Matineh Rahmatbakhsh
| Snapshot Date: 2026-03-05 13:45 -0500 (Thu, 05 Mar 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 2026-03-06 11:57 -0500 (Fri, 06 Mar 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" | 4894 |
| 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: 2026-03-06 00:44:05 -0500 (Fri, 06 Mar 2026) |
| EndedAt: 2026-03-06 00:59:01 -0500 (Fri, 06 Mar 2026) |
| EllapsedTime: 896.0 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 34.268 0.536 34.805
FSmethod 33.219 0.451 33.672
var_imp 33.099 0.541 33.641
pred_ensembel 12.916 0.136 11.771
enrichfindP 0.536 0.043 12.655
* 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 101.475631
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.477688
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.682126
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.798916
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.693609
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 101.402508
iter 10 value 93.319677
iter 20 value 92.435471
iter 30 value 90.013385
iter 40 value 89.718456
final value 89.717856
converged
Fitting Repeat 2
# weights: 305
initial value 93.155696
iter 10 value 91.239036
iter 20 value 91.236693
final value 91.236679
converged
Fitting Repeat 3
# weights: 305
initial value 105.793624
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 96.397294
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 97.902645
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 126.291135
iter 10 value 94.002455
iter 20 value 93.986765
final value 93.986764
converged
Fitting Repeat 2
# weights: 507
initial value 97.676416
iter 10 value 93.609954
final value 93.573669
converged
Fitting Repeat 3
# weights: 507
initial value 105.964749
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 103.416222
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 107.422529
iter 10 value 93.653871
iter 10 value 93.653871
iter 10 value 93.653871
final value 93.653871
converged
Fitting Repeat 1
# weights: 103
initial value 104.521703
iter 10 value 94.419367
iter 20 value 93.731970
iter 30 value 93.636830
iter 40 value 90.690805
iter 50 value 87.491432
iter 60 value 86.652493
iter 70 value 84.340648
iter 80 value 82.979624
iter 90 value 82.892132
iter 100 value 82.744988
final value 82.744988
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 100.769213
iter 10 value 93.686168
iter 20 value 92.359382
iter 30 value 88.425349
iter 40 value 85.435544
iter 50 value 83.901689
iter 60 value 83.746514
iter 70 value 83.535160
iter 80 value 83.198886
iter 90 value 82.631647
iter 100 value 82.596919
final value 82.596919
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.927128
iter 10 value 94.054873
iter 20 value 93.921258
iter 30 value 90.347913
iter 40 value 87.616320
iter 50 value 86.286853
iter 60 value 85.493200
iter 70 value 85.054894
iter 80 value 84.892122
final value 84.888840
converged
Fitting Repeat 4
# weights: 103
initial value 104.834628
iter 10 value 94.375196
iter 20 value 94.028999
iter 30 value 92.892645
iter 40 value 92.694726
iter 50 value 92.692535
iter 60 value 84.322188
iter 70 value 83.670393
iter 80 value 83.097600
iter 90 value 82.597878
iter 100 value 82.174473
final value 82.174473
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 101.539282
iter 10 value 94.015172
iter 20 value 86.069953
iter 30 value 85.799267
iter 40 value 85.741013
iter 50 value 84.573450
iter 60 value 84.062753
iter 70 value 83.079272
iter 80 value 82.622480
iter 90 value 82.404635
iter 100 value 82.278658
final value 82.278658
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 100.371167
iter 10 value 93.945529
iter 20 value 90.924866
iter 30 value 84.946975
iter 40 value 83.773297
iter 50 value 82.874455
iter 60 value 82.095730
iter 70 value 81.461067
iter 80 value 80.949198
iter 90 value 80.913527
iter 100 value 80.891639
final value 80.891639
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.082814
iter 10 value 93.288441
iter 20 value 86.152868
iter 30 value 85.656482
iter 40 value 84.419452
iter 50 value 83.601127
iter 60 value 83.029531
iter 70 value 81.540338
iter 80 value 81.350051
iter 90 value 81.158647
iter 100 value 80.968270
final value 80.968270
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 134.272235
iter 10 value 93.894903
iter 20 value 84.853871
iter 30 value 84.216606
iter 40 value 83.653619
iter 50 value 82.665797
iter 60 value 81.817693
iter 70 value 81.184592
iter 80 value 80.888338
iter 90 value 80.875906
iter 100 value 80.874656
final value 80.874656
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.767826
iter 10 value 93.773502
iter 20 value 92.249597
iter 30 value 90.289503
iter 40 value 89.708800
iter 50 value 89.557664
iter 60 value 89.471558
iter 70 value 89.194312
iter 80 value 85.168663
iter 90 value 83.559575
iter 100 value 82.630772
final value 82.630772
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.462399
iter 10 value 94.442043
iter 20 value 93.563583
iter 30 value 84.906101
iter 40 value 84.016461
iter 50 value 82.627059
iter 60 value 82.032853
iter 70 value 81.559714
iter 80 value 81.461908
iter 90 value 81.386107
iter 100 value 81.322268
final value 81.322268
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.373708
iter 10 value 94.194255
iter 20 value 91.417049
iter 30 value 83.947249
iter 40 value 83.245263
iter 50 value 81.664074
iter 60 value 81.252725
iter 70 value 81.018187
iter 80 value 80.774405
iter 90 value 80.637228
iter 100 value 80.498239
final value 80.498239
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 135.207462
iter 10 value 94.167131
iter 20 value 90.151942
iter 30 value 89.073320
iter 40 value 88.772929
iter 50 value 86.126661
iter 60 value 84.253485
iter 70 value 83.796728
iter 80 value 83.004488
iter 90 value 82.071621
iter 100 value 81.723427
final value 81.723427
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 118.902012
iter 10 value 95.005973
iter 20 value 94.045993
iter 30 value 93.796716
iter 40 value 93.080440
iter 50 value 84.616418
iter 60 value 83.995466
iter 70 value 83.368993
iter 80 value 83.127318
iter 90 value 81.418155
iter 100 value 80.811086
final value 80.811086
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 121.586604
iter 10 value 94.927279
iter 20 value 90.909189
iter 30 value 87.348814
iter 40 value 86.698688
iter 50 value 85.959866
iter 60 value 85.668862
iter 70 value 84.358613
iter 80 value 82.294202
iter 90 value 81.145989
iter 100 value 80.554428
final value 80.554428
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.125711
iter 10 value 94.037557
iter 20 value 90.222016
iter 30 value 84.628617
iter 40 value 83.174091
iter 50 value 82.637749
iter 60 value 82.589723
iter 70 value 82.515491
iter 80 value 82.148426
iter 90 value 81.933601
iter 100 value 81.423103
final value 81.423103
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.731150
iter 10 value 93.993358
iter 20 value 93.992125
iter 30 value 88.111018
iter 40 value 84.228747
iter 50 value 84.185201
iter 60 value 84.180542
iter 70 value 84.055687
iter 80 value 83.610948
iter 90 value 83.607033
iter 100 value 83.605988
final value 83.605988
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.406439
final value 94.054475
converged
Fitting Repeat 3
# weights: 103
initial value 94.656180
iter 10 value 94.034642
final value 94.034635
converged
Fitting Repeat 4
# weights: 103
initial value 95.338007
final value 94.054794
converged
Fitting Repeat 5
# weights: 103
initial value 109.516606
final value 94.054582
converged
Fitting Repeat 1
# weights: 305
initial value 97.062000
iter 10 value 94.037920
iter 20 value 94.030608
iter 30 value 93.472496
iter 40 value 83.255683
iter 50 value 82.995913
iter 60 value 82.975698
iter 70 value 82.756446
iter 80 value 82.730079
iter 90 value 82.729546
iter 100 value 82.728870
final value 82.728870
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 111.645870
iter 10 value 94.058361
iter 20 value 94.022881
iter 30 value 93.594034
iter 30 value 93.594033
iter 30 value 93.594033
final value 93.594033
converged
Fitting Repeat 3
# weights: 305
initial value 116.371787
iter 10 value 94.058566
iter 20 value 93.738480
iter 30 value 89.147970
iter 40 value 89.138835
final value 89.138350
converged
Fitting Repeat 4
# weights: 305
initial value 102.970251
iter 10 value 93.889497
iter 20 value 93.886826
iter 30 value 91.206870
final value 89.285238
converged
Fitting Repeat 5
# weights: 305
initial value 100.630763
iter 10 value 94.037926
iter 20 value 94.033192
iter 30 value 94.032711
iter 40 value 85.236515
iter 50 value 84.964267
iter 60 value 84.941538
iter 70 value 84.940960
iter 80 value 84.940871
iter 90 value 84.827229
iter 100 value 83.143351
final value 83.143351
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 94.712396
iter 10 value 94.060141
iter 20 value 94.053090
final value 94.053076
converged
Fitting Repeat 2
# weights: 507
initial value 94.875123
iter 10 value 94.059519
iter 20 value 94.033344
iter 30 value 94.032769
iter 40 value 88.286652
final value 85.387501
converged
Fitting Repeat 3
# weights: 507
initial value 105.409305
iter 10 value 94.042041
iter 20 value 93.970768
iter 30 value 93.544558
iter 40 value 93.544046
iter 50 value 93.543309
iter 60 value 93.515832
iter 70 value 90.279640
iter 80 value 88.926082
iter 90 value 88.669788
iter 100 value 88.369139
final value 88.369139
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 98.758287
iter 10 value 90.508616
iter 20 value 90.435836
iter 30 value 90.435449
iter 40 value 90.433453
final value 90.430926
converged
Fitting Repeat 5
# weights: 507
initial value 104.421915
iter 10 value 94.040929
iter 20 value 94.033276
final value 94.033263
converged
Fitting Repeat 1
# weights: 103
initial value 97.051742
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 98.909295
iter 10 value 84.586755
iter 20 value 84.558225
final value 84.558071
converged
Fitting Repeat 3
# weights: 103
initial value 110.715995
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.286469
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 105.057373
final value 94.252920
converged
Fitting Repeat 1
# weights: 305
initial value 96.450162
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 100.005503
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 95.085517
iter 10 value 93.164727
final value 93.164282
converged
Fitting Repeat 4
# weights: 305
initial value 101.009009
iter 10 value 94.026548
final value 94.026542
converged
Fitting Repeat 5
# weights: 305
initial value 101.165264
iter 10 value 83.962982
iter 20 value 82.725848
iter 30 value 82.564906
iter 40 value 82.169737
final value 82.169462
converged
Fitting Repeat 1
# weights: 507
initial value 115.314729
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 108.331019
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 95.670232
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 96.614229
final value 94.026542
converged
Fitting Repeat 5
# weights: 507
initial value 108.036391
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 96.726389
iter 10 value 94.483866
iter 20 value 94.238344
iter 30 value 94.223016
iter 40 value 94.217142
iter 50 value 93.360780
iter 60 value 93.342476
iter 70 value 84.548993
iter 80 value 83.616182
iter 90 value 83.347060
iter 100 value 82.927942
final value 82.927942
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 98.138008
iter 10 value 94.422891
iter 20 value 84.322308
iter 30 value 81.356729
iter 40 value 81.089025
iter 50 value 80.855591
iter 60 value 79.885840
iter 70 value 79.443690
iter 80 value 79.377503
iter 90 value 79.342972
iter 100 value 79.335616
final value 79.335616
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 98.456181
iter 10 value 93.483121
iter 20 value 81.482444
iter 30 value 80.219367
iter 40 value 79.450292
iter 50 value 79.282283
iter 60 value 79.189714
final value 79.189015
converged
Fitting Repeat 4
# weights: 103
initial value 100.970823
iter 10 value 93.684325
iter 20 value 93.346775
iter 30 value 93.342210
iter 40 value 87.862879
iter 50 value 86.426902
iter 60 value 82.047281
iter 70 value 80.821790
iter 80 value 80.689440
iter 90 value 80.683835
iter 100 value 80.668953
final value 80.668953
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 101.504273
iter 10 value 94.488074
iter 20 value 89.668889
iter 30 value 84.696637
iter 40 value 82.930167
iter 50 value 82.391162
iter 60 value 82.376787
iter 70 value 80.576559
iter 80 value 79.499602
iter 90 value 79.416403
iter 100 value 79.402723
final value 79.402723
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.402132
iter 10 value 95.699791
iter 20 value 92.832884
iter 30 value 82.365582
iter 40 value 81.937519
iter 50 value 80.369769
iter 60 value 79.821924
iter 70 value 79.481904
iter 80 value 78.402327
iter 90 value 78.281540
iter 100 value 78.235897
final value 78.235897
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 119.205252
iter 10 value 94.151364
iter 20 value 88.612227
iter 30 value 84.918046
iter 40 value 83.123877
iter 50 value 80.958377
iter 60 value 80.587181
iter 70 value 79.921389
iter 80 value 78.872505
iter 90 value 78.667571
iter 100 value 78.549790
final value 78.549790
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.850082
iter 10 value 94.376174
iter 20 value 89.297584
iter 30 value 86.460712
iter 40 value 83.351550
iter 50 value 81.341424
iter 60 value 80.698565
iter 70 value 80.239355
iter 80 value 80.111033
iter 90 value 79.219123
iter 100 value 78.559991
final value 78.559991
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 110.457373
iter 10 value 93.534354
iter 20 value 85.294851
iter 30 value 82.622511
iter 40 value 81.957694
iter 50 value 79.484609
iter 60 value 78.242592
iter 70 value 78.124692
iter 80 value 77.811097
iter 90 value 77.778837
iter 100 value 77.710272
final value 77.710272
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.767037
iter 10 value 93.962769
iter 20 value 92.958376
iter 30 value 87.777024
iter 40 value 86.738873
iter 50 value 83.774348
iter 60 value 83.062633
iter 70 value 82.200548
iter 80 value 79.381626
iter 90 value 78.612257
iter 100 value 78.346724
final value 78.346724
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.050154
iter 10 value 96.540049
iter 20 value 85.968301
iter 30 value 83.192050
iter 40 value 80.672134
iter 50 value 79.043382
iter 60 value 78.599900
iter 70 value 78.378134
iter 80 value 78.130777
iter 90 value 78.106005
iter 100 value 78.101481
final value 78.101481
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.865035
iter 10 value 93.581486
iter 20 value 93.317419
iter 30 value 92.424872
iter 40 value 84.575639
iter 50 value 84.266627
iter 60 value 82.086008
iter 70 value 79.711960
iter 80 value 79.213787
iter 90 value 78.809783
iter 100 value 78.536792
final value 78.536792
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.576080
iter 10 value 93.999243
iter 20 value 86.928230
iter 30 value 80.741122
iter 40 value 80.483930
iter 50 value 79.952985
iter 60 value 79.844633
iter 70 value 79.190195
iter 80 value 78.845130
iter 90 value 78.385564
iter 100 value 78.198434
final value 78.198434
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.496272
iter 10 value 93.800606
iter 20 value 86.350532
iter 30 value 80.965152
iter 40 value 79.128803
iter 50 value 78.788983
iter 60 value 78.272981
iter 70 value 78.047357
iter 80 value 77.956891
iter 90 value 77.782475
iter 100 value 77.700392
final value 77.700392
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 122.862200
iter 10 value 95.184852
iter 20 value 93.078467
iter 30 value 89.764695
iter 40 value 83.366645
iter 50 value 82.853562
iter 60 value 79.673249
iter 70 value 79.184717
iter 80 value 78.437667
iter 90 value 78.262219
iter 100 value 78.027649
final value 78.027649
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.520227
iter 10 value 94.485902
final value 94.484217
converged
Fitting Repeat 2
# weights: 103
initial value 97.356905
iter 10 value 94.485766
final value 94.484425
converged
Fitting Repeat 3
# weights: 103
initial value 94.862686
iter 10 value 82.526863
iter 20 value 81.999226
iter 30 value 81.998190
final value 81.997851
converged
Fitting Repeat 4
# weights: 103
initial value 95.244192
final value 94.485956
converged
Fitting Repeat 5
# weights: 103
initial value 96.441732
iter 10 value 94.028346
iter 20 value 94.026905
final value 94.026702
converged
Fitting Repeat 1
# weights: 305
initial value 97.665056
iter 10 value 93.161152
iter 20 value 93.095160
iter 30 value 93.054355
iter 40 value 86.840830
iter 50 value 84.418951
iter 60 value 83.683103
iter 70 value 82.850097
iter 80 value 82.129076
iter 90 value 81.679436
iter 100 value 78.423761
final value 78.423761
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.825393
iter 10 value 94.033954
iter 20 value 94.030940
iter 30 value 93.577913
iter 40 value 83.079188
final value 83.079160
converged
Fitting Repeat 3
# weights: 305
initial value 99.855970
iter 10 value 94.031415
iter 20 value 93.887246
iter 30 value 83.741220
iter 40 value 82.756577
iter 50 value 82.667836
iter 60 value 82.652613
iter 70 value 82.483064
iter 80 value 82.058261
iter 90 value 80.042575
iter 100 value 77.442512
final value 77.442512
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 97.847838
iter 10 value 94.487050
iter 20 value 92.944923
iter 30 value 92.678579
iter 40 value 92.657767
iter 50 value 83.741388
iter 60 value 83.731584
iter 70 value 83.617929
iter 80 value 80.974170
iter 90 value 79.584098
iter 100 value 79.583828
final value 79.583828
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.950040
iter 10 value 93.091900
iter 20 value 93.021208
iter 30 value 93.020761
iter 40 value 92.947693
iter 50 value 92.943111
iter 60 value 92.941882
iter 60 value 92.941881
iter 60 value 92.941881
final value 92.941881
converged
Fitting Repeat 1
# weights: 507
initial value 109.010617
iter 10 value 94.034972
iter 20 value 94.027990
iter 30 value 91.924805
iter 40 value 86.285632
iter 50 value 82.147011
iter 60 value 82.139646
final value 82.139618
converged
Fitting Repeat 2
# weights: 507
initial value 96.655989
iter 10 value 94.034654
iter 20 value 94.028350
final value 94.027995
converged
Fitting Repeat 3
# weights: 507
initial value 107.226297
iter 10 value 94.035088
iter 20 value 93.389573
iter 30 value 93.322155
iter 40 value 92.938651
iter 50 value 92.901625
iter 60 value 92.899653
iter 70 value 92.139149
iter 80 value 91.740819
iter 90 value 91.596454
iter 100 value 91.449348
final value 91.449348
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 101.011806
iter 10 value 89.424227
iter 20 value 83.438342
iter 30 value 82.699510
iter 40 value 82.650733
iter 50 value 82.638151
iter 60 value 80.164160
iter 70 value 79.802065
iter 80 value 79.801356
iter 90 value 79.799215
iter 100 value 79.479991
final value 79.479991
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 95.300400
iter 10 value 94.491940
iter 20 value 93.504042
iter 30 value 90.355796
iter 40 value 90.345752
iter 50 value 90.345516
iter 60 value 88.989829
iter 70 value 84.172493
iter 80 value 84.151036
iter 90 value 83.757691
iter 100 value 83.577205
final value 83.577205
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 105.449056
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.073266
final value 94.466823
converged
Fitting Repeat 3
# weights: 103
initial value 101.812490
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 102.100356
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 115.356609
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 100.416886
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 109.739550
final value 94.466823
converged
Fitting Repeat 3
# weights: 305
initial value 96.692264
iter 10 value 91.866363
iter 20 value 83.315690
final value 83.304372
converged
Fitting Repeat 4
# weights: 305
initial value 105.980551
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 101.035586
final value 94.484137
converged
Fitting Repeat 1
# weights: 507
initial value 100.381201
final value 94.466823
converged
Fitting Repeat 2
# weights: 507
initial value 99.389418
final value 94.484210
converged
Fitting Repeat 3
# weights: 507
initial value 101.395032
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 104.004399
iter 10 value 90.257477
iter 20 value 87.593556
iter 30 value 87.590805
iter 40 value 87.556953
iter 50 value 87.225281
final value 87.224767
converged
Fitting Repeat 5
# weights: 507
initial value 98.666263
iter 10 value 94.476471
iter 10 value 94.476471
iter 10 value 94.476471
final value 94.476471
converged
Fitting Repeat 1
# weights: 103
initial value 98.426122
iter 10 value 94.488600
iter 20 value 93.593698
iter 30 value 87.599416
iter 40 value 84.917434
iter 50 value 83.030023
iter 60 value 82.018376
iter 70 value 81.800342
iter 80 value 81.655291
final value 81.651190
converged
Fitting Repeat 2
# weights: 103
initial value 101.118626
iter 10 value 93.255385
iter 20 value 91.654886
iter 30 value 90.733629
iter 40 value 86.841805
iter 50 value 83.551250
iter 60 value 83.205923
iter 70 value 82.858451
iter 80 value 81.796279
iter 90 value 81.313043
iter 100 value 81.126930
final value 81.126930
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 102.571462
iter 10 value 94.488531
iter 20 value 94.487607
iter 30 value 94.486873
iter 40 value 94.451854
iter 40 value 94.451854
iter 50 value 94.204752
iter 60 value 92.420818
iter 70 value 89.795220
iter 80 value 88.169090
iter 90 value 84.741001
iter 100 value 84.381779
final value 84.381779
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 102.020545
iter 10 value 94.486863
iter 20 value 94.241915
iter 30 value 87.074849
iter 40 value 84.228742
iter 50 value 84.073202
iter 60 value 83.763903
iter 70 value 83.589623
iter 80 value 83.553040
final value 83.552227
converged
Fitting Repeat 5
# weights: 103
initial value 99.766868
iter 10 value 94.479139
iter 20 value 86.496509
iter 30 value 85.980433
iter 40 value 85.800970
iter 50 value 85.749213
iter 60 value 85.704797
iter 70 value 85.311058
iter 80 value 83.868453
iter 90 value 82.977743
iter 100 value 81.428056
final value 81.428056
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 118.737829
iter 10 value 94.838734
iter 20 value 89.994547
iter 30 value 88.177094
iter 40 value 85.529614
iter 50 value 83.963829
iter 60 value 83.547769
iter 70 value 83.456129
iter 80 value 83.224777
iter 90 value 82.950181
iter 100 value 81.011670
final value 81.011670
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.364845
iter 10 value 94.674838
iter 20 value 87.847426
iter 30 value 86.266490
iter 40 value 85.003425
iter 50 value 84.548070
iter 60 value 83.183866
iter 70 value 82.017435
iter 80 value 81.303070
iter 90 value 80.503678
iter 100 value 80.132747
final value 80.132747
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.945463
iter 10 value 95.242473
iter 20 value 94.887140
iter 30 value 87.891242
iter 40 value 86.914746
iter 50 value 84.105775
iter 60 value 82.426790
iter 70 value 82.276656
iter 80 value 81.127470
iter 90 value 80.532647
iter 100 value 80.223904
final value 80.223904
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.516508
iter 10 value 94.401043
iter 20 value 91.456582
iter 30 value 89.157050
iter 40 value 88.665587
iter 50 value 87.446431
iter 60 value 87.121398
iter 70 value 84.359672
iter 80 value 81.954733
iter 90 value 79.973321
iter 100 value 79.663141
final value 79.663141
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.441537
iter 10 value 94.493385
iter 20 value 91.178107
iter 30 value 88.613718
iter 40 value 84.645239
iter 50 value 80.688538
iter 60 value 80.032690
iter 70 value 79.618794
iter 80 value 79.387457
iter 90 value 79.368667
iter 100 value 79.350755
final value 79.350755
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.024801
iter 10 value 94.501037
iter 20 value 88.908380
iter 30 value 85.520722
iter 40 value 85.015847
iter 50 value 84.317868
iter 60 value 82.729934
iter 70 value 81.058576
iter 80 value 79.939927
iter 90 value 79.888056
iter 100 value 79.867201
final value 79.867201
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 118.150185
iter 10 value 94.430710
iter 20 value 87.956014
iter 30 value 85.636001
iter 40 value 83.861903
iter 50 value 81.463195
iter 60 value 80.324220
iter 70 value 79.940541
iter 80 value 79.858010
iter 90 value 79.747917
iter 100 value 79.555856
final value 79.555856
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.748411
iter 10 value 96.853098
iter 20 value 86.803175
iter 30 value 82.974203
iter 40 value 81.316900
iter 50 value 80.346643
iter 60 value 79.660849
iter 70 value 79.557627
iter 80 value 79.503958
iter 90 value 79.486735
iter 100 value 79.406451
final value 79.406451
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 126.007201
iter 10 value 94.757079
iter 20 value 94.661685
iter 30 value 94.285816
iter 40 value 90.178172
iter 50 value 88.253200
iter 60 value 87.471431
iter 70 value 84.686117
iter 80 value 81.472237
iter 90 value 80.949503
iter 100 value 80.497553
final value 80.497553
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.686676
iter 10 value 94.442893
iter 20 value 88.523999
iter 30 value 83.818235
iter 40 value 83.149624
iter 50 value 82.932079
iter 60 value 82.827575
iter 70 value 82.654328
iter 80 value 82.139788
iter 90 value 81.496079
iter 100 value 81.243800
final value 81.243800
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.020490
final value 94.485654
converged
Fitting Repeat 2
# weights: 103
initial value 95.156276
iter 10 value 94.418490
iter 20 value 94.401770
iter 30 value 94.014418
iter 40 value 92.128544
iter 50 value 86.066793
iter 60 value 84.558043
iter 70 value 83.589450
iter 80 value 82.737776
iter 90 value 82.736032
final value 82.732593
converged
Fitting Repeat 3
# weights: 103
initial value 94.506149
iter 10 value 94.468485
iter 20 value 94.466859
final value 94.466852
converged
Fitting Repeat 4
# weights: 103
initial value 104.086430
final value 94.485709
converged
Fitting Repeat 5
# weights: 103
initial value 104.510932
final value 94.430384
converged
Fitting Repeat 1
# weights: 305
initial value 109.999494
iter 10 value 94.489756
iter 20 value 94.461221
iter 30 value 88.398454
iter 40 value 87.915712
iter 50 value 87.610228
iter 60 value 86.849193
final value 86.842013
converged
Fitting Repeat 2
# weights: 305
initial value 107.186823
iter 10 value 94.471792
iter 20 value 94.467258
iter 30 value 94.466723
final value 94.466704
converged
Fitting Repeat 3
# weights: 305
initial value 102.529428
iter 10 value 94.488978
iter 20 value 88.907000
iter 30 value 87.133318
iter 40 value 87.133106
iter 40 value 87.133105
iter 40 value 87.133105
final value 87.133105
converged
Fitting Repeat 4
# weights: 305
initial value 95.613134
iter 10 value 94.471397
iter 20 value 92.158449
iter 30 value 91.956279
iter 40 value 91.952093
iter 50 value 86.347327
iter 60 value 84.988738
iter 70 value 84.879391
iter 80 value 84.879199
iter 90 value 84.879024
final value 84.878960
converged
Fitting Repeat 5
# weights: 305
initial value 99.286567
iter 10 value 94.489050
iter 20 value 94.431900
iter 30 value 84.058682
iter 40 value 83.203921
iter 50 value 82.251205
iter 60 value 82.189197
iter 70 value 82.162297
iter 80 value 82.137053
iter 90 value 81.949251
iter 100 value 81.841115
final value 81.841115
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 101.841005
iter 10 value 94.340535
iter 20 value 94.339239
iter 30 value 94.334823
iter 40 value 94.334255
iter 50 value 94.331560
iter 60 value 94.331045
iter 70 value 94.330714
iter 80 value 94.330565
iter 90 value 94.306477
iter 100 value 93.590170
final value 93.590170
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 120.003382
iter 10 value 94.491599
iter 20 value 94.484273
final value 94.484221
converged
Fitting Repeat 3
# weights: 507
initial value 96.671020
iter 10 value 94.474712
iter 20 value 94.469265
iter 30 value 89.332742
iter 40 value 87.223351
iter 50 value 87.218875
final value 87.218849
converged
Fitting Repeat 4
# weights: 507
initial value 95.580707
iter 10 value 83.784609
iter 20 value 83.343420
iter 30 value 83.339289
iter 40 value 83.338213
iter 50 value 83.335599
iter 60 value 83.125834
iter 70 value 83.123935
iter 80 value 83.121679
iter 90 value 83.066620
iter 100 value 82.422464
final value 82.422464
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.692640
iter 10 value 92.071417
iter 20 value 87.423938
iter 30 value 87.017618
iter 40 value 86.719505
iter 50 value 86.711652
final value 86.711195
converged
Fitting Repeat 1
# weights: 103
initial value 99.739526
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 100.104746
final value 93.836066
converged
Fitting Repeat 3
# weights: 103
initial value 100.776095
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 99.403760
final value 93.288889
converged
Fitting Repeat 5
# weights: 103
initial value 102.693478
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 95.694884
final value 93.836066
converged
Fitting Repeat 2
# weights: 305
initial value 101.778351
iter 10 value 87.313353
iter 20 value 87.212697
iter 30 value 87.210078
iter 40 value 87.208036
final value 87.208029
converged
Fitting Repeat 3
# weights: 305
initial value 108.539484
final value 94.042012
converged
Fitting Repeat 4
# weights: 305
initial value 111.275260
iter 10 value 92.937710
iter 20 value 92.522525
final value 92.505646
converged
Fitting Repeat 5
# weights: 305
initial value 102.836908
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 98.085047
final value 93.836066
converged
Fitting Repeat 2
# weights: 507
initial value 101.117469
final value 93.836066
converged
Fitting Repeat 3
# weights: 507
initial value 114.078974
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 105.965611
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 95.429103
iter 10 value 93.858428
iter 20 value 93.854624
iter 30 value 93.854549
final value 93.854522
converged
Fitting Repeat 1
# weights: 103
initial value 103.975633
iter 10 value 94.063153
iter 20 value 93.638904
iter 30 value 93.327887
iter 40 value 93.317247
iter 50 value 93.265832
iter 60 value 90.819117
iter 70 value 85.339048
iter 80 value 84.386283
iter 90 value 83.753940
iter 100 value 83.706842
final value 83.706842
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.192135
iter 10 value 93.422878
iter 20 value 87.390654
iter 30 value 85.706712
iter 40 value 85.596927
iter 50 value 85.564421
iter 50 value 85.564420
iter 50 value 85.564420
final value 85.564420
converged
Fitting Repeat 3
# weights: 103
initial value 99.470498
iter 10 value 94.054668
iter 20 value 93.758485
iter 30 value 92.686677
iter 40 value 91.705427
iter 50 value 90.618725
iter 60 value 89.799050
iter 70 value 87.277303
iter 80 value 86.334697
iter 90 value 86.071848
iter 100 value 85.986620
final value 85.986620
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 97.334652
iter 10 value 94.053473
iter 20 value 92.577105
iter 30 value 88.835826
iter 40 value 87.344661
iter 50 value 85.902067
iter 60 value 85.797379
final value 85.796288
converged
Fitting Repeat 5
# weights: 103
initial value 107.925820
iter 10 value 94.300450
iter 20 value 94.125456
iter 30 value 88.629515
iter 40 value 86.953159
iter 50 value 85.646503
iter 60 value 84.379414
iter 70 value 84.102908
iter 80 value 82.750115
iter 90 value 82.519160
final value 82.519158
converged
Fitting Repeat 1
# weights: 305
initial value 106.601094
iter 10 value 93.070878
iter 20 value 88.451742
iter 30 value 86.279359
iter 40 value 85.926082
iter 50 value 83.840105
iter 60 value 82.561165
iter 70 value 82.455146
final value 82.455000
converged
Fitting Repeat 2
# weights: 305
initial value 102.434601
iter 10 value 94.080567
iter 20 value 94.054501
iter 30 value 92.196306
iter 40 value 87.775504
iter 50 value 85.563461
iter 60 value 82.912063
iter 70 value 82.555896
iter 80 value 82.323889
iter 90 value 82.290989
iter 100 value 82.203545
final value 82.203545
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.472393
iter 10 value 94.026761
iter 20 value 93.470908
iter 30 value 91.999258
iter 40 value 91.390486
iter 50 value 91.067392
iter 60 value 86.631304
iter 70 value 85.500352
iter 80 value 84.102489
iter 90 value 82.345678
iter 100 value 81.972447
final value 81.972447
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.647296
iter 10 value 93.353023
iter 20 value 90.394670
iter 30 value 88.493656
iter 40 value 86.674158
iter 50 value 84.852671
iter 60 value 83.995799
iter 70 value 82.953298
iter 80 value 82.407845
iter 90 value 82.031773
iter 100 value 81.878521
final value 81.878521
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 114.228318
iter 10 value 93.874942
iter 20 value 93.356548
iter 30 value 88.354736
iter 40 value 86.969385
iter 50 value 85.145716
iter 60 value 84.618169
iter 70 value 84.117024
iter 80 value 83.721818
iter 90 value 82.328321
iter 100 value 81.003171
final value 81.003171
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.611165
iter 10 value 95.233754
iter 20 value 90.436044
iter 30 value 84.983545
iter 40 value 84.100992
iter 50 value 83.196457
iter 60 value 82.919523
iter 70 value 82.733932
iter 80 value 82.285232
iter 90 value 81.785056
iter 100 value 81.483557
final value 81.483557
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 118.037727
iter 10 value 90.178820
iter 20 value 85.739303
iter 30 value 85.475937
iter 40 value 84.886211
iter 50 value 82.161693
iter 60 value 81.711860
iter 70 value 81.425024
iter 80 value 81.018146
iter 90 value 80.861388
iter 100 value 80.847890
final value 80.847890
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.661909
iter 10 value 93.843240
iter 20 value 93.034263
iter 30 value 90.503628
iter 40 value 88.399471
iter 50 value 86.256811
iter 60 value 84.846174
iter 70 value 83.402953
iter 80 value 82.699995
iter 90 value 82.043341
iter 100 value 81.437739
final value 81.437739
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.994263
iter 10 value 94.550160
iter 20 value 87.603106
iter 30 value 84.598305
iter 40 value 82.559890
iter 50 value 81.657613
iter 60 value 81.071250
iter 70 value 80.967278
iter 80 value 80.856270
iter 90 value 80.740108
iter 100 value 80.665925
final value 80.665925
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.378623
iter 10 value 94.092062
iter 20 value 90.389221
iter 30 value 88.754295
iter 40 value 88.441517
iter 50 value 86.047650
iter 60 value 85.015414
iter 70 value 83.948046
iter 80 value 82.764673
iter 90 value 82.133192
iter 100 value 81.996764
final value 81.996764
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.421697
iter 10 value 94.054681
iter 20 value 94.010077
iter 30 value 90.273439
iter 40 value 86.952431
iter 50 value 86.945895
iter 60 value 86.943371
iter 70 value 86.939027
final value 86.934956
converged
Fitting Repeat 2
# weights: 103
initial value 96.840475
final value 94.054650
converged
Fitting Repeat 3
# weights: 103
initial value 96.459518
iter 10 value 92.557635
iter 20 value 90.837777
iter 30 value 85.377834
iter 40 value 85.365991
final value 85.365811
converged
Fitting Repeat 4
# weights: 103
initial value 98.583402
iter 10 value 94.054581
iter 20 value 94.052888
iter 30 value 93.804993
final value 93.804984
converged
Fitting Repeat 5
# weights: 103
initial value 117.941005
final value 94.054292
converged
Fitting Repeat 1
# weights: 305
initial value 97.514672
iter 10 value 92.521974
iter 20 value 92.292812
final value 92.290235
converged
Fitting Repeat 2
# weights: 305
initial value 119.425454
iter 10 value 94.058200
iter 20 value 94.054851
iter 30 value 93.836663
final value 93.836426
converged
Fitting Repeat 3
# weights: 305
initial value 98.227621
iter 10 value 93.840572
iter 20 value 93.837278
final value 93.836880
converged
Fitting Repeat 4
# weights: 305
initial value 108.552654
iter 10 value 93.841256
iter 20 value 93.829678
iter 30 value 87.923830
iter 40 value 85.632571
final value 85.611734
converged
Fitting Repeat 5
# weights: 305
initial value 102.840149
iter 10 value 94.057848
iter 20 value 93.937366
iter 30 value 87.975975
iter 40 value 87.969282
final value 87.968637
converged
Fitting Repeat 1
# weights: 507
initial value 108.546495
iter 10 value 94.025128
iter 20 value 94.015412
iter 30 value 86.951360
final value 85.433830
converged
Fitting Repeat 2
# weights: 507
initial value 124.345961
iter 10 value 94.061259
iter 20 value 93.945321
iter 30 value 93.184145
final value 93.184134
converged
Fitting Repeat 3
# weights: 507
initial value 137.440006
iter 10 value 93.221820
iter 20 value 87.155800
iter 30 value 86.982479
iter 40 value 86.977867
iter 50 value 86.931355
iter 60 value 86.720701
iter 70 value 86.720355
iter 80 value 86.719260
final value 86.718740
converged
Fitting Repeat 4
# weights: 507
initial value 105.827399
iter 10 value 93.541138
iter 20 value 93.438448
iter 30 value 93.231195
iter 40 value 92.767646
iter 50 value 87.923309
iter 60 value 85.664275
iter 70 value 85.175149
iter 80 value 83.754944
iter 90 value 83.625747
iter 100 value 83.556825
final value 83.556825
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.527581
iter 10 value 93.824154
iter 20 value 93.541447
iter 20 value 93.541446
final value 93.541446
converged
Fitting Repeat 1
# weights: 103
initial value 100.484551
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.087071
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.218117
iter 10 value 91.744323
iter 20 value 91.094096
iter 30 value 88.994736
iter 40 value 88.175988
final value 88.168628
converged
Fitting Repeat 4
# weights: 103
initial value 111.187826
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 104.232794
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 99.267433
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 100.069274
iter 10 value 94.152144
iter 20 value 93.548834
iter 30 value 93.545114
final value 93.544972
converged
Fitting Repeat 3
# weights: 305
initial value 111.932486
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 97.615627
iter 10 value 93.567607
final value 93.567535
converged
Fitting Repeat 5
# weights: 305
initial value 96.129272
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 96.892099
final value 94.443243
converged
Fitting Repeat 2
# weights: 507
initial value 101.384637
final value 94.443243
converged
Fitting Repeat 3
# weights: 507
initial value 97.257498
final value 94.443243
converged
Fitting Repeat 4
# weights: 507
initial value 103.044506
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 105.048171
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 97.032949
iter 10 value 94.476606
iter 20 value 94.346412
iter 30 value 91.044949
iter 40 value 89.095280
iter 50 value 86.549646
iter 60 value 85.588319
iter 70 value 85.530216
iter 80 value 85.215614
iter 90 value 84.454045
iter 100 value 83.725760
final value 83.725760
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.103949
iter 10 value 94.493600
iter 20 value 92.059556
iter 30 value 87.569396
iter 40 value 86.373931
iter 50 value 85.322216
iter 60 value 84.532078
iter 70 value 84.226075
iter 80 value 84.171412
iter 80 value 84.171412
iter 80 value 84.171412
final value 84.171412
converged
Fitting Repeat 3
# weights: 103
initial value 98.394173
iter 10 value 94.528279
iter 20 value 94.469868
iter 30 value 89.357589
iter 40 value 85.677275
iter 50 value 85.029261
iter 60 value 84.976531
iter 70 value 83.809898
iter 80 value 83.333261
iter 90 value 83.228493
iter 100 value 83.197154
final value 83.197154
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.884925
iter 10 value 94.539884
iter 20 value 94.486829
iter 30 value 94.393754
iter 40 value 91.515763
iter 50 value 91.199350
iter 60 value 87.986482
iter 70 value 86.650262
iter 80 value 84.497227
iter 90 value 84.020974
iter 100 value 83.794717
final value 83.794717
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 97.778385
iter 10 value 90.495300
iter 20 value 86.746778
iter 30 value 84.539431
iter 40 value 84.021902
iter 50 value 83.882921
iter 60 value 83.814405
iter 70 value 83.809938
iter 80 value 83.793760
iter 90 value 83.682462
final value 83.682449
converged
Fitting Repeat 1
# weights: 305
initial value 116.097632
iter 10 value 94.576980
iter 20 value 90.946428
iter 30 value 83.775438
iter 40 value 81.907293
iter 50 value 80.902381
iter 60 value 80.171486
iter 70 value 80.094663
iter 80 value 80.085379
iter 90 value 80.006758
iter 100 value 79.857571
final value 79.857571
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 112.679000
iter 10 value 94.583438
iter 20 value 94.358158
iter 30 value 91.557049
iter 40 value 90.274135
iter 50 value 89.549547
iter 60 value 87.539761
iter 70 value 85.979484
iter 80 value 85.659375
iter 90 value 84.743979
iter 100 value 82.206398
final value 82.206398
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.922198
iter 10 value 94.368474
iter 20 value 85.062767
iter 30 value 82.959637
iter 40 value 82.859050
iter 50 value 82.741520
iter 60 value 82.667382
iter 70 value 82.616916
iter 80 value 82.500668
iter 90 value 82.320064
iter 100 value 81.377453
final value 81.377453
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 115.536316
iter 10 value 94.473160
iter 20 value 88.067011
iter 30 value 84.644589
iter 40 value 83.900216
iter 50 value 83.374384
iter 60 value 81.076285
iter 70 value 80.358090
iter 80 value 80.106951
iter 90 value 79.912217
iter 100 value 79.809454
final value 79.809454
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.841689
iter 10 value 94.576712
iter 20 value 93.473574
iter 30 value 87.574312
iter 40 value 86.601642
iter 50 value 84.888665
iter 60 value 83.296985
iter 70 value 81.347400
iter 80 value 79.866794
iter 90 value 79.373390
iter 100 value 79.262400
final value 79.262400
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.482010
iter 10 value 94.501235
iter 20 value 93.647283
iter 30 value 93.405016
iter 40 value 93.092950
iter 50 value 86.158799
iter 60 value 83.707314
iter 70 value 82.734861
iter 80 value 82.486540
iter 90 value 80.983419
iter 100 value 79.951470
final value 79.951470
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 118.172533
iter 10 value 94.541547
iter 20 value 87.274700
iter 30 value 86.314658
iter 40 value 82.665061
iter 50 value 81.492077
iter 60 value 81.147824
iter 70 value 80.903754
iter 80 value 80.665535
iter 90 value 80.552840
iter 100 value 80.231548
final value 80.231548
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.885627
iter 10 value 94.492013
iter 20 value 89.606185
iter 30 value 87.504708
iter 40 value 82.564906
iter 50 value 81.552426
iter 60 value 80.419800
iter 70 value 80.159918
iter 80 value 79.898757
iter 90 value 79.431160
iter 100 value 79.219357
final value 79.219357
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.226097
iter 10 value 94.221833
iter 20 value 88.676615
iter 30 value 84.132086
iter 40 value 82.185360
iter 50 value 81.076166
iter 60 value 80.146679
iter 70 value 79.733458
iter 80 value 79.668599
iter 90 value 79.568844
iter 100 value 79.312589
final value 79.312589
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.416253
iter 10 value 94.661793
iter 20 value 94.221600
iter 30 value 88.767026
iter 40 value 85.943645
iter 50 value 85.025248
iter 60 value 84.395612
iter 70 value 83.774829
iter 80 value 81.242666
iter 90 value 80.538908
iter 100 value 79.741458
final value 79.741458
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.122589
final value 94.486012
converged
Fitting Repeat 2
# weights: 103
initial value 99.802027
final value 94.485573
converged
Fitting Repeat 3
# weights: 103
initial value 102.041418
final value 94.485911
converged
Fitting Repeat 4
# weights: 103
initial value 103.052698
final value 94.485815
converged
Fitting Repeat 5
# weights: 103
initial value 121.019010
iter 10 value 94.485938
final value 94.484277
converged
Fitting Repeat 1
# weights: 305
initial value 104.868013
iter 10 value 94.489530
iter 20 value 94.484211
iter 30 value 87.477183
iter 40 value 87.122832
iter 50 value 87.119197
iter 60 value 87.117554
iter 70 value 86.891294
iter 80 value 85.918607
iter 90 value 85.916016
final value 85.915993
converged
Fitting Repeat 2
# weights: 305
initial value 98.583486
iter 10 value 94.489332
iter 20 value 94.484319
iter 30 value 85.668868
final value 85.650543
converged
Fitting Repeat 3
# weights: 305
initial value 112.920518
iter 10 value 89.474997
iter 20 value 87.444867
iter 30 value 85.988432
iter 40 value 82.688753
iter 50 value 82.168761
iter 60 value 82.161642
iter 70 value 82.120389
iter 80 value 82.097874
iter 90 value 82.091075
final value 82.090537
converged
Fitting Repeat 4
# weights: 305
initial value 99.563537
iter 10 value 94.489452
iter 20 value 92.623885
iter 30 value 87.826710
iter 40 value 87.817240
iter 50 value 87.777473
iter 60 value 84.620207
iter 70 value 83.819073
iter 80 value 83.806675
iter 90 value 83.734857
iter 100 value 83.212604
final value 83.212604
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 96.833783
iter 10 value 94.448576
iter 20 value 94.443906
iter 30 value 94.386107
iter 40 value 93.914136
iter 50 value 93.172749
iter 60 value 92.891193
iter 70 value 92.881962
final value 92.881384
converged
Fitting Repeat 1
# weights: 507
initial value 109.241870
iter 10 value 94.491804
iter 20 value 94.477531
iter 30 value 87.946384
iter 40 value 87.840119
iter 50 value 86.977662
final value 86.977658
converged
Fitting Repeat 2
# weights: 507
initial value 101.890612
iter 10 value 94.450565
iter 20 value 94.304053
iter 30 value 94.297017
iter 40 value 94.289955
iter 50 value 83.964959
iter 60 value 83.368092
iter 70 value 83.349030
iter 80 value 83.127355
iter 90 value 82.944812
iter 100 value 81.075240
final value 81.075240
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 102.839171
iter 10 value 94.451615
iter 20 value 92.152886
iter 30 value 85.615659
final value 85.615487
converged
Fitting Repeat 4
# weights: 507
initial value 101.797660
iter 10 value 94.435157
iter 20 value 88.525885
iter 30 value 88.388224
iter 40 value 87.784521
iter 50 value 86.794935
iter 60 value 86.752808
iter 70 value 84.408749
iter 80 value 84.403472
iter 90 value 84.378443
iter 100 value 84.241403
final value 84.241403
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.859133
iter 10 value 94.451191
iter 20 value 93.263743
iter 30 value 89.172737
iter 40 value 83.667385
iter 50 value 80.967920
iter 60 value 79.865863
iter 70 value 78.672013
iter 80 value 78.561973
iter 90 value 78.560930
iter 100 value 78.554322
final value 78.554322
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 136.519878
iter 10 value 117.736606
iter 20 value 117.645004
iter 30 value 108.682661
final value 108.528019
converged
Fitting Repeat 2
# weights: 507
initial value 148.434850
iter 10 value 117.214468
iter 20 value 117.207659
iter 30 value 117.206209
final value 117.206177
converged
Fitting Repeat 3
# weights: 507
initial value 122.255856
iter 10 value 114.946526
iter 20 value 114.942867
iter 30 value 114.869343
iter 40 value 114.856226
iter 50 value 114.855488
iter 60 value 114.625928
final value 114.574192
converged
Fitting Repeat 4
# weights: 507
initial value 127.747603
iter 10 value 117.898568
iter 20 value 117.747299
iter 30 value 109.501332
iter 40 value 104.402342
iter 50 value 101.636846
iter 60 value 101.605479
final value 101.604782
converged
Fitting Repeat 5
# weights: 507
initial value 118.732636
iter 10 value 117.894609
iter 20 value 117.778346
iter 30 value 110.221894
final value 110.199498
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 -- Fri Mar 6 00:49:23 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
39.287 1.461 93.225
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.219 | 0.451 | 33.672 | |
| FreqInteractors | 0.456 | 0.023 | 0.478 | |
| calculateAAC | 0.031 | 0.001 | 0.033 | |
| calculateAutocor | 0.322 | 0.004 | 0.328 | |
| calculateCTDC | 0.074 | 0.001 | 0.075 | |
| calculateCTDD | 0.531 | 0.001 | 0.532 | |
| calculateCTDT | 0.190 | 0.004 | 0.195 | |
| calculateCTriad | 0.336 | 0.008 | 0.345 | |
| calculateDC | 0.084 | 0.000 | 0.084 | |
| calculateF | 0.315 | 0.000 | 0.315 | |
| calculateKSAAP | 0.102 | 0.000 | 0.102 | |
| calculateQD_Sm | 1.555 | 0.016 | 1.572 | |
| calculateTC | 1.547 | 0.033 | 1.580 | |
| calculateTC_Sm | 0.263 | 0.002 | 0.265 | |
| corr_plot | 34.268 | 0.536 | 34.805 | |
| enrichfindP | 0.536 | 0.043 | 12.655 | |
| enrichfind_hp | 0.038 | 0.004 | 1.859 | |
| enrichplot | 0.540 | 0.003 | 0.543 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.392 | 0.020 | 3.965 | |
| getHPI | 0.001 | 0.000 | 0.000 | |
| get_negativePPI | 0.001 | 0.000 | 0.001 | |
| get_positivePPI | 0.000 | 0.000 | 0.001 | |
| impute_missing_data | 0.001 | 0.000 | 0.001 | |
| plotPPI | 0.080 | 0.000 | 0.081 | |
| pred_ensembel | 12.916 | 0.136 | 11.771 | |
| var_imp | 33.099 | 0.541 | 33.641 | |