Back to Multiple platform build/check report for BioC 3.21:   simplified   long
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This page was generated on 2025-01-21 11:43 -0500 (Tue, 21 Jan 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.1 LTS)x86_64R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences" 4777
palomino7Windows Server 2022 Datacenterx64R Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences" 4502
lconwaymacOS 12.7.1 Montereyx86_64R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" 4467
kjohnson3macOS 13.7.1 Venturaarm64R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" 4422
kunpeng2Linux (openEuler 22.03 LTS-SP1)aarch64R Under development (unstable) (2024-11-24 r87369) -- "Unsuffered Consequences" 4406
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 977/2286HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
HPiP 1.13.0  (landing page)
Matineh Rahmatbakhsh
Snapshot Date: 2025-01-20 13:40 -0500 (Mon, 20 Jan 2025)
git_url: https://git.bioconductor.org/packages/HPiP
git_branch: devel
git_last_commit: 65e718f
git_last_commit_date: 2024-10-29 11:04:11 -0500 (Tue, 29 Oct 2024)
nebbiolo1Linux (Ubuntu 24.04.1 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
lconwaymacOS 12.7.1 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson3macOS 13.7.1 Ventura / arm64  OK    OK    OK    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 22.03 LTS-SP1) / aarch64  OK    OK    OK  


CHECK results for HPiP on lconway

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: 1.13.0
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.13.0.tar.gz
StartedAt: 2025-01-20 21:20:01 -0500 (Mon, 20 Jan 2025)
EndedAt: 2025-01-20 21:25:56 -0500 (Mon, 20 Jan 2025)
EllapsedTime: 354.7 seconds
RetCode: 0
Status:   OK  
CheckDir: HPiP.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2024-11-20 r87352)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.13.0’
* 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 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       35.320  1.684  37.404
corr_plot     33.951  1.577  35.772
FSmethod      33.858  1.576  35.764
pred_ensembel 14.111  0.442  12.646
enrichfindP    0.462  0.058   8.568
* 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
  ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.


Installation output

HPiP.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** 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) (2024-11-20 r87352) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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 98.491231 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.300721 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.296347 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.713976 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.020814 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.933208 
final  value 94.164201 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.829343 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.886147 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.664524 
iter  10 value 94.397515
iter  20 value 94.312581
final  value 94.312039 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.101137 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.876622 
iter  10 value 94.164207
final  value 94.164201 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.500458 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.678040 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.259283 
final  value 94.164201 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.581493 
iter  10 value 94.115458
final  value 94.112570 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.194202 
iter  10 value 94.638102
iter  20 value 93.352249
iter  30 value 86.209139
iter  40 value 85.895465
iter  50 value 85.875973
iter  60 value 83.827528
iter  70 value 81.234356
iter  80 value 80.391968
iter  90 value 80.325856
iter 100 value 80.273674
final  value 80.273674 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.393526 
iter  10 value 93.368084
iter  20 value 82.735196
iter  30 value 82.395073
iter  40 value 80.656344
iter  50 value 80.259016
iter  60 value 79.898104
iter  70 value 79.768393
iter  80 value 79.690000
final  value 79.689893 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.379296 
iter  10 value 94.342797
iter  20 value 90.345494
iter  30 value 86.030252
iter  40 value 85.878483
iter  50 value 83.594662
iter  60 value 82.976569
iter  70 value 82.967509
final  value 82.966208 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.164003 
iter  10 value 94.472838
iter  20 value 94.197072
iter  30 value 91.731992
iter  40 value 86.549016
iter  50 value 83.234731
iter  60 value 83.102129
iter  70 value 83.001516
iter  80 value 82.966222
final  value 82.966208 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.552481 
iter  10 value 94.520457
iter  20 value 94.107598
iter  30 value 89.723845
iter  40 value 85.781934
iter  50 value 83.005470
iter  60 value 82.409342
iter  70 value 82.379140
iter  80 value 82.367565
final  value 82.367558 
converged
Fitting Repeat 1 

# weights:  305
initial  value 135.609453 
iter  10 value 94.442458
iter  20 value 92.397619
iter  30 value 87.526907
iter  40 value 86.561297
iter  50 value 84.763959
iter  60 value 81.463698
iter  70 value 79.241338
iter  80 value 78.309863
iter  90 value 77.935129
iter 100 value 77.907915
final  value 77.907915 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.750957 
iter  10 value 94.760582
iter  20 value 93.507835
iter  30 value 91.048591
iter  40 value 89.797828
iter  50 value 84.937370
iter  60 value 80.329356
iter  70 value 79.746344
iter  80 value 78.980912
iter  90 value 78.269348
iter 100 value 78.126372
final  value 78.126372 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.657202 
iter  10 value 94.101867
iter  20 value 87.731228
iter  30 value 84.536830
iter  40 value 84.123847
iter  50 value 83.817208
iter  60 value 81.546422
iter  70 value 79.921565
iter  80 value 79.603411
iter  90 value 78.265525
iter 100 value 77.924292
final  value 77.924292 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.503993 
iter  10 value 86.600158
iter  20 value 85.921112
iter  30 value 84.419461
iter  40 value 82.869728
iter  50 value 81.479163
iter  60 value 81.258208
iter  70 value 80.681741
iter  80 value 80.429795
iter  90 value 80.283255
iter 100 value 80.092763
final  value 80.092763 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.238211 
iter  10 value 93.946743
iter  20 value 82.569112
iter  30 value 82.077396
iter  40 value 81.888753
iter  50 value 79.534247
iter  60 value 79.284887
iter  70 value 78.404143
iter  80 value 78.042081
iter  90 value 77.889136
iter 100 value 77.740930
final  value 77.740930 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.306604 
iter  10 value 91.057582
iter  20 value 85.295441
iter  30 value 83.146680
iter  40 value 82.791442
iter  50 value 81.877415
iter  60 value 80.251780
iter  70 value 79.336249
iter  80 value 78.618526
iter  90 value 78.542516
iter 100 value 78.379298
final  value 78.379298 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.596543 
iter  10 value 94.734567
iter  20 value 94.579877
iter  30 value 94.139787
iter  40 value 83.317562
iter  50 value 82.075313
iter  60 value 81.509707
iter  70 value 80.039130
iter  80 value 79.866074
iter  90 value 79.789647
iter 100 value 79.346638
final  value 79.346638 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.371094 
iter  10 value 95.683507
iter  20 value 94.150813
iter  30 value 88.667471
iter  40 value 86.148386
iter  50 value 84.454331
iter  60 value 83.600356
iter  70 value 81.022573
iter  80 value 79.908936
iter  90 value 79.249091
iter 100 value 78.526961
final  value 78.526961 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.348896 
iter  10 value 95.055704
iter  20 value 85.589500
iter  30 value 85.366998
iter  40 value 83.084911
iter  50 value 81.197099
iter  60 value 80.818801
iter  70 value 79.201674
iter  80 value 78.943771
iter  90 value 78.482286
iter 100 value 77.942594
final  value 77.942594 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.603723 
iter  10 value 96.023337
iter  20 value 94.549888
iter  30 value 93.397734
iter  40 value 85.406531
iter  50 value 84.474380
iter  60 value 84.098273
iter  70 value 83.602092
iter  80 value 81.890080
iter  90 value 80.357426
iter 100 value 80.126717
final  value 80.126717 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.196696 
final  value 94.485855 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.776131 
final  value 94.485847 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.886764 
final  value 94.485601 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.088189 
final  value 94.485952 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.913582 
final  value 94.485706 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.014388 
iter  10 value 94.313220
iter  20 value 86.140683
iter  30 value 83.725644
iter  40 value 83.621791
iter  50 value 83.612360
iter  60 value 83.610914
iter  70 value 83.607521
final  value 83.607009 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.599377 
iter  10 value 94.359287
iter  20 value 93.635836
iter  30 value 92.857010
iter  40 value 92.856013
iter  50 value 92.855924
final  value 92.855911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.257572 
iter  10 value 94.359761
iter  20 value 94.354678
final  value 94.354619 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.176259 
iter  10 value 94.359322
iter  20 value 94.056895
iter  30 value 87.737034
iter  40 value 87.712626
iter  50 value 84.380187
iter  60 value 83.648446
iter  70 value 83.633416
iter  80 value 83.632719
iter  90 value 83.619828
iter 100 value 83.613772
final  value 83.613772 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.801315 
iter  10 value 94.359027
iter  20 value 92.996026
iter  30 value 85.364149
iter  40 value 85.360912
iter  50 value 85.360755
iter  60 value 85.360262
iter  70 value 85.359879
iter  80 value 85.070181
iter  90 value 84.887390
iter 100 value 84.886391
final  value 84.886391 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.165500 
iter  10 value 94.320342
iter  20 value 94.289126
final  value 94.113833 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.712562 
iter  10 value 94.492262
iter  20 value 86.253830
iter  30 value 84.040866
iter  40 value 84.017905
iter  50 value 84.015950
iter  60 value 83.987691
iter  70 value 83.172944
iter  80 value 83.167750
iter  90 value 82.896734
iter 100 value 82.080281
final  value 82.080281 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.832654 
iter  10 value 94.362600
iter  20 value 94.110931
iter  30 value 83.278257
iter  40 value 80.475672
iter  50 value 77.898904
iter  60 value 75.648519
iter  70 value 75.421567
final  value 75.408335 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.604551 
iter  10 value 94.492387
iter  20 value 94.344748
iter  30 value 94.032667
iter  40 value 84.554934
iter  50 value 83.737575
iter  60 value 83.736662
iter  70 value 83.734018
iter  80 value 83.733083
iter  90 value 82.286799
iter 100 value 80.396150
final  value 80.396150 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.060512 
iter  10 value 94.171361
iter  20 value 94.117350
iter  30 value 94.110850
iter  40 value 92.402274
iter  50 value 86.964299
iter  60 value 86.961314
iter  70 value 84.579555
iter  80 value 84.558329
iter  90 value 84.557732
iter  90 value 84.557732
final  value 84.557732 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.173027 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.833561 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.595724 
iter  10 value 94.026550
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.712433 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.252095 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.955657 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.273023 
iter  10 value 86.843485
iter  20 value 83.712496
iter  30 value 82.894056
iter  40 value 82.496644
iter  50 value 82.495295
final  value 82.495275 
converged
Fitting Repeat 3 

# weights:  305
initial  value 120.264134 
final  value 94.020991 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.697219 
iter  10 value 94.484214
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.894183 
iter  10 value 93.320244
final  value 93.320225 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.373364 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.577914 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.460062 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.238634 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.455218 
iter  10 value 93.550186
final  value 93.264982 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.135752 
iter  10 value 94.240929
iter  20 value 93.299884
iter  30 value 89.935766
iter  40 value 84.745002
iter  50 value 83.878014
iter  60 value 83.403634
iter  70 value 83.102608
iter  80 value 82.894176
iter  80 value 82.894175
iter  80 value 82.894175
final  value 82.894175 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.292720 
iter  10 value 94.480835
iter  20 value 85.347638
iter  30 value 84.793224
iter  40 value 84.052142
iter  50 value 83.857861
iter  60 value 83.705762
iter  70 value 83.657528
iter  80 value 83.619415
iter  90 value 83.614022
final  value 83.613974 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.271977 
iter  10 value 86.700980
iter  20 value 83.814052
iter  30 value 83.670392
iter  40 value 83.620741
iter  50 value 83.614027
final  value 83.613977 
converged
Fitting Repeat 4 

# weights:  103
initial  value 117.861739 
iter  10 value 94.427166
iter  20 value 91.788880
iter  30 value 87.141136
iter  40 value 86.732952
iter  50 value 86.088306
iter  60 value 85.308800
iter  70 value 83.313457
iter  80 value 82.904857
iter  90 value 82.897072
iter 100 value 82.894336
final  value 82.894336 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 112.192927 
iter  10 value 94.394857
iter  20 value 90.170200
iter  30 value 84.648730
iter  40 value 83.057665
iter  50 value 82.892350
iter  60 value 82.761870
iter  70 value 81.937190
iter  80 value 81.154934
iter  90 value 81.089015
iter 100 value 81.073505
final  value 81.073505 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 135.564661 
iter  10 value 94.573902
iter  20 value 93.514890
iter  30 value 92.549338
iter  40 value 88.537364
iter  50 value 85.830649
iter  60 value 83.137327
iter  70 value 82.247355
iter  80 value 81.837181
iter  90 value 81.651740
iter 100 value 81.258436
final  value 81.258436 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.297012 
iter  10 value 94.054251
iter  20 value 91.319988
iter  30 value 88.763219
iter  40 value 87.956524
iter  50 value 85.923993
iter  60 value 83.890704
iter  70 value 82.705795
iter  80 value 81.399750
iter  90 value 80.736460
iter 100 value 80.422459
final  value 80.422459 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.449288 
iter  10 value 94.635268
iter  20 value 94.460120
iter  30 value 92.967961
iter  40 value 91.446533
iter  50 value 84.395537
iter  60 value 83.279833
iter  70 value 82.626797
iter  80 value 81.728265
iter  90 value 80.622930
iter 100 value 79.886651
final  value 79.886651 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.885336 
iter  10 value 94.409512
iter  20 value 92.472705
iter  30 value 85.457992
iter  40 value 83.475661
iter  50 value 83.389608
iter  60 value 83.205019
iter  70 value 82.439668
iter  80 value 80.340340
iter  90 value 79.880340
iter 100 value 79.739282
final  value 79.739282 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.565802 
iter  10 value 94.481281
iter  20 value 90.929161
iter  30 value 87.527158
iter  40 value 83.864811
iter  50 value 83.547726
iter  60 value 82.345318
iter  70 value 81.810913
iter  80 value 81.373305
iter  90 value 81.181591
iter 100 value 81.170623
final  value 81.170623 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.458807 
iter  10 value 95.138211
iter  20 value 93.960152
iter  30 value 91.608226
iter  40 value 85.057917
iter  50 value 83.654478
iter  60 value 82.437766
iter  70 value 81.614910
iter  80 value 80.607724
iter  90 value 80.347267
iter 100 value 80.022229
final  value 80.022229 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.018677 
iter  10 value 95.679557
iter  20 value 93.093735
iter  30 value 87.118309
iter  40 value 85.853200
iter  50 value 85.466402
iter  60 value 85.141106
iter  70 value 83.825670
iter  80 value 81.534426
iter  90 value 80.741253
iter 100 value 80.412215
final  value 80.412215 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.615945 
iter  10 value 95.113794
iter  20 value 94.206844
iter  30 value 93.570017
iter  40 value 87.175283
iter  50 value 84.688927
iter  60 value 82.272805
iter  70 value 81.218340
iter  80 value 80.375361
iter  90 value 80.130082
iter 100 value 79.865829
final  value 79.865829 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.330769 
iter  10 value 94.852381
iter  20 value 94.553615
iter  30 value 94.501079
iter  40 value 89.743016
iter  50 value 84.112480
iter  60 value 83.582594
iter  70 value 83.434512
iter  80 value 83.220238
iter  90 value 83.036203
iter 100 value 81.561121
final  value 81.561121 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.044970 
iter  10 value 95.241424
iter  20 value 87.111129
iter  30 value 85.828135
iter  40 value 85.496603
iter  50 value 82.651871
iter  60 value 81.957250
iter  70 value 81.200565
iter  80 value 79.942410
iter  90 value 79.818277
iter 100 value 79.790378
final  value 79.790378 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.066503 
final  value 94.486086 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.868681 
final  value 94.486082 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.833229 
iter  10 value 94.485829
iter  20 value 94.484217
iter  30 value 84.199370
iter  40 value 83.999312
final  value 83.950406 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.277550 
iter  10 value 92.591871
iter  20 value 92.552548
iter  30 value 91.617655
iter  40 value 91.470132
iter  50 value 91.466327
iter  60 value 91.465956
final  value 91.465791 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.202996 
final  value 93.789647 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.342076 
iter  10 value 94.488969
iter  20 value 92.987971
iter  30 value 85.645502
iter  40 value 85.644002
final  value 85.643268 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.723748 
iter  10 value 94.509470
iter  20 value 94.489347
iter  30 value 93.331019
iter  40 value 93.322227
iter  50 value 93.289314
iter  60 value 84.311676
iter  70 value 81.306063
iter  80 value 80.207747
iter  90 value 79.948607
iter 100 value 79.781794
final  value 79.781794 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 128.235478 
iter  10 value 94.488628
iter  20 value 94.474737
final  value 94.027248 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.763422 
iter  10 value 94.489691
iter  20 value 94.484632
final  value 94.484433 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.247178 
iter  10 value 94.489341
iter  20 value 94.484234
iter  30 value 93.788262
final  value 93.788238 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.628529 
iter  10 value 93.742964
iter  20 value 93.718782
iter  30 value 93.281785
iter  40 value 93.280178
iter  50 value 89.404138
iter  60 value 82.437931
iter  70 value 81.766565
iter  80 value 79.315144
iter  90 value 79.005272
iter 100 value 78.995107
final  value 78.995107 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.107455 
iter  10 value 94.410276
iter  20 value 93.349072
iter  30 value 93.327701
iter  40 value 93.326627
final  value 93.321379 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.853449 
iter  10 value 88.107895
iter  20 value 88.030814
iter  30 value 87.677025
iter  40 value 87.547736
iter  50 value 87.545061
iter  60 value 85.605496
iter  70 value 80.941512
iter  80 value 79.468962
iter  90 value 79.193043
iter 100 value 79.046613
final  value 79.046613 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.904384 
iter  10 value 94.490940
iter  20 value 94.482725
iter  30 value 85.440098
iter  40 value 85.418461
iter  50 value 84.751725
iter  60 value 81.884244
iter  70 value 80.065526
iter  80 value 79.788413
iter  90 value 79.088963
iter 100 value 78.189869
final  value 78.189869 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.536988 
iter  10 value 92.434963
iter  20 value 92.400882
iter  30 value 92.390293
iter  40 value 83.423985
iter  50 value 83.339419
iter  60 value 83.338535
iter  70 value 83.276612
iter  80 value 82.646728
final  value 82.639933 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.320073 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.096668 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.686613 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.000578 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.738984 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.459995 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.578518 
iter  10 value 88.187873
final  value 87.609764 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.274585 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.484568 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.644649 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.656684 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.504522 
iter  10 value 94.017176
final  value 94.017114 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.027199 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.203795 
final  value 93.810010 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.381070 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.788490 
iter  10 value 94.064700
iter  20 value 94.007727
iter  30 value 92.876697
iter  40 value 89.519466
iter  50 value 88.814658
iter  60 value 85.494145
iter  70 value 84.930900
iter  80 value 84.755365
iter  90 value 84.729705
iter  90 value 84.729705
final  value 84.729705 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.670507 
iter  10 value 93.903585
iter  20 value 92.764066
iter  30 value 92.388857
iter  40 value 90.681708
iter  50 value 86.474602
iter  60 value 85.152688
iter  70 value 85.115357
iter  80 value 85.019749
iter  90 value 84.526056
iter 100 value 84.394135
final  value 84.394135 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.389262 
iter  10 value 94.077955
iter  20 value 93.024183
iter  30 value 88.158698
iter  40 value 87.395239
iter  50 value 87.118637
iter  60 value 85.533438
iter  70 value 84.877437
iter  80 value 84.227369
final  value 84.225265 
converged
Fitting Repeat 4 

# weights:  103
initial  value 129.291347 
iter  10 value 93.965616
iter  20 value 93.426222
iter  30 value 90.497099
iter  40 value 86.030223
iter  50 value 85.320454
iter  60 value 84.636870
iter  70 value 84.428018
final  value 84.425386 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.509522 
iter  10 value 94.058243
iter  20 value 89.172336
iter  30 value 87.268893
iter  40 value 86.472271
iter  50 value 86.020078
iter  60 value 85.538130
iter  70 value 85.154209
iter  80 value 84.983441
final  value 84.981528 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.459363 
iter  10 value 94.244604
iter  20 value 93.809234
iter  30 value 93.035308
iter  40 value 88.691583
iter  50 value 86.329998
iter  60 value 86.155926
iter  70 value 84.840732
iter  80 value 83.926158
iter  90 value 82.861522
iter 100 value 82.426752
final  value 82.426752 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.444869 
iter  10 value 93.997811
iter  20 value 86.934439
iter  30 value 86.679640
iter  40 value 86.320307
iter  50 value 85.018925
iter  60 value 82.913977
iter  70 value 82.199497
iter  80 value 82.020340
iter  90 value 81.690780
iter 100 value 81.654950
final  value 81.654950 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 128.698835 
iter  10 value 94.059119
iter  20 value 87.049516
iter  30 value 86.323128
iter  40 value 85.678324
iter  50 value 84.748099
iter  60 value 84.583799
iter  70 value 84.514033
iter  80 value 84.207193
iter  90 value 83.321883
iter 100 value 82.296719
final  value 82.296719 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.648991 
iter  10 value 95.114756
iter  20 value 92.437425
iter  30 value 88.502993
iter  40 value 86.134882
iter  50 value 85.327202
iter  60 value 82.654215
iter  70 value 82.182853
iter  80 value 82.051582
iter  90 value 81.944173
iter 100 value 81.812419
final  value 81.812419 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 124.397094 
iter  10 value 94.041048
iter  20 value 87.840956
iter  30 value 86.733196
iter  40 value 86.191034
iter  50 value 85.076125
iter  60 value 84.477007
iter  70 value 84.352019
iter  80 value 84.180288
iter  90 value 83.898795
iter 100 value 82.427194
final  value 82.427194 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.838392 
iter  10 value 95.031953
iter  20 value 94.177888
iter  30 value 86.380142
iter  40 value 84.311772
iter  50 value 82.515477
iter  60 value 81.914756
iter  70 value 81.745431
iter  80 value 81.608629
iter  90 value 81.549784
iter 100 value 81.492161
final  value 81.492161 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.105005 
iter  10 value 93.893216
iter  20 value 86.885750
iter  30 value 85.087409
iter  40 value 84.961895
iter  50 value 84.508900
iter  60 value 83.601850
iter  70 value 83.304005
iter  80 value 83.242158
iter  90 value 82.487265
iter 100 value 81.811660
final  value 81.811660 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.100480 
iter  10 value 93.047395
iter  20 value 88.111599
iter  30 value 87.391624
iter  40 value 84.958308
iter  50 value 82.425549
iter  60 value 81.511210
iter  70 value 81.385813
iter  80 value 81.338563
iter  90 value 81.228720
iter 100 value 80.976935
final  value 80.976935 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.590721 
iter  10 value 94.010514
iter  20 value 92.207031
iter  30 value 91.173782
iter  40 value 88.023200
iter  50 value 85.764707
iter  60 value 83.636088
iter  70 value 82.047251
iter  80 value 81.634601
iter  90 value 81.428115
iter 100 value 81.276400
final  value 81.276400 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.100955 
iter  10 value 93.902443
iter  20 value 93.147973
iter  30 value 91.393834
iter  40 value 90.867246
iter  50 value 86.490968
iter  60 value 85.193392
iter  70 value 83.563772
iter  80 value 82.235925
iter  90 value 81.940167
iter 100 value 81.618283
final  value 81.618283 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.105221 
iter  10 value 94.054788
final  value 94.052931 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.090414 
final  value 94.054588 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.961623 
final  value 94.043859 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.861422 
iter  10 value 93.840076
iter  20 value 93.837680
iter  30 value 93.786436
final  value 93.786221 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.202533 
final  value 94.054513 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.195905 
iter  10 value 94.057484
iter  20 value 93.869388
iter  30 value 88.462112
iter  40 value 88.069167
iter  50 value 88.053241
iter  60 value 87.877338
iter  70 value 87.056305
iter  80 value 86.446370
iter  90 value 85.545420
iter 100 value 85.393372
final  value 85.393372 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.186244 
iter  10 value 94.057475
iter  20 value 94.018925
final  value 93.836363 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.888695 
iter  10 value 94.057714
iter  20 value 94.053002
final  value 94.052918 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.912239 
iter  10 value 93.921049
iter  20 value 93.483208
iter  30 value 93.448072
iter  40 value 93.440621
iter  50 value 87.879870
iter  60 value 85.579431
iter  70 value 85.287393
iter  80 value 85.284473
final  value 85.284453 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.016375 
iter  10 value 94.058572
iter  20 value 93.869847
iter  30 value 87.133068
iter  40 value 86.415167
iter  50 value 86.403258
iter  60 value 86.396045
iter  70 value 84.997870
iter  80 value 83.291530
iter  90 value 83.191404
iter 100 value 83.190502
final  value 83.190502 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.861046 
iter  10 value 94.060546
iter  20 value 93.987059
iter  30 value 87.959431
iter  40 value 86.835840
iter  50 value 86.829934
final  value 86.829806 
converged
Fitting Repeat 2 

# weights:  507
initial  value 125.293033 
iter  10 value 89.290208
iter  20 value 85.217734
iter  30 value 84.393237
iter  40 value 83.983626
iter  50 value 83.977447
iter  60 value 83.971827
final  value 83.971779 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.102542 
iter  10 value 94.061712
iter  20 value 92.634343
iter  30 value 86.258222
iter  40 value 86.247736
iter  50 value 86.247644
iter  60 value 86.208489
iter  70 value 85.419570
iter  80 value 84.587571
iter  90 value 84.488325
iter 100 value 84.164975
final  value 84.164975 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.127607 
iter  10 value 88.131914
iter  20 value 87.260610
iter  30 value 86.745408
iter  40 value 85.578774
final  value 85.500189 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.944774 
iter  10 value 94.060790
iter  20 value 94.052965
iter  30 value 85.757675
iter  40 value 85.538852
iter  40 value 85.538852
final  value 85.538852 
converged
Fitting Repeat 1 

# weights:  103
initial  value 110.279264 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.865184 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.611218 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.884710 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.663133 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.420406 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.478859 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.659744 
final  value 93.991525 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.314581 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.815986 
iter  10 value 89.483489
iter  20 value 85.665756
iter  30 value 85.491483
iter  40 value 84.686715
iter  50 value 84.357864
final  value 84.350220 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.286129 
final  value 93.967787 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.157209 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.789173 
iter  10 value 84.249599
iter  20 value 84.150174
final  value 84.150007 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.668131 
iter  10 value 93.177687
iter  20 value 87.487056
iter  30 value 84.131782
iter  40 value 83.951985
iter  50 value 83.950932
final  value 83.950858 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.443460 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.320493 
iter  10 value 94.035575
iter  20 value 93.797296
iter  30 value 89.837052
iter  40 value 87.440778
iter  50 value 87.260463
iter  60 value 86.855250
iter  70 value 85.915521
iter  80 value 85.490192
final  value 85.488696 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.609307 
iter  10 value 94.057027
iter  20 value 87.312008
iter  30 value 86.766394
iter  40 value 84.896619
iter  50 value 83.135413
iter  60 value 82.624621
iter  70 value 82.363066
iter  80 value 82.317351
iter  90 value 82.249719
iter 100 value 82.200080
final  value 82.200080 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.371045 
iter  10 value 90.417863
iter  20 value 86.706073
iter  30 value 86.563966
iter  40 value 86.337244
iter  50 value 85.718244
iter  60 value 84.846173
iter  70 value 84.788694
iter  80 value 84.703470
iter  90 value 84.542433
iter 100 value 84.517675
final  value 84.517675 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.254037 
iter  10 value 94.118997
iter  20 value 93.977129
iter  30 value 93.577757
iter  40 value 87.154051
iter  50 value 85.481607
iter  60 value 85.185898
iter  70 value 84.976402
iter  80 value 84.912708
iter  90 value 84.865899
final  value 84.864880 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.900783 
iter  10 value 94.056681
iter  20 value 93.860389
iter  30 value 93.825099
iter  40 value 93.821610
iter  50 value 93.793794
iter  60 value 87.191208
iter  70 value 86.715512
iter  80 value 85.186435
iter  90 value 84.996533
iter 100 value 84.902486
final  value 84.902486 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.157366 
iter  10 value 94.039919
iter  20 value 93.620190
iter  30 value 86.420532
iter  40 value 83.302463
iter  50 value 82.259658
iter  60 value 81.481119
iter  70 value 81.392729
iter  80 value 81.366832
iter  90 value 81.339786
iter 100 value 81.296302
final  value 81.296302 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.015088 
iter  10 value 94.054851
iter  20 value 93.840054
iter  30 value 90.603702
iter  40 value 88.099695
iter  50 value 86.065073
iter  60 value 85.588914
iter  70 value 85.396772
iter  80 value 85.284879
iter  90 value 84.883805
iter 100 value 83.367158
final  value 83.367158 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.118499 
iter  10 value 94.518216
iter  20 value 93.844046
iter  30 value 92.389115
iter  40 value 85.511243
iter  50 value 83.987064
iter  60 value 82.834570
iter  70 value 82.000463
iter  80 value 81.564325
iter  90 value 81.296506
iter 100 value 81.180105
final  value 81.180105 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.753898 
iter  10 value 94.271436
iter  20 value 90.615922
iter  30 value 84.900339
iter  40 value 83.402645
iter  50 value 82.555061
iter  60 value 82.144697
iter  70 value 82.142238
iter  80 value 82.110330
iter  90 value 81.646805
iter 100 value 81.384796
final  value 81.384796 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.851597 
iter  10 value 93.976302
iter  20 value 90.125146
iter  30 value 87.257143
iter  40 value 85.054680
iter  50 value 82.682352
iter  60 value 82.008301
iter  70 value 81.723284
iter  80 value 81.486189
iter  90 value 81.439599
iter 100 value 81.382547
final  value 81.382547 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.005774 
iter  10 value 94.094912
iter  20 value 93.075767
iter  30 value 85.579575
iter  40 value 84.319948
iter  50 value 83.634997
iter  60 value 82.248601
iter  70 value 81.826033
iter  80 value 81.754975
iter  90 value 81.688010
iter 100 value 81.612659
final  value 81.612659 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.274855 
iter  10 value 93.883588
iter  20 value 88.153194
iter  30 value 85.569834
iter  40 value 84.659661
iter  50 value 83.278821
iter  60 value 82.280505
iter  70 value 82.062730
iter  80 value 81.951030
iter  90 value 81.762266
iter 100 value 81.482279
final  value 81.482279 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.514988 
iter  10 value 95.235317
iter  20 value 91.618432
iter  30 value 88.303810
iter  40 value 88.017334
iter  50 value 85.591731
iter  60 value 81.292558
iter  70 value 81.013301
iter  80 value 80.955803
iter  90 value 80.825982
iter 100 value 80.755780
final  value 80.755780 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 137.060741 
iter  10 value 94.485879
iter  20 value 88.576069
iter  30 value 86.458319
iter  40 value 85.967177
iter  50 value 85.097996
iter  60 value 84.863231
iter  70 value 84.732344
iter  80 value 83.567908
iter  90 value 82.002429
iter 100 value 81.354621
final  value 81.354621 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.506824 
iter  10 value 94.693441
iter  20 value 94.087678
iter  30 value 93.967776
iter  40 value 88.605369
iter  50 value 86.855233
iter  60 value 83.954322
iter  70 value 83.179058
iter  80 value 82.964935
iter  90 value 82.854060
iter 100 value 82.595633
final  value 82.595633 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.066303 
final  value 94.054340 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.361110 
final  value 93.970777 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.008663 
final  value 94.054517 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.026702 
final  value 94.054598 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.440690 
final  value 94.054558 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.742412 
iter  10 value 94.038008
iter  20 value 93.880514
iter  30 value 90.083572
iter  40 value 90.081114
iter  40 value 90.081114
final  value 90.081102 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.434503 
iter  10 value 94.057502
iter  20 value 94.053089
iter  30 value 88.509306
iter  40 value 86.013401
iter  50 value 85.553062
iter  60 value 82.745034
iter  70 value 82.217512
iter  80 value 82.201859
iter  90 value 81.961523
final  value 81.879571 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.527564 
iter  10 value 94.057664
iter  20 value 94.008481
iter  30 value 87.484024
iter  40 value 87.371860
final  value 87.365001 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.160168 
iter  10 value 94.038487
iter  20 value 93.575293
iter  30 value 88.164775
iter  40 value 88.155081
iter  50 value 88.154134
final  value 88.154061 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.597857 
iter  10 value 94.057728
iter  20 value 94.052963
iter  30 value 94.032444
iter  40 value 92.942029
iter  50 value 92.744425
iter  60 value 88.729988
iter  70 value 88.153865
iter  80 value 88.098069
iter  90 value 88.066057
iter 100 value 88.057317
final  value 88.057317 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.900340 
iter  10 value 94.061346
iter  20 value 93.971810
iter  30 value 85.792928
iter  40 value 85.429884
iter  50 value 85.428191
final  value 85.427477 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.822152 
iter  10 value 94.061108
iter  20 value 93.986923
iter  30 value 93.792624
iter  40 value 93.695754
iter  50 value 92.903218
iter  60 value 88.782669
iter  70 value 86.837521
iter  80 value 81.740878
iter  90 value 81.028620
iter 100 value 80.546666
final  value 80.546666 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.000094 
iter  10 value 94.041451
iter  20 value 94.037402
iter  30 value 94.037095
final  value 94.037069 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.737059 
iter  10 value 94.041331
iter  20 value 93.973583
iter  30 value 89.016645
iter  40 value 85.825022
iter  50 value 85.822614
iter  60 value 85.660550
iter  70 value 85.659846
iter  80 value 85.657529
iter  90 value 85.578566
final  value 85.578466 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.531732 
iter  10 value 93.975951
iter  20 value 93.969538
iter  30 value 93.790691
iter  40 value 93.789709
final  value 93.789606 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.106006 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.691537 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.058860 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.769012 
iter  10 value 93.268391
iter  20 value 92.897403
iter  30 value 92.896665
final  value 92.896662 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.438284 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.940751 
iter  10 value 92.340453
iter  20 value 92.300909
final  value 92.300753 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.442091 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.833938 
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.162399 
final  value 94.473118 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.020734 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.736567 
iter  10 value 93.787953
final  value 93.783550 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.397713 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.745171 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.351912 
final  value 94.473118 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.082032 
final  value 94.473118 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.688402 
iter  10 value 94.413317
iter  20 value 90.862857
iter  30 value 89.202420
iter  40 value 87.332441
iter  50 value 84.682907
iter  60 value 83.918068
iter  70 value 82.554657
iter  80 value 82.265298
iter  90 value 81.805087
iter 100 value 81.396972
final  value 81.396972 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.520146 
iter  10 value 93.082157
iter  20 value 84.859280
iter  30 value 83.683703
iter  40 value 83.441025
iter  50 value 83.418286
final  value 83.418269 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.431140 
iter  10 value 94.487854
iter  20 value 94.486973
iter  30 value 94.221355
iter  40 value 93.573623
iter  50 value 92.041620
iter  60 value 90.822297
iter  70 value 90.731307
iter  80 value 90.668354
final  value 90.668036 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.544190 
iter  10 value 94.486600
iter  20 value 93.474531
iter  30 value 86.334181
iter  40 value 84.727852
iter  50 value 84.246172
iter  60 value 84.152379
iter  70 value 83.962157
iter  80 value 83.858021
final  value 83.856356 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.227752 
iter  10 value 94.245059
iter  20 value 86.504505
iter  30 value 85.965122
iter  40 value 85.741840
iter  50 value 85.068699
iter  60 value 82.682380
iter  70 value 81.373895
iter  80 value 81.309517
final  value 81.309449 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.899064 
iter  10 value 94.634261
iter  20 value 94.499335
iter  30 value 93.310498
iter  40 value 91.847827
iter  50 value 85.938504
iter  60 value 85.285185
iter  70 value 82.707238
iter  80 value 81.172230
iter  90 value 80.768939
iter 100 value 80.577018
final  value 80.577018 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.275547 
iter  10 value 94.492140
iter  20 value 92.912236
iter  30 value 86.761833
iter  40 value 84.808174
iter  50 value 83.816882
iter  60 value 83.593353
iter  70 value 82.692331
iter  80 value 81.066663
iter  90 value 80.892747
iter 100 value 80.642593
final  value 80.642593 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.800369 
iter  10 value 94.153199
iter  20 value 89.310346
iter  30 value 86.402150
iter  40 value 85.545321
iter  50 value 83.655607
iter  60 value 81.666408
iter  70 value 81.406197
iter  80 value 81.152469
iter  90 value 81.119407
iter 100 value 81.106389
final  value 81.106389 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.556878 
iter  10 value 99.910014
iter  20 value 89.987563
iter  30 value 85.041476
iter  40 value 84.908005
iter  50 value 82.910275
iter  60 value 81.926565
iter  70 value 81.018623
iter  80 value 80.476801
iter  90 value 80.306281
iter 100 value 80.186821
final  value 80.186821 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.038391 
iter  10 value 95.082498
iter  20 value 89.631260
iter  30 value 86.417463
iter  40 value 84.222119
iter  50 value 83.381966
iter  60 value 82.585393
iter  70 value 82.319368
iter  80 value 82.030056
iter  90 value 80.848435
iter 100 value 79.932589
final  value 79.932589 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.412453 
iter  10 value 91.777514
iter  20 value 87.719790
iter  30 value 85.805721
iter  40 value 84.238472
iter  50 value 82.385023
iter  60 value 81.720717
iter  70 value 80.970325
iter  80 value 80.387290
iter  90 value 79.795496
iter 100 value 79.537393
final  value 79.537393 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.003581 
iter  10 value 94.914522
iter  20 value 94.315922
iter  30 value 89.110791
iter  40 value 85.117556
iter  50 value 84.299185
iter  60 value 83.689055
iter  70 value 83.000626
iter  80 value 82.364450
iter  90 value 80.971119
iter 100 value 80.615607
final  value 80.615607 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.199268 
iter  10 value 96.050247
iter  20 value 93.602311
iter  30 value 86.534330
iter  40 value 86.211932
iter  50 value 85.234160
iter  60 value 83.344614
iter  70 value 82.264595
iter  80 value 81.526285
iter  90 value 80.948076
iter 100 value 80.393935
final  value 80.393935 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.697569 
iter  10 value 94.948866
iter  20 value 94.724093
iter  30 value 87.635442
iter  40 value 84.865674
iter  50 value 84.606913
iter  60 value 83.899957
iter  70 value 82.388124
iter  80 value 81.735700
iter  90 value 81.267815
iter 100 value 81.024110
final  value 81.024110 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.782887 
iter  10 value 94.723310
iter  20 value 94.217572
iter  30 value 93.645487
iter  40 value 85.782216
iter  50 value 84.704914
iter  60 value 84.378367
iter  70 value 83.442313
iter  80 value 82.329351
iter  90 value 82.002008
iter 100 value 81.919803
final  value 81.919803 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.811483 
final  value 94.485664 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.527310 
final  value 94.485833 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.385368 
final  value 94.485961 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.941247 
iter  10 value 94.474567
iter  10 value 94.474566
iter  10 value 94.474566
final  value 94.474566 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.713536 
iter  10 value 94.485752
iter  20 value 94.484222
iter  30 value 91.676156
iter  40 value 85.880340
iter  50 value 85.877161
iter  60 value 85.876805
iter  60 value 85.876805
iter  70 value 85.631477
iter  80 value 85.630133
final  value 85.630131 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.095728 
iter  10 value 94.478432
iter  20 value 93.879569
iter  30 value 93.787638
iter  40 value 93.767998
iter  50 value 93.683011
iter  60 value 92.680619
iter  70 value 90.675735
iter  80 value 89.736642
iter  90 value 88.300729
iter 100 value 83.360214
final  value 83.360214 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.698674 
iter  10 value 94.478308
iter  20 value 94.474342
iter  30 value 89.490005
iter  40 value 87.268308
iter  50 value 87.266805
iter  60 value 87.137783
iter  70 value 87.119137
iter  80 value 87.117525
iter  90 value 87.117399
final  value 87.117372 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.331531 
iter  10 value 94.477771
iter  20 value 94.171114
iter  30 value 93.900552
final  value 93.819110 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.599100 
iter  10 value 94.489222
iter  20 value 92.917942
iter  30 value 84.761063
iter  40 value 84.304732
iter  50 value 84.081704
iter  60 value 83.881306
iter  70 value 83.877351
iter  80 value 83.678651
iter  90 value 83.404508
iter 100 value 83.235341
final  value 83.235341 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.964437 
iter  10 value 94.489078
iter  20 value 94.245746
iter  30 value 89.810450
iter  40 value 89.541997
iter  50 value 89.057555
iter  60 value 89.051614
iter  70 value 89.051340
final  value 89.050711 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.189120 
iter  10 value 89.025513
iter  20 value 87.340543
iter  30 value 87.329236
iter  40 value 84.288255
iter  50 value 83.905490
iter  60 value 83.619241
iter  70 value 83.283438
iter  80 value 83.187509
iter  90 value 83.185607
iter 100 value 82.342840
final  value 82.342840 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.557686 
iter  10 value 94.492478
iter  20 value 94.476388
final  value 94.473376 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.982434 
iter  10 value 94.274568
iter  20 value 93.942162
iter  30 value 91.388582
iter  40 value 84.232991
iter  50 value 84.230018
iter  60 value 84.226840
iter  70 value 84.208269
iter  80 value 83.975220
iter  90 value 83.661935
iter 100 value 80.807675
final  value 80.807675 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.889176 
iter  10 value 88.381649
iter  20 value 87.275105
iter  30 value 87.269783
iter  40 value 87.268982
iter  50 value 87.268452
iter  60 value 87.265714
final  value 87.265672 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.560542 
iter  10 value 94.478026
iter  20 value 94.064590
iter  30 value 94.053890
iter  40 value 93.873014
iter  50 value 93.859237
iter  60 value 93.266724
iter  70 value 93.260466
iter  80 value 93.256697
iter  90 value 91.758375
iter 100 value 84.277467
final  value 84.277467 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 158.356706 
iter  10 value 117.767380
iter  20 value 117.642156
iter  30 value 107.660073
iter  40 value 107.119594
iter  50 value 107.087874
iter  60 value 107.085213
iter  70 value 107.084202
final  value 107.084096 
converged
Fitting Repeat 2 

# weights:  507
initial  value 141.307850 
iter  10 value 117.898158
iter  20 value 116.950923
iter  30 value 105.989956
iter  40 value 104.908330
iter  50 value 104.907328
iter  50 value 104.907328
iter  50 value 104.907328
final  value 104.907328 
converged
Fitting Repeat 3 

# weights:  507
initial  value 121.530001 
iter  10 value 117.899597
iter  20 value 117.751958
iter  30 value 116.858213
iter  40 value 107.123926
iter  50 value 107.006532
iter  60 value 105.113900
iter  70 value 105.048813
iter  80 value 105.014064
iter  90 value 104.153534
iter 100 value 103.430513
final  value 103.430513 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.773822 
iter  10 value 117.865468
iter  20 value 117.858768
final  value 117.858748 
converged
Fitting Repeat 5 

# weights:  507
initial  value 122.604554 
iter  10 value 117.898345
iter  20 value 117.718797
iter  30 value 108.082533
iter  40 value 106.445254
iter  50 value 101.868476
iter  60 value 100.852262
iter  70 value 100.678631
iter  80 value 100.668375
iter  90 value 100.594218
iter 100 value 99.937851
final  value 99.937851 
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 Jan 20 21:25:45 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 
 41.243   1.644 105.991 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod33.858 1.57635.764
FreqInteractors0.2450.0130.260
calculateAAC0.0430.0070.051
calculateAutocor0.3880.0630.455
calculateCTDC0.0800.0040.084
calculateCTDD0.5850.0200.610
calculateCTDT0.2420.0100.255
calculateCTriad0.3880.0300.422
calculateDC0.1060.0120.157
calculateF0.3450.0090.355
calculateKSAAP0.1040.0120.116
calculateQD_Sm1.7810.1121.905
calculateTC1.6460.1411.796
calculateTC_Sm0.2690.0210.291
corr_plot33.951 1.57735.772
enrichfindP0.4620.0588.568
enrichfind_hp0.0760.0241.039
enrichplot0.4010.0080.412
filter_missing_values0.0010.0000.001
getFASTA0.0680.0113.557
getHPI0.0010.0000.001
get_negativePPI0.0020.0000.003
get_positivePPI000
impute_missing_data0.0020.0010.002
plotPPI0.0850.0030.089
pred_ensembel14.111 0.44212.646
var_imp35.320 1.68437.404