##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-10-20 r88955)
* 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 ‘1.17.1’
* 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 ... WARNING
Codoc mismatches from Rd file 'pred_ensembel.Rd':
pred_ensembel
  Code: function(features, gold_standard, classifier = c("avNNet",
                 "svmRadial", "ranger"), resampling.method = "cv",
                 ncross = 2, repeats = 2, verboseIter = TRUE, plots =
                 FALSE, filename = "plots.pdf")
  Docs: function(features, gold_standard, classifier = c("avNNet",
                 "svmRadial", "ranger"), resampling.method = "cv",
                 ncross = 2, repeats = 2, verboseIter = TRUE, plots =
                 TRUE, filename = "plots.pdf")
  Mismatches in argument default values:
    Name: 'plots' Code: FALSE Docs: TRUE

* 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 ... ERROR
Running examples in ‘HPiP-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: enrichfindP
> ### Title: Functional Enrichment Analysis for Pathogen Interactors in the
> ###   High-Confidence Network.
> ### Aliases: enrichfindP
> 
> ### ** Examples
> 
> data('predicted_PPIs')
> #perform enrichment
> enrich.df <- enrichfindP(predicted_PPIs,
+ threshold = 0.05,
+ sources = c("GO", "KEGG"),
+ p.corrction.method = "bonferroni",
+ org = "hsapiens")
Error: Request to g:Profiler failed (HTTP 504). The service may be temporarily unavailable.
If the issue persists, please contact biit.support@ut.ee with a reproducible example.
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
            user system elapsed
corr_plot 33.704  0.455  34.168
FSmethod  32.244  0.581  32.827
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 ERROR
Running the tests in ‘tests/runTests.R’ failed.
Last 13 lines of output:
  ERROR in test_enrich.df: Error : Request to g:Profiler failed (HTTP 504). The service may be temporarily unavailable.
  If the issue persists, please contact biit.support@ut.ee with a reproducible example.
  
  Test files with failing tests
  
     test_enrich.df.R 
       test_enrich.df 
  
  
  Error in BiocGenerics:::testPackage("HPiP") : 
    unit tests failed for package HPiP
  In addition: Warning messages:
  1: `repeats` has no meaning for this resampling method. 
  2: executing %dopar% sequentially: no parallel backend registered 
  Execution halted
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... ERROR
Error(s) in re-building vignettes:
--- re-building ‘HPiP_tutorial.Rmd’ using rmarkdown
The magick package is required to crop "/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/vign_test/HPiP/vignettes/HPiP_tutorial_files/figure-html/unnamed-chunk-53-1.png" but not available.
The magick package is required to crop "/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/vign_test/HPiP/vignettes/HPiP_tutorial_files/figure-html/unnamed-chunk-54-1.png" but not available.
The magick package is required to crop "/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/vign_test/HPiP/vignettes/HPiP_tutorial_files/figure-html/unnamed-chunk-60-1.png" but not available.
The magick package is required to crop "/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/vign_test/HPiP/vignettes/HPiP_tutorial_files/figure-html/unnamed-chunk-61-1.png" but not available.

Quitting from HPiP_tutorial.Rmd:1236-1242 [unnamed-chunk-64]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error:
! Request to g:Profiler failed (HTTP 504). The service may be temporarily unavailable.
If the issue persists, please contact biit.support@ut.ee with a reproducible example.
---
Backtrace:
    ▆
 1. └─HPiP::enrichfind_cpx(...)
 2.   └─base::lapply(...)
 3.     └─HPiP (local) FUN(X[[i]], ...)
 4.       └─gprofiler2::gost(...)
 5.         └─gprofiler2::gprofiler_request(url, body)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Error: processing vignette 'HPiP_tutorial.Rmd' failed with diagnostics:
Request to g:Profiler failed (HTTP 504). The service may be temporarily unavailable.
If the issue persists, please contact biit.support@ut.ee with a reproducible example.
--- failed re-building ‘HPiP_tutorial.Rmd’

SUMMARY: processing the following file failed:
  ‘HPiP_tutorial.Rmd’

Error: Vignette re-building failed.
Execution halted

* checking PDF version of manual ... OK
* DONE

Status: 3 ERRORs, 1 WARNING, 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.1’
** 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)

R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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')
Timing stopped at: 0.237 0.037 0.857
Error : Request to g:Profiler failed (HTTP 504). The service may be temporarily unavailable.
If the issue persists, please contact biit.support@ut.ee with a reproducible example.
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 101.026358 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.666437 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 119.358118 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 93.789342 
iter  10 value 90.082292
iter  20 value 90.053104
iter  30 value 90.051798
iter  40 value 88.099080
iter  50 value 87.991077
iter  50 value 87.991076
iter  50 value 87.991076
final  value 87.991076 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.882207 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.286800 
iter  10 value 93.814477
iter  20 value 93.631530
iter  30 value 93.628471
final  value 93.628456 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.787521 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.171082 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.603293 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.887146 
final  value 93.818713 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.330798 
iter  10 value 93.628453
iter  10 value 93.628453
iter  10 value 93.628453
final  value 93.628453 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.089779 
iter  10 value 89.006893
iter  20 value 84.099302
iter  30 value 83.766924
iter  40 value 83.763768
final  value 83.763629 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.348883 
iter  10 value 93.645350
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.868632 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.792264 
final  value 93.574846 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.560905 
iter  10 value 93.769949
iter  20 value 91.084185
iter  30 value 88.259227
iter  40 value 87.984811
iter  50 value 87.559625
iter  60 value 87.467113
iter  70 value 87.259571
iter  80 value 85.100228
iter  90 value 84.906100
final  value 84.895867 
converged
Fitting Repeat 2 

# weights:  103
initial  value 115.149253 
iter  10 value 94.019467
iter  20 value 88.779427
iter  30 value 87.931811
iter  40 value 87.689080
iter  50 value 85.411652
iter  60 value 84.934089
iter  70 value 84.896390
iter  80 value 84.895867
iter  80 value 84.895867
iter  80 value 84.895867
final  value 84.895867 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.764313 
iter  10 value 94.056670
iter  20 value 93.871470
iter  30 value 89.547263
iter  40 value 88.246219
iter  50 value 86.475182
iter  60 value 84.728311
iter  70 value 83.388200
iter  80 value 83.180676
iter  90 value 82.449011
iter 100 value 82.285860
final  value 82.285860 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.787580 
iter  10 value 94.057772
iter  20 value 94.040699
iter  30 value 93.800347
iter  40 value 93.766483
iter  50 value 92.839253
iter  60 value 88.806868
iter  70 value 87.782645
iter  80 value 86.858030
iter  90 value 84.735665
iter 100 value 84.365885
final  value 84.365885 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.156301 
iter  10 value 94.055258
iter  20 value 93.979576
iter  30 value 91.055344
iter  40 value 86.810620
iter  50 value 85.211432
iter  60 value 85.049615
iter  70 value 84.823123
iter  80 value 84.119344
iter  90 value 83.844814
iter 100 value 83.751020
final  value 83.751020 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.307069 
iter  10 value 93.781162
iter  20 value 88.428270
iter  30 value 87.093865
iter  40 value 86.111820
iter  50 value 85.990244
iter  60 value 85.121126
iter  70 value 83.302243
iter  80 value 82.162705
iter  90 value 81.538916
iter 100 value 81.431520
final  value 81.431520 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.784944 
iter  10 value 93.715146
iter  20 value 90.787209
iter  30 value 84.224310
iter  40 value 83.715770
iter  50 value 82.971449
iter  60 value 81.742477
iter  70 value 81.301149
iter  80 value 81.160440
iter  90 value 81.101613
iter 100 value 80.883778
final  value 80.883778 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.051424 
iter  10 value 93.787473
iter  20 value 92.835489
iter  30 value 88.938098
iter  40 value 85.476495
iter  50 value 84.359765
iter  60 value 82.765202
iter  70 value 82.025884
iter  80 value 81.453398
iter  90 value 81.006820
iter 100 value 80.857829
final  value 80.857829 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.092762 
iter  10 value 94.066615
iter  20 value 93.860917
iter  30 value 92.651268
iter  40 value 92.240601
iter  50 value 92.175645
iter  60 value 91.524713
iter  70 value 85.613072
iter  80 value 84.704386
iter  90 value 83.823422
iter 100 value 82.244943
final  value 82.244943 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.650742 
iter  10 value 93.772899
iter  20 value 93.104435
iter  30 value 86.334976
iter  40 value 85.655351
iter  50 value 85.618019
iter  60 value 85.300837
iter  70 value 83.637059
iter  80 value 82.406605
iter  90 value 81.918579
iter 100 value 81.809817
final  value 81.809817 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.035250 
iter  10 value 91.510630
iter  20 value 87.596536
iter  30 value 84.286652
iter  40 value 83.099090
iter  50 value 82.438682
iter  60 value 81.585041
iter  70 value 81.486931
iter  80 value 81.328662
iter  90 value 81.323773
iter 100 value 81.268426
final  value 81.268426 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.367018 
iter  10 value 94.121762
iter  20 value 89.058751
iter  30 value 84.427332
iter  40 value 84.160203
iter  50 value 83.452879
iter  60 value 82.384047
iter  70 value 81.715700
iter  80 value 81.350300
iter  90 value 81.312630
iter 100 value 81.258365
final  value 81.258365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 131.346215 
iter  10 value 106.438763
iter  20 value 104.612692
iter  30 value 87.441498
iter  40 value 84.733472
iter  50 value 83.734271
iter  60 value 82.450597
iter  70 value 81.928340
iter  80 value 81.336927
iter  90 value 81.007826
iter 100 value 80.701963
final  value 80.701963 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.862066 
iter  10 value 94.168441
iter  20 value 93.803937
iter  30 value 93.595568
iter  40 value 93.031175
iter  50 value 87.879459
iter  60 value 85.848160
iter  70 value 82.436274
iter  80 value 81.727343
iter  90 value 81.148244
iter 100 value 80.845081
final  value 80.845081 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.379130 
iter  10 value 96.197859
iter  20 value 93.994228
iter  30 value 92.886997
iter  40 value 83.816181
iter  50 value 82.531397
iter  60 value 82.392887
iter  70 value 82.239202
iter  80 value 81.991327
iter  90 value 81.758495
iter 100 value 81.550561
final  value 81.550561 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.156789 
final  value 94.054533 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.778547 
iter  10 value 94.053021
iter  20 value 94.045333
iter  30 value 94.044875
iter  40 value 94.043073
iter  50 value 92.001239
iter  60 value 90.743321
iter  70 value 88.892864
iter  80 value 88.851683
iter  90 value 88.658775
iter 100 value 86.730445
final  value 86.730445 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.607596 
iter  10 value 94.054602
iter  20 value 94.052928
final  value 94.052921 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.799692 
final  value 94.054502 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.670579 
final  value 94.054700 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.862501 
iter  10 value 94.058204
iter  20 value 94.051441
iter  30 value 90.573949
iter  40 value 87.562645
iter  50 value 87.555811
iter  60 value 87.547321
iter  70 value 87.534275
iter  80 value 87.395574
final  value 87.394312 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.379742 
iter  10 value 85.304478
iter  20 value 85.223091
iter  30 value 84.571520
iter  40 value 84.554479
iter  50 value 84.543672
iter  60 value 84.541492
iter  70 value 84.534213
iter  80 value 84.288137
iter  90 value 83.768633
final  value 83.765320 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.113156 
iter  10 value 93.633587
iter  20 value 93.629530
iter  30 value 93.628571
iter  40 value 87.006381
iter  50 value 85.181445
final  value 85.178740 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.659169 
iter  10 value 94.057513
iter  20 value 94.052175
iter  30 value 93.840075
iter  40 value 87.688739
iter  50 value 87.240596
iter  60 value 87.212446
final  value 87.212420 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.222430 
iter  10 value 94.066455
iter  20 value 94.061225
iter  30 value 92.515287
iter  40 value 90.645509
iter  50 value 90.643547
iter  60 value 88.199996
iter  70 value 86.936466
iter  80 value 86.359114
iter  90 value 86.358424
iter 100 value 85.904784
final  value 85.904784 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.157805 
iter  10 value 94.060928
iter  20 value 93.914425
final  value 93.582692 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.006069 
iter  10 value 93.591302
iter  20 value 93.582873
iter  30 value 93.531086
iter  40 value 89.771842
iter  50 value 88.082636
iter  60 value 85.303949
iter  70 value 85.174385
iter  80 value 85.171099
iter  90 value 85.169311
final  value 85.169223 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.372455 
iter  10 value 92.249087
iter  20 value 92.246337
iter  30 value 92.165140
iter  40 value 92.164274
iter  50 value 92.119433
iter  60 value 91.242485
iter  70 value 91.179167
final  value 91.178808 
converged
Fitting Repeat 4 

# weights:  507
initial  value 126.346042 
iter  10 value 93.905538
iter  20 value 93.047328
iter  30 value 93.043235
iter  40 value 91.652619
iter  50 value 91.532846
iter  60 value 91.337820
iter  70 value 91.273013
iter  80 value 91.269353
iter  90 value 90.952466
final  value 90.949392 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.344997 
iter  10 value 92.874493
iter  20 value 92.866723
iter  30 value 92.457051
iter  40 value 86.472620
iter  50 value 84.307758
iter  60 value 84.306556
iter  70 value 84.240129
iter  80 value 83.151054
iter  90 value 82.478743
iter 100 value 81.540120
final  value 81.540120 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.117408 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.882607 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.223038 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.653712 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.827407 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.756798 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.545483 
final  value 94.484210 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.703453 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.648023 
iter  10 value 87.816338
iter  20 value 85.335064
iter  30 value 85.290069
final  value 85.289863 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.459289 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.778794 
iter  10 value 92.792298
final  value 92.614233 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.699610 
final  value 94.484218 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.884802 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.672806 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.122899 
iter  10 value 91.292842
iter  20 value 86.511120
iter  30 value 85.142760
iter  40 value 85.133948
final  value 85.133938 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.685064 
iter  10 value 94.483120
iter  20 value 94.198301
iter  30 value 93.748783
iter  40 value 93.691717
iter  50 value 92.712818
iter  60 value 86.095683
iter  70 value 85.757342
iter  80 value 84.334619
iter  90 value 84.314883
iter 100 value 84.235219
final  value 84.235219 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.374479 
iter  10 value 94.178775
iter  20 value 87.725009
iter  30 value 86.678532
iter  40 value 86.295083
iter  50 value 84.115631
iter  60 value 84.020774
iter  70 value 83.975321
iter  80 value 83.974726
final  value 83.974564 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.738782 
iter  10 value 93.836078
iter  20 value 90.320088
iter  30 value 86.249493
iter  40 value 84.249688
iter  50 value 84.133730
iter  60 value 84.088327
final  value 84.085709 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.529496 
iter  10 value 94.486848
iter  20 value 93.985113
iter  30 value 93.300931
iter  40 value 85.446849
iter  50 value 83.293887
iter  60 value 82.361974
iter  70 value 82.127129
iter  80 value 81.786815
iter  90 value 81.012352
iter 100 value 80.730341
final  value 80.730341 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.380832 
iter  10 value 94.543208
iter  20 value 94.486535
iter  30 value 93.254685
iter  40 value 86.041408
iter  50 value 83.872567
iter  60 value 83.649386
iter  70 value 83.600449
iter  80 value 83.558566
iter  90 value 83.540081
final  value 83.540074 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.083452 
iter  10 value 94.498413
iter  20 value 94.443938
iter  30 value 93.946854
iter  40 value 89.248908
iter  50 value 86.328754
iter  60 value 85.576348
iter  70 value 82.901899
iter  80 value 82.329340
iter  90 value 81.784862
iter 100 value 81.023414
final  value 81.023414 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.717050 
iter  10 value 93.957693
iter  20 value 86.478896
iter  30 value 84.028156
iter  40 value 81.587122
iter  50 value 79.635738
iter  60 value 79.573620
iter  70 value 79.329307
iter  80 value 79.313328
iter  90 value 79.309999
iter 100 value 79.309065
final  value 79.309065 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.590915 
iter  10 value 94.210852
iter  20 value 89.115939
iter  30 value 84.104870
iter  40 value 82.095584
iter  50 value 81.079542
iter  60 value 80.264987
iter  70 value 80.175481
iter  80 value 80.087293
iter  90 value 79.919430
iter 100 value 79.631223
final  value 79.631223 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.626764 
iter  10 value 94.498586
iter  20 value 93.979197
iter  30 value 87.694323
iter  40 value 81.544438
iter  50 value 81.086385
iter  60 value 80.749315
iter  70 value 80.470034
iter  80 value 79.777798
iter  90 value 79.288584
iter 100 value 79.241097
final  value 79.241097 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 126.977348 
iter  10 value 94.473258
iter  20 value 85.655719
iter  30 value 84.059910
iter  40 value 83.857748
iter  50 value 83.274823
iter  60 value 81.903072
iter  70 value 80.708434
iter  80 value 80.220688
iter  90 value 80.140818
iter 100 value 79.835949
final  value 79.835949 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.924166 
iter  10 value 95.420332
iter  20 value 92.280961
iter  30 value 86.706400
iter  40 value 85.972455
iter  50 value 85.057362
iter  60 value 83.316352
iter  70 value 82.956428
iter  80 value 81.431583
iter  90 value 80.141623
iter 100 value 79.222457
final  value 79.222457 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.440547 
iter  10 value 94.926318
iter  20 value 94.560879
iter  30 value 94.498581
iter  40 value 94.344248
iter  50 value 87.233296
iter  60 value 85.975333
iter  70 value 85.231489
iter  80 value 84.677537
iter  90 value 83.687301
iter 100 value 80.502111
final  value 80.502111 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.297497 
iter  10 value 94.149222
iter  20 value 92.682915
iter  30 value 84.847253
iter  40 value 83.051406
iter  50 value 81.636719
iter  60 value 81.111857
iter  70 value 81.009215
iter  80 value 80.876131
iter  90 value 80.766619
iter 100 value 80.354214
final  value 80.354214 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.698460 
iter  10 value 94.441035
iter  20 value 91.126710
iter  30 value 86.557056
iter  40 value 84.895079
iter  50 value 82.918951
iter  60 value 82.198943
iter  70 value 81.481862
iter  80 value 80.460736
iter  90 value 79.597444
iter 100 value 79.454087
final  value 79.454087 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 143.066709 
iter  10 value 95.519890
iter  20 value 94.425212
iter  30 value 86.457494
iter  40 value 83.848580
iter  50 value 82.694521
iter  60 value 80.808661
iter  70 value 80.152150
iter  80 value 79.570736
iter  90 value 79.106604
iter 100 value 78.766201
final  value 78.766201 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.211082 
iter  10 value 94.485934
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.770941 
final  value 94.485806 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.995531 
final  value 94.485746 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.442959 
final  value 94.485804 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.933344 
final  value 94.486033 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.734940 
iter  10 value 93.639314
iter  20 value 86.398640
iter  30 value 85.963664
iter  40 value 85.956254
iter  50 value 85.193758
iter  60 value 84.870974
iter  70 value 82.715567
iter  80 value 80.506597
iter  90 value 80.118346
iter 100 value 79.992270
final  value 79.992270 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.369337 
iter  10 value 93.458793
iter  20 value 93.191917
iter  30 value 93.190834
iter  40 value 93.188326
iter  50 value 87.412732
iter  60 value 85.171038
iter  70 value 85.167172
iter  80 value 85.167061
iter  80 value 85.167061
iter  80 value 85.167061
final  value 85.167061 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.664877 
iter  10 value 93.478441
iter  20 value 93.427584
iter  30 value 91.510260
iter  40 value 91.503089
iter  50 value 88.055578
iter  60 value 85.174566
iter  70 value 85.168512
iter  80 value 85.163650
iter  90 value 83.777141
iter 100 value 81.650396
final  value 81.650396 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.943834 
iter  10 value 94.488780
iter  20 value 94.434076
iter  30 value 91.048236
iter  40 value 88.139230
iter  50 value 88.130182
iter  60 value 87.641468
iter  70 value 86.478973
iter  80 value 86.475476
iter  90 value 84.488000
iter 100 value 82.997994
final  value 82.997994 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.143008 
iter  10 value 94.488682
iter  20 value 94.435395
final  value 94.275444 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.052893 
iter  10 value 94.288282
iter  20 value 94.238182
iter  30 value 94.230049
iter  40 value 89.539304
iter  50 value 89.169076
iter  60 value 88.662679
iter  70 value 87.509113
iter  80 value 86.687402
iter  90 value 86.657196
iter 100 value 86.411682
final  value 86.411682 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.698868 
iter  10 value 92.266905
iter  20 value 90.600462
iter  30 value 83.258344
iter  40 value 82.573133
iter  50 value 82.571947
iter  50 value 82.571947
iter  50 value 82.571947
final  value 82.571947 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.429524 
iter  10 value 88.428094
iter  20 value 85.116020
iter  30 value 85.112520
iter  40 value 85.107687
iter  50 value 85.107642
iter  60 value 85.107394
final  value 85.107360 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.676337 
iter  10 value 94.492568
iter  20 value 94.484551
iter  30 value 89.601928
iter  40 value 89.107769
iter  50 value 85.324495
iter  60 value 85.287409
iter  70 value 83.849591
iter  80 value 80.302443
iter  90 value 79.732105
iter 100 value 79.731242
final  value 79.731242 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.237713 
iter  10 value 94.441280
iter  20 value 91.560303
iter  30 value 86.710272
iter  40 value 83.866016
iter  50 value 83.572821
iter  60 value 83.381622
iter  70 value 83.381002
iter  80 value 83.358704
iter  90 value 83.306889
iter 100 value 83.306232
final  value 83.306232 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.662969 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.771978 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.950042 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.636428 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.983610 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.848209 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.645866 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.926444 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.599752 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.890167 
iter  10 value 94.483938
iter  20 value 94.266249
iter  30 value 94.262570
final  value 94.262524 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.076386 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.148125 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.323281 
iter  10 value 94.382901
final  value 94.378860 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.481504 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.873902 
iter  10 value 94.466824
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.222822 
iter  10 value 94.492160
iter  20 value 91.751149
iter  30 value 90.829305
iter  40 value 89.440386
iter  50 value 85.515824
iter  60 value 85.179235
iter  70 value 84.662071
iter  80 value 84.625327
iter  90 value 84.566411
iter 100 value 84.326628
final  value 84.326628 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 109.640403 
iter  10 value 94.309228
iter  20 value 85.967227
iter  30 value 84.476079
iter  40 value 84.210080
iter  50 value 83.755520
iter  60 value 83.625812
final  value 83.623578 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.391825 
iter  10 value 94.494843
iter  20 value 94.366846
iter  30 value 94.330998
iter  40 value 94.167826
iter  50 value 94.152965
iter  60 value 88.151186
iter  70 value 86.890760
iter  80 value 86.132835
iter  90 value 84.123848
iter 100 value 84.057533
final  value 84.057533 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.039752 
iter  10 value 94.494867
iter  20 value 91.361611
iter  30 value 88.771090
iter  40 value 88.487524
iter  50 value 88.357091
iter  60 value 84.168496
iter  70 value 84.070651
iter  80 value 84.064085
final  value 84.064072 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.152557 
iter  10 value 94.398008
iter  20 value 90.051885
iter  30 value 88.122088
iter  40 value 85.564024
iter  50 value 84.370653
iter  60 value 83.648843
iter  70 value 83.514653
iter  80 value 83.398760
final  value 83.397951 
converged
Fitting Repeat 1 

# weights:  305
initial  value 126.768298 
iter  10 value 94.038027
iter  20 value 86.280792
iter  30 value 85.303484
iter  40 value 84.471993
iter  50 value 83.925612
iter  60 value 82.550781
iter  70 value 82.055189
iter  80 value 81.537171
iter  90 value 81.164765
iter 100 value 80.903516
final  value 80.903516 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.046552 
iter  10 value 94.471072
iter  20 value 91.989054
iter  30 value 87.831067
iter  40 value 87.188080
iter  50 value 85.256892
iter  60 value 82.560679
iter  70 value 80.800927
iter  80 value 80.296191
iter  90 value 80.231703
iter 100 value 79.723059
final  value 79.723059 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.400042 
iter  10 value 95.214061
iter  20 value 92.209000
iter  30 value 90.826915
iter  40 value 88.671556
iter  50 value 83.507167
iter  60 value 80.579367
iter  70 value 79.496325
iter  80 value 79.117412
iter  90 value 78.543414
iter 100 value 78.363959
final  value 78.363959 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.178797 
iter  10 value 89.381778
iter  20 value 87.542621
iter  30 value 86.812086
iter  40 value 82.465955
iter  50 value 80.331313
iter  60 value 79.355194
iter  70 value 78.752796
iter  80 value 78.486455
iter  90 value 78.463884
iter 100 value 78.298003
final  value 78.298003 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.368960 
iter  10 value 94.538205
iter  20 value 94.488732
iter  30 value 90.868207
iter  40 value 86.184874
iter  50 value 84.583961
iter  60 value 83.956739
iter  70 value 83.686135
iter  80 value 82.901863
iter  90 value 80.333909
iter 100 value 79.190354
final  value 79.190354 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.687159 
iter  10 value 96.063184
iter  20 value 94.525480
iter  30 value 91.584805
iter  40 value 86.848092
iter  50 value 81.730451
iter  60 value 80.439913
iter  70 value 79.666769
iter  80 value 78.973085
iter  90 value 78.759936
iter 100 value 78.532671
final  value 78.532671 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.857036 
iter  10 value 94.600298
iter  20 value 94.424503
iter  30 value 89.679239
iter  40 value 87.061346
iter  50 value 83.361901
iter  60 value 79.147037
iter  70 value 78.457854
iter  80 value 78.237557
iter  90 value 78.147452
iter 100 value 78.002749
final  value 78.002749 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.133418 
iter  10 value 94.498806
iter  20 value 92.288885
iter  30 value 84.175736
iter  40 value 81.977935
iter  50 value 79.999674
iter  60 value 79.546552
iter  70 value 79.081471
iter  80 value 78.922716
iter  90 value 78.764894
iter 100 value 78.717623
final  value 78.717623 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.098237 
iter  10 value 97.404317
iter  20 value 96.506800
iter  30 value 88.814108
iter  40 value 87.717492
iter  50 value 86.358525
iter  60 value 85.959268
iter  70 value 84.089043
iter  80 value 82.057809
iter  90 value 81.256175
iter 100 value 80.855516
final  value 80.855516 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.376601 
iter  10 value 94.391285
iter  20 value 90.772662
iter  30 value 85.280439
iter  40 value 84.182961
iter  50 value 81.960441
iter  60 value 80.654257
iter  70 value 80.084688
iter  80 value 80.024161
iter  90 value 79.408897
iter 100 value 78.851728
final  value 78.851728 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.197893 
iter  10 value 94.485750
iter  20 value 94.394604
iter  30 value 88.821032
iter  40 value 88.820752
final  value 88.820748 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.281369 
final  value 94.485814 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.687111 
final  value 94.468411 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.489859 
final  value 94.485779 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.799026 
final  value 94.468354 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.090992 
iter  10 value 94.471607
iter  20 value 94.465827
iter  30 value 86.757694
iter  40 value 86.660611
iter  50 value 86.549344
iter  60 value 86.541567
iter  70 value 86.208823
iter  80 value 85.785761
final  value 85.785626 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.114889 
iter  10 value 94.471660
iter  20 value 94.408595
iter  30 value 94.288681
iter  40 value 94.179309
iter  50 value 94.177820
final  value 94.177817 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.166841 
iter  10 value 94.489430
iter  20 value 94.080964
iter  30 value 87.415013
final  value 87.391025 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.033116 
iter  10 value 94.487975
iter  20 value 86.741216
iter  30 value 85.074831
iter  40 value 85.029524
iter  50 value 85.026819
iter  60 value 85.026421
iter  70 value 84.079345
iter  80 value 79.893079
iter  90 value 79.882276
iter 100 value 79.881986
final  value 79.881986 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.648420 
iter  10 value 94.489192
iter  20 value 92.563034
iter  30 value 85.544709
iter  40 value 85.525224
iter  50 value 85.422394
iter  60 value 85.420479
iter  70 value 85.418263
iter  80 value 85.418239
final  value 85.417594 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.159684 
iter  10 value 94.476155
iter  20 value 94.325913
iter  30 value 85.401874
iter  40 value 84.701501
iter  50 value 84.523666
iter  60 value 78.402180
iter  70 value 77.457617
iter  80 value 77.307093
iter  90 value 77.199935
final  value 77.198111 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.930006 
iter  10 value 94.492266
iter  20 value 94.434927
iter  30 value 85.523749
iter  40 value 84.304221
iter  50 value 78.023864
iter  60 value 77.159358
iter  70 value 76.920490
iter  80 value 76.894994
iter  90 value 76.889406
iter 100 value 76.887121
final  value 76.887121 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.498487 
iter  10 value 94.492042
iter  20 value 94.484242
iter  30 value 91.807841
iter  40 value 90.271180
iter  50 value 82.491736
iter  60 value 80.271142
iter  70 value 79.106766
iter  80 value 78.344467
iter  90 value 77.004330
iter 100 value 76.433023
final  value 76.433023 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.074364 
iter  10 value 92.690265
iter  20 value 91.941632
iter  30 value 91.541664
iter  40 value 81.256823
iter  50 value 80.855833
final  value 80.835158 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.084977 
iter  10 value 94.435810
iter  20 value 94.369481
iter  30 value 94.177968
iter  40 value 94.169587
iter  40 value 94.169587
iter  40 value 94.169587
final  value 94.169587 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.960447 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.859996 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.179579 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.320141 
iter  10 value 93.726981
final  value 93.720301 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.758852 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.908248 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.707950 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.514526 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.463115 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.205618 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.267295 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.250928 
iter  10 value 94.288317
final  value 94.288300 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.710210 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.808279 
final  value 94.305882 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.058484 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.340897 
iter  10 value 93.068938
iter  20 value 83.934865
iter  30 value 83.571090
iter  40 value 83.515125
iter  50 value 83.482311
iter  60 value 83.479360
iter  60 value 83.479360
iter  60 value 83.479360
final  value 83.479360 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.471178 
iter  10 value 94.286225
iter  20 value 92.110334
iter  30 value 90.013291
iter  40 value 86.600327
iter  50 value 86.085334
iter  60 value 86.070766
iter  70 value 85.867190
iter  80 value 84.227767
iter  90 value 84.040713
iter 100 value 83.949719
final  value 83.949719 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.260938 
iter  10 value 93.367239
iter  20 value 84.139270
iter  30 value 83.571189
iter  40 value 83.542011
iter  50 value 83.502512
iter  60 value 83.499968
final  value 83.499961 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.324449 
iter  10 value 94.487825
iter  20 value 94.308911
iter  30 value 93.933245
iter  40 value 93.285610
iter  50 value 88.656817
iter  60 value 86.522697
iter  70 value 86.082103
iter  80 value 85.876272
iter  90 value 85.423117
iter 100 value 85.016326
final  value 85.016326 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.155700 
iter  10 value 94.489160
iter  20 value 93.981539
iter  30 value 93.918038
iter  40 value 93.907259
iter  50 value 93.902507
iter  60 value 89.989528
iter  70 value 87.739941
iter  80 value 87.232647
iter  90 value 83.617640
iter 100 value 83.580876
final  value 83.580876 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 112.748032 
iter  10 value 94.072795
iter  20 value 93.942851
iter  30 value 84.809152
iter  40 value 83.555139
iter  50 value 83.207883
iter  60 value 83.035256
iter  70 value 82.265158
iter  80 value 81.143278
iter  90 value 80.663810
iter 100 value 80.202661
final  value 80.202661 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.470576 
iter  10 value 95.209793
iter  20 value 94.387260
iter  30 value 93.618295
iter  40 value 92.092545
iter  50 value 91.632591
iter  60 value 86.917066
iter  70 value 84.806630
iter  80 value 83.555038
iter  90 value 82.594136
iter 100 value 82.287500
final  value 82.287500 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.351155 
iter  10 value 94.568135
iter  20 value 94.498211
iter  30 value 88.815643
iter  40 value 85.087706
iter  50 value 84.624583
iter  60 value 83.865104
iter  70 value 82.785802
iter  80 value 81.997036
iter  90 value 81.541673
iter 100 value 80.377573
final  value 80.377573 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.357408 
iter  10 value 95.292933
iter  20 value 94.485373
iter  30 value 85.515523
iter  40 value 84.567966
iter  50 value 83.790147
iter  60 value 83.417178
iter  70 value 82.399692
iter  80 value 81.912480
iter  90 value 81.456125
iter 100 value 80.802727
final  value 80.802727 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.025555 
iter  10 value 93.024097
iter  20 value 84.864964
iter  30 value 83.719821
iter  40 value 83.228702
iter  50 value 83.143895
iter  60 value 82.799123
iter  70 value 81.976122
iter  80 value 81.224558
iter  90 value 80.426248
iter 100 value 80.068252
final  value 80.068252 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.958236 
iter  10 value 92.102473
iter  20 value 83.780835
iter  30 value 83.524502
iter  40 value 83.434401
iter  50 value 82.924724
iter  60 value 82.529976
iter  70 value 82.159509
iter  80 value 81.752519
iter  90 value 80.312863
iter 100 value 80.026004
final  value 80.026004 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.314510 
iter  10 value 94.856537
iter  20 value 94.552940
iter  30 value 92.346812
iter  40 value 86.198255
iter  50 value 84.436218
iter  60 value 83.648044
iter  70 value 83.601556
final  value 83.597836 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.356507 
iter  10 value 95.325523
iter  20 value 91.603145
iter  30 value 85.834682
iter  40 value 85.479041
iter  50 value 83.514797
iter  60 value 81.636058
iter  70 value 81.062899
iter  80 value 80.260488
iter  90 value 80.153863
iter 100 value 80.103089
final  value 80.103089 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.698567 
iter  10 value 94.894215
iter  20 value 93.574837
iter  30 value 87.981321
iter  40 value 84.689581
iter  50 value 83.548716
iter  60 value 82.821402
iter  70 value 82.363345
iter  80 value 82.077503
iter  90 value 81.686773
iter 100 value 80.833963
final  value 80.833963 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.821437 
iter  10 value 94.419010
iter  20 value 89.200054
iter  30 value 85.695591
iter  40 value 83.809500
iter  50 value 81.666853
iter  60 value 80.595269
iter  70 value 80.203208
iter  80 value 80.155525
iter  90 value 79.887301
iter 100 value 79.724591
final  value 79.724591 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.779436 
final  value 94.485595 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.981219 
iter  10 value 94.468499
iter  20 value 94.429813
iter  30 value 93.399987
iter  40 value 85.200122
iter  50 value 85.171834
iter  60 value 83.338497
iter  70 value 82.738035
final  value 82.737845 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.737052 
final  value 94.486038 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.741610 
final  value 94.485770 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.301332 
iter  10 value 94.468513
iter  20 value 94.142810
iter  30 value 93.872152
iter  40 value 93.856173
final  value 93.839239 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.556512 
iter  10 value 94.488876
iter  20 value 94.484505
final  value 94.484502 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.673393 
iter  10 value 94.487636
iter  20 value 87.566758
iter  30 value 84.193879
iter  40 value 84.189249
final  value 84.187468 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.826639 
iter  10 value 94.489058
iter  20 value 94.370860
iter  30 value 94.314974
iter  40 value 93.876617
final  value 93.872528 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.830077 
iter  10 value 94.294928
iter  20 value 94.003730
iter  30 value 93.780784
iter  40 value 93.780708
iter  40 value 93.780708
iter  40 value 93.780708
final  value 93.780708 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.830480 
iter  10 value 94.488623
iter  20 value 94.274681
iter  30 value 91.374657
iter  40 value 91.195906
iter  50 value 91.194455
iter  60 value 91.194334
iter  70 value 90.358964
iter  80 value 90.319760
iter  90 value 90.319645
iter 100 value 90.318329
final  value 90.318329 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.541478 
iter  10 value 94.492062
iter  20 value 94.340211
iter  30 value 93.850655
iter  40 value 84.746801
iter  50 value 82.799583
iter  60 value 81.947849
iter  70 value 81.913228
iter  80 value 81.883781
iter  90 value 81.541768
iter 100 value 79.282870
final  value 79.282870 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.233078 
iter  10 value 93.710894
iter  20 value 93.703287
final  value 93.702950 
converged
Fitting Repeat 3 

# weights:  507
initial  value 130.255786 
iter  10 value 94.475150
iter  20 value 94.448005
iter  30 value 93.425292
iter  40 value 86.206495
iter  50 value 82.836841
iter  60 value 82.796795
iter  70 value 82.771020
iter  80 value 82.755628
iter  90 value 82.749138
iter 100 value 82.683757
final  value 82.683757 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.763292 
iter  10 value 94.492364
iter  20 value 94.411062
iter  30 value 93.871613
iter  40 value 93.780486
final  value 93.780478 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.324651 
iter  10 value 94.492954
iter  20 value 94.484233
iter  30 value 84.197060
iter  40 value 83.609857
iter  50 value 82.110629
iter  60 value 79.988016
iter  70 value 79.985039
iter  80 value 79.577695
iter  90 value 79.472075
iter 100 value 78.578928
final  value 78.578928 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.535942 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.852411 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.667738 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.748660 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.539187 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.639766 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.515155 
iter  10 value 86.392966
iter  20 value 84.497594
iter  30 value 84.323580
final  value 84.320151 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.570107 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.518258 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.023028 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.789961 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.105583 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.602023 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.793745 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.517587 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.031720 
iter  10 value 94.062784
iter  20 value 89.804730
iter  30 value 86.113067
iter  40 value 85.843704
iter  50 value 85.668192
iter  60 value 85.606367
iter  70 value 84.043380
iter  80 value 83.783767
final  value 83.783698 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.594475 
iter  10 value 92.166362
iter  20 value 88.664026
iter  30 value 86.629023
iter  40 value 84.916425
iter  50 value 84.188852
iter  60 value 83.772914
iter  70 value 83.709572
iter  80 value 83.685242
iter  90 value 83.661481
iter 100 value 83.470992
final  value 83.470992 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.383255 
iter  10 value 93.059548
iter  20 value 85.610943
iter  30 value 84.900835
iter  40 value 84.361678
iter  50 value 84.144974
iter  60 value 83.863270
iter  70 value 83.783741
final  value 83.783697 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.821600 
iter  10 value 93.927364
iter  20 value 90.255702
iter  30 value 88.980497
iter  40 value 87.232548
iter  50 value 85.625701
iter  60 value 85.219708
iter  70 value 84.929009
iter  80 value 84.811584
iter  90 value 84.254109
iter 100 value 83.902706
final  value 83.902706 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.059238 
iter  10 value 94.056683
iter  20 value 85.540948
iter  30 value 84.971880
iter  40 value 84.893096
iter  50 value 84.172056
iter  60 value 84.074201
final  value 84.071553 
converged
Fitting Repeat 1 

# weights:  305
initial  value 126.324343 
iter  10 value 93.496199
iter  20 value 86.421328
iter  30 value 84.025731
iter  40 value 83.086344
iter  50 value 82.752116
iter  60 value 82.541753
iter  70 value 82.426180
iter  80 value 82.422414
iter  90 value 82.421675
final  value 82.421441 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.192422 
iter  10 value 93.799764
iter  20 value 86.157966
iter  30 value 85.619430
iter  40 value 84.318084
iter  50 value 83.637425
iter  60 value 83.286898
iter  70 value 82.191085
iter  80 value 81.734863
iter  90 value 81.544733
iter 100 value 81.527028
final  value 81.527028 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.784782 
iter  10 value 93.922446
iter  20 value 92.155340
iter  30 value 85.967111
iter  40 value 85.743071
iter  50 value 84.410814
iter  60 value 84.116393
iter  70 value 84.092955
iter  80 value 83.932891
iter  90 value 83.318785
iter 100 value 83.247401
final  value 83.247401 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.059573 
iter  10 value 93.683240
iter  20 value 87.879797
iter  30 value 87.168306
iter  40 value 86.193355
iter  50 value 86.039298
iter  60 value 85.836015
iter  70 value 83.636579
iter  80 value 82.218253
iter  90 value 82.022429
iter 100 value 81.558366
final  value 81.558366 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.048357 
iter  10 value 94.077952
iter  20 value 88.424826
iter  30 value 86.630715
iter  40 value 84.630999
iter  50 value 83.599213
iter  60 value 83.371311
iter  70 value 83.303149
iter  80 value 83.236948
iter  90 value 83.168887
iter 100 value 82.776761
final  value 82.776761 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.545564 
iter  10 value 94.337396
iter  20 value 93.005848
iter  30 value 87.521570
iter  40 value 85.531841
iter  50 value 84.612665
iter  60 value 82.698981
iter  70 value 82.236364
iter  80 value 81.941180
iter  90 value 81.678247
iter 100 value 81.507425
final  value 81.507425 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.641194 
iter  10 value 93.999462
iter  20 value 88.381725
iter  30 value 86.348797
iter  40 value 82.966592
iter  50 value 82.647752
iter  60 value 82.178609
iter  70 value 81.892697
iter  80 value 81.771538
iter  90 value 81.754003
iter 100 value 81.698376
final  value 81.698376 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.023642 
iter  10 value 93.987119
iter  20 value 86.980787
iter  30 value 85.642078
iter  40 value 84.724152
iter  50 value 82.997745
iter  60 value 82.631792
iter  70 value 82.151584
iter  80 value 81.661290
iter  90 value 81.493527
iter 100 value 81.486639
final  value 81.486639 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.102479 
iter  10 value 94.192560
iter  20 value 94.034028
iter  30 value 93.356693
iter  40 value 87.672274
iter  50 value 85.200605
iter  60 value 83.693028
iter  70 value 83.479469
iter  80 value 82.608768
iter  90 value 81.830897
iter 100 value 81.340918
final  value 81.340918 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.233334 
iter  10 value 93.798871
iter  20 value 86.821325
iter  30 value 85.286125
iter  40 value 83.604751
iter  50 value 82.466090
iter  60 value 81.590869
iter  70 value 81.288774
iter  80 value 81.032491
iter  90 value 80.953405
iter 100 value 80.945312
final  value 80.945312 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.753635 
final  value 94.054518 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.581609 
final  value 94.054586 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.434491 
final  value 94.054475 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.032035 
final  value 94.054509 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.432368 
final  value 94.054532 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.283574 
iter  10 value 94.056821
iter  20 value 93.842561
iter  30 value 86.757610
iter  40 value 85.374591
final  value 85.348893 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.990574 
iter  10 value 94.013337
iter  20 value 94.009083
iter  30 value 93.937135
iter  40 value 93.322918
iter  40 value 93.322918
iter  40 value 93.322918
final  value 93.322918 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.133223 
iter  10 value 94.014029
iter  20 value 93.907760
iter  30 value 89.003796
iter  40 value 88.961245
iter  50 value 87.002008
iter  60 value 86.927528
iter  70 value 86.926493
final  value 86.926381 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.721905 
iter  10 value 94.057456
iter  20 value 93.880654
iter  30 value 84.643138
iter  40 value 84.454201
iter  50 value 84.452971
iter  60 value 84.243667
iter  70 value 83.720905
iter  80 value 83.446390
iter  90 value 83.291063
iter 100 value 83.074540
final  value 83.074540 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.500953 
iter  10 value 94.056869
iter  20 value 91.705118
iter  30 value 85.352675
iter  40 value 83.862358
iter  50 value 82.313323
iter  60 value 82.277876
iter  70 value 82.273038
iter  80 value 82.272316
iter  90 value 82.231776
iter 100 value 82.148636
final  value 82.148636 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.187759 
iter  10 value 94.061416
iter  20 value 93.438113
iter  30 value 91.582986
iter  40 value 91.465626
iter  50 value 84.268948
iter  60 value 84.005159
final  value 84.005111 
converged
Fitting Repeat 2 

# weights:  507
initial  value 131.685009 
iter  10 value 94.061434
iter  20 value 93.995359
iter  30 value 89.381093
iter  40 value 86.125490
iter  50 value 85.679089
iter  60 value 84.268944
iter  70 value 82.614414
iter  80 value 81.446788
iter  90 value 81.136938
iter 100 value 80.122943
final  value 80.122943 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 94.995977 
iter  10 value 92.780837
iter  20 value 92.615252
iter  30 value 85.522362
iter  40 value 85.084720
iter  50 value 82.784860
iter  60 value 81.740748
iter  70 value 81.377229
iter  80 value 81.347245
iter  90 value 81.265179
iter 100 value 81.123251
final  value 81.123251 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.131757 
iter  10 value 94.060490
iter  20 value 92.267950
iter  30 value 85.332382
final  value 85.332192 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.936335 
iter  10 value 94.039161
iter  20 value 94.015957
iter  30 value 93.973974
iter  40 value 87.596256
iter  50 value 86.150046
iter  60 value 86.097659
iter  70 value 86.021346
iter  80 value 82.988466
final  value 82.986779 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.058102 
iter  10 value 117.895086
iter  20 value 117.422015
iter  30 value 107.383477
iter  40 value 106.708093
final  value 106.643772 
converged
Fitting Repeat 2 

# weights:  305
initial  value 131.000298 
iter  10 value 117.894827
iter  20 value 117.860337
iter  30 value 106.976315
iter  40 value 106.718689
iter  50 value 106.641487
final  value 106.295344 
converged
Fitting Repeat 3 

# weights:  305
initial  value 137.886892 
iter  10 value 117.974516
iter  20 value 115.872762
iter  30 value 115.540717
iter  40 value 115.537858
iter  50 value 114.868415
iter  60 value 110.653852
iter  70 value 105.476482
iter  80 value 105.309144
iter  90 value 105.305094
iter 100 value 105.303879
final  value 105.303879 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 127.168932 
iter  10 value 117.894994
iter  20 value 117.890342
final  value 117.890337 
converged
Fitting Repeat 5 

# weights:  305
initial  value 125.847972 
iter  10 value 110.620333
iter  20 value 106.660090
final  value 106.659705 
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 -- Tue Dec  2 00:38:30 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 1 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 1 error, 0 failures
ERROR in test_enrich.df: Error : Request to g:Profiler failed (HTTP 504). The service may be temporarily unavailable.
If the issue persists, please contact biit.support@ut.ee with a reproducible example.

Test files with failing tests

   test_enrich.df.R 
     test_enrich.df 


Error in BiocGenerics:::testPackage("HPiP") : 
  unit tests failed for package HPiP
In addition: Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
Execution halted