Matineh Rahmatbakhsh
| Snapshot Date: 2026-02-25 13:45 -0500 (Wed, 25 Feb 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_22 |
| git_last_commit: 6cf0d22 |
| git_last_commit_date: 2025-12-28 18:31:13 -0500 (Sun, 28 Dec 2025) |
| Back to Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-02-26 11:57 -0500 (Thu, 26 Feb 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4891 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 1006/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.16.1 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| See other builds for HPiP in R Universe. | ||||||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.16.1 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz |
| StartedAt: 2026-02-26 01:00:01 -0500 (Thu, 26 Feb 2026) |
| EndedAt: 2026-02-26 01:15:30 -0500 (Thu, 26 Feb 2026) |
| EllapsedTime: 929.2 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.2 (2025-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.16.1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
corr_plot 33.986 0.456 34.443
var_imp 33.127 0.602 33.731
FSmethod 32.907 0.486 33.399
pred_ensembel 12.826 0.330 11.891
enrichfindP 0.560 0.041 28.323
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘runTests.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.16.1’ ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 94.780767
iter 10 value 91.156497
iter 20 value 91.013009
final value 91.012988
converged
Fitting Repeat 2
# weights: 103
initial value 95.588394
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.022381
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.762493
final value 94.354396
converged
Fitting Repeat 5
# weights: 103
initial value 96.163172
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 102.189675
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 104.335353
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 113.202961
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 103.612584
final value 94.354396
converged
Fitting Repeat 5
# weights: 305
initial value 122.219984
final value 94.354396
converged
Fitting Repeat 1
# weights: 507
initial value 107.214534
final value 94.354396
converged
Fitting Repeat 2
# weights: 507
initial value 112.735343
iter 10 value 94.164311
final value 94.164201
converged
Fitting Repeat 3
# weights: 507
initial value 105.332419
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 101.421438
iter 10 value 93.352576
final value 93.018688
converged
Fitting Repeat 5
# weights: 507
initial value 106.845236
final value 94.354396
converged
Fitting Repeat 1
# weights: 103
initial value 108.229221
iter 10 value 94.435191
iter 20 value 88.064467
iter 30 value 87.135281
iter 40 value 86.634603
iter 50 value 85.612870
iter 60 value 85.153937
iter 70 value 85.128601
iter 80 value 85.126440
iter 80 value 85.126440
iter 80 value 85.126440
final value 85.126440
converged
Fitting Repeat 2
# weights: 103
initial value 109.836650
iter 10 value 94.486657
iter 20 value 94.343268
iter 30 value 92.040884
iter 40 value 91.769452
iter 50 value 91.763361
iter 60 value 91.762708
iter 70 value 91.762252
iter 80 value 91.367829
iter 90 value 87.635600
iter 100 value 87.026214
final value 87.026214
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 99.792845
iter 10 value 94.490681
iter 20 value 94.353410
iter 30 value 94.148993
iter 40 value 94.142598
iter 50 value 94.141380
iter 60 value 93.984264
iter 70 value 92.773254
iter 80 value 92.636866
iter 90 value 87.704903
iter 100 value 84.638350
final value 84.638350
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 115.560537
iter 10 value 95.583178
iter 20 value 94.487823
iter 30 value 94.151255
iter 40 value 93.258526
iter 50 value 91.747492
iter 60 value 88.870593
iter 70 value 88.751318
iter 80 value 84.241814
iter 90 value 83.903933
iter 100 value 83.772069
final value 83.772069
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 113.571316
iter 10 value 94.405862
iter 20 value 92.682018
iter 30 value 92.192142
iter 40 value 87.820953
iter 50 value 86.203398
iter 60 value 86.025169
iter 70 value 85.873507
iter 80 value 85.241354
iter 90 value 85.145403
iter 100 value 85.126487
final value 85.126487
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 104.519052
iter 10 value 94.573971
iter 20 value 88.774714
iter 30 value 87.840385
iter 40 value 87.333085
iter 50 value 85.390402
iter 60 value 85.109132
iter 70 value 84.603103
iter 80 value 84.117653
iter 90 value 83.463045
iter 100 value 83.262723
final value 83.262723
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.871384
iter 10 value 94.376784
iter 20 value 86.857093
iter 30 value 86.433579
iter 40 value 85.732834
iter 50 value 83.518949
iter 60 value 82.966035
iter 70 value 82.674636
iter 80 value 82.538340
iter 90 value 82.277269
iter 100 value 81.994838
final value 81.994838
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.789916
iter 10 value 94.627764
iter 20 value 91.464799
iter 30 value 91.259775
iter 40 value 90.530283
iter 50 value 88.521853
iter 60 value 87.971304
iter 70 value 86.287069
iter 80 value 84.932289
iter 90 value 83.975768
iter 100 value 83.593606
final value 83.593606
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.458586
iter 10 value 94.502294
iter 20 value 87.721785
iter 30 value 87.547734
iter 40 value 85.019292
iter 50 value 84.556606
iter 60 value 82.128329
iter 70 value 81.659004
iter 80 value 81.339805
iter 90 value 81.208678
iter 100 value 81.019454
final value 81.019454
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.897461
iter 10 value 93.234070
iter 20 value 87.856556
iter 30 value 87.311559
iter 40 value 86.457420
iter 50 value 86.124702
iter 60 value 85.778161
iter 70 value 85.427703
iter 80 value 85.005152
iter 90 value 84.844952
iter 100 value 84.818940
final value 84.818940
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 115.515721
iter 10 value 94.762755
iter 20 value 93.512049
iter 30 value 90.587831
iter 40 value 90.371305
iter 50 value 90.102790
iter 60 value 85.324730
iter 70 value 84.422250
iter 80 value 83.782971
iter 90 value 83.228751
iter 100 value 83.111255
final value 83.111255
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.260058
iter 10 value 94.662469
iter 20 value 90.364376
iter 30 value 86.725517
iter 40 value 85.495268
iter 50 value 84.918559
iter 60 value 84.527378
iter 70 value 83.636257
iter 80 value 83.396505
iter 90 value 83.253003
iter 100 value 83.186484
final value 83.186484
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.496562
iter 10 value 94.445910
iter 20 value 91.068416
iter 30 value 87.436645
iter 40 value 85.079028
iter 50 value 84.249259
iter 60 value 84.037175
iter 70 value 83.878333
iter 80 value 83.806913
iter 90 value 83.734293
iter 100 value 83.690311
final value 83.690311
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.007887
iter 10 value 95.640402
iter 20 value 88.627772
iter 30 value 87.032003
iter 40 value 85.280535
iter 50 value 84.764779
iter 60 value 83.184267
iter 70 value 82.716199
iter 80 value 82.079244
iter 90 value 81.513449
iter 100 value 81.082570
final value 81.082570
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 126.602476
iter 10 value 88.674561
iter 20 value 86.362942
iter 30 value 84.129078
iter 40 value 83.081440
iter 50 value 82.998773
iter 60 value 82.921038
iter 70 value 82.827927
iter 80 value 82.634518
iter 90 value 82.589656
iter 100 value 82.550923
final value 82.550923
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.079144
final value 94.485759
converged
Fitting Repeat 2
# weights: 103
initial value 95.689085
final value 94.486017
converged
Fitting Repeat 3
# weights: 103
initial value 95.942061
final value 94.356085
converged
Fitting Repeat 4
# weights: 103
initial value 114.144065
iter 10 value 94.485790
iter 20 value 94.484231
iter 30 value 94.422957
iter 40 value 94.109724
final value 94.109722
converged
Fitting Repeat 5
# weights: 103
initial value 103.780341
iter 10 value 94.488321
iter 20 value 94.477688
iter 30 value 94.312555
final value 94.312198
converged
Fitting Repeat 1
# weights: 305
initial value 100.124662
final value 94.317139
converged
Fitting Repeat 2
# weights: 305
initial value 104.149367
iter 10 value 94.359762
iter 20 value 94.354640
iter 30 value 92.706558
iter 40 value 87.826253
iter 50 value 87.777827
iter 60 value 87.769807
iter 70 value 87.768225
final value 87.768181
converged
Fitting Repeat 3
# weights: 305
initial value 109.796797
iter 10 value 94.357907
iter 20 value 94.354455
iter 30 value 87.052435
iter 40 value 84.913376
iter 50 value 84.701815
iter 60 value 83.313176
iter 70 value 83.130051
iter 80 value 83.004689
iter 90 value 81.281500
iter 100 value 81.083398
final value 81.083398
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.562578
iter 10 value 94.489154
iter 20 value 94.484282
final value 94.484230
converged
Fitting Repeat 5
# weights: 305
initial value 96.616708
iter 10 value 94.486436
iter 20 value 94.476253
iter 30 value 91.441222
iter 40 value 89.808847
iter 50 value 88.479240
iter 60 value 88.478337
iter 70 value 88.476717
iter 80 value 84.851461
iter 90 value 82.985458
iter 100 value 82.967806
final value 82.967806
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.667515
iter 10 value 93.709867
iter 20 value 93.665389
iter 30 value 92.265792
iter 40 value 91.734910
iter 50 value 91.730680
final value 91.730584
converged
Fitting Repeat 2
# weights: 507
initial value 95.625280
iter 10 value 94.491976
iter 20 value 94.087378
iter 30 value 93.459184
iter 40 value 89.635049
iter 50 value 86.748883
iter 60 value 86.713476
iter 70 value 86.574175
iter 80 value 86.328468
iter 90 value 84.778293
iter 100 value 84.662611
final value 84.662611
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 119.033305
iter 10 value 92.817925
iter 20 value 92.418912
iter 30 value 92.416654
iter 40 value 92.403407
iter 50 value 91.671615
iter 60 value 91.641184
iter 70 value 91.620908
iter 80 value 91.499965
iter 90 value 89.356383
iter 100 value 89.305452
final value 89.305452
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 96.406067
iter 10 value 90.955626
iter 20 value 90.764915
iter 30 value 88.133789
iter 40 value 87.818299
final value 87.814271
converged
Fitting Repeat 5
# weights: 507
initial value 100.601652
iter 10 value 94.491942
iter 20 value 94.484231
iter 30 value 94.113744
final value 94.112621
converged
Fitting Repeat 1
# weights: 103
initial value 96.696120
final value 94.484137
converged
Fitting Repeat 2
# weights: 103
initial value 95.166500
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.016073
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 101.438634
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 97.727638
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 120.508694
final value 94.484137
converged
Fitting Repeat 2
# weights: 305
initial value 101.018874
iter 10 value 90.568544
iter 20 value 83.765345
iter 30 value 83.360677
iter 40 value 82.093026
iter 50 value 82.046625
final value 82.046622
converged
Fitting Repeat 3
# weights: 305
initial value 110.304397
iter 10 value 93.310934
final value 93.300000
converged
Fitting Repeat 4
# weights: 305
initial value 105.055847
final value 94.275362
converged
Fitting Repeat 5
# weights: 305
initial value 97.968382
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 96.603060
iter 10 value 82.852214
iter 20 value 82.144289
iter 30 value 82.120037
final value 82.119841
converged
Fitting Repeat 2
# weights: 507
initial value 104.249730
iter 10 value 93.885246
iter 20 value 90.006173
iter 30 value 89.981794
iter 40 value 89.336923
final value 89.252046
converged
Fitting Repeat 3
# weights: 507
initial value 103.546816
iter 10 value 87.364818
iter 20 value 83.807866
iter 30 value 83.794465
final value 83.794447
converged
Fitting Repeat 4
# weights: 507
initial value 121.592745
iter 10 value 91.938751
iter 20 value 91.045153
iter 30 value 90.979415
iter 40 value 90.939413
iter 50 value 90.118474
final value 89.935795
converged
Fitting Repeat 5
# weights: 507
initial value 100.588060
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 96.290177
iter 10 value 94.490393
iter 20 value 94.396093
iter 30 value 94.257572
iter 40 value 94.232589
iter 50 value 94.229800
iter 60 value 94.223560
iter 70 value 83.290902
iter 80 value 81.748256
iter 90 value 81.537575
iter 100 value 81.528853
final value 81.528853
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 100.037494
iter 10 value 94.487442
iter 20 value 92.811450
iter 30 value 86.888901
iter 40 value 85.897017
iter 50 value 85.778232
iter 60 value 84.214249
iter 70 value 82.028487
iter 80 value 81.396035
iter 90 value 81.316578
iter 100 value 81.111313
final value 81.111313
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.887102
iter 10 value 94.488265
iter 20 value 91.104510
iter 30 value 86.446706
iter 40 value 83.246508
iter 50 value 82.195038
iter 60 value 81.456909
iter 70 value 81.114463
iter 80 value 81.063723
final value 81.043388
converged
Fitting Repeat 4
# weights: 103
initial value 103.016644
iter 10 value 94.434110
iter 20 value 93.791017
iter 30 value 88.952451
iter 40 value 82.847308
iter 50 value 81.762872
iter 60 value 81.457690
iter 70 value 81.369823
iter 80 value 81.320780
iter 90 value 81.084622
iter 100 value 80.857513
final value 80.857513
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.933572
iter 10 value 94.486726
iter 20 value 93.066943
iter 30 value 86.113610
iter 40 value 82.156383
iter 50 value 81.827067
iter 60 value 81.643883
iter 70 value 81.573915
iter 80 value 81.535553
iter 90 value 81.529004
final value 81.528852
converged
Fitting Repeat 1
# weights: 305
initial value 120.836267
iter 10 value 94.493147
iter 20 value 94.302950
iter 30 value 91.438072
iter 40 value 84.626214
iter 50 value 82.285175
iter 60 value 81.212912
iter 70 value 80.081288
iter 80 value 79.870432
iter 90 value 79.695986
iter 100 value 79.466479
final value 79.466479
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.606397
iter 10 value 94.608670
iter 20 value 93.148615
iter 30 value 85.363081
iter 40 value 83.012512
iter 50 value 82.454157
iter 60 value 81.815883
iter 70 value 81.630447
iter 80 value 81.367597
iter 90 value 81.202816
iter 100 value 80.725548
final value 80.725548
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 116.205099
iter 10 value 94.454338
iter 20 value 88.465063
iter 30 value 83.651307
iter 40 value 81.227657
iter 50 value 80.629783
iter 60 value 80.533789
iter 70 value 80.489713
iter 80 value 80.276219
iter 90 value 79.950500
iter 100 value 79.482956
final value 79.482956
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.725608
iter 10 value 94.340671
iter 20 value 84.643677
iter 30 value 82.971798
iter 40 value 80.812901
iter 50 value 80.097519
iter 60 value 80.042568
iter 70 value 79.753011
iter 80 value 79.324969
iter 90 value 79.163713
iter 100 value 79.133946
final value 79.133946
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.177438
iter 10 value 94.468643
iter 20 value 92.619903
iter 30 value 89.952485
iter 40 value 88.773044
iter 50 value 88.019630
iter 60 value 87.476837
iter 70 value 83.866487
iter 80 value 81.768319
iter 90 value 80.536016
iter 100 value 80.287662
final value 80.287662
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.454229
iter 10 value 90.861295
iter 20 value 84.738778
iter 30 value 82.177344
iter 40 value 80.270545
iter 50 value 79.809772
iter 60 value 79.713370
iter 70 value 79.614626
iter 80 value 79.536779
iter 90 value 79.486059
iter 100 value 79.358292
final value 79.358292
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.367909
iter 10 value 97.024491
iter 20 value 86.805229
iter 30 value 85.598215
iter 40 value 82.387245
iter 50 value 81.698884
iter 60 value 81.389923
iter 70 value 81.233902
iter 80 value 80.534304
iter 90 value 80.002662
iter 100 value 79.919016
final value 79.919016
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.007160
iter 10 value 94.493126
iter 20 value 87.851963
iter 30 value 82.614149
iter 40 value 82.333237
iter 50 value 81.794078
iter 60 value 81.244169
iter 70 value 80.212461
iter 80 value 79.748069
iter 90 value 79.462174
iter 100 value 79.394040
final value 79.394040
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 116.846593
iter 10 value 94.585018
iter 20 value 94.317370
iter 30 value 86.439324
iter 40 value 85.471092
iter 50 value 81.578529
iter 60 value 81.014313
iter 70 value 80.907457
iter 80 value 80.878470
iter 90 value 80.870026
iter 100 value 80.769538
final value 80.769538
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.360283
iter 10 value 93.749105
iter 20 value 87.648538
iter 30 value 86.588825
iter 40 value 86.073160
iter 50 value 84.929206
iter 60 value 81.400536
iter 70 value 81.200631
iter 80 value 80.450224
iter 90 value 79.642047
iter 100 value 79.040643
final value 79.040643
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.174156
final value 94.485807
converged
Fitting Repeat 2
# weights: 103
initial value 100.018467
final value 94.485873
converged
Fitting Repeat 3
# weights: 103
initial value 99.047114
final value 94.486027
converged
Fitting Repeat 4
# weights: 103
initial value 96.993883
final value 94.485806
converged
Fitting Repeat 5
# weights: 103
initial value 97.167727
final value 94.485799
converged
Fitting Repeat 1
# weights: 305
initial value 98.164987
iter 10 value 90.401235
iter 20 value 80.918778
iter 30 value 80.855768
iter 40 value 80.854316
iter 50 value 80.853750
iter 60 value 80.852658
iter 70 value 80.851739
final value 80.851533
converged
Fitting Repeat 2
# weights: 305
initial value 111.576698
iter 10 value 93.713702
iter 20 value 93.148337
iter 30 value 93.136607
iter 40 value 86.022508
iter 50 value 84.783546
iter 60 value 84.782601
final value 84.780223
converged
Fitting Repeat 3
# weights: 305
initial value 107.405422
iter 10 value 94.543693
iter 20 value 91.395362
iter 30 value 81.892374
iter 40 value 81.845493
iter 50 value 81.830791
iter 60 value 81.202224
iter 70 value 81.198505
iter 80 value 81.197507
iter 90 value 81.197418
final value 81.197389
converged
Fitting Repeat 4
# weights: 305
initial value 109.002656
iter 10 value 85.663809
iter 20 value 85.654267
iter 30 value 85.651222
iter 40 value 85.649081
iter 50 value 84.166966
iter 60 value 82.462186
iter 70 value 81.570276
iter 80 value 81.363698
iter 90 value 81.270841
final value 81.270748
converged
Fitting Repeat 5
# weights: 305
initial value 112.318056
iter 10 value 94.489420
iter 20 value 87.823309
iter 30 value 87.700056
iter 40 value 85.652065
iter 50 value 84.534341
iter 60 value 82.574248
iter 70 value 82.502278
iter 80 value 82.501215
iter 90 value 82.328738
iter 100 value 82.327203
final value 82.327203
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 99.620635
iter 10 value 94.492761
iter 20 value 94.454612
iter 30 value 86.152031
iter 40 value 81.942109
iter 50 value 81.231132
iter 60 value 79.127422
iter 70 value 78.901971
iter 80 value 78.881794
iter 90 value 78.881598
iter 100 value 78.878519
final value 78.878519
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 99.031308
iter 10 value 86.640100
iter 20 value 84.273139
iter 30 value 84.256564
iter 40 value 82.025017
iter 50 value 81.642345
iter 60 value 81.591128
iter 70 value 81.588306
iter 80 value 81.585172
iter 90 value 81.582811
iter 100 value 81.440900
final value 81.440900
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 107.741401
iter 10 value 94.284239
iter 20 value 94.276590
final value 94.276007
converged
Fitting Repeat 4
# weights: 507
initial value 98.642218
iter 10 value 94.492190
iter 20 value 94.484993
iter 30 value 94.240894
iter 40 value 87.953608
iter 50 value 87.319833
iter 60 value 87.309716
iter 70 value 87.308887
iter 80 value 87.308763
iter 90 value 87.298488
iter 100 value 84.593449
final value 84.593449
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 97.039566
iter 10 value 94.491517
iter 20 value 94.190354
iter 30 value 87.736927
iter 40 value 81.741098
final value 81.522508
converged
Fitting Repeat 1
# weights: 103
initial value 95.410890
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 99.051011
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 94.248988
final value 93.426573
converged
Fitting Repeat 4
# weights: 103
initial value 98.783730
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 103.651540
final value 93.628453
converged
Fitting Repeat 1
# weights: 305
initial value 97.947587
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 106.552236
iter 10 value 92.341330
iter 20 value 91.916699
iter 30 value 91.916353
final value 91.897239
converged
Fitting Repeat 3
# weights: 305
initial value 100.925751
iter 10 value 94.163153
iter 20 value 93.921272
final value 93.921213
converged
Fitting Repeat 4
# weights: 305
initial value 105.849703
final value 94.052911
converged
Fitting Repeat 5
# weights: 305
initial value 108.178252
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 96.191075
iter 10 value 86.514615
iter 20 value 85.446131
iter 30 value 85.359076
iter 40 value 85.355055
iter 50 value 85.353855
final value 85.353850
converged
Fitting Repeat 2
# weights: 507
initial value 115.960718
iter 10 value 94.049875
iter 20 value 92.629341
iter 30 value 91.803872
iter 40 value 91.034348
final value 91.032039
converged
Fitting Repeat 3
# weights: 507
initial value 96.149201
final value 94.043243
converged
Fitting Repeat 4
# weights: 507
initial value 97.359720
iter 10 value 94.043245
final value 94.043243
converged
Fitting Repeat 5
# weights: 507
initial value 108.358874
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 108.597563
iter 10 value 94.058252
iter 20 value 93.001623
iter 30 value 85.831151
iter 40 value 84.830043
iter 50 value 84.321015
iter 60 value 84.186669
iter 70 value 84.164699
iter 80 value 84.145997
final value 84.145910
converged
Fitting Repeat 2
# weights: 103
initial value 98.386974
iter 10 value 94.074359
iter 20 value 92.022403
iter 30 value 91.689843
iter 40 value 91.605976
iter 50 value 91.540791
final value 91.540737
converged
Fitting Repeat 3
# weights: 103
initial value 99.537707
iter 10 value 94.025033
iter 20 value 92.745148
iter 30 value 90.886927
iter 40 value 88.628538
iter 50 value 85.595894
iter 60 value 84.971116
iter 70 value 84.799931
final value 84.795887
converged
Fitting Repeat 4
# weights: 103
initial value 99.888949
iter 10 value 89.300257
iter 20 value 87.030230
iter 30 value 84.624045
iter 40 value 83.745966
iter 50 value 83.664669
iter 60 value 83.644272
iter 70 value 83.628211
final value 83.628202
converged
Fitting Repeat 5
# weights: 103
initial value 97.885691
iter 10 value 94.056680
iter 20 value 93.972087
iter 30 value 91.277600
iter 40 value 86.497670
iter 50 value 86.226156
iter 60 value 84.749913
iter 70 value 82.210884
iter 80 value 81.891099
iter 90 value 81.659545
iter 100 value 81.520594
final value 81.520594
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 102.568330
iter 10 value 94.059876
iter 20 value 91.204447
iter 30 value 88.197929
iter 40 value 85.274391
iter 50 value 84.751307
iter 60 value 83.216458
iter 70 value 81.960995
iter 80 value 81.262719
iter 90 value 80.716281
iter 100 value 80.563219
final value 80.563219
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.831096
iter 10 value 94.041605
iter 20 value 86.662208
iter 30 value 84.989986
iter 40 value 84.694055
iter 50 value 83.554714
iter 60 value 82.247788
iter 70 value 80.682522
iter 80 value 80.524529
iter 90 value 80.404763
iter 100 value 80.215133
final value 80.215133
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.646829
iter 10 value 94.042591
iter 20 value 93.580863
iter 30 value 91.221378
iter 40 value 89.341071
iter 50 value 86.288450
iter 60 value 85.075320
iter 70 value 83.551172
iter 80 value 82.753308
iter 90 value 82.536255
iter 100 value 81.704343
final value 81.704343
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.946472
iter 10 value 97.779885
iter 20 value 87.221320
iter 30 value 83.154900
iter 40 value 81.909817
iter 50 value 81.712595
iter 60 value 81.654782
iter 70 value 80.923732
iter 80 value 80.445122
iter 90 value 80.247009
iter 100 value 80.119787
final value 80.119787
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 115.528399
iter 10 value 94.292050
iter 20 value 86.794321
iter 30 value 85.643734
iter 40 value 85.546401
iter 50 value 84.311846
iter 60 value 83.064137
iter 70 value 81.633462
iter 80 value 81.362298
iter 90 value 81.144531
iter 100 value 80.191772
final value 80.191772
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 108.564615
iter 10 value 94.150367
iter 20 value 86.347123
iter 30 value 84.493499
iter 40 value 83.111936
iter 50 value 82.558886
iter 60 value 82.446593
iter 70 value 82.052127
iter 80 value 81.943668
iter 90 value 81.762174
iter 100 value 81.630250
final value 81.630250
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 135.357155
iter 10 value 94.606169
iter 20 value 94.051124
iter 30 value 85.991739
iter 40 value 84.991507
iter 50 value 83.811932
iter 60 value 83.756755
iter 70 value 82.855495
iter 80 value 81.775754
iter 90 value 81.043649
iter 100 value 80.824826
final value 80.824826
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.996238
iter 10 value 93.990139
iter 20 value 86.727221
iter 30 value 84.087980
iter 40 value 82.558700
iter 50 value 80.963101
iter 60 value 80.907482
iter 70 value 80.443994
iter 80 value 80.224973
iter 90 value 79.987991
iter 100 value 79.893059
final value 79.893059
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.762167
iter 10 value 94.041371
iter 20 value 91.283653
iter 30 value 86.196816
iter 40 value 82.350158
iter 50 value 81.680857
iter 60 value 80.656226
iter 70 value 80.496630
iter 80 value 80.452643
iter 90 value 80.321229
iter 100 value 80.161037
final value 80.161037
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.437604
iter 10 value 94.077368
iter 20 value 90.615335
iter 30 value 87.471602
iter 40 value 84.126776
iter 50 value 82.757800
iter 60 value 81.109848
iter 70 value 80.725288
iter 80 value 80.478535
iter 90 value 80.429354
iter 100 value 80.417852
final value 80.417852
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.744963
final value 94.054573
converged
Fitting Repeat 2
# weights: 103
initial value 94.616806
iter 10 value 94.054292
iter 20 value 94.008663
iter 30 value 86.996047
iter 40 value 86.969979
iter 50 value 85.550478
iter 60 value 85.536759
final value 85.536395
converged
Fitting Repeat 3
# weights: 103
initial value 94.351837
final value 94.054415
converged
Fitting Repeat 4
# weights: 103
initial value 94.741051
final value 94.054431
converged
Fitting Repeat 5
# weights: 103
initial value 100.827834
final value 94.054532
converged
Fitting Repeat 1
# weights: 305
initial value 96.611645
iter 10 value 94.057537
iter 20 value 94.047873
iter 30 value 94.045719
iter 40 value 94.043281
iter 50 value 93.511334
iter 60 value 88.614628
iter 70 value 88.606814
iter 80 value 88.603259
iter 90 value 88.600346
iter 100 value 86.891868
final value 86.891868
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 96.215756
final value 94.061526
converged
Fitting Repeat 3
# weights: 305
initial value 104.037373
iter 10 value 94.057831
iter 20 value 94.052928
iter 30 value 91.382631
iter 40 value 86.092442
iter 50 value 84.994997
iter 60 value 84.988186
iter 70 value 84.983933
iter 80 value 83.791697
iter 90 value 83.460263
iter 100 value 83.448499
final value 83.448499
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 98.895838
iter 10 value 92.576501
iter 20 value 89.496314
iter 30 value 88.384721
iter 40 value 85.363925
iter 50 value 84.508706
iter 60 value 82.165767
iter 70 value 82.161622
iter 80 value 82.154140
iter 90 value 82.152708
final value 82.152672
converged
Fitting Repeat 5
# weights: 305
initial value 95.406777
iter 10 value 93.488539
iter 20 value 93.431485
iter 30 value 93.429138
iter 40 value 93.428932
iter 50 value 93.427839
final value 93.427377
converged
Fitting Repeat 1
# weights: 507
initial value 106.036870
iter 10 value 94.050830
iter 20 value 94.043340
iter 30 value 94.028598
iter 40 value 87.512205
iter 50 value 85.188298
iter 60 value 84.996740
iter 70 value 84.993520
final value 84.993517
converged
Fitting Repeat 2
# weights: 507
initial value 113.902972
iter 10 value 86.866312
iter 20 value 86.815419
iter 30 value 85.250066
iter 40 value 83.368630
iter 50 value 82.353808
iter 60 value 82.300898
final value 82.298183
converged
Fitting Repeat 3
# weights: 507
initial value 108.186463
iter 10 value 93.668556
iter 20 value 89.589925
iter 30 value 86.811733
iter 40 value 85.405906
iter 50 value 85.375127
iter 60 value 85.372754
iter 70 value 85.368050
final value 85.366940
converged
Fitting Repeat 4
# weights: 507
initial value 123.467757
iter 10 value 94.061245
iter 20 value 94.045548
iter 30 value 91.820479
iter 40 value 90.832429
iter 50 value 90.567794
iter 60 value 90.169270
iter 70 value 90.160210
iter 80 value 90.160016
final value 90.160014
converged
Fitting Repeat 5
# weights: 507
initial value 101.448366
iter 10 value 93.929384
iter 20 value 93.924156
iter 30 value 86.679833
iter 40 value 84.939901
iter 50 value 84.939766
iter 50 value 84.939766
iter 50 value 84.939765
final value 84.939765
converged
Fitting Repeat 1
# weights: 103
initial value 99.925640
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 101.628666
final value 93.582418
converged
Fitting Repeat 3
# weights: 103
initial value 104.788752
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 106.120515
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 95.766614
final value 93.818713
converged
Fitting Repeat 1
# weights: 305
initial value 124.194136
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 128.593167
iter 10 value 93.582441
final value 93.582418
converged
Fitting Repeat 3
# weights: 305
initial value 117.686289
iter 10 value 94.008596
iter 20 value 93.604544
final value 93.604520
converged
Fitting Repeat 4
# weights: 305
initial value 107.910560
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 103.088288
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 99.846058
iter 10 value 93.924050
iter 20 value 93.734325
iter 30 value 93.513496
final value 93.288893
converged
Fitting Repeat 2
# weights: 507
initial value 114.613695
iter 10 value 94.052910
iter 10 value 94.052910
iter 10 value 94.052910
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 115.718525
iter 10 value 93.818713
iter 10 value 93.818713
iter 10 value 93.818713
final value 93.818713
converged
Fitting Repeat 4
# weights: 507
initial value 127.084629
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 117.265821
iter 10 value 93.582419
final value 93.582418
converged
Fitting Repeat 1
# weights: 103
initial value 98.468507
iter 10 value 94.112387
iter 20 value 93.351809
iter 30 value 93.036592
iter 40 value 90.744205
iter 50 value 88.045400
iter 60 value 87.134517
iter 70 value 84.508650
iter 80 value 83.485551
iter 90 value 81.499839
iter 100 value 80.899031
final value 80.899031
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.253979
iter 10 value 93.629590
iter 20 value 91.205500
iter 30 value 89.190671
iter 40 value 88.155921
iter 50 value 83.964783
iter 60 value 83.710956
iter 70 value 83.220638
iter 80 value 80.837645
iter 90 value 80.825287
iter 90 value 80.825287
final value 80.825287
converged
Fitting Repeat 3
# weights: 103
initial value 96.884273
iter 10 value 94.063736
iter 20 value 94.054866
iter 30 value 93.525463
iter 40 value 93.450817
iter 50 value 93.435964
iter 60 value 89.403397
iter 70 value 86.565478
iter 80 value 85.799402
iter 90 value 85.650762
iter 100 value 85.026712
final value 85.026712
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.674326
iter 10 value 94.008830
iter 20 value 93.689207
iter 30 value 93.661404
iter 40 value 87.583423
iter 50 value 86.711677
iter 60 value 85.273495
iter 70 value 84.549531
iter 80 value 84.542250
iter 90 value 84.540592
iter 100 value 84.484847
final value 84.484847
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 94.552489
iter 10 value 86.592742
iter 20 value 83.724942
iter 30 value 83.499153
iter 40 value 83.170377
iter 50 value 83.161763
final value 83.161760
converged
Fitting Repeat 1
# weights: 305
initial value 108.016308
iter 10 value 93.980986
iter 20 value 86.957044
iter 30 value 85.224033
iter 40 value 85.148757
iter 50 value 83.578786
iter 60 value 81.544946
iter 70 value 80.486850
iter 80 value 79.826710
iter 90 value 79.712618
iter 100 value 79.590005
final value 79.590005
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.214214
iter 10 value 94.103539
iter 20 value 94.042022
iter 30 value 93.224712
iter 40 value 90.794311
iter 50 value 89.993094
iter 60 value 89.659622
iter 70 value 84.668702
iter 80 value 81.620761
iter 90 value 80.695909
iter 100 value 80.532602
final value 80.532602
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.450408
iter 10 value 94.043503
iter 20 value 93.508585
iter 30 value 93.086231
iter 40 value 92.414582
iter 50 value 85.979530
iter 60 value 84.536177
iter 70 value 83.806437
iter 80 value 83.527190
iter 90 value 81.525482
iter 100 value 80.247795
final value 80.247795
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.115206
iter 10 value 93.742617
iter 20 value 89.087992
iter 30 value 87.191359
iter 40 value 86.498268
iter 50 value 83.852983
iter 60 value 83.186279
iter 70 value 81.820463
iter 80 value 81.255289
iter 90 value 81.104250
iter 100 value 80.945855
final value 80.945855
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 114.016042
iter 10 value 93.835009
iter 20 value 90.286602
iter 30 value 88.328681
iter 40 value 88.134039
iter 50 value 86.526102
iter 60 value 83.148054
iter 70 value 80.653187
iter 80 value 80.125613
iter 90 value 79.951055
iter 100 value 79.673586
final value 79.673586
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.876501
iter 10 value 87.075699
iter 20 value 83.849005
iter 30 value 83.053434
iter 40 value 82.994308
iter 50 value 82.853501
iter 60 value 82.599021
iter 70 value 82.580200
iter 80 value 82.485580
iter 90 value 81.967288
iter 100 value 81.235751
final value 81.235751
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 131.207255
iter 10 value 94.172943
iter 20 value 93.844442
iter 30 value 83.632810
iter 40 value 83.112617
iter 50 value 82.244686
iter 60 value 80.416599
iter 70 value 80.063946
iter 80 value 79.850875
iter 90 value 79.675827
iter 100 value 79.386927
final value 79.386927
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.971800
iter 10 value 93.995009
iter 20 value 85.362554
iter 30 value 83.899377
iter 40 value 83.610996
iter 50 value 83.416375
iter 60 value 82.997467
iter 70 value 81.898547
iter 80 value 81.131955
iter 90 value 80.928473
iter 100 value 80.827469
final value 80.827469
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.012340
iter 10 value 94.733566
iter 20 value 91.444278
iter 30 value 88.645512
iter 40 value 86.126906
iter 50 value 85.824194
iter 60 value 85.296035
iter 70 value 83.638042
iter 80 value 83.053054
iter 90 value 82.433525
iter 100 value 81.135106
final value 81.135106
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 100.876747
iter 10 value 87.110909
iter 20 value 85.399745
iter 30 value 81.925861
iter 40 value 81.482707
iter 50 value 80.748391
iter 60 value 80.025966
iter 70 value 79.685847
iter 80 value 79.363698
iter 90 value 79.162265
iter 100 value 79.080918
final value 79.080918
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.488672
iter 10 value 94.054569
iter 20 value 94.052926
final value 94.052916
converged
Fitting Repeat 2
# weights: 103
initial value 98.676046
final value 94.054453
converged
Fitting Repeat 3
# weights: 103
initial value 95.753617
final value 94.054412
converged
Fitting Repeat 4
# weights: 103
initial value 97.656776
iter 10 value 94.054437
iter 20 value 94.052377
iter 30 value 93.363539
iter 40 value 93.342748
final value 93.342178
converged
Fitting Repeat 5
# weights: 103
initial value 97.576623
final value 94.054775
converged
Fitting Repeat 1
# weights: 305
initial value 105.142191
iter 10 value 94.057470
iter 20 value 93.686162
final value 93.582756
converged
Fitting Repeat 2
# weights: 305
initial value 99.906032
iter 10 value 88.001442
iter 20 value 85.664336
iter 30 value 85.525051
iter 40 value 85.500207
final value 85.499829
converged
Fitting Repeat 3
# weights: 305
initial value 102.271340
iter 10 value 94.057376
iter 20 value 94.052915
iter 30 value 93.364151
iter 40 value 86.002908
iter 50 value 85.341358
iter 60 value 85.319666
iter 70 value 85.263517
iter 80 value 84.767970
iter 90 value 83.309309
iter 100 value 79.641306
final value 79.641306
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 111.593429
iter 10 value 93.627959
iter 20 value 93.621479
iter 30 value 93.620036
iter 40 value 93.580142
iter 50 value 90.236709
iter 60 value 88.678895
iter 70 value 88.671987
iter 80 value 85.995396
iter 90 value 84.484603
iter 100 value 81.931471
final value 81.931471
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 97.132162
iter 10 value 94.057824
iter 20 value 94.053156
iter 30 value 89.489465
iter 40 value 85.981744
iter 50 value 85.696079
iter 60 value 85.135225
final value 85.135203
converged
Fitting Repeat 1
# weights: 507
initial value 103.767512
iter 10 value 94.061114
iter 20 value 93.984323
iter 30 value 84.186102
iter 40 value 84.038958
iter 50 value 81.610013
iter 60 value 81.596268
iter 70 value 81.421530
iter 80 value 79.986978
iter 90 value 79.012780
iter 100 value 78.841866
final value 78.841866
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 94.087241
iter 10 value 93.590733
iter 20 value 93.586445
iter 30 value 92.871558
iter 40 value 87.541338
iter 50 value 86.874458
iter 60 value 85.252663
iter 70 value 81.897542
iter 80 value 81.736685
iter 90 value 81.734185
iter 100 value 81.706347
final value 81.706347
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 126.803486
iter 10 value 85.960627
iter 20 value 83.917846
iter 30 value 82.667014
iter 40 value 82.594827
iter 50 value 82.587505
iter 60 value 82.556655
iter 70 value 82.530245
final value 82.526631
converged
Fitting Repeat 4
# weights: 507
initial value 95.189451
iter 10 value 93.269165
iter 20 value 90.265819
iter 30 value 83.436932
iter 40 value 83.234029
iter 50 value 83.233174
iter 60 value 83.111461
iter 70 value 82.877602
iter 80 value 82.482416
iter 90 value 82.431785
iter 100 value 82.425851
final value 82.425851
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.488576
iter 10 value 93.065076
iter 20 value 93.063283
iter 30 value 93.059659
iter 40 value 93.058831
iter 50 value 92.890263
iter 60 value 88.458045
iter 70 value 83.738248
iter 80 value 83.493838
iter 90 value 83.492310
iter 90 value 83.492310
final value 83.492310
converged
Fitting Repeat 1
# weights: 103
initial value 94.809573
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.553781
final value 94.484210
converged
Fitting Repeat 3
# weights: 103
initial value 116.191922
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 93.495005
iter 10 value 84.149006
iter 20 value 84.126411
iter 30 value 83.550063
iter 40 value 83.535128
iter 50 value 83.451762
final value 83.382042
converged
Fitting Repeat 5
# weights: 103
initial value 97.680439
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 101.139943
final value 94.483810
converged
Fitting Repeat 2
# weights: 305
initial value 94.862441
iter 10 value 94.126522
iter 20 value 94.041217
final value 94.041215
converged
Fitting Repeat 3
# weights: 305
initial value 102.901372
final value 94.466823
converged
Fitting Repeat 4
# weights: 305
initial value 99.873356
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 95.691039
final value 94.461538
converged
Fitting Repeat 1
# weights: 507
initial value 102.964629
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 119.698778
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 103.647503
iter 10 value 94.466824
final value 94.466823
converged
Fitting Repeat 4
# weights: 507
initial value 95.475329
iter 10 value 90.965535
iter 20 value 90.776804
final value 90.776777
converged
Fitting Repeat 5
# weights: 507
initial value 104.592772
final value 94.466823
converged
Fitting Repeat 1
# weights: 103
initial value 102.141993
iter 10 value 94.472269
iter 20 value 92.748789
iter 30 value 91.509217
iter 40 value 91.386878
iter 50 value 86.031261
iter 60 value 84.506173
iter 70 value 83.787344
iter 80 value 82.710106
iter 90 value 80.336027
iter 100 value 79.832345
final value 79.832345
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 105.430058
iter 10 value 94.218815
iter 20 value 84.907997
iter 30 value 83.670283
iter 40 value 81.747416
iter 50 value 81.645408
iter 60 value 80.241122
iter 70 value 79.617513
iter 80 value 79.572977
iter 80 value 79.572976
iter 80 value 79.572976
final value 79.572976
converged
Fitting Repeat 3
# weights: 103
initial value 97.715360
iter 10 value 94.421877
iter 20 value 90.381645
iter 30 value 87.208257
iter 40 value 86.039217
iter 50 value 85.848857
iter 60 value 85.754725
iter 70 value 84.172060
iter 80 value 83.710511
iter 90 value 83.670874
iter 100 value 83.575413
final value 83.575413
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 97.699810
iter 10 value 94.456141
iter 20 value 93.855403
iter 30 value 87.620990
iter 40 value 86.961135
iter 50 value 86.493173
iter 60 value 85.348104
iter 70 value 83.547731
iter 80 value 82.266796
iter 90 value 82.136912
iter 100 value 82.031133
final value 82.031133
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 96.283761
iter 10 value 93.971262
iter 20 value 90.673392
iter 30 value 86.381091
iter 40 value 84.185909
iter 50 value 83.930482
iter 60 value 83.646021
iter 70 value 83.578648
final value 83.572548
converged
Fitting Repeat 1
# weights: 305
initial value 121.152475
iter 10 value 94.627325
iter 20 value 94.478773
iter 30 value 94.375270
iter 40 value 92.367334
iter 50 value 88.143443
iter 60 value 82.948709
iter 70 value 81.952422
iter 80 value 81.507856
iter 90 value 81.032783
iter 100 value 80.698400
final value 80.698400
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.316002
iter 10 value 94.056205
iter 20 value 89.767720
iter 30 value 84.778309
iter 40 value 83.721851
iter 50 value 83.630889
iter 60 value 83.582129
iter 70 value 83.069705
iter 80 value 82.847689
iter 90 value 81.956525
iter 100 value 80.166713
final value 80.166713
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.017872
iter 10 value 94.394816
iter 20 value 89.175346
iter 30 value 87.388307
iter 40 value 82.677467
iter 50 value 82.218834
iter 60 value 81.980279
iter 70 value 81.763688
iter 80 value 80.952141
iter 90 value 80.477483
iter 100 value 79.276708
final value 79.276708
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 112.878420
iter 10 value 94.421785
iter 20 value 91.136356
iter 30 value 84.826915
iter 40 value 83.887520
iter 50 value 82.878483
iter 60 value 81.450131
iter 70 value 81.124828
iter 80 value 80.814454
iter 90 value 80.435546
iter 100 value 79.993295
final value 79.993295
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.337464
iter 10 value 94.842254
iter 20 value 94.520159
iter 30 value 88.938423
iter 40 value 85.379735
iter 50 value 83.059013
iter 60 value 80.933050
iter 70 value 79.895635
iter 80 value 78.912905
iter 90 value 78.289825
iter 100 value 78.203607
final value 78.203607
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.841139
iter 10 value 94.511300
iter 20 value 90.341093
iter 30 value 87.984633
iter 40 value 87.100117
iter 50 value 81.866744
iter 60 value 80.505479
iter 70 value 79.730641
iter 80 value 78.808382
iter 90 value 78.505545
iter 100 value 78.184736
final value 78.184736
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.471098
iter 10 value 95.230577
iter 20 value 92.168080
iter 30 value 82.736881
iter 40 value 81.404450
iter 50 value 80.760652
iter 60 value 80.499206
iter 70 value 79.874258
iter 80 value 79.745391
iter 90 value 79.523997
iter 100 value 79.147873
final value 79.147873
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.742157
iter 10 value 95.125209
iter 20 value 88.081358
iter 30 value 84.230986
iter 40 value 83.550373
iter 50 value 81.207949
iter 60 value 79.680144
iter 70 value 78.551373
iter 80 value 78.258748
iter 90 value 78.149415
iter 100 value 78.091183
final value 78.091183
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 113.288238
iter 10 value 94.958865
iter 20 value 94.867063
iter 30 value 94.509528
iter 40 value 94.218362
iter 50 value 85.262808
iter 60 value 82.858045
iter 70 value 80.458716
iter 80 value 79.767263
iter 90 value 79.273112
iter 100 value 78.994507
final value 78.994507
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.702644
iter 10 value 95.336094
iter 20 value 91.078578
iter 30 value 86.383300
iter 40 value 86.073001
iter 50 value 83.586728
iter 60 value 81.846532
iter 70 value 80.541840
iter 80 value 79.942273
iter 90 value 79.661613
iter 100 value 79.138632
final value 79.138632
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.662854
iter 10 value 94.486095
iter 20 value 94.423236
iter 30 value 91.685967
iter 40 value 86.369672
iter 50 value 86.133555
iter 60 value 86.133087
iter 70 value 85.658053
iter 80 value 85.657815
iter 90 value 85.657319
iter 100 value 85.654622
final value 85.654622
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 94.676220
iter 10 value 85.376915
iter 20 value 84.903270
iter 30 value 84.805213
iter 40 value 84.758085
iter 50 value 84.738267
iter 60 value 84.737919
iter 70 value 84.737144
iter 80 value 84.467149
iter 90 value 84.423780
final value 84.423703
converged
Fitting Repeat 3
# weights: 103
initial value 102.566001
iter 10 value 94.486009
final value 94.484215
converged
Fitting Repeat 4
# weights: 103
initial value 95.601517
final value 94.463180
converged
Fitting Repeat 5
# weights: 103
initial value 97.582602
final value 94.485814
converged
Fitting Repeat 1
# weights: 305
initial value 101.402599
iter 10 value 94.489234
final value 94.485329
converged
Fitting Repeat 2
# weights: 305
initial value 101.179915
iter 10 value 94.258763
iter 20 value 94.254090
iter 30 value 90.847321
iter 40 value 87.258927
iter 50 value 87.257245
iter 60 value 87.255946
iter 70 value 85.343720
iter 80 value 85.070493
iter 90 value 85.070380
iter 100 value 84.875496
final value 84.875496
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 118.283123
iter 10 value 94.471767
iter 20 value 94.467199
iter 30 value 92.125313
iter 40 value 82.630833
iter 50 value 82.521586
iter 60 value 80.153721
iter 70 value 79.909816
iter 80 value 79.903766
iter 90 value 79.510448
iter 100 value 79.308653
final value 79.308653
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 98.033221
iter 10 value 94.488569
iter 20 value 89.311780
iter 30 value 88.196212
iter 40 value 84.323234
iter 50 value 80.839031
iter 60 value 80.820912
final value 80.818811
converged
Fitting Repeat 5
# weights: 305
initial value 102.990318
iter 10 value 94.471287
iter 20 value 94.216380
iter 30 value 87.436668
iter 40 value 84.829401
iter 50 value 84.817604
final value 84.817510
converged
Fitting Repeat 1
# weights: 507
initial value 103.603203
iter 10 value 94.492612
iter 20 value 94.045520
iter 30 value 83.821655
iter 40 value 82.995143
iter 50 value 81.145874
iter 60 value 77.593573
iter 70 value 77.390143
iter 80 value 77.199028
iter 90 value 77.124879
iter 100 value 77.118819
final value 77.118819
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 101.313484
iter 10 value 94.492279
iter 20 value 94.417041
iter 30 value 88.191193
iter 40 value 85.154416
iter 50 value 85.148321
iter 50 value 85.148321
iter 50 value 85.148321
final value 85.148321
converged
Fitting Repeat 3
# weights: 507
initial value 109.040389
iter 10 value 94.493910
iter 20 value 94.485724
iter 30 value 88.973565
iter 40 value 88.165992
final value 88.165636
converged
Fitting Repeat 4
# weights: 507
initial value 98.164836
iter 10 value 94.492338
iter 20 value 94.484106
iter 30 value 94.281611
iter 40 value 93.147857
iter 50 value 92.303692
iter 50 value 92.303691
final value 92.303680
converged
Fitting Repeat 5
# weights: 507
initial value 110.329910
iter 10 value 94.493150
iter 20 value 94.423836
iter 30 value 85.812514
iter 40 value 83.530237
iter 50 value 83.481294
iter 60 value 83.479534
final value 83.479305
converged
Fitting Repeat 1
# weights: 305
initial value 128.082813
final value 117.895066
converged
Fitting Repeat 2
# weights: 305
initial value 117.897150
iter 10 value 117.894099
final value 117.890298
converged
Fitting Repeat 3
# weights: 305
initial value 127.231562
iter 10 value 117.870821
iter 20 value 117.841265
iter 30 value 117.710954
iter 40 value 117.648963
final value 117.648887
converged
Fitting Repeat 4
# weights: 305
initial value 136.997520
iter 10 value 117.895894
iter 20 value 117.890537
iter 30 value 106.735458
iter 40 value 106.414609
iter 50 value 106.316975
iter 60 value 106.310581
iter 70 value 106.083587
iter 80 value 104.574288
iter 90 value 104.006736
iter 100 value 102.061350
final value 102.061350
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 118.957876
iter 10 value 108.377538
iter 20 value 107.008144
iter 30 value 106.768142
iter 40 value 106.599258
final value 106.596373
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Thu Feb 26 01:05:40 2026
***********************************************
Number of test functions: 7
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7
Number of errors: 0
Number of failures: 0
Warning messages:
1: `repeats` has no meaning for this resampling method.
2: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
39.879 1.107 95.189
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 32.907 | 0.486 | 33.399 | |
| FreqInteractors | 0.436 | 0.033 | 0.468 | |
| calculateAAC | 0.032 | 0.000 | 0.031 | |
| calculateAutocor | 0.303 | 0.014 | 0.317 | |
| calculateCTDC | 0.072 | 0.000 | 0.072 | |
| calculateCTDD | 0.519 | 0.002 | 0.522 | |
| calculateCTDT | 0.193 | 0.002 | 0.196 | |
| calculateCTriad | 0.340 | 0.007 | 0.347 | |
| calculateDC | 0.081 | 0.001 | 0.083 | |
| calculateF | 0.292 | 0.000 | 0.293 | |
| calculateKSAAP | 0.098 | 0.003 | 0.100 | |
| calculateQD_Sm | 1.542 | 0.003 | 1.546 | |
| calculateTC | 1.443 | 0.020 | 1.464 | |
| calculateTC_Sm | 0.242 | 0.002 | 0.244 | |
| corr_plot | 33.986 | 0.456 | 34.443 | |
| enrichfindP | 0.560 | 0.041 | 28.323 | |
| enrichfind_hp | 0.043 | 0.002 | 3.623 | |
| enrichplot | 0.585 | 0.004 | 0.589 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.482 | 0.056 | 3.941 | |
| getHPI | 0.002 | 0.000 | 0.002 | |
| get_negativePPI | 0.003 | 0.001 | 0.004 | |
| get_positivePPI | 0.000 | 0.000 | 0.001 | |
| impute_missing_data | 0.003 | 0.000 | 0.003 | |
| plotPPI | 0.094 | 0.011 | 0.105 | |
| pred_ensembel | 12.826 | 0.330 | 11.891 | |
| var_imp | 33.127 | 0.602 | 33.731 | |