Back to Build/check report for BioC 3.22:   simplified   long
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This page was generated on 2026-02-23 11:57 -0500 (Mon, 23 Feb 2026).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.3 LTS)x86_644.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 4890
Click on any hostname to see more info about the system (e.g. compilers)      (*) as reported by 'uname -p', except on Windows and Mac OS X

Package 1006/2361HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
HPiP 1.16.1  (landing page)
Matineh Rahmatbakhsh
Snapshot Date: 2026-02-22 13:45 -0500 (Sun, 22 Feb 2026)
git_url: https://git.bioconductor.org/packages/HPiP
git_branch: RELEASE_3_22
git_last_commit: 6cf0d22
git_last_commit_date: 2025-12-28 18:31:13 -0500 (Sun, 28 Dec 2025)
nebbiolo2Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  YES
See other builds for HPiP in R Universe.


CHECK results for HPiP on nebbiolo2

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.

raw results


Summary

Package: HPiP
Version: 1.16.1
Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz
StartedAt: 2026-02-23 00:43:11 -0500 (Mon, 23 Feb 2026)
EndedAt: 2026-02-23 00:58:10 -0500 (Mon, 23 Feb 2026)
EllapsedTime: 899.0 seconds
RetCode: 0
Status:   OK  
CheckDir: HPiP.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.2 (2025-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.16.1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
corr_plot     34.248  0.472  34.776
FSmethod      33.263  0.428  33.775
var_imp       32.984  0.559  33.544
pred_ensembel 12.532  0.096  11.364
enrichfindP    0.491  0.038  12.781
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.


Installation output

HPiP.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.16.1’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

Tests output

HPiP.Rcheck/tests/runTests.Rout


R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 96.041847 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.880937 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.094497 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.036422 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.620813 
iter  10 value 94.276975
final  value 94.275361 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.956100 
final  value 94.448052 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.692818 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.486893 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.823637 
iter  10 value 93.571116
iter  20 value 93.460526
final  value 93.460022 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.669420 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.674614 
iter  10 value 92.399620
final  value 92.387354 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.034674 
iter  10 value 94.468716
iter  20 value 94.284726
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.318247 
final  value 94.252920 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.328276 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.313730 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.908579 
iter  10 value 94.457021
iter  20 value 91.438214
iter  30 value 89.089843
iter  40 value 85.520225
iter  50 value 84.932163
iter  60 value 84.256278
iter  70 value 83.887438
iter  80 value 81.716604
iter  90 value 80.737299
iter 100 value 80.583680
final  value 80.583680 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.825042 
iter  10 value 94.517376
iter  20 value 94.353483
iter  30 value 90.765203
iter  40 value 90.383065
iter  50 value 89.342347
iter  60 value 86.092039
iter  70 value 85.609358
iter  80 value 85.235533
iter  90 value 85.105618
iter 100 value 84.681720
final  value 84.681720 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.407892 
iter  10 value 94.623328
iter  20 value 94.488677
iter  30 value 94.290510
iter  40 value 87.016380
iter  50 value 86.409780
iter  60 value 86.148068
iter  70 value 85.294110
iter  80 value 84.926393
iter  90 value 84.880686
iter 100 value 84.151978
final  value 84.151978 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 107.206071 
iter  10 value 94.398727
iter  20 value 94.244623
iter  30 value 85.636164
iter  40 value 84.822717
iter  50 value 84.249686
iter  60 value 84.099681
iter  70 value 82.902391
iter  80 value 82.383660
iter  90 value 82.020313
iter 100 value 81.930388
final  value 81.930388 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.812224 
iter  10 value 94.483994
iter  20 value 94.384702
iter  30 value 94.259287
iter  40 value 94.249335
iter  50 value 94.187959
iter  60 value 87.957415
iter  70 value 86.617147
iter  80 value 85.243707
iter  90 value 85.166241
iter 100 value 85.099181
final  value 85.099181 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 117.315739 
iter  10 value 94.395861
iter  20 value 89.978457
iter  30 value 88.740206
iter  40 value 85.650418
iter  50 value 85.039779
iter  60 value 84.818527
iter  70 value 84.726373
iter  80 value 84.568401
iter  90 value 84.463836
iter 100 value 83.587273
final  value 83.587273 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.046869 
iter  10 value 91.930150
iter  20 value 85.715272
iter  30 value 85.172216
iter  40 value 84.806599
iter  50 value 84.137769
iter  60 value 83.738738
iter  70 value 83.364566
iter  80 value 82.767807
iter  90 value 82.360331
iter 100 value 81.631313
final  value 81.631313 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.720514 
iter  10 value 94.356760
iter  20 value 89.273200
iter  30 value 86.602192
iter  40 value 83.810695
iter  50 value 83.164450
iter  60 value 83.014888
iter  70 value 82.957193
iter  80 value 82.805890
iter  90 value 82.322185
iter 100 value 82.246157
final  value 82.246157 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.004920 
iter  10 value 94.422382
iter  20 value 91.991123
iter  30 value 83.658101
iter  40 value 81.973884
iter  50 value 80.969691
iter  60 value 79.597465
iter  70 value 79.328577
iter  80 value 79.237558
iter  90 value 79.154236
iter 100 value 79.023446
final  value 79.023446 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.744581 
iter  10 value 91.146648
iter  20 value 86.138479
iter  30 value 84.736365
iter  40 value 81.393270
iter  50 value 79.630693
iter  60 value 79.375368
iter  70 value 79.218852
iter  80 value 79.196889
final  value 79.194096 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.211703 
iter  10 value 96.852410
iter  20 value 86.079411
iter  30 value 85.582496
iter  40 value 83.220743
iter  50 value 80.061627
iter  60 value 79.656050
iter  70 value 79.230992
iter  80 value 78.955503
iter  90 value 78.903336
iter 100 value 78.797583
final  value 78.797583 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.144197 
iter  10 value 94.783554
iter  20 value 87.709692
iter  30 value 85.208333
iter  40 value 84.981666
iter  50 value 84.212208
iter  60 value 81.988999
iter  70 value 81.604812
iter  80 value 80.703777
iter  90 value 80.009976
iter 100 value 79.177820
final  value 79.177820 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.194566 
iter  10 value 99.480939
iter  20 value 94.584953
iter  30 value 87.087735
iter  40 value 84.637019
iter  50 value 82.309677
iter  60 value 80.344445
iter  70 value 79.361946
iter  80 value 78.847140
iter  90 value 78.301979
iter 100 value 78.254994
final  value 78.254994 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.491181 
iter  10 value 94.425232
iter  20 value 93.508120
iter  30 value 90.392639
iter  40 value 90.065317
iter  50 value 84.333391
iter  60 value 82.289859
iter  70 value 80.425098
iter  80 value 79.534381
iter  90 value 79.163421
iter 100 value 78.705807
final  value 78.705807 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.580776 
iter  10 value 95.456976
iter  20 value 93.443359
iter  30 value 90.045380
iter  40 value 83.335950
iter  50 value 82.333064
iter  60 value 81.853967
iter  70 value 81.555880
iter  80 value 81.528352
iter  90 value 81.487522
iter 100 value 81.300724
final  value 81.300724 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.051779 
final  value 94.485993 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.438582 
final  value 94.485916 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.502937 
final  value 94.485936 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.814006 
final  value 94.486392 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.245092 
iter  10 value 94.276838
iter  20 value 94.275627
final  value 94.275478 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.735535 
iter  10 value 88.796094
iter  20 value 87.878454
iter  30 value 87.847341
iter  40 value 87.844505
iter  50 value 87.843303
iter  60 value 87.841902
final  value 87.841880 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.573879 
iter  10 value 94.489032
iter  20 value 94.484230
final  value 94.484216 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.626004 
iter  10 value 94.488883
iter  20 value 94.455511
iter  30 value 92.937099
iter  30 value 92.937099
iter  30 value 92.937099
final  value 92.937099 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.587583 
iter  10 value 94.280324
iter  20 value 94.213771
iter  30 value 94.185152
iter  40 value 94.178096
iter  50 value 94.169715
final  value 94.169653 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.694354 
iter  10 value 94.488441
iter  20 value 94.257594
iter  30 value 87.928984
iter  40 value 87.923344
iter  50 value 87.921889
iter  60 value 87.484915
final  value 87.484666 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.811637 
iter  10 value 94.295592
iter  20 value 94.238138
iter  30 value 94.204663
iter  40 value 94.178588
iter  50 value 93.297345
iter  60 value 87.314090
iter  70 value 83.460828
iter  80 value 83.392322
iter  90 value 82.288431
iter 100 value 82.070437
final  value 82.070437 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.527434 
iter  10 value 94.238421
iter  20 value 94.230236
iter  30 value 94.229808
iter  40 value 93.896090
iter  50 value 92.149577
iter  60 value 83.947835
iter  70 value 82.108238
iter  80 value 79.827377
final  value 79.798021 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.691904 
iter  10 value 94.494499
iter  20 value 94.408662
iter  30 value 91.200015
iter  40 value 90.044706
iter  50 value 89.870767
iter  60 value 89.860693
iter  70 value 89.860221
iter  80 value 89.859570
final  value 89.859542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.170051 
iter  10 value 94.283598
iter  20 value 94.269720
iter  30 value 84.501284
iter  40 value 83.616507
iter  50 value 83.615782
iter  60 value 83.613519
final  value 83.613314 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.613209 
iter  10 value 84.794283
iter  20 value 84.722660
iter  30 value 84.135909
iter  40 value 82.914143
iter  50 value 82.887093
iter  60 value 82.884153
iter  70 value 82.879158
iter  80 value 82.523533
iter  90 value 81.781361
iter 100 value 81.460758
final  value 81.460758 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.644927 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.127233 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.473225 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.114953 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.673047 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.019210 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.966902 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.976275 
final  value 94.309797 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.955217 
final  value 94.325945 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.101010 
iter  10 value 94.665802
iter  20 value 94.463209
iter  30 value 94.448515
iter  30 value 94.448515
iter  30 value 94.448515
final  value 94.448515 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.391938 
iter  10 value 94.232900
iter  20 value 86.950722
iter  30 value 86.076749
iter  40 value 86.062223
final  value 86.062150 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.058536 
iter  10 value 94.475658
iter  20 value 94.325996
final  value 94.325945 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.268973 
iter  10 value 94.339997
final  value 94.295858 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.796480 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.420793 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.010822 
iter  10 value 94.494436
iter  20 value 94.424382
iter  30 value 90.306388
iter  40 value 86.691709
iter  50 value 86.425777
iter  60 value 85.783536
iter  70 value 85.588695
iter  80 value 85.368127
iter  90 value 85.175211
final  value 85.175206 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.621850 
iter  10 value 94.488164
iter  20 value 93.162513
iter  30 value 92.742492
iter  40 value 88.187032
iter  50 value 86.245975
iter  60 value 85.544764
iter  70 value 85.309756
iter  80 value 85.175224
final  value 85.175206 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.981132 
iter  10 value 94.815389
iter  20 value 93.916835
iter  30 value 87.325381
iter  40 value 86.980197
iter  50 value 85.539453
final  value 85.538909 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.670696 
iter  10 value 92.226391
iter  20 value 90.218830
iter  30 value 89.574771
iter  40 value 88.871666
iter  50 value 87.420244
iter  60 value 87.034064
iter  70 value 86.617064
iter  80 value 85.672356
iter  90 value 85.127003
iter 100 value 84.805867
final  value 84.805867 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 121.297357 
iter  10 value 93.366777
iter  20 value 86.674236
iter  30 value 86.428603
iter  40 value 85.399216
iter  50 value 85.175618
final  value 85.175206 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.060876 
iter  10 value 94.819808
iter  20 value 94.430202
iter  30 value 92.443459
iter  40 value 90.507882
iter  50 value 89.021415
iter  60 value 88.584812
iter  70 value 87.679666
iter  80 value 85.322343
iter  90 value 83.973071
iter 100 value 83.292378
final  value 83.292378 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.749761 
iter  10 value 94.350855
iter  20 value 89.028245
iter  30 value 87.574974
iter  40 value 87.294300
iter  50 value 84.656690
iter  60 value 83.913503
iter  70 value 83.742509
iter  80 value 83.621605
iter  90 value 83.545280
iter 100 value 83.418550
final  value 83.418550 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.250715 
iter  10 value 94.633518
iter  20 value 92.768564
iter  30 value 89.282198
iter  40 value 85.818332
iter  50 value 85.415269
iter  60 value 84.782773
iter  70 value 84.534020
iter  80 value 84.479930
iter  90 value 84.384441
iter 100 value 84.234582
final  value 84.234582 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.570968 
iter  10 value 94.329330
iter  20 value 89.209722
iter  30 value 85.725827
iter  40 value 85.319329
iter  50 value 84.742799
iter  60 value 84.543351
iter  70 value 84.421407
iter  80 value 84.367929
iter  90 value 83.890127
iter 100 value 82.845930
final  value 82.845930 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.027290 
iter  10 value 94.109726
iter  20 value 86.368271
iter  30 value 85.790413
iter  40 value 85.293763
iter  50 value 83.362787
iter  60 value 82.597293
iter  70 value 82.079064
iter  80 value 82.018378
iter  90 value 82.002957
iter 100 value 81.968168
final  value 81.968168 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.586389 
iter  10 value 96.537158
iter  20 value 93.907158
iter  30 value 88.509676
iter  40 value 86.568589
iter  50 value 85.944196
iter  60 value 85.176620
iter  70 value 84.677289
iter  80 value 83.363293
iter  90 value 82.540252
iter 100 value 82.044250
final  value 82.044250 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.706433 
iter  10 value 94.617620
iter  20 value 94.450990
iter  30 value 87.957865
iter  40 value 87.141141
iter  50 value 84.132982
iter  60 value 82.774477
iter  70 value 82.054610
iter  80 value 81.802291
iter  90 value 81.553633
iter 100 value 81.479029
final  value 81.479029 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.805698 
iter  10 value 93.114541
iter  20 value 88.067693
iter  30 value 86.354020
iter  40 value 84.620265
iter  50 value 83.547905
iter  60 value 83.389080
iter  70 value 83.216929
iter  80 value 83.012738
iter  90 value 82.671809
iter 100 value 82.273033
final  value 82.273033 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.675491 
iter  10 value 94.505280
iter  20 value 94.186933
iter  30 value 93.988495
iter  40 value 91.749910
iter  50 value 88.723470
iter  60 value 87.710982
iter  70 value 85.988835
iter  80 value 84.914541
iter  90 value 84.149217
iter 100 value 82.746486
final  value 82.746486 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.182476 
iter  10 value 94.516358
iter  20 value 92.984880
iter  30 value 87.561081
iter  40 value 86.722092
iter  50 value 85.236429
iter  60 value 84.232233
iter  70 value 83.939223
iter  80 value 83.568718
iter  90 value 82.904901
iter 100 value 82.175918
final  value 82.175918 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.832173 
final  value 94.485785 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.171786 
final  value 94.485769 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.214118 
final  value 94.485814 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.830212 
final  value 94.485739 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.810928 
final  value 94.485863 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.225778 
iter  10 value 94.471715
iter  20 value 93.958990
iter  30 value 91.119172
iter  40 value 90.573590
iter  50 value 88.679664
iter  60 value 86.650103
iter  70 value 84.630077
iter  80 value 83.402471
iter  90 value 82.866399
iter 100 value 82.820282
final  value 82.820282 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.252163 
iter  10 value 94.331058
iter  20 value 94.326625
iter  30 value 93.722134
iter  40 value 86.020872
iter  50 value 85.826936
iter  60 value 85.554643
final  value 85.554550 
converged
Fitting Repeat 3 

# weights:  305
initial  value 128.968048 
iter  10 value 94.490176
iter  20 value 94.479949
iter  30 value 86.777222
iter  40 value 85.667085
iter  50 value 85.664392
iter  60 value 85.663689
iter  60 value 85.663689
iter  60 value 85.663689
final  value 85.663689 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.837841 
iter  10 value 94.485451
iter  20 value 94.483124
iter  30 value 86.419625
iter  40 value 85.606960
final  value 85.439704 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.279039 
iter  10 value 94.472020
iter  20 value 94.252277
iter  30 value 86.657197
iter  40 value 86.644013
iter  50 value 86.618472
iter  60 value 86.611690
iter  70 value 86.138218
iter  80 value 85.829893
final  value 85.827188 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.015086 
iter  10 value 94.492150
iter  20 value 94.477715
iter  30 value 89.159060
iter  40 value 86.068196
iter  50 value 85.447118
iter  60 value 85.144771
iter  70 value 85.143286
iter  80 value 85.139990
iter  90 value 84.573110
iter 100 value 83.667203
final  value 83.667203 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.233531 
iter  10 value 94.493200
iter  20 value 94.485597
final  value 94.484684 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.148721 
iter  10 value 94.474394
iter  20 value 93.455205
iter  30 value 92.489570
iter  40 value 85.933165
iter  50 value 85.640127
iter  60 value 84.662696
iter  70 value 84.116637
final  value 84.116627 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.895658 
iter  10 value 94.188668
iter  20 value 90.372681
iter  30 value 90.043245
iter  40 value 90.036689
iter  40 value 90.036689
final  value 90.036689 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.448254 
iter  10 value 94.492385
iter  20 value 94.436672
iter  30 value 86.873955
iter  40 value 86.255411
iter  50 value 85.657456
iter  60 value 83.977290
iter  70 value 83.653567
iter  80 value 82.050908
iter  90 value 81.266919
iter 100 value 81.215596
final  value 81.215596 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.306430 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.753852 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.830293 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.347340 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.834118 
iter  10 value 90.605973
iter  20 value 90.444444
iter  20 value 90.444444
iter  20 value 90.444444
final  value 90.444444 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.558040 
iter  10 value 94.026543
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.420645 
iter  10 value 92.983415
iter  20 value 91.533642
iter  30 value 91.382300
iter  40 value 91.381642
final  value 91.381640 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.724282 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.566892 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.926711 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.336260 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.084303 
iter  10 value 93.829784
iter  20 value 93.335260
iter  30 value 93.103968
final  value 93.103897 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.954226 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.499059 
iter  10 value 94.026546
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.822205 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.276290 
iter  10 value 94.469591
iter  20 value 94.216631
iter  30 value 94.214390
iter  40 value 94.190411
iter  50 value 85.872443
iter  60 value 84.544195
iter  70 value 83.860422
iter  80 value 83.742128
final  value 83.742010 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.269067 
iter  10 value 94.145489
iter  20 value 92.087848
iter  30 value 91.990513
iter  40 value 84.874574
iter  50 value 84.606765
iter  60 value 84.309769
iter  70 value 83.963888
iter  80 value 83.302497
iter  90 value 83.215638
iter 100 value 83.214324
final  value 83.214324 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.692018 
iter  10 value 94.488624
iter  20 value 94.230988
iter  30 value 94.140803
iter  40 value 94.102671
iter  50 value 93.013979
iter  60 value 89.870734
iter  70 value 89.676495
iter  80 value 89.560537
iter  90 value 89.555316
iter  90 value 89.555316
iter  90 value 89.555316
final  value 89.555316 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.341127 
iter  10 value 89.462269
iter  20 value 85.636903
iter  30 value 85.335943
iter  40 value 84.285479
iter  50 value 83.998122
iter  60 value 83.980107
final  value 83.979675 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.398903 
iter  10 value 94.483971
iter  20 value 86.202820
iter  30 value 85.563455
iter  40 value 85.340646
iter  50 value 84.260400
iter  60 value 83.980187
final  value 83.979675 
converged
Fitting Repeat 1 

# weights:  305
initial  value 126.023277 
iter  10 value 95.151763
iter  20 value 90.097350
iter  30 value 89.434398
iter  40 value 87.141855
iter  50 value 82.341123
iter  60 value 81.658853
iter  70 value 80.613531
iter  80 value 80.275096
iter  90 value 80.141283
iter 100 value 79.978836
final  value 79.978836 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.599725 
iter  10 value 94.506399
iter  20 value 87.399962
iter  30 value 85.460989
iter  40 value 85.120003
iter  50 value 83.711585
iter  60 value 83.670164
iter  70 value 83.541404
iter  80 value 82.737207
iter  90 value 81.211059
iter 100 value 80.948367
final  value 80.948367 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.168655 
iter  10 value 94.301503
iter  20 value 87.256905
iter  30 value 84.644818
iter  40 value 84.043115
iter  50 value 83.773916
iter  60 value 83.683859
iter  70 value 83.626490
iter  80 value 82.728275
iter  90 value 81.923056
iter 100 value 81.726146
final  value 81.726146 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.149914 
iter  10 value 95.432033
iter  20 value 91.151244
iter  30 value 87.388450
iter  40 value 82.996345
iter  50 value 81.405329
iter  60 value 80.881042
iter  70 value 80.810913
iter  80 value 80.636062
iter  90 value 80.412121
iter 100 value 80.169145
final  value 80.169145 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.391347 
iter  10 value 94.044475
iter  20 value 86.091592
iter  30 value 85.278456
iter  40 value 84.769623
iter  50 value 84.396125
iter  60 value 82.586197
iter  70 value 81.744080
iter  80 value 81.434267
iter  90 value 81.235995
iter 100 value 80.741379
final  value 80.741379 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.000532 
iter  10 value 94.200755
iter  20 value 86.541330
iter  30 value 84.198427
iter  40 value 82.473839
iter  50 value 82.238701
iter  60 value 81.736945
iter  70 value 81.571290
iter  80 value 81.485382
iter  90 value 80.654297
iter 100 value 80.226060
final  value 80.226060 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.167658 
iter  10 value 93.723177
iter  20 value 85.276575
iter  30 value 84.156642
iter  40 value 83.434605
iter  50 value 82.364401
iter  60 value 81.326475
iter  70 value 80.895041
iter  80 value 80.835378
iter  90 value 80.801365
iter 100 value 80.778362
final  value 80.778362 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.484837 
iter  10 value 96.044710
iter  20 value 91.949346
iter  30 value 83.872489
iter  40 value 83.637781
iter  50 value 83.611232
iter  60 value 83.518682
iter  70 value 82.355348
iter  80 value 81.491664
iter  90 value 81.378005
iter 100 value 81.059066
final  value 81.059066 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.483067 
iter  10 value 94.419403
iter  20 value 88.089696
iter  30 value 84.821069
iter  40 value 81.431918
iter  50 value 80.778858
iter  60 value 80.376471
iter  70 value 80.066241
iter  80 value 79.730916
iter  90 value 79.693744
iter 100 value 79.613864
final  value 79.613864 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.675878 
iter  10 value 93.763331
iter  20 value 84.924849
iter  30 value 81.591001
iter  40 value 80.682605
iter  50 value 80.217885
iter  60 value 79.781162
iter  70 value 79.681741
iter  80 value 79.636352
iter  90 value 79.498598
iter 100 value 79.436867
final  value 79.436867 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.806024 
final  value 94.485969 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.013488 
iter  10 value 94.485790
iter  20 value 94.450340
iter  30 value 93.119330
final  value 93.110531 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.832794 
final  value 93.111717 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.881337 
iter  10 value 94.485928
iter  20 value 94.470654
iter  30 value 90.638551
iter  40 value 85.204277
iter  50 value 84.739983
final  value 84.739813 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.041934 
final  value 94.485714 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.388268 
iter  10 value 94.489313
iter  20 value 87.233047
iter  30 value 87.150571
iter  40 value 86.698416
iter  50 value 86.506995
iter  60 value 86.505696
iter  70 value 86.505552
iter  80 value 86.500107
final  value 86.499951 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.969197 
iter  10 value 94.363487
iter  20 value 94.343375
iter  30 value 94.063190
iter  40 value 94.028195
iter  50 value 93.848724
iter  60 value 92.511798
iter  70 value 90.464522
iter  80 value 90.342624
iter  90 value 90.340788
iter 100 value 90.340607
final  value 90.340607 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.496219 
final  value 94.488856 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.295986 
iter  10 value 94.489384
iter  20 value 94.464054
iter  30 value 91.287035
iter  40 value 91.126623
iter  50 value 90.845286
final  value 90.845284 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.233670 
iter  10 value 94.031672
iter  20 value 94.026954
iter  30 value 94.026690
iter  40 value 86.196153
iter  50 value 86.039422
iter  60 value 84.746775
iter  70 value 84.721146
iter  80 value 84.706444
iter  90 value 84.705606
iter 100 value 84.705299
final  value 84.705299 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 99.325313 
iter  10 value 92.484160
iter  20 value 86.953753
iter  30 value 86.952576
iter  40 value 85.893797
iter  50 value 82.936952
iter  60 value 82.323454
iter  70 value 82.269067
iter  80 value 80.872273
iter  90 value 80.169077
iter 100 value 79.561327
final  value 79.561327 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.983210 
iter  10 value 94.348557
iter  20 value 94.232955
iter  30 value 94.028824
iter  40 value 94.027158
final  value 94.027157 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.215119 
iter  10 value 88.798386
iter  20 value 86.385382
iter  30 value 86.225862
iter  40 value 85.826181
iter  50 value 85.806923
iter  60 value 85.802756
iter  70 value 85.799755
final  value 85.799443 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.227548 
iter  10 value 94.491526
iter  20 value 94.475026
iter  30 value 88.383411
iter  40 value 87.380409
iter  50 value 81.641829
iter  60 value 80.543550
iter  70 value 80.309099
iter  80 value 80.305316
iter  90 value 80.304772
iter 100 value 80.298204
final  value 80.298204 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.175295 
iter  10 value 94.492098
iter  20 value 94.226088
iter  30 value 92.939330
iter  40 value 88.347060
iter  50 value 86.793430
iter  60 value 81.131399
iter  70 value 80.751580
final  value 80.750294 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.865145 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.183895 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.180832 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.398754 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.203750 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.914437 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.935739 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.388777 
iter  10 value 92.826038
iter  10 value 92.826038
iter  10 value 92.826038
final  value 92.826038 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.450516 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.674086 
iter  10 value 93.838571
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.698106 
iter  10 value 93.328844
final  value 93.328261 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.556158 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.614554 
final  value 92.826036 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.362491 
final  value 93.482759 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.476508 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.994538 
iter  10 value 94.201822
iter  20 value 94.057331
iter  30 value 94.042521
iter  40 value 92.429379
iter  50 value 91.772414
iter  60 value 90.352842
iter  70 value 89.882318
iter  80 value 89.443219
final  value 89.442848 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.245956 
iter  10 value 94.058595
iter  20 value 93.270180
iter  30 value 92.935962
iter  40 value 90.447774
iter  50 value 85.838688
iter  60 value 83.454763
iter  70 value 82.792376
iter  80 value 82.240783
iter  90 value 81.369404
iter 100 value 81.073349
final  value 81.073349 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 112.494967 
iter  10 value 94.073868
iter  20 value 93.970147
iter  30 value 93.266668
iter  40 value 92.945708
iter  50 value 92.029674
iter  60 value 89.134181
iter  70 value 87.958156
iter  80 value 87.520108
iter  90 value 85.986542
iter 100 value 84.026059
final  value 84.026059 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.828665 
iter  10 value 94.051084
iter  20 value 93.903536
iter  30 value 93.897415
iter  40 value 93.569621
iter  50 value 84.708824
iter  60 value 83.976132
iter  70 value 83.645796
iter  80 value 83.588854
final  value 83.588814 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.570497 
iter  10 value 94.082420
iter  20 value 94.048621
iter  30 value 93.016196
iter  40 value 90.754435
iter  50 value 83.859367
iter  60 value 83.202352
iter  70 value 82.285766
iter  80 value 81.850452
iter  90 value 81.775376
iter 100 value 81.714537
final  value 81.714537 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.802939 
iter  10 value 94.094769
iter  20 value 93.933895
iter  30 value 92.018529
iter  40 value 91.368668
iter  50 value 84.397633
iter  60 value 82.944295
iter  70 value 81.238735
iter  80 value 80.733796
iter  90 value 80.581394
iter 100 value 80.538075
final  value 80.538075 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 132.145195 
iter  10 value 97.930685
iter  20 value 94.044832
iter  30 value 87.457425
iter  40 value 86.666798
iter  50 value 82.365350
iter  60 value 80.264521
iter  70 value 79.943497
iter  80 value 79.569559
iter  90 value 79.279213
iter 100 value 79.203536
final  value 79.203536 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.742586 
iter  10 value 94.081349
iter  20 value 92.111620
iter  30 value 86.865535
iter  40 value 86.006465
iter  50 value 85.771339
iter  60 value 85.532469
iter  70 value 84.488782
iter  80 value 82.123194
iter  90 value 81.170525
iter 100 value 81.011350
final  value 81.011350 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.734378 
iter  10 value 94.243494
iter  20 value 85.604231
iter  30 value 83.797503
iter  40 value 82.648481
iter  50 value 82.437767
iter  60 value 82.358623
iter  70 value 82.062031
iter  80 value 80.440173
iter  90 value 79.226750
iter 100 value 79.050702
final  value 79.050702 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.789327 
iter  10 value 94.060191
iter  20 value 84.488900
iter  30 value 83.491049
iter  40 value 83.350927
iter  50 value 82.026373
iter  60 value 80.603159
iter  70 value 79.918651
iter  80 value 79.150662
iter  90 value 79.083424
iter 100 value 79.044751
final  value 79.044751 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.869366 
iter  10 value 90.079045
iter  20 value 84.413260
iter  30 value 83.419877
iter  40 value 81.433990
iter  50 value 80.758717
iter  60 value 80.679790
iter  70 value 80.373494
iter  80 value 80.135963
iter  90 value 80.119174
iter 100 value 79.868113
final  value 79.868113 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.292912 
iter  10 value 93.766550
iter  20 value 87.699152
iter  30 value 84.616820
iter  40 value 82.898718
iter  50 value 80.894871
iter  60 value 79.704661
iter  70 value 79.105350
iter  80 value 79.073148
iter  90 value 79.048782
iter 100 value 79.041243
final  value 79.041243 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.546593 
iter  10 value 93.997834
iter  20 value 85.038235
iter  30 value 84.075089
iter  40 value 83.340343
iter  50 value 82.680342
iter  60 value 81.483666
iter  70 value 79.347978
iter  80 value 78.996753
iter  90 value 78.895960
iter 100 value 78.838104
final  value 78.838104 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.836759 
iter  10 value 93.947584
iter  20 value 89.283736
iter  30 value 84.588122
iter  40 value 82.854358
iter  50 value 82.352523
iter  60 value 82.179485
iter  70 value 81.256469
iter  80 value 79.894175
iter  90 value 79.332725
iter 100 value 79.191840
final  value 79.191840 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.366878 
iter  10 value 94.400928
iter  20 value 93.327516
iter  30 value 92.927016
iter  40 value 91.970371
iter  50 value 84.031427
iter  60 value 82.330028
iter  70 value 81.567858
iter  80 value 80.266366
iter  90 value 79.479954
iter 100 value 78.799183
final  value 78.799183 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.704748 
final  value 94.054545 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.764878 
iter  10 value 94.054392
iter  20 value 94.022584
final  value 93.836194 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.260478 
iter  10 value 94.054657
iter  20 value 94.053000
iter  30 value 92.879757
final  value 92.826353 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.030768 
iter  10 value 93.837859
iter  20 value 93.678466
iter  30 value 90.737608
iter  40 value 89.335673
iter  50 value 89.290000
iter  60 value 88.828154
iter  70 value 88.759547
final  value 88.759540 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.482898 
final  value 94.054526 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.280977 
iter  10 value 94.057168
iter  20 value 82.696341
iter  30 value 81.330916
iter  40 value 81.324083
iter  50 value 81.284352
iter  60 value 81.278372
iter  70 value 81.268067
iter  80 value 81.158927
iter  90 value 80.675829
iter 100 value 80.000444
final  value 80.000444 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.977497 
iter  10 value 94.055482
iter  20 value 93.972337
iter  30 value 83.674886
iter  40 value 83.671680
iter  50 value 83.214193
iter  60 value 83.199664
iter  70 value 82.189360
iter  80 value 82.173503
final  value 82.170565 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.986119 
iter  10 value 94.054439
iter  20 value 93.249117
iter  30 value 89.300421
iter  40 value 89.295276
iter  50 value 89.292404
final  value 89.292362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.917604 
iter  10 value 94.057603
iter  20 value 94.052911
iter  30 value 83.766540
final  value 83.671542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.369153 
iter  10 value 94.057679
iter  20 value 94.038146
iter  30 value 87.982652
iter  40 value 82.813216
final  value 82.810353 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.136907 
iter  10 value 94.061144
iter  20 value 93.861819
iter  30 value 83.781730
iter  40 value 83.775179
iter  50 value 83.760662
iter  60 value 83.744688
iter  70 value 83.711343
iter  80 value 83.279636
iter  90 value 82.433818
iter 100 value 79.755986
final  value 79.755986 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.289350 
iter  10 value 94.061343
iter  20 value 93.921887
iter  30 value 92.826447
final  value 92.826386 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.688973 
iter  10 value 94.060995
iter  20 value 93.675380
iter  30 value 92.826327
iter  40 value 91.899616
iter  50 value 85.480403
iter  60 value 82.955531
iter  70 value 80.782864
iter  80 value 80.257323
iter  90 value 80.071737
iter 100 value 80.051017
final  value 80.051017 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.082777 
iter  10 value 93.335946
iter  20 value 93.329934
iter  30 value 91.512631
iter  40 value 86.421477
iter  50 value 86.403182
iter  60 value 86.402165
iter  70 value 84.700029
iter  80 value 84.301352
iter  90 value 83.786038
iter 100 value 83.756533
final  value 83.756533 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.704284 
iter  10 value 94.061350
iter  20 value 94.053024
iter  30 value 94.036070
iter  40 value 92.493223
iter  50 value 87.056601
iter  60 value 86.894990
iter  70 value 86.794695
iter  80 value 86.791918
iter  80 value 86.791918
final  value 86.791918 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.623124 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.631522 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.165323 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.397292 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.623497 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.922679 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.515517 
final  value 94.038251 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.685207 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.946344 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.372416 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.578077 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.714270 
final  value 93.962011 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.395871 
final  value 93.962011 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.411737 
final  value 93.869755 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.062326 
iter  10 value 86.702780
iter  20 value 85.525832
iter  30 value 84.755853
final  value 84.755832 
converged
Fitting Repeat 1 

# weights:  103
initial  value 116.292195 
iter  10 value 94.051552
iter  20 value 93.604533
iter  30 value 88.492741
iter  40 value 86.986121
iter  50 value 85.281114
iter  60 value 84.592944
iter  70 value 83.708251
iter  80 value 82.047383
iter  90 value 81.789195
iter 100 value 81.444337
final  value 81.444337 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.872162 
iter  10 value 93.826663
iter  20 value 86.961844
iter  30 value 86.487080
iter  40 value 85.662162
iter  50 value 84.291471
iter  60 value 84.169687
iter  70 value 84.007718
iter  80 value 83.951868
final  value 83.950799 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.742129 
iter  10 value 93.890061
iter  20 value 85.593046
iter  30 value 84.944539
iter  40 value 84.636751
iter  50 value 84.442926
iter  60 value 84.425387
iter  70 value 83.554562
iter  80 value 83.464169
final  value 83.463415 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.598531 
iter  10 value 94.057450
iter  20 value 93.827665
iter  30 value 92.738996
iter  40 value 85.403769
iter  50 value 84.915908
iter  60 value 84.629093
iter  70 value 83.705118
iter  80 value 83.469403
iter  90 value 83.463494
final  value 83.463417 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.957406 
iter  10 value 94.054788
iter  20 value 88.564471
iter  30 value 87.008957
iter  40 value 85.749132
iter  50 value 84.310495
iter  60 value 84.282044
final  value 84.282043 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.550540 
iter  10 value 94.886197
iter  20 value 92.184777
iter  30 value 85.812639
iter  40 value 83.146482
iter  50 value 81.248105
iter  60 value 80.387607
iter  70 value 80.067705
iter  80 value 79.714684
iter  90 value 79.419898
iter 100 value 79.261938
final  value 79.261938 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.155255 
iter  10 value 94.054435
iter  20 value 91.724962
iter  30 value 85.041499
iter  40 value 83.340267
iter  50 value 83.055613
iter  60 value 82.204420
iter  70 value 82.032648
iter  80 value 81.595718
iter  90 value 80.412093
iter 100 value 79.497505
final  value 79.497505 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.090615 
iter  10 value 93.989596
iter  20 value 88.377036
iter  30 value 85.094055
iter  40 value 84.173674
iter  50 value 83.988600
iter  60 value 83.877673
iter  70 value 81.751903
iter  80 value 81.299194
iter  90 value 80.782938
iter 100 value 80.694488
final  value 80.694488 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.169198 
iter  10 value 93.988094
iter  20 value 88.304827
iter  30 value 84.322780
iter  40 value 83.582451
iter  50 value 83.313328
iter  60 value 82.415314
iter  70 value 81.549118
iter  80 value 81.237814
iter  90 value 81.005745
iter 100 value 80.914345
final  value 80.914345 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.427047 
iter  10 value 93.924674
iter  20 value 85.169777
iter  30 value 84.652196
iter  40 value 83.945706
iter  50 value 82.917107
iter  60 value 82.805293
iter  70 value 82.643028
iter  80 value 82.540117
iter  90 value 81.986876
iter 100 value 81.413451
final  value 81.413451 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 128.397137 
iter  10 value 94.141915
iter  20 value 93.406285
iter  30 value 92.312260
iter  40 value 88.030066
iter  50 value 84.815461
iter  60 value 83.731186
iter  70 value 82.126672
iter  80 value 81.415747
iter  90 value 81.108198
iter 100 value 80.868091
final  value 80.868091 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.225539 
iter  10 value 85.821238
iter  20 value 84.397993
iter  30 value 83.941305
iter  40 value 83.895406
iter  50 value 82.764404
iter  60 value 81.409337
iter  70 value 81.059111
iter  80 value 80.695050
iter  90 value 80.456707
iter 100 value 80.361136
final  value 80.361136 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.962284 
iter  10 value 94.064938
iter  20 value 92.974000
iter  30 value 89.416117
iter  40 value 86.569250
iter  50 value 83.602405
iter  60 value 81.835623
iter  70 value 80.808956
iter  80 value 80.562908
iter  90 value 79.557731
iter 100 value 79.215564
final  value 79.215564 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.574461 
iter  10 value 94.347466
iter  20 value 88.669152
iter  30 value 84.511539
iter  40 value 83.828039
iter  50 value 83.516662
iter  60 value 82.229558
iter  70 value 81.613236
iter  80 value 81.028591
iter  90 value 80.303613
iter 100 value 79.904156
final  value 79.904156 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.327870 
iter  10 value 87.542157
iter  20 value 84.860003
iter  30 value 83.482326
iter  40 value 81.410405
iter  50 value 80.916202
iter  60 value 80.398112
iter  70 value 79.960849
iter  80 value 79.875469
iter  90 value 79.591850
iter 100 value 79.462851
final  value 79.462851 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.104709 
iter  10 value 92.831510
iter  20 value 88.058238
iter  30 value 85.882352
iter  40 value 85.881798
iter  50 value 85.855289
iter  60 value 85.740530
iter  70 value 85.740390
final  value 85.740215 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.565893 
final  value 94.054539 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.085105 
iter  10 value 94.039826
iter  20 value 93.838995
final  value 93.764104 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.215665 
final  value 94.054494 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.705143 
final  value 94.054721 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.614164 
iter  10 value 94.055337
iter  20 value 94.036212
iter  30 value 93.423841
iter  40 value 92.922393
iter  50 value 90.308598
iter  60 value 84.108229
iter  70 value 83.383064
iter  80 value 83.379257
iter  90 value 82.615215
final  value 82.614517 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.599355 
iter  10 value 93.921180
iter  20 value 93.677734
iter  30 value 93.674519
iter  40 value 93.674304
iter  50 value 93.669509
iter  60 value 93.455747
iter  70 value 83.295367
iter  80 value 83.273640
iter  90 value 83.271940
iter 100 value 83.269512
final  value 83.269512 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.303946 
iter  10 value 94.057557
iter  20 value 88.384573
iter  30 value 87.049824
iter  40 value 87.038536
final  value 87.037907 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.170531 
iter  10 value 94.059372
iter  20 value 93.544560
iter  30 value 90.431121
iter  40 value 90.251014
iter  50 value 89.609917
iter  60 value 86.936710
iter  70 value 85.288831
iter  80 value 84.643443
iter  90 value 84.642321
iter 100 value 83.996006
final  value 83.996006 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.280286 
iter  10 value 94.056691
iter  20 value 94.032348
iter  30 value 93.579683
iter  40 value 87.906200
iter  50 value 80.995690
iter  60 value 80.536123
iter  70 value 80.501385
final  value 80.501214 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.348667 
iter  10 value 94.047165
iter  20 value 93.994465
iter  30 value 93.400974
iter  40 value 92.415309
iter  50 value 92.313524
final  value 92.313066 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.753020 
iter  10 value 94.046211
iter  20 value 93.949819
iter  30 value 87.796959
iter  40 value 82.104512
iter  50 value 79.441810
iter  60 value 79.241745
iter  70 value 78.986766
iter  80 value 78.864821
iter  90 value 78.851104
final  value 78.850473 
converged
Fitting Repeat 3 

# weights:  507
initial  value 132.872601 
iter  10 value 93.915770
iter  20 value 93.580231
iter  30 value 93.457553
iter  40 value 93.455227
iter  50 value 93.363828
iter  60 value 93.345007
iter  70 value 91.874642
iter  80 value 85.241243
iter  90 value 83.181566
iter 100 value 83.172381
final  value 83.172381 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.235841 
iter  10 value 94.060383
iter  20 value 93.937599
iter  30 value 93.531618
iter  40 value 93.454123
final  value 93.453773 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.751324 
iter  10 value 94.047207
iter  20 value 94.039748
iter  30 value 94.039121
iter  40 value 88.413083
iter  50 value 83.089439
iter  60 value 80.131619
iter  70 value 79.111036
iter  80 value 78.411512
iter  90 value 78.186571
iter 100 value 77.949589
final  value 77.949589 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 152.391476 
iter  10 value 117.767159
iter  20 value 117.761282
final  value 117.760511 
converged
Fitting Repeat 2 

# weights:  507
initial  value 137.556303 
iter  10 value 117.185230
iter  20 value 109.893791
iter  30 value 109.480476
iter  40 value 107.103119
iter  50 value 104.189233
iter  60 value 103.878923
iter  70 value 103.795323
iter  80 value 103.760763
final  value 103.760592 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.667894 
iter  10 value 117.898257
iter  20 value 117.766706
iter  30 value 117.759236
iter  40 value 115.248361
final  value 108.506935 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.729370 
iter  10 value 117.095669
iter  20 value 116.883496
iter  30 value 116.848482
iter  40 value 116.846539
iter  50 value 116.842739
iter  60 value 109.154700
iter  70 value 109.043303
iter  80 value 107.599758
iter  90 value 106.820054
iter 100 value 106.818988
final  value 106.818988 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.678068 
iter  10 value 117.898172
iter  20 value 114.557304
iter  30 value 107.970951
iter  40 value 107.797369
iter  50 value 107.795089
iter  60 value 105.728727
iter  70 value 105.170892
iter  80 value 105.086891
iter  90 value 104.375497
iter 100 value 101.944451
final  value 101.944451 
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 -- Mon Feb 23 00:48:29 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 
 42.525   1.328  92.595 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod33.263 0.42833.775
FreqInteractors0.4280.0190.448
calculateAAC0.0280.0010.030
calculateAutocor0.2990.0090.309
calculateCTDC0.0700.0010.071
calculateCTDD0.5070.0060.513
calculateCTDT0.1810.0070.189
calculateCTriad0.3630.0040.367
calculateDC0.0830.0000.083
calculateF0.3060.0010.307
calculateKSAAP0.0970.0010.099
calculateQD_Sm1.5060.0101.516
calculateTC1.4670.0301.498
calculateTC_Sm0.2470.0040.251
corr_plot34.248 0.47234.776
enrichfindP 0.491 0.03812.781
enrichfind_hp0.0580.0040.893
enrichplot0.5130.0010.515
filter_missing_values0.0010.0000.001
getFASTA0.3530.0283.334
getHPI0.0000.0000.001
get_negativePPI0.0010.0000.001
get_positivePPI0.0010.0000.000
impute_missing_data0.0010.0000.001
plotPPI0.0770.0020.078
pred_ensembel12.532 0.09611.364
var_imp32.984 0.55933.544