Matineh Rahmatbakhsh
| Snapshot Date: 2026-05-13 13:45 -0400 (Wed, 13 May 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: a85ff66 |
| git_last_commit_date: 2026-04-28 08:56:55 -0400 (Tue, 28 Apr 2026) |
| Back to Build/check report for BioC 3.24: simplified long |
|
This page was generated on 2026-05-14 11:32 -0400 (Thu, 14 May 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4893 |
| 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 1014/2374 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.19.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.4 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: 1.19.0 |
| Command: /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings HPiP_1.19.0.tar.gz |
| StartedAt: 2026-05-14 00:47:17 -0400 (Thu, 14 May 2026) |
| EndedAt: 2026-05-14 01:02:29 -0400 (Thu, 14 May 2026) |
| EllapsedTime: 911.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings HPiP_1.19.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-14 04:47:18 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.19.0’
* 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 34.638 0.367 35.005
FSmethod 34.255 0.370 34.626
var_imp 33.711 0.595 34.308
pred_ensembel 12.905 0.259 11.843
getFASTA 1.450 0.304 5.603
enrichfindP 0.552 0.050 10.668
* 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-3.24-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.24-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.19.0’ ** 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 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 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
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 102.327355
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 96.100906
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 110.508651
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 96.097495
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 96.255310
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 108.066131
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 96.808287
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 99.353018
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 107.398778
final value 93.836066
converged
Fitting Repeat 5
# weights: 305
initial value 99.749282
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 99.138606
iter 10 value 92.007501
iter 20 value 91.834328
final value 91.834167
converged
Fitting Repeat 2
# weights: 507
initial value 97.567160
iter 10 value 88.224418
iter 20 value 87.118280
iter 20 value 87.118279
final value 87.118261
converged
Fitting Repeat 3
# weights: 507
initial value 135.007698
iter 10 value 93.912644
iter 10 value 93.912644
iter 10 value 93.912644
final value 93.912644
converged
Fitting Repeat 4
# weights: 507
initial value 97.392408
iter 10 value 93.763669
final value 93.763158
converged
Fitting Repeat 5
# weights: 507
initial value 97.401662
iter 10 value 88.521869
iter 20 value 87.585904
iter 30 value 86.252752
iter 40 value 80.467688
iter 50 value 78.615141
iter 60 value 78.447251
iter 70 value 78.368048
iter 80 value 78.364537
iter 90 value 78.364228
final value 78.364192
converged
Fitting Repeat 1
# weights: 103
initial value 96.494419
iter 10 value 94.103406
iter 20 value 93.937180
iter 30 value 93.782951
iter 40 value 86.625388
iter 50 value 85.483231
iter 60 value 82.021478
iter 70 value 80.832828
iter 80 value 80.748164
iter 90 value 80.693815
final value 80.692490
converged
Fitting Repeat 2
# weights: 103
initial value 95.807999
iter 10 value 91.232027
iter 20 value 90.273435
iter 30 value 90.220014
iter 30 value 90.220014
iter 30 value 90.220014
final value 90.220014
converged
Fitting Repeat 3
# weights: 103
initial value 110.031284
iter 10 value 94.014914
iter 20 value 86.494259
iter 30 value 83.091829
iter 40 value 81.944932
iter 50 value 81.647763
iter 60 value 81.388016
iter 70 value 81.352365
final value 81.351390
converged
Fitting Repeat 4
# weights: 103
initial value 98.334632
iter 10 value 93.993040
iter 20 value 87.638627
iter 30 value 87.463556
iter 40 value 87.124907
iter 50 value 86.885388
iter 60 value 81.585071
iter 70 value 81.456285
iter 80 value 81.357958
final value 81.351390
converged
Fitting Repeat 5
# weights: 103
initial value 107.179038
iter 10 value 93.993773
iter 20 value 88.734745
iter 30 value 83.394257
iter 40 value 81.739974
iter 50 value 81.560211
iter 60 value 81.351514
final value 81.351390
converged
Fitting Repeat 1
# weights: 305
initial value 104.833115
iter 10 value 93.948437
iter 20 value 93.277290
iter 30 value 85.859879
iter 40 value 81.567993
iter 50 value 81.205018
iter 60 value 80.770484
iter 70 value 79.741422
iter 80 value 78.935384
iter 90 value 78.596114
iter 100 value 78.143378
final value 78.143378
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.716574
iter 10 value 93.765278
iter 20 value 89.393698
iter 30 value 86.012719
iter 40 value 81.501056
iter 50 value 81.252243
iter 60 value 80.898467
iter 70 value 79.664892
iter 80 value 78.890087
iter 90 value 78.585431
iter 100 value 78.343782
final value 78.343782
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.187685
iter 10 value 95.252209
iter 20 value 85.603153
iter 30 value 84.715177
iter 40 value 84.041366
iter 50 value 82.969847
iter 60 value 80.971438
iter 70 value 79.089352
iter 80 value 78.646017
iter 90 value 78.619789
iter 100 value 78.474343
final value 78.474343
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 115.847658
iter 10 value 94.078548
iter 20 value 93.831664
iter 30 value 85.815940
iter 40 value 85.262578
iter 50 value 84.834668
iter 60 value 83.640459
iter 70 value 80.917484
iter 80 value 80.262012
iter 90 value 79.969911
iter 100 value 79.018809
final value 79.018809
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.889871
iter 10 value 93.851784
iter 20 value 85.291558
iter 30 value 83.003227
iter 40 value 82.884221
iter 50 value 82.457963
iter 60 value 81.343199
iter 70 value 80.078443
iter 80 value 79.048842
iter 90 value 78.312447
iter 100 value 78.183228
final value 78.183228
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.676580
iter 10 value 94.747445
iter 20 value 90.349787
iter 30 value 84.882516
iter 40 value 83.422226
iter 50 value 82.558466
iter 60 value 81.994481
iter 70 value 81.880138
iter 80 value 80.168684
iter 90 value 78.770599
iter 100 value 78.571173
final value 78.571173
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.633683
iter 10 value 94.173917
iter 20 value 85.608855
iter 30 value 85.022514
iter 40 value 80.847834
iter 50 value 80.448975
iter 60 value 80.265213
iter 70 value 80.064732
iter 80 value 79.246387
iter 90 value 78.758070
iter 100 value 78.529792
final value 78.529792
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.891820
iter 10 value 94.378826
iter 20 value 94.172560
iter 30 value 86.443323
iter 40 value 85.771083
iter 50 value 83.804641
iter 60 value 82.112385
iter 70 value 80.463982
iter 80 value 78.841340
iter 90 value 78.513096
iter 100 value 78.169194
final value 78.169194
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.306325
iter 10 value 93.720417
iter 20 value 85.609757
iter 30 value 81.539596
iter 40 value 79.263472
iter 50 value 78.965060
iter 60 value 78.860429
iter 70 value 78.707220
iter 80 value 78.667969
iter 90 value 78.616774
iter 100 value 78.567166
final value 78.567166
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.422358
iter 10 value 94.520268
iter 20 value 82.632324
iter 30 value 81.476714
iter 40 value 81.223059
iter 50 value 79.431604
iter 60 value 78.948150
iter 70 value 78.527290
iter 80 value 78.238719
iter 90 value 77.886255
iter 100 value 77.802630
final value 77.802630
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.387684
final value 94.054527
converged
Fitting Repeat 2
# weights: 103
initial value 96.706013
final value 94.054654
converged
Fitting Repeat 3
# weights: 103
initial value 94.184596
final value 94.054591
converged
Fitting Repeat 4
# weights: 103
initial value 98.195945
final value 94.054715
converged
Fitting Repeat 5
# weights: 103
initial value 100.144500
final value 94.054368
converged
Fitting Repeat 1
# weights: 305
initial value 119.827520
iter 10 value 90.666861
iter 20 value 89.300663
iter 30 value 89.298969
iter 40 value 89.290844
iter 50 value 82.861868
iter 60 value 82.860280
iter 70 value 82.857604
iter 80 value 82.855922
iter 90 value 82.786874
iter 100 value 82.392384
final value 82.392384
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 94.482527
iter 10 value 94.054953
iter 20 value 93.868026
iter 30 value 88.020951
iter 40 value 83.770722
iter 50 value 82.366334
iter 60 value 81.108542
iter 70 value 80.117603
iter 80 value 78.793050
iter 90 value 78.759560
iter 100 value 78.756362
final value 78.756362
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.391542
iter 10 value 86.973786
iter 20 value 81.536877
iter 30 value 81.535026
iter 40 value 81.534156
iter 50 value 79.771332
iter 60 value 78.949687
iter 70 value 78.660126
iter 80 value 78.631634
iter 90 value 78.631380
iter 100 value 78.630932
final value 78.630932
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 110.648417
iter 10 value 94.058158
iter 20 value 94.052941
final value 94.052923
converged
Fitting Repeat 5
# weights: 305
initial value 100.781116
iter 10 value 93.841199
iter 20 value 93.836612
iter 30 value 93.297647
iter 40 value 91.504185
iter 50 value 91.067887
iter 60 value 83.688149
iter 70 value 81.442538
iter 80 value 80.475276
iter 90 value 80.434222
final value 80.434135
converged
Fitting Repeat 1
# weights: 507
initial value 98.251849
iter 10 value 94.060572
iter 20 value 86.301483
iter 30 value 84.352341
final value 84.352261
converged
Fitting Repeat 2
# weights: 507
initial value 102.187227
iter 10 value 93.844252
iter 20 value 93.838596
iter 30 value 93.452491
iter 40 value 91.495475
iter 50 value 85.069430
iter 60 value 81.532286
final value 81.532253
converged
Fitting Repeat 3
# weights: 507
initial value 102.358045
iter 10 value 94.061003
iter 20 value 94.038772
iter 30 value 92.641070
iter 40 value 84.782515
iter 50 value 80.829563
iter 60 value 78.395280
iter 70 value 78.360541
iter 80 value 78.132646
iter 90 value 77.298833
iter 100 value 76.230824
final value 76.230824
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 98.959213
iter 10 value 93.911562
iter 20 value 93.904242
iter 30 value 89.543993
iter 40 value 87.052548
iter 50 value 83.061210
iter 60 value 77.110604
iter 70 value 77.060550
iter 80 value 76.870939
iter 90 value 76.735001
iter 100 value 76.141774
final value 76.141774
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 95.645633
iter 10 value 93.907947
iter 20 value 93.833460
final value 93.697968
converged
Fitting Repeat 1
# weights: 103
initial value 97.722984
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 104.708961
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 100.247607
final value 94.052874
converged
Fitting Repeat 4
# weights: 103
initial value 101.199882
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 96.533899
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 102.347438
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 107.857735
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 115.347565
iter 10 value 94.022604
final value 94.022599
converged
Fitting Repeat 4
# weights: 305
initial value 105.728108
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 102.692323
iter 10 value 94.052910
iter 10 value 94.052910
iter 10 value 94.052910
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 96.904682
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 100.731231
iter 10 value 94.034003
final value 94.032967
converged
Fitting Repeat 3
# weights: 507
initial value 101.802208
final value 94.032967
converged
Fitting Repeat 4
# weights: 507
initial value 108.919297
final value 94.032967
converged
Fitting Repeat 5
# weights: 507
initial value 95.804931
iter 10 value 94.049801
iter 20 value 93.828509
final value 93.540906
converged
Fitting Repeat 1
# weights: 103
initial value 95.985904
iter 10 value 93.411153
iter 20 value 87.929776
iter 30 value 86.698797
iter 40 value 84.237849
iter 50 value 83.369459
iter 60 value 83.292310
final value 83.281842
converged
Fitting Repeat 2
# weights: 103
initial value 109.890126
iter 10 value 93.952280
iter 20 value 89.351160
iter 30 value 88.173968
iter 40 value 84.021557
iter 50 value 83.116616
iter 60 value 83.029546
iter 70 value 82.862237
iter 80 value 82.602041
iter 90 value 82.353050
iter 100 value 82.177050
final value 82.177050
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 95.618646
iter 10 value 94.056755
iter 20 value 93.958904
iter 30 value 91.741958
iter 40 value 90.156457
iter 50 value 85.563756
iter 60 value 85.144352
iter 70 value 84.930589
iter 80 value 84.636071
iter 90 value 84.560121
iter 100 value 84.500068
final value 84.500068
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 99.606599
iter 10 value 94.056871
iter 20 value 93.554150
iter 30 value 87.960897
iter 40 value 86.021366
iter 50 value 85.772876
iter 60 value 85.298747
iter 70 value 84.036204
iter 80 value 83.408962
iter 90 value 83.268139
iter 100 value 83.021895
final value 83.021895
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 106.540450
iter 10 value 93.930038
iter 20 value 87.852971
iter 30 value 87.075486
iter 40 value 86.830125
iter 50 value 85.506768
iter 60 value 85.484397
iter 70 value 84.306900
iter 80 value 84.146083
iter 90 value 84.076535
final value 84.070010
converged
Fitting Repeat 1
# weights: 305
initial value 120.123887
iter 10 value 94.353647
iter 20 value 90.638800
iter 30 value 88.571362
iter 40 value 85.218172
iter 50 value 84.809764
iter 60 value 84.685134
iter 70 value 84.631829
iter 80 value 84.269376
iter 90 value 84.255618
iter 100 value 84.225081
final value 84.225081
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.087143
iter 10 value 94.058090
iter 20 value 91.556092
iter 30 value 86.652256
iter 40 value 85.521476
iter 50 value 83.918734
iter 60 value 83.745229
iter 70 value 82.530515
iter 80 value 80.715671
iter 90 value 80.122789
iter 100 value 80.007972
final value 80.007972
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.863514
iter 10 value 94.178580
iter 20 value 94.052363
iter 30 value 89.148797
iter 40 value 85.811990
iter 50 value 85.490576
iter 60 value 84.703870
iter 70 value 84.587413
iter 80 value 82.762572
iter 90 value 81.042528
iter 100 value 80.958950
final value 80.958950
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.505783
iter 10 value 92.278881
iter 20 value 84.606933
iter 30 value 82.775734
iter 40 value 82.517963
iter 50 value 82.042336
iter 60 value 81.901552
iter 70 value 81.834547
iter 80 value 81.814063
iter 90 value 81.793644
iter 100 value 81.228539
final value 81.228539
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.861722
iter 10 value 94.007421
iter 20 value 91.475362
iter 30 value 87.540152
iter 40 value 87.291228
iter 50 value 85.784110
iter 60 value 83.765217
iter 70 value 82.794352
iter 80 value 82.112578
iter 90 value 81.949708
iter 100 value 81.424635
final value 81.424635
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 117.003564
iter 10 value 94.072813
iter 20 value 93.423958
iter 30 value 90.740507
iter 40 value 85.673609
iter 50 value 85.072693
iter 60 value 83.039519
iter 70 value 81.697133
iter 80 value 81.111041
iter 90 value 80.592153
iter 100 value 80.439715
final value 80.439715
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.481911
iter 10 value 94.322485
iter 20 value 93.966365
iter 30 value 89.071250
iter 40 value 88.321210
iter 50 value 86.333546
iter 60 value 82.252864
iter 70 value 81.608419
iter 80 value 81.360783
iter 90 value 81.047861
iter 100 value 80.207733
final value 80.207733
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 118.853292
iter 10 value 98.512917
iter 20 value 93.472654
iter 30 value 84.705792
iter 40 value 83.849923
iter 50 value 83.049310
iter 60 value 82.423884
iter 70 value 81.184998
iter 80 value 81.039389
iter 90 value 80.841986
iter 100 value 80.654711
final value 80.654711
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.783203
iter 10 value 94.532084
iter 20 value 93.223621
iter 30 value 87.846556
iter 40 value 81.754364
iter 50 value 80.349641
iter 60 value 80.240475
iter 70 value 79.933034
iter 80 value 79.625288
iter 90 value 79.570352
iter 100 value 79.555293
final value 79.555293
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 119.434043
iter 10 value 94.159307
iter 20 value 87.657754
iter 30 value 87.383538
iter 40 value 85.150618
iter 50 value 84.594076
iter 60 value 83.429967
iter 70 value 82.041396
iter 80 value 81.683866
iter 90 value 80.916422
iter 100 value 80.487786
final value 80.487786
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.060019
final value 94.054497
converged
Fitting Repeat 2
# weights: 103
initial value 98.078506
final value 94.054491
converged
Fitting Repeat 3
# weights: 103
initial value 96.758107
final value 94.054783
converged
Fitting Repeat 4
# weights: 103
initial value 94.656180
iter 10 value 94.034642
final value 94.034635
converged
Fitting Repeat 5
# weights: 103
initial value 97.599238
iter 10 value 94.054716
iter 20 value 94.052971
iter 30 value 93.765055
iter 40 value 93.721205
final value 93.721200
converged
Fitting Repeat 1
# weights: 305
initial value 100.459769
iter 10 value 94.063086
iter 20 value 92.105445
iter 30 value 87.606650
iter 40 value 87.140344
iter 50 value 87.043286
iter 60 value 86.842998
iter 70 value 86.824339
iter 80 value 86.823969
iter 90 value 86.279870
iter 100 value 86.277492
final value 86.277492
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 94.522954
iter 10 value 88.891297
iter 20 value 88.385327
iter 30 value 88.244566
iter 40 value 88.240127
iter 50 value 86.016268
iter 60 value 85.950169
iter 70 value 85.944849
final value 85.944377
converged
Fitting Repeat 3
# weights: 305
initial value 101.717749
iter 10 value 94.037201
iter 20 value 94.033309
iter 30 value 93.477088
iter 40 value 84.762899
iter 50 value 83.742217
iter 60 value 83.543716
iter 70 value 81.243887
iter 80 value 79.533435
iter 90 value 79.449781
iter 100 value 79.449208
final value 79.449208
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.841909
iter 10 value 94.058395
iter 20 value 93.907163
iter 30 value 91.972858
iter 40 value 91.959209
iter 50 value 91.958077
iter 60 value 91.785039
iter 70 value 91.656144
iter 80 value 91.647432
iter 90 value 91.647279
final value 91.647276
converged
Fitting Repeat 5
# weights: 305
initial value 97.329192
iter 10 value 93.416086
iter 20 value 85.607814
iter 30 value 85.318943
iter 40 value 85.145411
iter 50 value 83.634992
iter 60 value 83.423519
iter 70 value 83.243374
iter 80 value 82.419251
iter 90 value 81.319762
iter 100 value 81.313146
final value 81.313146
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 96.582107
iter 10 value 91.833504
iter 20 value 87.391126
iter 30 value 87.082965
iter 40 value 87.080643
iter 50 value 87.075168
final value 87.073073
converged
Fitting Repeat 2
# weights: 507
initial value 96.427619
iter 10 value 94.061208
iter 20 value 94.052919
iter 20 value 94.052919
final value 94.052919
converged
Fitting Repeat 3
# weights: 507
initial value 101.692511
iter 10 value 83.747395
iter 20 value 83.446138
final value 83.440413
converged
Fitting Repeat 4
# weights: 507
initial value 96.707940
iter 10 value 94.063925
iter 20 value 94.054361
iter 30 value 90.253407
iter 40 value 85.901010
iter 50 value 85.824920
iter 60 value 85.747265
iter 70 value 85.669685
iter 80 value 85.636375
iter 90 value 85.556859
iter 100 value 85.115724
final value 85.115724
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 97.187483
iter 10 value 94.030501
iter 20 value 94.022759
iter 30 value 85.484452
iter 40 value 84.270854
iter 50 value 82.373998
iter 60 value 81.983792
iter 70 value 81.774609
iter 80 value 81.350846
iter 90 value 80.414609
iter 100 value 79.712478
final value 79.712478
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.530326
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.701443
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.219493
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.911750
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 101.182669
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 120.876350
iter 10 value 94.112570
iter 10 value 94.112570
iter 10 value 94.112570
final value 94.112570
converged
Fitting Repeat 2
# weights: 305
initial value 97.142866
final value 94.466823
converged
Fitting Repeat 3
# weights: 305
initial value 101.059549
final value 94.466823
converged
Fitting Repeat 4
# weights: 305
initial value 131.562106
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 118.230613
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 111.184286
final value 94.466823
converged
Fitting Repeat 2
# weights: 507
initial value 113.387437
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 97.722605
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 104.146068
iter 10 value 94.466823
iter 10 value 94.466823
iter 10 value 94.466823
final value 94.466823
converged
Fitting Repeat 5
# weights: 507
initial value 113.709112
final value 94.466823
converged
Fitting Repeat 1
# weights: 103
initial value 102.762321
iter 10 value 94.488533
iter 20 value 89.715015
iter 30 value 84.861824
iter 40 value 82.083606
iter 50 value 81.941686
iter 60 value 80.196801
iter 70 value 79.873692
final value 79.841553
converged
Fitting Repeat 2
# weights: 103
initial value 108.030808
iter 10 value 94.481361
iter 20 value 94.208014
iter 30 value 94.133826
iter 40 value 91.397060
iter 50 value 85.637798
iter 60 value 84.567814
iter 70 value 81.299372
iter 80 value 80.291843
iter 90 value 79.957631
iter 100 value 79.890973
final value 79.890973
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.321224
iter 10 value 94.495837
iter 20 value 94.289725
iter 30 value 87.334724
iter 40 value 86.083491
iter 50 value 85.989253
iter 60 value 85.083015
iter 70 value 84.598974
iter 80 value 84.556304
iter 90 value 84.460659
iter 100 value 84.445208
final value 84.445208
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 97.604315
iter 10 value 94.409691
iter 20 value 88.072286
iter 30 value 86.000558
iter 40 value 85.975040
iter 50 value 85.912911
iter 60 value 84.470395
iter 70 value 84.447000
final value 84.446965
converged
Fitting Repeat 5
# weights: 103
initial value 103.547113
iter 10 value 94.450018
iter 20 value 85.153805
iter 30 value 84.906125
iter 40 value 84.676844
iter 50 value 84.566474
iter 60 value 84.457839
iter 70 value 84.446981
iter 80 value 84.444801
final value 84.444683
converged
Fitting Repeat 1
# weights: 305
initial value 116.829293
iter 10 value 94.542271
iter 20 value 86.185787
iter 30 value 82.361298
iter 40 value 80.999916
iter 50 value 80.607281
iter 60 value 80.409730
iter 70 value 80.223190
iter 80 value 80.029021
iter 90 value 79.696938
iter 100 value 79.567615
final value 79.567615
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 127.879725
iter 10 value 95.009583
iter 20 value 94.429178
iter 30 value 87.216260
iter 40 value 86.505782
iter 50 value 84.429284
iter 60 value 84.237857
iter 70 value 84.218415
iter 80 value 84.157796
iter 90 value 83.089495
iter 100 value 82.102678
final value 82.102678
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.114845
iter 10 value 94.789779
iter 20 value 94.416402
iter 30 value 92.537310
iter 40 value 88.419118
iter 50 value 88.006625
iter 60 value 84.653331
iter 70 value 81.698204
iter 80 value 81.279965
iter 90 value 81.121397
iter 100 value 81.117182
final value 81.117182
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 112.821139
iter 10 value 93.826411
iter 20 value 87.465174
iter 30 value 86.509352
iter 40 value 86.143646
iter 50 value 82.869723
iter 60 value 81.141152
iter 70 value 80.013460
iter 80 value 79.697381
iter 90 value 79.487270
iter 100 value 79.412657
final value 79.412657
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.697979
iter 10 value 94.659196
iter 20 value 94.395561
iter 30 value 89.018970
iter 40 value 87.619302
iter 50 value 85.236036
iter 60 value 83.151655
iter 70 value 82.315961
iter 80 value 80.890309
iter 90 value 80.239697
iter 100 value 79.586316
final value 79.586316
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.952955
iter 10 value 94.568730
iter 20 value 94.179153
iter 30 value 91.652489
iter 40 value 87.577986
iter 50 value 84.879011
iter 60 value 84.338178
iter 70 value 80.478913
iter 80 value 79.514133
iter 90 value 79.091193
iter 100 value 78.846453
final value 78.846453
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.628458
iter 10 value 92.562053
iter 20 value 85.085311
iter 30 value 84.649509
iter 40 value 84.409920
iter 50 value 84.306219
iter 60 value 84.234260
iter 70 value 83.456829
iter 80 value 80.753822
iter 90 value 80.297907
iter 100 value 79.925367
final value 79.925367
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 118.256242
iter 10 value 94.298101
iter 20 value 83.704111
iter 30 value 82.159544
iter 40 value 82.039764
iter 50 value 80.175888
iter 60 value 79.676252
iter 70 value 79.610885
iter 80 value 79.507275
iter 90 value 79.203762
iter 100 value 78.864823
final value 78.864823
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.495921
iter 10 value 95.599585
iter 20 value 86.377672
iter 30 value 83.875978
iter 40 value 80.453917
iter 50 value 79.995443
iter 60 value 79.559231
iter 70 value 79.439718
iter 80 value 79.243717
iter 90 value 79.054765
iter 100 value 78.937189
final value 78.937189
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.061404
iter 10 value 91.049460
iter 20 value 85.203720
iter 30 value 82.762248
iter 40 value 81.387861
iter 50 value 80.780467
iter 60 value 80.344371
iter 70 value 80.268199
iter 80 value 79.448058
iter 90 value 79.082917
iter 100 value 78.945670
final value 78.945670
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.436826
final value 94.486156
converged
Fitting Repeat 2
# weights: 103
initial value 111.563177
iter 10 value 94.486265
iter 20 value 94.484228
iter 30 value 94.354865
iter 40 value 94.069112
iter 50 value 94.062110
final value 94.062106
converged
Fitting Repeat 3
# weights: 103
initial value 95.013094
final value 94.485752
converged
Fitting Repeat 4
# weights: 103
initial value 98.964291
final value 94.485617
converged
Fitting Repeat 5
# weights: 103
initial value 98.613022
final value 94.486014
converged
Fitting Repeat 1
# weights: 305
initial value 98.593371
iter 10 value 94.485542
iter 20 value 93.842640
iter 30 value 92.202605
final value 90.548827
converged
Fitting Repeat 2
# weights: 305
initial value 96.322688
iter 10 value 94.489099
iter 20 value 94.473058
iter 30 value 86.110503
iter 40 value 85.487887
iter 50 value 85.418043
final value 85.417256
converged
Fitting Repeat 3
# weights: 305
initial value 99.306234
iter 10 value 94.489634
iter 20 value 94.449778
iter 30 value 93.439041
iter 40 value 92.472126
iter 50 value 92.469613
iter 60 value 92.387982
final value 92.387751
converged
Fitting Repeat 4
# weights: 305
initial value 107.885666
iter 10 value 94.471551
iter 20 value 92.977916
iter 30 value 84.591294
iter 40 value 84.438947
iter 50 value 84.435726
final value 84.426970
converged
Fitting Repeat 5
# weights: 305
initial value 106.601735
iter 10 value 94.488541
iter 20 value 94.484282
iter 30 value 94.247691
iter 40 value 91.646623
iter 50 value 85.807807
iter 60 value 84.093550
iter 70 value 84.090426
iter 80 value 84.057206
iter 90 value 84.054572
iter 100 value 83.427883
final value 83.427883
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 121.388690
iter 10 value 94.492441
iter 20 value 94.484609
iter 30 value 86.333249
iter 40 value 80.763259
iter 50 value 79.922795
iter 60 value 79.775666
iter 70 value 79.747977
iter 80 value 79.383098
iter 90 value 79.381608
iter 100 value 79.381440
final value 79.381440
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 95.025769
iter 10 value 92.852641
iter 20 value 92.844655
iter 30 value 92.843815
iter 40 value 92.772511
iter 50 value 92.756385
iter 60 value 92.755866
iter 70 value 92.751606
iter 80 value 92.751081
iter 90 value 92.414813
iter 100 value 91.749230
final value 91.749230
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 116.831694
iter 10 value 94.105404
iter 20 value 94.085892
iter 30 value 94.050553
iter 40 value 94.033071
iter 50 value 94.031144
final value 94.031009
converged
Fitting Repeat 4
# weights: 507
initial value 132.528796
iter 10 value 94.155895
iter 20 value 94.149143
iter 30 value 94.067416
iter 40 value 94.030676
final value 94.029739
converged
Fitting Repeat 5
# weights: 507
initial value 98.684661
iter 10 value 94.492361
final value 94.484287
converged
Fitting Repeat 1
# weights: 103
initial value 104.911612
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 102.337588
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.309593
iter 10 value 92.935559
iter 20 value 92.756441
final value 92.655174
converged
Fitting Repeat 4
# weights: 103
initial value 104.388160
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 104.734954
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 94.849780
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 104.762645
iter 10 value 87.627982
iter 20 value 85.417205
iter 30 value 85.371915
iter 40 value 85.371796
final value 85.371795
converged
Fitting Repeat 3
# weights: 305
initial value 97.935115
iter 10 value 94.069055
final value 94.065746
converged
Fitting Repeat 4
# weights: 305
initial value 96.867328
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 97.357973
iter 10 value 93.359401
final value 88.522367
converged
Fitting Repeat 1
# weights: 507
initial value 115.368472
iter 10 value 94.479530
final value 94.479526
converged
Fitting Repeat 2
# weights: 507
initial value 109.345979
final value 94.443182
converged
Fitting Repeat 3
# weights: 507
initial value 102.577078
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 97.597157
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 99.532668
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 96.782872
iter 10 value 94.491669
iter 20 value 91.415532
iter 30 value 87.098307
iter 40 value 86.141296
iter 50 value 85.595056
iter 60 value 85.557687
final value 85.552223
converged
Fitting Repeat 2
# weights: 103
initial value 102.004580
iter 10 value 94.486822
iter 20 value 94.338747
iter 30 value 94.035221
iter 40 value 93.930742
iter 50 value 87.288593
iter 60 value 86.304435
iter 70 value 85.914649
iter 80 value 85.344903
iter 90 value 85.053873
iter 100 value 84.973530
final value 84.973530
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 105.793420
iter 10 value 94.138410
iter 20 value 88.706744
iter 30 value 86.796229
iter 40 value 85.326834
iter 50 value 84.479312
iter 60 value 84.220138
iter 70 value 83.626136
iter 80 value 83.034775
iter 90 value 82.853232
final value 82.847674
converged
Fitting Repeat 4
# weights: 103
initial value 98.118369
iter 10 value 94.515488
iter 20 value 94.484630
iter 30 value 87.012587
iter 40 value 86.067897
iter 50 value 85.911333
iter 60 value 85.641829
iter 70 value 85.552370
iter 80 value 85.552225
final value 85.552223
converged
Fitting Repeat 5
# weights: 103
initial value 100.110175
iter 10 value 94.488697
iter 20 value 94.483771
iter 30 value 94.332260
iter 40 value 89.700772
iter 50 value 86.410420
iter 60 value 86.302044
iter 70 value 85.950127
iter 80 value 85.561307
final value 85.552223
converged
Fitting Repeat 1
# weights: 305
initial value 100.760376
iter 10 value 94.449445
iter 20 value 92.345610
iter 30 value 89.528187
iter 40 value 86.137409
iter 50 value 84.361839
iter 60 value 83.796859
iter 70 value 83.444830
iter 80 value 83.277669
iter 90 value 83.262465
iter 100 value 83.183963
final value 83.183963
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.831075
iter 10 value 94.552194
iter 20 value 89.188056
iter 30 value 86.853738
iter 40 value 85.951377
iter 50 value 83.726984
iter 60 value 82.259104
iter 70 value 81.507514
iter 80 value 81.149811
iter 90 value 81.136061
iter 100 value 81.132116
final value 81.132116
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.782959
iter 10 value 94.614557
iter 20 value 94.073010
iter 30 value 94.017402
iter 40 value 93.835940
iter 50 value 91.420860
iter 60 value 86.367432
iter 70 value 85.136547
iter 80 value 83.854196
iter 90 value 83.288541
iter 100 value 82.620172
final value 82.620172
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.294771
iter 10 value 94.466238
iter 20 value 89.400240
iter 30 value 85.376017
iter 40 value 84.608888
iter 50 value 82.808993
iter 60 value 81.941380
iter 70 value 81.661958
iter 80 value 81.478429
iter 90 value 81.462871
iter 100 value 81.453257
final value 81.453257
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.370842
iter 10 value 94.482407
iter 20 value 87.579968
iter 30 value 85.895841
iter 40 value 85.819067
iter 50 value 85.717188
iter 60 value 84.280877
iter 70 value 83.150320
iter 80 value 82.546766
iter 90 value 81.569504
iter 100 value 81.192785
final value 81.192785
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 119.383796
iter 10 value 94.735768
iter 20 value 94.591103
iter 30 value 94.329865
iter 40 value 93.534442
iter 50 value 91.451248
iter 60 value 89.101763
iter 70 value 86.851524
iter 80 value 86.300921
iter 90 value 84.160928
iter 100 value 83.043749
final value 83.043749
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 121.249607
iter 10 value 95.156377
iter 20 value 87.325286
iter 30 value 86.824918
iter 40 value 83.848219
iter 50 value 82.283398
iter 60 value 81.712451
iter 70 value 81.290634
iter 80 value 81.210502
iter 90 value 80.899536
iter 100 value 80.695549
final value 80.695549
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.641340
iter 10 value 94.681416
iter 20 value 92.806787
iter 30 value 87.819598
iter 40 value 85.749124
iter 50 value 84.483940
iter 60 value 84.031400
iter 70 value 82.385772
iter 80 value 81.714930
iter 90 value 81.064715
iter 100 value 80.965134
final value 80.965134
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.494249
iter 10 value 94.708307
iter 20 value 92.616266
iter 30 value 84.657819
iter 40 value 83.290696
iter 50 value 82.665971
iter 60 value 82.253665
iter 70 value 81.574545
iter 80 value 81.301259
iter 90 value 81.281691
iter 100 value 81.264904
final value 81.264904
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.322854
iter 10 value 94.231934
iter 20 value 87.073854
iter 30 value 86.825580
iter 40 value 86.385864
iter 50 value 83.577227
iter 60 value 83.027187
iter 70 value 82.371142
iter 80 value 82.000207
iter 90 value 81.206261
iter 100 value 81.028475
final value 81.028475
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.714729
final value 94.485704
converged
Fitting Repeat 2
# weights: 103
initial value 103.743106
iter 10 value 94.444997
iter 20 value 94.215267
iter 30 value 93.922512
final value 93.922507
converged
Fitting Repeat 3
# weights: 103
initial value 96.711478
final value 94.444842
converged
Fitting Repeat 4
# weights: 103
initial value 101.218256
final value 94.485835
converged
Fitting Repeat 5
# weights: 103
initial value 106.924522
iter 10 value 93.925312
iter 20 value 93.923892
iter 30 value 93.923713
iter 40 value 93.923029
final value 93.922982
converged
Fitting Repeat 1
# weights: 305
initial value 108.083193
iter 10 value 94.489120
iter 20 value 94.484308
iter 20 value 94.484307
final value 94.484307
converged
Fitting Repeat 2
# weights: 305
initial value 117.061152
iter 10 value 94.048196
iter 20 value 93.137955
iter 30 value 92.761525
iter 40 value 92.620082
iter 50 value 92.561639
iter 60 value 92.319545
iter 70 value 92.307356
iter 80 value 92.306693
iter 90 value 92.306173
final value 92.306166
converged
Fitting Repeat 3
# weights: 305
initial value 95.378451
iter 10 value 94.488893
iter 20 value 94.443383
iter 30 value 90.734588
iter 40 value 87.338012
iter 50 value 87.031753
iter 60 value 86.315307
iter 70 value 86.313457
iter 80 value 86.308186
iter 80 value 86.308186
final value 86.308186
converged
Fitting Repeat 4
# weights: 305
initial value 109.961680
iter 10 value 94.489306
iter 20 value 94.129807
iter 30 value 88.279243
iter 40 value 84.519072
iter 50 value 81.381154
iter 60 value 80.684554
iter 70 value 80.012578
iter 80 value 79.735860
iter 90 value 79.630298
iter 100 value 79.614468
final value 79.614468
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.944434
iter 10 value 94.448107
iter 20 value 94.023944
iter 30 value 85.270772
iter 40 value 85.068665
iter 50 value 85.027766
iter 60 value 85.026068
iter 70 value 84.994063
iter 80 value 84.599133
iter 90 value 84.429762
iter 100 value 82.296528
final value 82.296528
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.519877
iter 10 value 94.331637
iter 20 value 93.988328
iter 30 value 89.429820
iter 40 value 88.907387
iter 50 value 88.847576
final value 88.847316
converged
Fitting Repeat 2
# weights: 507
initial value 99.180079
iter 10 value 90.378043
iter 20 value 87.214632
iter 30 value 87.163799
iter 40 value 87.162631
iter 50 value 87.158393
iter 60 value 85.774011
iter 70 value 83.688161
iter 80 value 83.680851
iter 90 value 83.680379
iter 100 value 83.296194
final value 83.296194
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 101.791562
iter 10 value 94.490590
iter 20 value 93.468700
iter 30 value 88.135124
iter 40 value 87.811859
iter 50 value 87.221630
iter 60 value 86.158431
iter 70 value 86.142679
iter 80 value 85.464778
iter 90 value 85.457697
final value 85.457649
converged
Fitting Repeat 4
# weights: 507
initial value 96.982237
iter 10 value 93.956988
iter 20 value 93.952062
iter 30 value 93.089149
iter 40 value 92.859405
iter 50 value 92.763779
iter 60 value 92.762699
iter 70 value 92.761047
iter 80 value 92.146410
iter 90 value 85.867279
iter 100 value 83.482521
final value 83.482521
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 129.928030
iter 10 value 94.452176
iter 20 value 94.444464
final value 94.443286
converged
Fitting Repeat 1
# weights: 103
initial value 110.342258
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 98.657046
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.744240
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 113.529332
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 100.346105
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 102.271654
final value 93.218182
converged
Fitting Repeat 2
# weights: 305
initial value 96.240648
final value 94.026542
converged
Fitting Repeat 3
# weights: 305
initial value 130.830070
iter 10 value 94.026568
final value 94.026542
converged
Fitting Repeat 4
# weights: 305
initial value 101.614045
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 96.147558
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 100.053012
iter 10 value 88.822963
final value 86.307879
converged
Fitting Repeat 2
# weights: 507
initial value 96.960411
iter 10 value 94.459471
final value 94.326057
converged
Fitting Repeat 3
# weights: 507
initial value 101.609003
iter 10 value 94.052265
final value 93.693109
converged
Fitting Repeat 4
# weights: 507
initial value 96.116549
iter 10 value 93.598424
iter 20 value 93.036631
iter 30 value 92.682159
final value 92.682071
converged
Fitting Repeat 5
# weights: 507
initial value 117.191145
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 99.368706
iter 10 value 94.374890
iter 20 value 93.818157
iter 30 value 91.905242
iter 40 value 86.569263
iter 50 value 85.846431
iter 60 value 85.625662
iter 70 value 85.599347
final value 85.599327
converged
Fitting Repeat 2
# weights: 103
initial value 111.468744
iter 10 value 94.486799
iter 20 value 93.935153
iter 30 value 93.723676
iter 40 value 89.703902
iter 50 value 87.651730
iter 60 value 86.619747
iter 70 value 84.177451
iter 80 value 83.845321
iter 90 value 83.149392
iter 100 value 82.814583
final value 82.814583
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 112.045204
iter 10 value 94.469273
iter 20 value 89.246417
iter 30 value 87.294859
iter 40 value 87.182952
iter 50 value 86.001631
iter 60 value 84.825798
iter 70 value 84.276533
iter 80 value 83.886655
iter 90 value 83.821481
iter 100 value 83.800875
final value 83.800875
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.039482
iter 10 value 94.486457
iter 20 value 87.669376
iter 30 value 84.227376
iter 40 value 84.014671
iter 50 value 83.972358
iter 60 value 83.942349
iter 70 value 83.928957
final value 83.928740
converged
Fitting Repeat 5
# weights: 103
initial value 99.451206
iter 10 value 94.477775
iter 20 value 93.067356
iter 30 value 91.461753
iter 40 value 91.116514
iter 50 value 86.462385
iter 60 value 83.870010
iter 70 value 83.688066
iter 80 value 83.319140
iter 90 value 82.773877
iter 100 value 82.711072
final value 82.711072
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 126.781841
iter 10 value 94.390892
iter 20 value 91.834364
iter 30 value 86.488836
iter 40 value 84.359089
iter 50 value 84.167724
iter 60 value 83.559631
iter 70 value 83.303665
iter 80 value 82.459595
iter 90 value 82.071216
iter 100 value 81.933633
final value 81.933633
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.959804
iter 10 value 94.055615
iter 20 value 85.617454
iter 30 value 85.468519
iter 40 value 84.458783
iter 50 value 83.059736
iter 60 value 82.675749
iter 70 value 82.244510
iter 80 value 82.065750
iter 90 value 81.916589
iter 100 value 81.721043
final value 81.721043
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.367659
iter 10 value 95.863174
iter 20 value 94.340351
iter 30 value 94.264071
iter 40 value 93.744932
iter 50 value 93.704912
iter 60 value 88.165269
iter 70 value 86.690380
iter 80 value 86.321341
iter 90 value 86.005493
iter 100 value 83.689796
final value 83.689796
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.752919
iter 10 value 94.377591
iter 20 value 85.079653
iter 30 value 84.391135
iter 40 value 84.112453
iter 50 value 83.819329
iter 60 value 83.761072
iter 70 value 83.381618
iter 80 value 82.073902
iter 90 value 81.895857
iter 100 value 81.730561
final value 81.730561
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.852276
iter 10 value 88.919477
iter 20 value 84.937339
iter 30 value 84.213988
iter 40 value 83.237384
iter 50 value 82.490492
iter 60 value 82.229649
iter 70 value 82.014063
iter 80 value 81.876780
iter 90 value 81.670473
iter 100 value 81.520776
final value 81.520776
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.223508
iter 10 value 94.837737
iter 20 value 93.250136
iter 30 value 84.513143
iter 40 value 83.493423
iter 50 value 81.905522
iter 60 value 81.570816
iter 70 value 81.463920
iter 80 value 81.354410
iter 90 value 81.160607
iter 100 value 80.930434
final value 80.930434
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.327207
iter 10 value 94.514287
iter 20 value 94.376697
iter 30 value 89.281630
iter 40 value 83.693661
iter 50 value 83.424415
iter 60 value 83.078290
iter 70 value 82.275567
iter 80 value 81.377715
iter 90 value 81.087935
iter 100 value 80.949982
final value 80.949982
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.032548
iter 10 value 94.105523
iter 20 value 91.455260
iter 30 value 85.854820
iter 40 value 83.067702
iter 50 value 82.557544
iter 60 value 82.227001
iter 70 value 82.000940
iter 80 value 81.918215
iter 90 value 81.736681
iter 100 value 81.323856
final value 81.323856
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.259577
iter 10 value 93.587958
iter 20 value 86.850168
iter 30 value 85.946481
iter 40 value 83.687184
iter 50 value 83.453059
iter 60 value 82.714032
iter 70 value 82.253497
iter 80 value 81.735011
iter 90 value 81.367889
iter 100 value 81.220406
final value 81.220406
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.278134
iter 10 value 95.485476
iter 20 value 94.285210
iter 30 value 91.244112
iter 40 value 85.207703
iter 50 value 83.155790
iter 60 value 82.797293
iter 70 value 82.654438
iter 80 value 82.249896
iter 90 value 81.636508
iter 100 value 81.248533
final value 81.248533
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.047805
iter 10 value 93.755131
iter 20 value 93.747724
final value 93.746404
converged
Fitting Repeat 2
# weights: 103
initial value 115.328882
final value 94.485890
converged
Fitting Repeat 3
# weights: 103
initial value 98.165382
final value 94.485852
converged
Fitting Repeat 4
# weights: 103
initial value 101.639261
final value 94.485911
converged
Fitting Repeat 5
# weights: 103
initial value 97.594035
final value 94.485717
converged
Fitting Repeat 1
# weights: 305
initial value 119.518376
iter 10 value 94.489421
iter 20 value 94.484535
final value 94.484505
converged
Fitting Repeat 2
# weights: 305
initial value 101.941577
iter 10 value 94.031609
iter 20 value 94.027102
final value 94.026878
converged
Fitting Repeat 3
# weights: 305
initial value 103.633983
iter 10 value 93.815241
iter 20 value 93.811103
iter 30 value 93.799398
iter 40 value 92.375499
iter 50 value 86.068208
iter 60 value 86.051801
iter 70 value 84.503531
iter 80 value 83.666555
iter 90 value 83.627630
iter 100 value 82.702974
final value 82.702974
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.364872
iter 10 value 94.485825
iter 20 value 93.235234
iter 30 value 85.646293
iter 40 value 85.420560
iter 50 value 85.198500
iter 60 value 85.051385
iter 70 value 82.914520
iter 80 value 81.263209
iter 90 value 81.119172
iter 100 value 81.072575
final value 81.072575
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.540393
iter 10 value 94.281185
iter 20 value 94.052581
final value 94.028385
converged
Fitting Repeat 1
# weights: 507
initial value 102.873476
iter 10 value 94.035205
iter 20 value 94.027933
iter 30 value 93.795677
final value 93.795670
converged
Fitting Repeat 2
# weights: 507
initial value 110.375940
iter 10 value 93.706405
iter 20 value 85.413223
iter 30 value 84.207835
iter 40 value 84.188741
iter 50 value 84.166878
iter 60 value 83.799793
iter 70 value 83.361835
iter 80 value 83.360233
final value 83.358444
converged
Fitting Repeat 3
# weights: 507
initial value 97.257971
iter 10 value 94.492002
iter 20 value 93.419214
iter 30 value 86.338745
iter 40 value 83.575406
iter 50 value 83.548866
iter 60 value 83.546578
final value 83.546529
converged
Fitting Repeat 4
# weights: 507
initial value 99.633991
iter 10 value 94.492413
iter 20 value 94.484285
iter 30 value 93.701530
final value 93.301897
converged
Fitting Repeat 5
# weights: 507
initial value 95.169679
iter 10 value 94.416189
iter 20 value 93.797691
iter 30 value 89.250746
iter 40 value 85.904056
iter 50 value 85.731271
iter 60 value 85.603294
iter 70 value 85.080732
iter 80 value 85.078310
final value 85.078306
converged
Fitting Repeat 1
# weights: 507
initial value 148.565866
iter 10 value 118.158790
iter 20 value 114.732928
iter 30 value 114.433352
iter 40 value 112.921045
iter 50 value 108.601389
iter 60 value 106.914197
iter 70 value 105.429738
iter 80 value 104.652180
iter 90 value 104.021769
iter 100 value 103.670512
final value 103.670512
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 133.250979
iter 10 value 117.994527
iter 20 value 109.977704
iter 30 value 108.794344
iter 40 value 107.890181
iter 50 value 105.202513
iter 60 value 102.381302
iter 70 value 101.697640
iter 80 value 100.992490
iter 90 value 100.692317
iter 100 value 100.576642
final value 100.576642
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 136.692988
iter 10 value 119.041471
iter 20 value 114.129247
iter 30 value 113.808149
iter 40 value 113.209788
iter 50 value 110.534040
iter 60 value 106.400799
iter 70 value 104.853844
iter 80 value 103.958962
iter 90 value 103.440923
iter 100 value 102.502927
final value 102.502927
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 142.594222
iter 10 value 117.871395
iter 20 value 113.465305
iter 30 value 110.004997
iter 40 value 107.161899
iter 50 value 103.955475
iter 60 value 103.551399
iter 70 value 103.414148
iter 80 value 102.448723
iter 90 value 101.040579
iter 100 value 100.684694
final value 100.684694
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 129.958437
iter 10 value 117.843851
iter 20 value 109.770288
iter 30 value 108.561317
iter 40 value 106.563505
iter 50 value 104.361456
iter 60 value 102.732269
iter 70 value 100.948295
iter 80 value 100.635117
iter 90 value 100.463948
iter 100 value 100.408409
final value 100.408409
stopped after 100 iterations
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 May 14 00:52:35 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
40.414 1.518 89.829
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 34.255 | 0.370 | 34.626 | |
| FreqInteractors | 0.451 | 0.030 | 0.482 | |
| calculateAAC | 0.033 | 0.000 | 0.034 | |
| calculateAutocor | 0.268 | 0.012 | 0.282 | |
| calculateCTDC | 0.076 | 0.000 | 0.076 | |
| calculateCTDD | 0.497 | 0.000 | 0.497 | |
| calculateCTDT | 0.138 | 0.001 | 0.138 | |
| calculateCTriad | 0.420 | 0.001 | 0.421 | |
| calculateDC | 0.084 | 0.001 | 0.085 | |
| calculateF | 0.307 | 0.001 | 0.307 | |
| calculateKSAAP | 0.091 | 0.002 | 0.093 | |
| calculateQD_Sm | 1.784 | 0.007 | 1.792 | |
| calculateTC | 1.468 | 0.022 | 1.490 | |
| calculateTC_Sm | 0.291 | 0.000 | 0.290 | |
| corr_plot | 34.638 | 0.367 | 35.005 | |
| enrichfindP | 0.552 | 0.050 | 10.668 | |
| enrichfind_hp | 0.045 | 0.003 | 0.959 | |
| enrichplot | 0.638 | 0.001 | 0.640 | |
| filter_missing_values | 0.002 | 0.000 | 0.002 | |
| getFASTA | 1.450 | 0.304 | 5.603 | |
| getHPI | 0.001 | 0.000 | 0.001 | |
| get_negativePPI | 0.000 | 0.002 | 0.003 | |
| get_positivePPI | 0.001 | 0.000 | 0.000 | |
| impute_missing_data | 0.002 | 0.000 | 0.002 | |
| plotPPI | 0.108 | 0.011 | 0.119 | |
| pred_ensembel | 12.905 | 0.259 | 11.843 | |
| var_imp | 33.711 | 0.595 | 34.308 | |