Back to Multiple platform build/check report for BioC 3.21:   simplified   long
ABCDEFG[H]IJKLMNOPQRSTUVWXYZ

This page was generated on 2025-08-04 11:47 -0400 (Mon, 04 Aug 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.2 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4823
palomino7Windows Server 2022 Datacenterx644.5.1 (2025-06-13 ucrt) -- "Great Square Root" 4565
merida1macOS 12.7.5 Montereyx86_644.5.1 RC (2025-06-05 r88288) -- "Great Square Root" 4603
kjohnson1macOS 13.6.6 Venturaarm644.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" 4544
kunpeng2Linux (openEuler 24.03 LTS)aarch64R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" 4579
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 997/2341HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
HPiP 1.14.0  (landing page)
Matineh Rahmatbakhsh
Snapshot Date: 2025-07-31 13:40 -0400 (Thu, 31 Jul 2025)
git_url: https://git.bioconductor.org/packages/HPiP
git_branch: RELEASE_3_21
git_last_commit: e2435b7
git_last_commit_date: 2025-04-15 12:38:30 -0400 (Tue, 15 Apr 2025)
nebbiolo1Linux (Ubuntu 24.04.2 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino7Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.7.5 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson1macOS 13.6.6 Ventura / arm64  OK    OK    OK    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 24.03 LTS) / aarch64  OK    OK    OK  


CHECK results for HPiP on kunpeng2

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.
- See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host.

raw results


Summary

Package: HPiP
Version: 1.14.0
Command: /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.14.0.tar.gz
StartedAt: 2025-08-01 10:29:23 -0000 (Fri, 01 Aug 2025)
EndedAt: 2025-08-01 10:35:53 -0000 (Fri, 01 Aug 2025)
EllapsedTime: 390.3 seconds
RetCode: 0
Status:   OK  
CheckDir: HPiP.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.14.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       38.973  0.371  39.425
corr_plot     37.421  0.371  37.862
FSmethod      37.465  0.215  37.781
pred_ensembel 17.828  0.726  17.364
enrichfindP    0.495  0.036  20.462
getFASTA       0.071  0.012   5.411
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.


Installation output

HPiP.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.14.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

Tests output

HPiP.Rcheck/tests/runTests.Rout


R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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 99.319323 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.569096 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.132402 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.644897 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.912016 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.316545 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.654267 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.411554 
final  value 94.050051 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.858350 
iter  10 value 93.362090
iter  20 value 93.311194
iter  30 value 93.310694
final  value 93.310690 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.780992 
iter  10 value 94.053110
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.040957 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.549754 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.451210 
iter  10 value 93.854207
final  value 93.854083 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.871967 
iter  10 value 92.569844
iter  20 value 92.294865
iter  30 value 92.293455
iter  30 value 92.293454
final  value 92.293454 
converged
Fitting Repeat 5 

# weights:  507
initial  value 148.265349 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.318158 
iter  10 value 94.056697
iter  20 value 90.463765
iter  30 value 87.756690
iter  40 value 87.419282
iter  50 value 86.984417
iter  60 value 86.566378
iter  70 value 85.764694
iter  80 value 85.385636
iter  90 value 85.290274
final  value 85.287135 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.551098 
iter  10 value 93.556650
iter  20 value 86.794545
iter  30 value 85.947387
iter  40 value 84.250313
iter  50 value 82.763694
iter  60 value 82.517112
iter  70 value 82.505680
final  value 82.505254 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.510473 
iter  10 value 93.916568
iter  20 value 89.161964
iter  30 value 88.016746
iter  40 value 86.910498
iter  50 value 86.021023
iter  60 value 85.400460
iter  70 value 85.304183
iter  80 value 85.287139
final  value 85.287135 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.889905 
iter  10 value 94.122587
iter  20 value 94.055245
iter  30 value 88.505857
iter  40 value 86.893305
iter  50 value 86.541899
iter  60 value 86.416081
iter  70 value 85.469015
iter  80 value 84.931353
iter  90 value 84.739390
iter 100 value 84.714002
final  value 84.714002 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.070908 
iter  10 value 93.942107
iter  20 value 92.705182
iter  30 value 91.322979
iter  40 value 88.498760
iter  50 value 87.213195
iter  60 value 86.669018
iter  70 value 85.832639
iter  80 value 85.343986
iter  90 value 84.908833
iter 100 value 84.717722
final  value 84.717722 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 122.777644 
iter  10 value 94.113286
iter  20 value 93.233879
iter  30 value 89.660195
iter  40 value 88.496822
iter  50 value 87.179620
iter  60 value 86.574771
iter  70 value 84.054625
iter  80 value 83.468580
iter  90 value 83.306046
iter 100 value 83.235987
final  value 83.235987 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.256946 
iter  10 value 94.168148
iter  20 value 88.418668
iter  30 value 87.690891
iter  40 value 85.769457
iter  50 value 84.731620
iter  60 value 82.980388
iter  70 value 81.933853
iter  80 value 81.608337
iter  90 value 81.435673
iter 100 value 81.391683
final  value 81.391683 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.854395 
iter  10 value 93.975786
iter  20 value 90.681067
iter  30 value 87.867331
iter  40 value 87.473623
iter  50 value 84.287941
iter  60 value 83.057728
iter  70 value 82.727523
iter  80 value 82.143354
iter  90 value 81.666039
iter 100 value 81.489020
final  value 81.489020 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.331285 
iter  10 value 94.097332
iter  20 value 92.599346
iter  30 value 90.330751
iter  40 value 88.253475
iter  50 value 85.872712
iter  60 value 85.729086
iter  70 value 84.591697
iter  80 value 83.413516
iter  90 value 82.367672
iter 100 value 81.858341
final  value 81.858341 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.812878 
iter  10 value 94.849052
iter  20 value 94.058345
iter  30 value 90.466336
iter  40 value 87.970357
iter  50 value 84.923944
iter  60 value 84.047432
iter  70 value 82.282878
iter  80 value 81.603553
iter  90 value 81.508878
iter 100 value 81.231496
final  value 81.231496 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.687657 
iter  10 value 95.733947
iter  20 value 92.017381
iter  30 value 87.663190
iter  40 value 86.388310
iter  50 value 84.950384
iter  60 value 82.572865
iter  70 value 82.279930
iter  80 value 82.117148
iter  90 value 81.982284
iter 100 value 81.812131
final  value 81.812131 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.431756 
iter  10 value 93.980342
iter  20 value 88.351520
iter  30 value 86.020247
iter  40 value 84.972311
iter  50 value 84.291545
iter  60 value 83.729430
iter  70 value 82.974374
iter  80 value 82.592296
iter  90 value 81.593895
iter 100 value 81.197413
final  value 81.197413 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.621281 
iter  10 value 94.052225
iter  20 value 91.057772
iter  30 value 85.507924
iter  40 value 84.660503
iter  50 value 83.130526
iter  60 value 81.954475
iter  70 value 81.392350
iter  80 value 81.158022
iter  90 value 80.998206
iter 100 value 80.925431
final  value 80.925431 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.907148 
iter  10 value 93.814498
iter  20 value 86.296532
iter  30 value 83.507496
iter  40 value 83.116228
iter  50 value 81.681077
iter  60 value 81.280373
iter  70 value 81.204023
iter  80 value 81.091429
iter  90 value 81.058368
iter 100 value 81.014850
final  value 81.014850 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.528969 
iter  10 value 94.188629
iter  20 value 93.959004
iter  30 value 88.013129
iter  40 value 86.584388
iter  50 value 86.265996
iter  60 value 85.024223
iter  70 value 84.711705
iter  80 value 84.549390
iter  90 value 84.437745
iter 100 value 84.357734
final  value 84.357734 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.030050 
final  value 94.054485 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.449567 
iter  10 value 94.034553
iter  20 value 94.033518
iter  30 value 93.333669
iter  40 value 92.830201
final  value 92.830073 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.599045 
final  value 94.054636 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.808638 
iter  10 value 94.020669
iter  20 value 94.018613
iter  30 value 93.036364
iter  40 value 92.825830
iter  50 value 92.824701
iter  60 value 92.823848
final  value 92.823828 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.127695 
final  value 94.054723 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.617798 
iter  10 value 94.057911
iter  20 value 94.053278
final  value 94.053015 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.400993 
iter  10 value 94.057548
iter  20 value 94.047519
iter  30 value 93.031093
iter  40 value 89.384311
iter  50 value 85.536496
iter  60 value 85.171470
iter  70 value 84.471558
iter  80 value 83.889938
iter  90 value 83.658581
iter 100 value 83.653470
final  value 83.653470 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.946688 
iter  10 value 94.056219
final  value 94.052923 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.334759 
iter  10 value 94.057855
iter  20 value 94.044257
iter  30 value 88.999014
iter  40 value 87.365617
iter  50 value 87.361800
iter  60 value 87.360763
iter  70 value 87.276801
iter  80 value 87.136808
iter  90 value 83.610417
iter 100 value 83.088362
final  value 83.088362 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.358654 
iter  10 value 94.057487
iter  20 value 94.054425
iter  30 value 94.035495
final  value 94.034235 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.908088 
iter  10 value 94.061533
iter  20 value 94.051122
iter  30 value 93.931643
iter  40 value 93.081892
iter  50 value 92.687081
iter  60 value 92.686068
iter  70 value 88.323134
iter  80 value 86.932648
iter  90 value 86.912052
iter 100 value 86.265829
final  value 86.265829 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.688634 
iter  10 value 94.024637
iter  20 value 94.018504
iter  30 value 93.206977
iter  40 value 92.901039
iter  50 value 92.797261
final  value 92.797204 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.031896 
iter  10 value 93.952078
iter  20 value 93.949126
iter  30 value 93.883315
iter  40 value 93.882933
iter  50 value 93.809395
iter  60 value 87.751745
iter  70 value 87.086474
iter  80 value 85.930306
iter  90 value 83.760185
iter 100 value 83.755022
final  value 83.755022 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.060076 
iter  10 value 94.041220
iter  20 value 94.035258
iter  30 value 94.022074
iter  40 value 88.606851
iter  50 value 88.155162
iter  60 value 88.145855
final  value 88.144961 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.218285 
iter  10 value 94.061449
iter  20 value 93.947047
iter  30 value 92.843853
iter  40 value 92.841556
final  value 92.841422 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.030848 
final  value 93.860355 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.065659 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.378072 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.633005 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.456681 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.932029 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.168458 
final  value 93.900000 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.306745 
iter  10 value 93.720460
iter  20 value 93.017565
final  value 92.701657 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.936111 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.253270 
iter  10 value 93.862892
final  value 93.860355 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.507448 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.558352 
final  value 94.011429 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.873417 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.244816 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.291142 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.521092 
iter  10 value 94.054867
iter  20 value 90.377740
iter  30 value 89.454751
iter  40 value 88.150599
iter  50 value 87.401259
iter  60 value 86.919695
iter  70 value 86.654358
final  value 86.651613 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.395861 
iter  10 value 94.060605
iter  20 value 94.056720
iter  30 value 93.867081
iter  40 value 93.803380
iter  50 value 93.697975
iter  60 value 89.340631
iter  70 value 88.654053
iter  80 value 88.384058
iter  90 value 88.263103
iter 100 value 88.099207
final  value 88.099207 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.149916 
iter  10 value 94.055063
iter  20 value 94.010019
iter  30 value 93.049444
iter  40 value 92.948965
iter  50 value 88.197577
iter  60 value 87.432261
iter  70 value 86.656690
iter  80 value 85.935308
iter  90 value 85.903659
iter 100 value 85.878019
final  value 85.878019 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.879117 
iter  10 value 93.976463
iter  20 value 89.825404
iter  30 value 89.073381
iter  40 value 88.776371
iter  50 value 88.374716
iter  60 value 86.223611
iter  70 value 85.767401
iter  80 value 85.751283
iter  90 value 85.726381
iter 100 value 85.722339
final  value 85.722339 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.234648 
iter  10 value 94.057872
iter  20 value 93.959522
iter  30 value 89.295625
iter  40 value 87.837486
iter  50 value 87.448247
iter  60 value 87.281192
iter  70 value 87.221477
iter  80 value 87.194273
iter  80 value 87.194273
iter  80 value 87.194273
final  value 87.194273 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.948823 
iter  10 value 94.210878
iter  20 value 93.700462
iter  30 value 88.636374
iter  40 value 87.952513
iter  50 value 86.189915
iter  60 value 85.297018
iter  70 value 84.784922
iter  80 value 84.640347
iter  90 value 84.534541
iter 100 value 84.447233
final  value 84.447233 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.699851 
iter  10 value 94.783901
iter  20 value 94.588557
iter  30 value 88.901579
iter  40 value 88.623246
iter  50 value 87.617234
iter  60 value 87.233019
iter  70 value 87.151472
iter  80 value 87.116142
iter  90 value 87.029035
iter 100 value 86.561483
final  value 86.561483 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.935065 
iter  10 value 93.891263
iter  20 value 90.596534
iter  30 value 89.417433
iter  40 value 88.739178
iter  50 value 88.653862
iter  60 value 88.525864
iter  70 value 88.484647
iter  80 value 86.832387
iter  90 value 85.383640
iter 100 value 84.761867
final  value 84.761867 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.131010 
iter  10 value 93.771713
iter  20 value 90.122515
iter  30 value 89.403115
iter  40 value 88.792470
iter  50 value 87.807855
iter  60 value 86.748310
iter  70 value 86.707002
iter  80 value 86.025373
iter  90 value 85.476090
iter 100 value 84.872595
final  value 84.872595 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.886892 
iter  10 value 94.009250
iter  20 value 90.908462
iter  30 value 88.891045
iter  40 value 87.701267
iter  50 value 86.294812
iter  60 value 85.789810
iter  70 value 85.697116
iter  80 value 85.675533
iter  90 value 85.662041
final  value 85.661792 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.590496 
iter  10 value 94.095605
iter  20 value 89.246483
iter  30 value 88.665276
iter  40 value 86.120196
iter  50 value 85.206856
iter  60 value 84.877520
iter  70 value 84.640568
iter  80 value 84.510740
iter  90 value 84.298840
iter 100 value 84.161592
final  value 84.161592 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.051306 
iter  10 value 94.617311
iter  20 value 94.052377
iter  30 value 88.927045
iter  40 value 88.594567
iter  50 value 88.006824
iter  60 value 87.507788
iter  70 value 87.239336
iter  80 value 86.957147
iter  90 value 86.635284
iter 100 value 86.496879
final  value 86.496879 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.068842 
iter  10 value 94.242715
iter  20 value 93.812736
iter  30 value 90.312704
iter  40 value 88.240875
iter  50 value 86.386710
iter  60 value 85.330722
iter  70 value 84.743716
iter  80 value 84.506415
iter  90 value 84.464214
iter 100 value 84.337558
final  value 84.337558 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 138.500146 
iter  10 value 93.928026
iter  20 value 92.737845
iter  30 value 91.016974
iter  40 value 88.872878
iter  50 value 86.612596
iter  60 value 86.104415
iter  70 value 85.440298
iter  80 value 85.203164
iter  90 value 85.090873
iter 100 value 84.714575
final  value 84.714575 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.896280 
iter  10 value 94.057915
iter  20 value 93.741832
iter  30 value 92.665129
iter  40 value 89.368354
iter  50 value 87.570602
iter  60 value 86.746000
iter  70 value 85.475030
iter  80 value 85.139885
iter  90 value 84.951281
iter 100 value 84.770018
final  value 84.770018 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.883294 
final  value 94.054522 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.034971 
final  value 94.054465 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.536195 
final  value 93.837556 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.899445 
final  value 94.054590 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.305711 
iter  10 value 93.837986
iter  20 value 93.817583
iter  30 value 93.704797
iter  40 value 89.707726
iter  50 value 88.889522
final  value 88.872725 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.335338 
iter  10 value 94.057416
iter  20 value 94.052998
iter  30 value 92.113322
iter  40 value 89.825213
iter  50 value 88.593751
iter  60 value 88.546060
iter  70 value 87.374501
final  value 87.370384 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.498934 
iter  10 value 94.057823
iter  20 value 93.934863
iter  30 value 88.595749
iter  40 value 88.170882
iter  50 value 88.169229
iter  60 value 88.132909
iter  70 value 87.751935
final  value 87.750518 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.622523 
iter  10 value 94.057531
iter  20 value 93.572057
iter  30 value 88.536567
iter  40 value 88.535697
iter  50 value 88.399570
iter  60 value 88.118154
iter  70 value 88.118041
iter  70 value 88.118041
final  value 88.118041 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.836561 
iter  10 value 93.769986
iter  20 value 93.706533
iter  30 value 90.162731
iter  40 value 90.159899
iter  50 value 89.720639
iter  60 value 89.458767
iter  70 value 87.987061
iter  80 value 86.620672
iter  90 value 84.620030
iter 100 value 83.747794
final  value 83.747794 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.333454 
iter  10 value 94.057299
iter  20 value 94.052919
iter  30 value 94.007108
iter  40 value 93.760977
iter  50 value 93.721092
iter  60 value 87.698203
iter  70 value 87.027333
iter  80 value 86.262354
iter  90 value 84.518239
iter 100 value 84.140718
final  value 84.140718 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.145863 
iter  10 value 94.060830
iter  20 value 93.226126
iter  30 value 88.598871
iter  40 value 88.593362
final  value 88.593346 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.936507 
iter  10 value 93.768759
iter  20 value 93.764507
iter  30 value 93.745583
iter  40 value 93.687387
final  value 93.687239 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.116658 
iter  10 value 94.059503
iter  20 value 94.037156
iter  30 value 94.035451
iter  40 value 94.030945
iter  50 value 94.028452
iter  60 value 93.880128
iter  70 value 89.029656
iter  80 value 86.811440
iter  90 value 86.810914
iter 100 value 86.517292
final  value 86.517292 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.212521 
iter  10 value 93.881016
iter  20 value 93.433587
iter  30 value 93.388414
iter  40 value 92.075728
iter  50 value 91.996595
iter  60 value 91.916177
iter  70 value 91.909165
iter  80 value 88.765362
iter  90 value 88.154856
iter 100 value 87.653466
final  value 87.653466 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.928854 
iter  10 value 93.791315
iter  20 value 93.741000
iter  30 value 93.735719
iter  40 value 93.733159
final  value 93.730028 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.193889 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.708551 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.175855 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.537390 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.235753 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.843955 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.393831 
final  value 93.688363 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.221215 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.961422 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.701745 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.153096 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.361419 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.968509 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.977698 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.932816 
iter  10 value 86.219587
iter  20 value 80.700776
iter  30 value 80.686475
iter  40 value 80.686362
final  value 80.686354 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.723439 
iter  10 value 94.486941
iter  20 value 85.333418
iter  30 value 76.682548
iter  40 value 76.175619
iter  50 value 76.024184
iter  60 value 75.772285
iter  70 value 75.339050
iter  80 value 75.163236
final  value 75.162008 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.840839 
iter  10 value 94.442844
iter  20 value 90.859421
iter  30 value 87.751849
iter  40 value 84.765513
iter  50 value 84.186242
iter  60 value 83.366216
iter  70 value 83.337537
iter  80 value 81.485062
iter  90 value 81.434469
iter 100 value 81.037644
final  value 81.037644 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.462580 
iter  10 value 94.466757
iter  20 value 88.914566
iter  30 value 81.377656
iter  40 value 80.631804
iter  50 value 78.805147
iter  60 value 75.460569
iter  70 value 75.316876
iter  80 value 75.175939
iter  90 value 75.162280
final  value 75.162008 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.376323 
iter  10 value 93.781481
iter  20 value 87.757166
iter  30 value 86.129271
iter  40 value 80.756837
iter  50 value 80.145520
iter  60 value 79.260323
iter  70 value 78.954338
iter  80 value 78.633615
iter  90 value 78.625216
final  value 78.625206 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.753960 
iter  10 value 94.049664
iter  20 value 77.724362
iter  30 value 77.470793
iter  40 value 76.990350
iter  50 value 76.205328
iter  60 value 75.297222
iter  70 value 75.262590
iter  80 value 75.217975
final  value 75.217895 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.308740 
iter  10 value 92.310245
iter  20 value 82.146577
iter  30 value 81.494895
iter  40 value 78.944899
iter  50 value 76.373120
iter  60 value 75.455991
iter  70 value 74.795306
iter  80 value 74.345011
iter  90 value 74.298245
iter 100 value 74.243440
final  value 74.243440 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.142964 
iter  10 value 92.101934
iter  20 value 80.335559
iter  30 value 79.403004
iter  40 value 78.435633
iter  50 value 76.443269
iter  60 value 75.832678
iter  70 value 75.021814
iter  80 value 73.920757
iter  90 value 73.687327
iter 100 value 73.550620
final  value 73.550620 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.582304 
iter  10 value 98.057905
iter  20 value 95.744982
iter  30 value 90.870110
iter  40 value 81.620642
iter  50 value 78.894210
iter  60 value 78.284155
iter  70 value 77.173442
iter  80 value 77.035322
iter  90 value 76.652046
iter 100 value 75.520261
final  value 75.520261 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.684176 
iter  10 value 91.575467
iter  20 value 87.859957
iter  30 value 87.272104
iter  40 value 85.902832
iter  50 value 80.796863
iter  60 value 77.242014
iter  70 value 76.818919
iter  80 value 76.734112
iter  90 value 76.325683
iter 100 value 76.219498
final  value 76.219498 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.544794 
iter  10 value 94.478853
iter  20 value 86.576587
iter  30 value 78.073171
iter  40 value 76.627603
iter  50 value 75.132969
iter  60 value 74.601858
iter  70 value 74.076703
iter  80 value 73.694716
iter  90 value 73.626857
iter 100 value 73.590056
final  value 73.590056 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.493303 
iter  10 value 94.604418
iter  20 value 84.232588
iter  30 value 80.762851
iter  40 value 80.326688
iter  50 value 76.545737
iter  60 value 75.130715
iter  70 value 74.475971
iter  80 value 74.244421
iter  90 value 74.211785
iter 100 value 73.980695
final  value 73.980695 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.122441 
iter  10 value 97.254748
iter  20 value 90.461674
iter  30 value 85.269561
iter  40 value 83.519500
iter  50 value 80.590458
iter  60 value 77.058698
iter  70 value 76.487562
iter  80 value 76.195318
iter  90 value 76.133680
iter 100 value 76.079312
final  value 76.079312 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 129.060500 
iter  10 value 94.614427
iter  20 value 82.588018
iter  30 value 80.946077
iter  40 value 77.960718
iter  50 value 75.168549
iter  60 value 74.092726
iter  70 value 73.855248
iter  80 value 73.801668
iter  90 value 73.780759
iter 100 value 73.725176
final  value 73.725176 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.470133 
iter  10 value 94.755922
iter  20 value 94.331512
iter  30 value 83.201741
iter  40 value 81.268199
iter  50 value 77.488909
iter  60 value 76.638945
iter  70 value 75.179099
iter  80 value 74.526250
iter  90 value 74.371655
iter 100 value 74.346189
final  value 74.346189 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.695723 
iter  10 value 92.926436
iter  20 value 86.369451
iter  30 value 78.193300
iter  40 value 77.406319
iter  50 value 77.166930
iter  60 value 76.574292
iter  70 value 75.440586
iter  80 value 75.057187
iter  90 value 74.917918
iter 100 value 74.632423
final  value 74.632423 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.000504 
final  value 94.485774 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.312180 
final  value 94.485491 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.364229 
iter  10 value 91.464148
iter  20 value 91.422822
iter  30 value 91.417202
iter  40 value 89.328956
iter  50 value 87.498261
iter  60 value 86.595417
iter  70 value 86.524288
final  value 86.518213 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.399102 
final  value 94.485866 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.910645 
final  value 94.485942 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.373360 
iter  10 value 94.489233
iter  20 value 94.483943
iter  30 value 91.658776
iter  40 value 91.652519
final  value 91.652253 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.842979 
iter  10 value 93.693787
iter  20 value 93.691002
iter  30 value 93.646654
iter  40 value 93.646383
iter  40 value 93.646383
iter  40 value 93.646383
final  value 93.646383 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.381786 
iter  10 value 91.239480
iter  20 value 82.805924
iter  30 value 82.666792
iter  40 value 82.665657
iter  50 value 82.664758
iter  60 value 77.562848
iter  70 value 74.747384
iter  80 value 73.712873
iter  90 value 72.827292
iter 100 value 72.593731
final  value 72.593731 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.031864 
iter  10 value 93.933079
iter  20 value 81.689104
iter  30 value 76.262489
iter  40 value 76.235271
iter  50 value 76.231851
iter  60 value 75.851374
iter  70 value 75.672108
iter  80 value 75.570325
iter  90 value 75.568365
iter 100 value 75.567400
final  value 75.567400 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.733559 
iter  10 value 83.205459
iter  20 value 82.180506
iter  30 value 82.172710
final  value 82.170109 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.014829 
iter  10 value 85.889614
iter  20 value 83.935564
iter  30 value 83.238590
iter  40 value 83.234414
iter  50 value 83.231966
iter  60 value 78.782977
iter  70 value 74.659180
iter  80 value 74.641066
iter  90 value 74.638628
final  value 74.638036 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.756663 
iter  10 value 94.260905
iter  20 value 94.231146
final  value 94.230066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.424472 
iter  10 value 93.286574
iter  20 value 91.656210
iter  30 value 91.650828
iter  40 value 91.615080
iter  50 value 91.495206
iter  60 value 91.490563
final  value 91.490549 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.956615 
iter  10 value 94.491270
iter  20 value 91.608363
iter  30 value 91.591511
iter  40 value 91.188260
iter  50 value 86.784584
iter  60 value 83.162750
iter  70 value 80.482267
iter  80 value 79.447602
final  value 79.436858 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.619152 
iter  10 value 94.365816
iter  20 value 92.636413
iter  30 value 82.582768
iter  40 value 78.691676
iter  50 value 78.691134
final  value 78.689735 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.956503 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.047754 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.891585 
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.843142 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.208995 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.774771 
iter  10 value 94.428841
final  value 94.428839 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.937455 
iter  10 value 94.396674
iter  20 value 87.576344
iter  30 value 84.855271
iter  40 value 84.783393
final  value 84.783333 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.633830 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.010678 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.711985 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.631210 
iter  10 value 93.772984
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.073290 
final  value 94.030602 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.490875 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.637057 
iter  10 value 86.915617
iter  20 value 81.860709
final  value 81.582895 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.480979 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 112.813282 
iter  10 value 93.854766
iter  20 value 87.223102
iter  30 value 86.745735
iter  40 value 86.435297
iter  50 value 84.344736
iter  60 value 81.956071
iter  70 value 81.912962
iter  80 value 80.479050
iter  90 value 79.280767
iter 100 value 78.433810
final  value 78.433810 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.834464 
iter  10 value 94.495294
iter  20 value 94.485461
iter  30 value 89.258746
iter  40 value 83.073176
iter  50 value 81.569038
iter  60 value 81.125192
iter  70 value 80.868629
iter  80 value 80.701237
iter  90 value 80.652360
iter 100 value 80.647480
final  value 80.647480 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.970429 
iter  10 value 94.068332
iter  20 value 89.061181
iter  30 value 80.777710
iter  40 value 79.322960
iter  50 value 78.912509
iter  60 value 78.546545
iter  70 value 78.483461
final  value 78.482942 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.722395 
iter  10 value 94.380067
iter  20 value 82.917350
iter  30 value 80.216601
iter  40 value 79.955389
iter  50 value 79.650050
iter  60 value 78.368074
iter  70 value 78.267635
iter  80 value 78.267386
iter  80 value 78.267386
final  value 78.267386 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.059399 
iter  10 value 94.658033
iter  20 value 94.483076
iter  30 value 82.140992
iter  40 value 81.853233
iter  50 value 80.107039
iter  60 value 80.098358
final  value 80.098347 
converged
Fitting Repeat 1 

# weights:  305
initial  value 124.949979 
iter  10 value 94.436757
iter  20 value 91.845824
iter  30 value 83.596440
iter  40 value 82.336948
iter  50 value 81.542652
iter  60 value 81.218005
iter  70 value 79.059380
iter  80 value 77.827179
iter  90 value 76.834877
iter 100 value 76.691723
final  value 76.691723 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.168103 
iter  10 value 94.489196
iter  20 value 85.591667
iter  30 value 82.487888
iter  40 value 79.994006
iter  50 value 78.992833
iter  60 value 78.049063
iter  70 value 77.609445
iter  80 value 76.619236
iter  90 value 76.367761
iter 100 value 76.308836
final  value 76.308836 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.469494 
iter  10 value 94.469084
iter  20 value 89.206080
iter  30 value 82.152513
iter  40 value 81.040851
iter  50 value 79.789120
iter  60 value 78.407064
iter  70 value 76.970921
iter  80 value 76.788817
iter  90 value 76.662001
iter 100 value 76.453018
final  value 76.453018 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.196113 
iter  10 value 94.045268
iter  20 value 83.172870
iter  30 value 81.924155
iter  40 value 79.981792
iter  50 value 79.533100
iter  60 value 78.352478
iter  70 value 77.915130
iter  80 value 77.848547
iter  90 value 77.730476
iter 100 value 77.143041
final  value 77.143041 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.816677 
iter  10 value 94.682885
iter  20 value 93.830685
iter  30 value 88.653002
iter  40 value 86.677339
iter  50 value 83.162807
iter  60 value 79.127265
iter  70 value 78.453429
iter  80 value 78.244864
iter  90 value 77.179336
iter 100 value 76.597221
final  value 76.597221 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.819203 
iter  10 value 94.092423
iter  20 value 81.223888
iter  30 value 80.835625
iter  40 value 80.483451
iter  50 value 79.728083
iter  60 value 77.876333
iter  70 value 77.834423
iter  80 value 77.499055
iter  90 value 77.131942
iter 100 value 76.569361
final  value 76.569361 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.372041 
iter  10 value 91.412363
iter  20 value 89.366970
iter  30 value 82.192607
iter  40 value 81.119455
iter  50 value 80.878708
iter  60 value 78.736097
iter  70 value 77.162928
iter  80 value 76.959370
iter  90 value 76.828298
iter 100 value 76.799341
final  value 76.799341 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.317169 
iter  10 value 95.254928
iter  20 value 85.826584
iter  30 value 79.828460
iter  40 value 78.988413
iter  50 value 78.458720
iter  60 value 78.170768
iter  70 value 78.086057
iter  80 value 77.881248
iter  90 value 77.580824
iter 100 value 76.751953
final  value 76.751953 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.792146 
iter  10 value 94.276150
iter  20 value 85.375304
iter  30 value 82.895644
iter  40 value 82.549429
iter  50 value 79.898465
iter  60 value 79.404843
iter  70 value 78.758880
iter  80 value 77.379540
iter  90 value 76.882760
iter 100 value 76.657375
final  value 76.657375 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.168259 
iter  10 value 94.955378
iter  20 value 93.973150
iter  30 value 87.203478
iter  40 value 86.290386
iter  50 value 85.832804
iter  60 value 81.839121
iter  70 value 78.867675
iter  80 value 77.971334
iter  90 value 77.611868
iter 100 value 77.134164
final  value 77.134164 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.055328 
final  value 94.485916 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.507686 
final  value 94.485798 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.388652 
iter  10 value 93.775099
iter  20 value 93.773818
iter  30 value 93.493621
final  value 93.453729 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.664854 
final  value 94.485888 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.794038 
final  value 94.486022 
converged
Fitting Repeat 1 

# weights:  305
initial  value 131.568322 
iter  10 value 94.489574
iter  20 value 94.200649
iter  30 value 80.753545
iter  40 value 79.934980
iter  50 value 79.205785
iter  60 value 78.995384
iter  70 value 78.964961
iter  80 value 78.960410
iter  90 value 78.878598
iter 100 value 78.756272
final  value 78.756272 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.971223 
iter  10 value 93.779147
iter  20 value 93.777529
iter  30 value 93.775528
iter  40 value 93.775356
iter  50 value 93.565551
iter  60 value 84.246247
final  value 84.231320 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.210625 
iter  10 value 93.778912
iter  20 value 93.778208
iter  30 value 93.471858
iter  40 value 93.456122
iter  50 value 93.416626
iter  60 value 90.035880
iter  70 value 88.405263
iter  80 value 88.304133
iter  90 value 88.303953
final  value 88.303593 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.533816 
iter  10 value 94.488877
iter  20 value 94.180676
iter  30 value 82.225465
iter  40 value 81.992770
iter  50 value 79.919707
iter  60 value 78.815723
iter  70 value 78.812117
iter  80 value 78.467395
iter  90 value 78.205755
iter 100 value 78.121112
final  value 78.121112 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.955359 
iter  10 value 94.488788
iter  20 value 94.473106
iter  30 value 93.637949
iter  30 value 93.637948
iter  30 value 93.637948
final  value 93.637948 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.093711 
iter  10 value 93.308586
iter  20 value 85.637556
iter  30 value 80.827215
iter  40 value 79.507349
iter  50 value 78.201709
iter  60 value 77.598294
iter  70 value 77.447916
iter  80 value 77.141374
final  value 77.140666 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.405637 
iter  10 value 93.781374
iter  20 value 93.572967
iter  30 value 85.209206
iter  40 value 82.487575
iter  50 value 82.076834
iter  60 value 82.071668
iter  70 value 82.071216
iter  80 value 82.041636
iter  90 value 81.859409
iter 100 value 81.857507
final  value 81.857507 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 132.718120 
iter  10 value 94.492709
iter  20 value 93.997119
iter  30 value 90.655123
iter  40 value 90.654457
iter  40 value 90.654456
iter  40 value 90.654456
final  value 90.654456 
converged
Fitting Repeat 4 

# weights:  507
initial  value 138.737429 
iter  10 value 94.492666
iter  20 value 94.484077
iter  30 value 89.092968
iter  40 value 81.317632
iter  50 value 80.867485
iter  60 value 78.767307
iter  70 value 78.749011
final  value 78.748802 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.795185 
iter  10 value 93.781773
iter  20 value 93.744518
iter  30 value 81.041348
final  value 81.010418 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.474622 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.794441 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.760337 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 118.136120 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.067902 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 124.229426 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.745488 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.701573 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.980919 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.932692 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.081172 
final  value 94.312038 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.196254 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.304034 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.255773 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 128.483252 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.226839 
iter  10 value 94.422556
iter  20 value 88.820170
iter  30 value 86.232487
iter  40 value 84.808274
iter  50 value 83.947881
iter  60 value 83.656757
iter  70 value 83.313640
iter  80 value 83.094995
iter  90 value 82.837426
iter 100 value 82.664720
final  value 82.664720 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.165894 
iter  10 value 94.490161
iter  20 value 93.835790
iter  30 value 92.368803
iter  40 value 92.162355
iter  50 value 92.094860
iter  60 value 91.997551
iter  70 value 85.442652
iter  80 value 84.736940
iter  90 value 84.013763
iter 100 value 83.094181
final  value 83.094181 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.860512 
iter  10 value 93.921728
iter  20 value 91.725000
iter  30 value 90.710152
iter  40 value 86.739260
iter  50 value 84.743409
iter  60 value 83.191769
iter  70 value 82.881030
iter  80 value 82.669795
iter  90 value 82.665763
iter  90 value 82.665762
iter  90 value 82.665762
final  value 82.665762 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.547106 
iter  10 value 94.498899
iter  20 value 94.485318
iter  30 value 94.342419
iter  40 value 92.943557
iter  50 value 90.089808
iter  60 value 87.025995
iter  70 value 86.098722
iter  80 value 86.016268
iter  90 value 85.557910
iter 100 value 84.865392
final  value 84.865392 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.730373 
iter  10 value 94.488281
iter  20 value 94.486707
iter  30 value 93.488747
iter  40 value 88.329679
iter  50 value 87.118644
iter  60 value 85.550669
iter  70 value 85.454146
final  value 85.453975 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.538105 
iter  10 value 94.729227
iter  20 value 90.889462
iter  30 value 86.771199
iter  40 value 86.477547
iter  50 value 85.374016
iter  60 value 82.784392
iter  70 value 82.190069
iter  80 value 81.814914
iter  90 value 81.661133
iter 100 value 81.417911
final  value 81.417911 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.277046 
iter  10 value 94.508307
iter  20 value 93.391946
iter  30 value 92.019487
iter  40 value 91.248930
iter  50 value 85.729249
iter  60 value 84.095974
iter  70 value 82.607234
iter  80 value 82.184915
iter  90 value 81.633050
iter 100 value 81.522547
final  value 81.522547 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.478386 
iter  10 value 94.643629
iter  20 value 90.717849
iter  30 value 88.870825
iter  40 value 88.055607
iter  50 value 86.267859
iter  60 value 83.080702
iter  70 value 82.125036
iter  80 value 81.906229
iter  90 value 81.711063
iter 100 value 81.341906
final  value 81.341906 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.580674 
iter  10 value 94.306902
iter  20 value 90.202006
iter  30 value 88.052558
iter  40 value 85.809692
iter  50 value 84.739458
iter  60 value 83.787191
iter  70 value 83.377951
iter  80 value 83.109100
iter  90 value 81.716395
iter 100 value 81.488612
final  value 81.488612 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.605196 
iter  10 value 93.949003
iter  20 value 92.503215
iter  30 value 92.073344
iter  40 value 91.987751
iter  50 value 91.823491
iter  60 value 89.996130
iter  70 value 84.108764
iter  80 value 83.135443
iter  90 value 82.237531
iter 100 value 82.057540
final  value 82.057540 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.842605 
iter  10 value 94.522097
iter  20 value 89.222361
iter  30 value 87.082978
iter  40 value 85.377494
iter  50 value 84.610643
iter  60 value 83.473861
iter  70 value 82.703688
iter  80 value 82.142645
iter  90 value 82.055205
iter 100 value 81.956250
final  value 81.956250 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.307909 
iter  10 value 95.112199
iter  20 value 93.503848
iter  30 value 92.565366
iter  40 value 89.138126
iter  50 value 86.858624
iter  60 value 84.884703
iter  70 value 84.443549
iter  80 value 83.296545
iter  90 value 82.410436
iter 100 value 82.151674
final  value 82.151674 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.653817 
iter  10 value 94.392121
iter  20 value 93.100892
iter  30 value 90.043660
iter  40 value 86.779712
iter  50 value 83.192051
iter  60 value 82.221630
iter  70 value 81.558538
iter  80 value 81.252374
iter  90 value 81.104944
iter 100 value 81.010341
final  value 81.010341 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 136.560632 
iter  10 value 94.533678
iter  20 value 93.872096
iter  30 value 92.946089
iter  40 value 91.210919
iter  50 value 88.077405
iter  60 value 85.405151
iter  70 value 84.400587
iter  80 value 84.128856
iter  90 value 83.092388
iter 100 value 82.252002
final  value 82.252002 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.372801 
iter  10 value 94.635035
iter  20 value 93.307736
iter  30 value 87.189169
iter  40 value 85.893806
iter  50 value 85.428544
iter  60 value 85.038464
iter  70 value 83.414265
iter  80 value 82.214458
iter  90 value 81.419997
iter 100 value 81.267411
final  value 81.267411 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.230747 
final  value 94.485592 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.600658 
final  value 94.485859 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.940107 
final  value 94.485814 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.134665 
iter  10 value 94.485509
final  value 94.484704 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.202109 
iter  10 value 94.485736
final  value 94.484434 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.372647 
iter  10 value 94.488927
iter  20 value 94.484239
iter  30 value 93.874273
iter  40 value 88.264191
iter  50 value 88.144255
iter  60 value 88.141822
iter  70 value 86.186016
iter  80 value 85.997195
iter  90 value 84.621225
iter 100 value 82.456336
final  value 82.456336 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.888625 
iter  10 value 92.573092
iter  20 value 92.473448
iter  30 value 92.414041
iter  40 value 92.047043
iter  50 value 92.035282
final  value 92.032663 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.924490 
iter  10 value 94.488737
iter  20 value 94.296879
iter  30 value 86.186661
iter  40 value 85.891867
iter  50 value 85.253263
iter  60 value 84.823025
iter  70 value 84.375532
iter  80 value 81.472133
iter  90 value 81.146695
iter 100 value 81.114189
final  value 81.114189 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.129611 
iter  10 value 94.489245
iter  20 value 94.442320
iter  30 value 94.317231
iter  40 value 94.315306
iter  50 value 94.312705
iter  60 value 94.311753
final  value 94.311661 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.726808 
iter  10 value 94.489321
iter  20 value 94.484239
iter  30 value 94.421647
iter  40 value 88.579610
final  value 88.556653 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.426884 
iter  10 value 94.475129
iter  20 value 94.261678
iter  30 value 94.259560
iter  40 value 94.253769
iter  50 value 94.252270
final  value 94.252224 
converged
Fitting Repeat 2 

# weights:  507
initial  value 118.417522 
iter  10 value 94.492432
iter  20 value 94.466826
iter  30 value 88.509595
iter  40 value 84.163740
iter  50 value 83.941665
iter  60 value 83.877511
iter  70 value 83.865825
iter  80 value 82.585425
iter  90 value 82.495866
iter 100 value 82.464185
final  value 82.464185 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.032578 
iter  10 value 94.492184
iter  20 value 94.467445
iter  30 value 94.467136
final  value 94.467110 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.026425 
iter  10 value 94.475329
iter  20 value 94.467351
final  value 94.467074 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.133915 
iter  10 value 94.494509
iter  20 value 94.481681
iter  30 value 92.813019
iter  40 value 85.876015
iter  50 value 83.469302
final  value 83.273517 
converged
Fitting Repeat 1 

# weights:  305
initial  value 140.005833 
iter  10 value 117.895154
iter  20 value 117.843520
final  value 117.758783 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.498792 
iter  10 value 117.895055
iter  20 value 117.890310
iter  30 value 117.026106
iter  40 value 109.122634
iter  50 value 108.417063
iter  60 value 107.070492
iter  70 value 107.050854
iter  80 value 106.883710
iter  90 value 105.587004
iter 100 value 105.252303
final  value 105.252303 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 126.632469 
iter  10 value 117.895484
iter  20 value 117.890447
final  value 117.890424 
converged
Fitting Repeat 4 

# weights:  305
initial  value 124.271699 
iter  10 value 110.924787
iter  20 value 110.083162
iter  30 value 110.037847
iter  40 value 110.036248
iter  50 value 108.772364
iter  60 value 108.150917
iter  70 value 108.129762
iter  80 value 108.127852
final  value 108.126649 
converged
Fitting Repeat 5 

# weights:  305
initial  value 178.156941 
iter  10 value 117.916144
iter  20 value 117.909466
iter  30 value 112.405353
iter  40 value 106.806311
iter  50 value 106.664071
iter  60 value 106.661524
iter  70 value 106.459494
iter  80 value 106.433386
iter  90 value 106.430416
final  value 106.423358 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri Aug  1 10:35:49 2025 
*********************************************** 
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 
 52.753   1.288 117.456 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod37.465 0.21537.781
FreqInteractors0.2850.0240.316
calculateAAC0.0490.0000.049
calculateAutocor0.6920.0280.723
calculateCTDC0.0930.0040.098
calculateCTDD0.8270.0000.830
calculateCTDT0.2680.0040.273
calculateCTriad0.4760.0040.481
calculateDC0.1320.0000.132
calculateF0.4570.0000.459
calculateKSAAP0.1410.0040.145
calculateQD_Sm2.3080.0122.325
calculateTC2.4500.0402.494
calculateTC_Sm0.3320.0000.334
corr_plot37.421 0.37137.862
enrichfindP 0.495 0.03620.462
enrichfind_hp0.0830.0041.397
enrichplot0.5460.0920.639
filter_missing_values0.0010.0000.002
getFASTA0.0710.0125.411
getHPI0.0010.0000.000
get_negativePPI0.0000.0030.002
get_positivePPI000
impute_missing_data0.0010.0000.002
plotPPI0.0870.0040.092
pred_ensembel17.828 0.72617.364
var_imp38.973 0.37139.425