798
-0.729488
-0.726129
-0.724036
-0.715908
-0.717865
-0.717477
-0.717128
A2_C1
0.935472
0.935841
0.908567
0.899299
0.888060
0.881056
0.877037
0.883940
0.879433
0.875926
...
-0.382418
-0.378680
-0.372909
-0.369781
-0.371126
-0.369199
-0.364311
-0.361594
-0.352687
-0.351891
A2_C2
1.158512
1.144798
1.121715
1.105654
1.093350
1.085824
1.081947
1.089141
1.091322
1.092816
...
-0.377883
-0.377993
-0.372845
-0.368990
-0.366301
-0.364235
-0.357963
-0.357411
-0.346926
-0.355019
A2_C3
0.985111
0.967353
0.945907
0.932657
0.918858
0.910982
0.903130
0.905938
0.904751
0.906540
...
-0.368778
-0.366620
-0.361434
-0.358179
-0.355562
-0.352399
-0.350112
-0.350852
-0.348430
-0.350412
A2_Gly1
-0.653039
-0.644274
-0.660734
-0.675299
-0.684295
-0.693129
-0.699082
-0.705805
-0.700840
-0.701705
...
-0.940429
-0.947496
-0.948869
-0.950410
-0.954629
-0.956604
-0.955229
-0.962084
-0.954225
-0.977703
A2_Gly2
0.071428
-0.001457
0.005733
-0.022198
-0.035514
-0.053115
-0.075821
-0.082115
-0.089870
-0.093132
...
-1.079406
-1.074151
-1.077680
-1.076815
-1.076246
-1.086893
-1.095661
-1.099941
-1.089136
-1.103185
A2_Gly3
-0.551143
-0.530746
-0.561035
-0.564277
-0.572445
-0.573582
-0.572611
-0.567570
-0.572997
-0.576791
...
-1.083314
-1.088158
-1.086930
-1.091265
-1.093413
-1.101263
-1.102511
-1.105650
-1.104230
-1.109212
A2_HC1
0.987652
0.971882
0.971590
0.959360
0.952873
0.946721
0.936687
0.939264
0.954750
0.955870
...
-1.932934
-1.937400
-1.947508
-1.952767
-1.959790
-1.965035
-1.972859
-1.974715
-1.988982
-1.978283
A2_HC2
0.998670
0.963005
0.968491
0.954208
0.949328
0.940720
0.930799
0.936607
0.948770
0.947992
...
-2.105510
-2.112495
-2.121931
-2.127573
-2.132590
-2.140614
-2.148865
-2.152174
-2.163699
-2.157480
A2_HC3
0.992058
0.935908
0.947432
0.931229
0.928147
0.917086
0.907468
0.916603
0.925011
0.922230
...
-2.250275
-2.259809
-2.268358
-2.274303
-2.277097
-2.287926
-2.296480
-2.301272
-2.309672
-2.308327
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
PMM_Phe1
0.637314
0.640142
0.624634
0.619588
0.615252
0.613673
0.613741
0.611704
0.613042
0.611226
...
-0.706864
-0.705516
-0.705839
-0.705287
-0.704553
-0.704950
-0.705582
-0.705212
-0.707699
-0.703349
PMM_Phe2
0.584885
0.592174
0.583540
0.580178
0.576687
0.568505
0.563385
0.566076
0.564192
0.562503
...
-0.709305
-0.710465
-0.710345
-0.709501
-0.709551
-0.708851
-0.706896
-0.706787
-0.704610
-0.709909
PMM_Phe3
0.905588
0.905742
0.897316
0.891288
0.885952
0.881950
0.877373
0.872003
0.870598
0.865764
...
-0.698644
-0.698240
-0.698781
-0.697496
-0.696784
-0.696348
-0.696175
-0.693508
-0.695660
-0.690233
PMM_PP11
0.815977
0.817445
0.805127
0.798517
0.795372
0.794588
0.789264
0.785491
0.783747
0.776654
...
-0.704295
-0.701602
-0.706570
-0.707906
-0.703058
-0.704698
-0.707306
-0.699635
-0.709885
-0.687870
PMM_PP12
0.517483
0.537008
0.556099
0.570079
0.572403
0.570857
0.563720
0.563614
0.559505
0.562267
...
-0.741982
-0.740173
-0.736041
-0.734968
-0.732043
-0.725712
-0.724010
-0.723341
-0.721369
-0.720603
PMM_PP13
0.587443
0.592637
0.595460
0.598090
0.599156
0.597968
0.594729
0.594277
0.591078
0.586304
...
-0.764151
-0.762880
-0.762638
-0.763273
-0.760839
-0.760261
-0.760703
-0.757790
-0.760787
-0.750308
PMM_SA1
1.047520
1.051150
1.042282
1.035403
1.029662
1.028837
1.023426
1.016776
1.012471
1.005003
...
-0.702037
-0.701128
-0.701802
-0.700713
-0.700323
-0.698723
-0.698580
-0.697397
-0.699710
-0.695959
PMM_SA2
1.021809
1.023659
1.011171
1.003713
0.996024
0.987316
0.982904
0.979772
0.977410
0.971076
...
-0.709567
-0.707675
-0.706016
-0.705607
-0.703106
-0.701051
-0.701089
-0.699318
-0.700454
-0.693500
PMM_SA3
1.052146
1.051640
1.045874
1.039358
1.031724
1.020829
1.017340
1.011720
1.005107
0.998165
...
-0.698674
-0.698771
-0.699094
-0.699773
-0.698065
-0.697214
-0.693891
-0.693740
-0.685805
-0.698983
PVA_C1
1.242274
1.249807
1.175229
1.137997
1.094611
1.073810
1.050117
1.046437
1.029770
1.009965
...
-1.201391
-1.201627
-1.197553
-1.198377
-1.198825
-1.197255
-1.185654
-1.192506
-1.156314
-1.224955
PVA_C2
1.235631
1.209775
1.134774
1.092499
1.054167
1.022297
0.991339
0.970859
0.966613
0.942636
...
-1.184168
-1.172218
-1.174408
-1.174938
-1.164382
-1.154692
-1.160359
-1.157490
-1.175720
-1.149859
PVA_C3
0.963854
0.924616
0.883383
0.846688
0.802584
0.767088
0.739365
0.728153
0.698506
0.691280
...
-1.127157
-1.128212
-1.113738
-1.109259
-1.114493
-1.108826
-1.111572
-1.116705
-1.134336
-1.131070
PVA_Gly1
-0.607385
-0.620992
-0.612369
-0.613153
-0.612634
-0.616694
-0.618716
-0.617665
-0.619355
-0.621616
...
-1.006219
-1.007851
-1.013633
-1.016920
-1.020334
-1.022367
-1.023174
-1.022556
-1.019726
-1.024835
PVA_Gly2
-0.601814
-0.595968
-0.604376
-0.602021
-0.609891
-0.620202
-0.617790
-0.622033
-0.630063
-0.630754
...
-1.003927
-1.004456
-1.007720
-1.010002
-1.014490
-1.016692
-1.021017
-1.023066
-1.023837
-1.027022
PVA_Gly3
-0.452498
-0.462984
-0.473169
-0.482157
-0.485942
-0.489088
-0.489010
-0.486775
-0.482844
-0.482932
...
-0.995383
-0.997011
-0.994097
-0.997257
-0.996517
-0.997953
-0.999410
-1.004793
-1.006402
-1.006947
PVA_HC1
1.464512
1.434199
1.408893
1.380138
1.343957
1.295286
1.248822
1.233347
1.187138
1.151964
...
-0.991746
-0.988324
-0.976171
-0.976306
-0.972443
-0.980980
-0.980983
-0.994746
-0.991319
-1.021694
PVA_HC2
1.348945
1.318255
1.291623
1.270819
1.247594
1.206341
1.163339
1.152631
1.111569
1.060652
...
-1.045845
-1.036696
-1.043121
-1.036662
-1.036230
-1.039325
-1.034483
-1.035646
-1.003085
-1.039469
PVA_HC3
1.885064
1.833207
1.847309
1.812597
1.794618
1.753924
1.712049
1.695128
1.673506
1.627103
...
-0.836395
-0.842685
-0.835892
-0.839715
-0.850595
-0.875873
-0.871877
-0.881899
-0.855438
-0.890074
PVA_Ile1
-0.375345
-0.375846
-0.384960
-0.387568
-0.395991
-0.397288
-0.401640
-0.403880
-0.411983
-0.417794
...
-1.136829
-1.145010
-1.145609
-1.144196
-1.144597
-1.149959
-1.142506
-1.138764
-1.127280
-1.115665
PVA_Ile2
-0.314365
-0.341121
-0.333439
-0.338621
-0.337549
-0.332423
-0.332970
-0.338416
-0.348358
-0.362183
...
-1.102612
-1.110711
-1.105837
-1.111824
-1.116344
-1.118632
-1.118101
-1.128548
-1.122982
-1.141953
PVA_Ile3
-0.385842
-0.350116
-0.364217
-0.362592
-0.371954
-0.374341
-0.375951
-0.385336
-0.392176
-0.396795
...
-1.122817
-1.116168
-1.118268
-1.127309
-1.125500
-1.124147
-1.129069
-1.131169
-1.133502
-1.141346
PVA_Phe1
-0.272667
-0.269867
-0.264444
-0.229406
-0.180450
-0.148743
-0.142760
-0.124634
-0.136315
-0.150088
...
-1.416184
-1.411030
-1.397035
-1.382608
-1.389395
-1.378877
-1.355233
-1.312524
-1.271868
-1.194295
PVA_Phe2
2.363550
2.207461
2.317818
2.288079
2.271639
2.225172
2.195966
2.159052
2.140546
2.121082
...
-1.298287
-1.302106
-1.303517
-1.298750
-1.297036
-1.298075
-1.294786
-1.288387
-1.274496
-1.307482
PVA_Phe3
0.273473
0.234172
0.247412
0.246188
0.284616
0.301562
0.289314
0.297310
0.296798
0.244532
...
-1.225612
-1.213098
-1.215280
-1.214623
-1.194341
-1.175907
-1.180645
-1.169926
-1.157723
-1.193575
PVA_PP11
2.238753
2.080170
2.117835
2.103226
2.100747
2.073809
2.061385
2.065248
2.074209
2.062846
...
-0.492153
-0.486639
-0.463717
-0.457328
-0.435389
-0.430261
-0.407883
-0.400925
-0.382799
-0.398639
PVA_PP12
2.218166
2.295647
2.221981
2.226949
2.215553
2.228912
2.246386
2.257493
2.266332
2.258836
...
-0.527981
-0.508188
-0.489538
-0.478636
-0.486346
-0.494609
-0.484663
-0.458805
-0.383655
-0.350781
PVA_PP13
2.471706
2.403227
2.361165
2.345810
2.328945
2.311124
2.309179
2.320247
2.313693
2.298704
...
-0.436659
-0.440341
-0.434676
-0.447300
-0.454170
-0.460779
-0.461049
-0.456171
-0.434816
-0.418187
PVA_SA1
1.323295
0.683266
0.284972
-0.128811
-0.375680
-0.639727
-0.651162
-0.662526
-0.647574
-0.727282
...
-1.074545
-0.983329
-1.001665
-0.963746
-1.005820
-0.836067
-0.721222
-0.629321
-0.217148
-0.806796
PVA_SA2
-0.195450
-0.272446
-0.556901
-0.607554
-0.572610
-0.521734
-0.343334
-0.146715
0.067028
0.196839
...
-0.643898
-0.552079
-0.359430
-0.364149
-0.296613
-0.242602
-0.310640
-0.463915
-0.650311
-0.620332
PVA_SA3
0.456641
0.118976
-0.049270
-0.228825
-0.347664
-0.541209
-0.503154
-0.531126
-0.472973
-0.414213
...
-0.771920
-0.708351
-0.739497
-0.771137
-0.782259
-0.676197
-0.595573
-0.555224
-0.198120
-0.696176
270 rows × 1213 columns
In [4]:
# How many points on each side to use for the comparison to consider comparator(n, n+x) to be True.
neighborhood = 5
for neighborhood in range(1,10):
local_maxima = []
for i in range(df.shape[0]):
row = np.array(df.iloc[[i]])
a = argrelmax(row[0], order = neighborhood)
local_maxima.append(len(a[0]))
print("The average of local maxima with neighborsize of: %d is %.3f"%(neighborhood,np.mean(local_maxima)))
The average of local maxima with neighborsize of: 1 is 106.826
The average of local maxima with neighborsize of: 2 is 64.559
The average of local maxima with neighborsize of: 3 is 50.033
The average of local maxima with neighborsize of: 4 is 44.026
The average of local maxima with neighborsize of: 5 is 40.259
The average of local maxima with neighborsize of: 6 is 35.244
The average of local maxima with neighborsize of: 7 is 31.648
The average of local maxima with neighborsize of: 8 is 29.152
The average of local maxima with neighborsize of: 9 is 27.030
In [ ]:
Content source: sabersf/Nanomaterials
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