Back to Multiple platform build/check report for BioC 3.16:   simplified   long
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This page was generated on 2023-04-12 11:05:07 -0400 (Wed, 12 Apr 2023).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 20.04.5 LTS)x86_644.2.3 (2023-03-15) -- "Shortstop Beagle" 4502
palomino4Windows Server 2022 Datacenterx644.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle" 4282
lconwaymacOS 12.5.1 Montereyx86_644.2.3 (2023-03-15) -- "Shortstop Beagle" 4310
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

CHECK results for HPiP on nebbiolo2


To the developers/maintainers of the HPiP package:
- Please 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 How and When does the builder pull? When will my changes propagate? for more information.
- Make sure to use the following settings in order to reproduce any error or warning you see on this page.

raw results

Package 926/2183HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
HPiP 1.4.3  (landing page)
Matineh Rahmatbakhsh
Snapshot Date: 2023-04-10 14:00:05 -0400 (Mon, 10 Apr 2023)
git_url: https://git.bioconductor.org/packages/HPiP
git_branch: RELEASE_3_16
git_last_commit: 3ed3d60
git_last_commit_date: 2023-04-04 18:50:04 -0400 (Tue, 04 Apr 2023)
nebbiolo2Linux (Ubuntu 20.04.5 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino4Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.5.1 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published

Summary

Package: HPiP
Version: 1.4.3
Command: /home/biocbuild/bbs-3.16-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.16-bioc/R/site-library --timings HPiP_1.4.3.tar.gz
StartedAt: 2023-04-10 21:19:11 -0400 (Mon, 10 Apr 2023)
EndedAt: 2023-04-10 21:34:21 -0400 (Mon, 10 Apr 2023)
EllapsedTime: 910.1 seconds
RetCode: 0
Status:   OK  
CheckDir: HPiP.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.16-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.16-bioc/R/site-library --timings HPiP_1.4.3.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.16-bioc/meat/HPiP.Rcheck’
* using R version 4.2.3 (2023-03-15)
* using platform: x86_64-pc-linux-gnu (64-bit)
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.4.3’
* 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 ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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 ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
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       34.805  0.768  35.574
FSmethod      33.480  0.535  34.017
corr_plot     33.107  0.564  33.672
pred_ensembel 15.258  0.695  12.477
enrichfindP    0.438  0.060  53.618
getFASTA       0.120  0.024   5.184
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
  ‘HPiP_tutorial.Rmd’ using ‘UTF-8’... OK
 NONE
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.16-bioc/meat/HPiP.Rcheck/00check.log’
for details.



Installation output

HPiP.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.16-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.16-bioc/R/site-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 version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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 95.820041 
iter  10 value 93.773015
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.159180 
final  value 94.484210 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.403491 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.004221 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.721236 
iter  10 value 87.449033
iter  20 value 82.807147
iter  30 value 82.803186
final  value 82.803172 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.870637 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.335272 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.357536 
iter  10 value 93.772977
final  value 93.772973 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.952322 
iter  10 value 93.724818
iter  20 value 93.722253
final  value 93.722222 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.895712 
iter  10 value 93.725264
final  value 93.720302 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.390493 
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.411594 
iter  10 value 93.339959
iter  20 value 93.315622
iter  30 value 93.312850
final  value 93.310437 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.851202 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.615603 
final  value 93.772973 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.306439 
iter  10 value 93.720315
final  value 93.720302 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.461778 
iter  10 value 94.147176
iter  20 value 93.729753
iter  30 value 88.774074
iter  40 value 85.149360
iter  50 value 83.396805
iter  60 value 79.596683
iter  70 value 78.165908
iter  80 value 77.812882
iter  90 value 77.810135
final  value 77.810089 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.780246 
iter  10 value 94.474723
iter  20 value 92.785938
iter  30 value 80.687531
iter  40 value 79.594487
iter  50 value 79.120339
iter  60 value 78.586560
iter  70 value 78.162723
iter  80 value 78.093168
final  value 78.093136 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.215402 
iter  10 value 96.857768
iter  20 value 94.488915
iter  30 value 90.775068
iter  40 value 86.528566
iter  50 value 85.306347
iter  60 value 85.206210
iter  70 value 81.656622
iter  80 value 81.554784
iter  90 value 81.416633
iter 100 value 81.281517
final  value 81.281517 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.056624 
iter  10 value 94.151617
iter  20 value 81.519142
iter  30 value 81.099286
iter  40 value 80.838540
iter  50 value 80.685376
iter  60 value 80.679549
iter  60 value 80.679548
iter  60 value 80.679548
final  value 80.679548 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.879229 
iter  10 value 93.613466
iter  20 value 85.941076
iter  30 value 81.602688
iter  40 value 80.641534
iter  50 value 79.432045
iter  60 value 78.850397
iter  70 value 78.353190
iter  80 value 78.098944
final  value 78.093136 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.480921 
iter  10 value 94.465706
iter  20 value 93.821464
iter  30 value 86.645824
iter  40 value 83.299726
iter  50 value 81.098477
iter  60 value 79.861863
iter  70 value 78.979756
iter  80 value 77.767969
iter  90 value 76.855433
iter 100 value 76.458044
final  value 76.458044 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.558703 
iter  10 value 83.711477
iter  20 value 81.285792
iter  30 value 80.937462
iter  40 value 80.827237
iter  50 value 80.788552
iter  60 value 80.047711
iter  70 value 78.970294
iter  80 value 78.706110
iter  90 value 78.361416
iter 100 value 77.339101
final  value 77.339101 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.102303 
iter  10 value 93.935037
iter  20 value 93.109044
iter  30 value 91.406224
iter  40 value 83.902907
iter  50 value 79.484325
iter  60 value 78.305823
iter  70 value 77.717002
iter  80 value 77.586867
iter  90 value 77.471069
iter 100 value 77.103137
final  value 77.103137 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.613450 
iter  10 value 94.439944
iter  20 value 89.161092
iter  30 value 85.527890
iter  40 value 82.956448
iter  50 value 82.017234
iter  60 value 80.891539
iter  70 value 78.978773
iter  80 value 78.244655
iter  90 value 78.080194
iter 100 value 78.029577
final  value 78.029577 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.045619 
iter  10 value 94.537561
iter  20 value 88.425040
iter  30 value 86.803397
iter  40 value 85.074344
iter  50 value 84.573558
iter  60 value 83.365368
iter  70 value 80.885884
iter  80 value 80.645221
iter  90 value 80.068975
iter 100 value 78.755128
final  value 78.755128 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.014016 
iter  10 value 94.503224
iter  20 value 93.635425
iter  30 value 89.360486
iter  40 value 85.249746
iter  50 value 82.988564
iter  60 value 79.161776
iter  70 value 78.222589
iter  80 value 77.391600
iter  90 value 77.075501
iter 100 value 77.016179
final  value 77.016179 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.827062 
iter  10 value 96.653001
iter  20 value 85.021543
iter  30 value 83.941482
iter  40 value 80.867916
iter  50 value 80.037913
iter  60 value 79.659466
iter  70 value 78.986899
iter  80 value 78.453640
iter  90 value 78.292113
iter 100 value 77.873510
final  value 77.873510 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.746169 
iter  10 value 93.560693
iter  20 value 85.251612
iter  30 value 82.389446
iter  40 value 79.655844
iter  50 value 77.893672
iter  60 value 76.926323
iter  70 value 76.538976
iter  80 value 76.254001
iter  90 value 76.070278
iter 100 value 75.918373
final  value 75.918373 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.968297 
iter  10 value 95.925969
iter  20 value 93.935920
iter  30 value 83.823015
iter  40 value 82.125596
iter  50 value 81.191689
iter  60 value 80.496848
iter  70 value 80.129932
iter  80 value 78.584549
iter  90 value 78.097633
iter 100 value 77.619076
final  value 77.619076 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.958553 
iter  10 value 94.612754
iter  20 value 94.419328
iter  30 value 84.581216
iter  40 value 83.163437
iter  50 value 82.215023
iter  60 value 81.283309
iter  70 value 80.337890
iter  80 value 78.843755
iter  90 value 77.341215
iter 100 value 77.152556
final  value 77.152556 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.791617 
final  value 94.485807 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.764896 
iter  10 value 93.775511
iter  20 value 93.775167
iter  30 value 93.773718
final  value 93.773708 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.799516 
final  value 94.485851 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.589424 
iter  10 value 94.114606
iter  20 value 94.114074
iter  30 value 92.969297
iter  40 value 90.078539
iter  50 value 87.072967
iter  60 value 80.278532
iter  70 value 79.942060
iter  80 value 79.922353
iter  90 value 77.835206
iter 100 value 76.803889
final  value 76.803889 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.393761 
final  value 94.486055 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.761251 
iter  10 value 85.147771
iter  20 value 85.113096
iter  30 value 85.106349
iter  40 value 85.104966
iter  50 value 84.186127
iter  60 value 83.919277
final  value 83.871454 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.670309 
iter  10 value 93.725720
iter  20 value 93.724917
iter  30 value 93.498465
iter  40 value 82.953479
final  value 81.460859 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.168582 
iter  10 value 93.782720
iter  20 value 93.777940
iter  30 value 93.768828
iter  40 value 93.509762
final  value 93.509253 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.338274 
iter  10 value 85.158064
iter  20 value 85.111218
iter  30 value 85.110131
iter  40 value 83.268006
iter  50 value 83.250744
iter  60 value 83.249816
iter  70 value 83.169866
iter  80 value 83.127794
iter  90 value 82.962354
final  value 82.951178 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.566052 
iter  10 value 94.488571
iter  20 value 94.470555
iter  30 value 90.548805
iter  40 value 82.686024
iter  50 value 82.564070
iter  60 value 82.562342
iter  70 value 82.320322
iter  80 value 79.363739
iter  90 value 78.074291
final  value 78.015837 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.034777 
iter  10 value 89.036154
iter  20 value 85.628512
iter  30 value 84.301768
iter  40 value 83.450962
iter  50 value 83.130632
iter  60 value 83.129222
iter  70 value 83.126664
final  value 83.126649 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.013679 
iter  10 value 93.896470
iter  20 value 93.729134
iter  30 value 93.725437
iter  40 value 88.267534
iter  50 value 84.907724
final  value 84.837730 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.896600 
iter  10 value 93.782778
iter  20 value 93.781506
iter  30 value 93.713065
iter  40 value 92.767993
iter  50 value 83.104238
iter  60 value 81.875562
iter  70 value 79.208675
iter  80 value 78.426015
iter  90 value 78.356539
iter 100 value 78.268789
final  value 78.268789 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.677044 
iter  10 value 94.492499
iter  20 value 94.482063
iter  30 value 87.738083
iter  40 value 82.810775
iter  50 value 82.803852
iter  60 value 82.791876
iter  70 value 81.820483
iter  80 value 81.759654
iter  90 value 81.258307
iter 100 value 81.249830
final  value 81.249830 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.496838 
iter  10 value 94.113810
iter  20 value 94.107212
iter  30 value 93.788734
iter  30 value 93.788734
iter  30 value 93.788733
final  value 93.788733 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.492931 
final  value 94.455556 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.299916 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.430347 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.337410 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.587658 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.917032 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.875158 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.684568 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.363721 
iter  10 value 94.406449
iter  20 value 94.275362
iter  20 value 94.275362
iter  20 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.243850 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.886261 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.692137 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 140.594790 
iter  10 value 94.474345
iter  20 value 94.370270
final  value 94.338750 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.089794 
iter  10 value 94.181913
iter  20 value 87.650832
iter  30 value 87.434126
iter  40 value 87.430354
final  value 87.430350 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.506916 
iter  10 value 94.315986
iter  20 value 89.507451
iter  30 value 89.432806
final  value 89.432716 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.988077 
iter  10 value 93.081686
iter  20 value 87.476922
iter  30 value 86.274844
iter  40 value 86.211233
iter  50 value 86.133932
iter  60 value 86.106739
iter  60 value 86.106739
iter  60 value 86.106739
final  value 86.106739 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.753279 
iter  10 value 94.490799
iter  20 value 93.537422
iter  30 value 87.943037
iter  40 value 86.720805
iter  50 value 85.663496
iter  60 value 85.168845
iter  70 value 84.360428
iter  80 value 83.923816
iter  90 value 83.883336
iter 100 value 83.850325
final  value 83.850325 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.287631 
iter  10 value 94.446980
iter  20 value 92.449050
iter  30 value 91.538674
iter  40 value 86.981171
iter  50 value 86.911057
iter  60 value 86.072188
iter  70 value 85.619460
iter  80 value 85.519538
iter  90 value 85.470737
final  value 85.470728 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.109680 
iter  10 value 94.467365
iter  20 value 93.629896
iter  30 value 91.542336
iter  40 value 89.638995
iter  50 value 86.978508
iter  60 value 86.465005
iter  70 value 86.365061
iter  80 value 86.277268
final  value 86.276465 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.362232 
iter  10 value 94.488360
iter  20 value 94.130796
iter  30 value 94.115747
iter  40 value 93.987292
iter  50 value 87.234729
iter  60 value 86.411163
iter  70 value 86.355912
iter  80 value 86.316555
iter  90 value 86.276517
final  value 86.276466 
converged
Fitting Repeat 1 

# weights:  305
initial  value 125.978431 
iter  10 value 94.559179
iter  20 value 87.855476
iter  30 value 86.378107
iter  40 value 84.230283
iter  50 value 83.589853
iter  60 value 82.905328
iter  70 value 82.799440
iter  80 value 82.617792
iter  90 value 82.396572
iter 100 value 82.280339
final  value 82.280339 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.670577 
iter  10 value 94.357429
iter  20 value 92.703432
iter  30 value 86.867024
iter  40 value 85.825725
iter  50 value 85.541602
iter  60 value 85.205031
iter  70 value 85.028674
iter  80 value 84.413287
iter  90 value 83.180559
iter 100 value 82.786822
final  value 82.786822 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.673621 
iter  10 value 94.282722
iter  20 value 87.898255
iter  30 value 86.570580
iter  40 value 86.392168
iter  50 value 85.739674
iter  60 value 85.338701
iter  70 value 85.270881
iter  80 value 84.512338
iter  90 value 83.893520
iter 100 value 83.339305
final  value 83.339305 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.301390 
iter  10 value 94.620190
iter  20 value 91.344903
iter  30 value 85.853018
iter  40 value 84.694244
iter  50 value 84.401594
iter  60 value 83.963589
iter  70 value 83.916777
iter  80 value 83.910085
iter  90 value 83.890030
iter 100 value 83.870229
final  value 83.870229 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.241035 
iter  10 value 95.317290
iter  20 value 88.703828
iter  30 value 87.030226
iter  40 value 85.834855
iter  50 value 85.440098
iter  60 value 85.233601
iter  70 value 85.116136
iter  80 value 85.044267
iter  90 value 84.624136
iter 100 value 83.736773
final  value 83.736773 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.040616 
iter  10 value 94.866358
iter  20 value 94.728878
iter  30 value 89.979590
iter  40 value 86.109061
iter  50 value 84.881560
iter  60 value 84.231807
iter  70 value 83.152622
iter  80 value 82.802282
iter  90 value 82.625641
iter 100 value 82.604007
final  value 82.604007 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.887243 
iter  10 value 94.341282
iter  20 value 88.557894
iter  30 value 87.504082
iter  40 value 86.253826
iter  50 value 84.508516
iter  60 value 83.528735
iter  70 value 83.271034
iter  80 value 83.167416
iter  90 value 83.085399
iter 100 value 83.039212
final  value 83.039212 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.007422 
iter  10 value 94.485195
iter  20 value 93.747518
iter  30 value 88.376243
iter  40 value 86.364251
iter  50 value 85.541296
iter  60 value 85.047210
iter  70 value 84.762666
iter  80 value 84.722457
iter  90 value 84.614612
iter 100 value 84.375856
final  value 84.375856 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.693536 
iter  10 value 96.511922
iter  20 value 93.147698
iter  30 value 88.286352
iter  40 value 86.722813
iter  50 value 85.937829
iter  60 value 84.366365
iter  70 value 83.749191
iter  80 value 83.296528
iter  90 value 82.919929
iter 100 value 82.639389
final  value 82.639389 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.242504 
iter  10 value 94.437320
iter  20 value 88.420065
iter  30 value 87.628306
iter  40 value 84.895939
iter  50 value 84.344804
iter  60 value 84.011451
iter  70 value 83.538668
iter  80 value 82.781761
iter  90 value 82.611749
iter 100 value 82.452910
final  value 82.452910 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.366414 
iter  10 value 94.290268
iter  20 value 94.290077
iter  30 value 94.032942
iter  40 value 92.360772
iter  50 value 89.609352
iter  60 value 87.546968
iter  70 value 87.172733
iter  80 value 87.162947
iter  90 value 86.809980
final  value 86.796643 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.983202 
iter  10 value 87.402525
iter  20 value 87.100597
iter  30 value 86.700253
iter  40 value 85.849144
iter  50 value 85.809864
final  value 85.809582 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.562972 
final  value 94.485999 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.787347 
final  value 94.485966 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.173067 
final  value 94.485716 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.790513 
iter  10 value 94.460165
iter  20 value 89.918516
iter  30 value 86.645125
iter  40 value 86.578036
iter  50 value 86.577891
final  value 86.577863 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.226950 
iter  10 value 87.528490
iter  20 value 86.878918
iter  30 value 86.872018
iter  40 value 86.871414
final  value 86.870907 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.320666 
iter  10 value 94.489544
iter  20 value 94.484730
final  value 94.484558 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.106124 
iter  10 value 94.489248
iter  20 value 94.484506
iter  30 value 94.474460
iter  40 value 92.320795
iter  50 value 92.285845
iter  60 value 92.276857
iter  70 value 92.260832
iter  80 value 90.061484
iter  90 value 90.022326
iter 100 value 90.020411
final  value 90.020411 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.062465 
iter  10 value 94.279753
iter  20 value 91.573934
iter  30 value 86.443192
iter  40 value 86.441303
iter  50 value 86.433784
iter  60 value 85.573318
iter  70 value 84.395610
iter  80 value 84.282298
iter  90 value 84.164416
iter 100 value 84.163972
final  value 84.163972 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.795449 
iter  10 value 94.492103
iter  20 value 93.625768
iter  30 value 90.489498
final  value 90.489450 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.142052 
iter  10 value 94.492249
iter  20 value 94.423406
iter  30 value 92.195490
iter  40 value 87.040729
iter  50 value 87.031338
iter  60 value 84.900335
iter  70 value 83.645794
iter  80 value 83.105270
iter  90 value 82.093049
iter 100 value 81.980741
final  value 81.980741 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.054595 
iter  10 value 94.283873
iter  20 value 94.276384
iter  30 value 94.275461
iter  40 value 90.371670
iter  50 value 87.500865
iter  60 value 86.040269
iter  70 value 83.648094
iter  80 value 83.237029
iter  90 value 83.233742
iter 100 value 83.229134
final  value 83.229134 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.099866 
iter  10 value 94.492127
iter  20 value 94.443892
iter  30 value 92.507965
iter  40 value 89.558238
iter  50 value 89.039057
iter  60 value 87.912039
iter  70 value 87.680068
iter  80 value 87.061232
iter  90 value 86.168838
iter 100 value 86.059170
final  value 86.059170 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.721863 
iter  10 value 94.284238
iter  20 value 94.280654
iter  30 value 89.637592
iter  40 value 87.622348
final  value 87.622331 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.663501 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.986589 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 113.191295 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.441215 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.571736 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.469403 
final  value 94.050051 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.150642 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.724948 
iter  10 value 93.446091
iter  20 value 88.640371
iter  30 value 86.618247
iter  40 value 86.613670
final  value 86.613513 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.817843 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.925706 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.687894 
iter  10 value 84.690257
iter  20 value 82.739047
iter  30 value 82.734442
final  value 82.730415 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.451419 
iter  10 value 93.536542
iter  20 value 93.317137
iter  30 value 93.131855
final  value 93.129023 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.093339 
iter  10 value 93.994184
final  value 93.993336 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.768524 
iter  10 value 93.884351
final  value 93.810106 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.522718 
iter  10 value 88.212550
final  value 88.170690 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.080570 
iter  10 value 93.289069
iter  20 value 89.575378
iter  30 value 88.005554
iter  40 value 83.716863
iter  50 value 82.644760
iter  60 value 82.312953
iter  70 value 82.274192
final  value 82.274179 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.401991 
iter  10 value 94.056354
iter  20 value 83.916539
iter  30 value 83.405008
iter  40 value 82.453935
iter  50 value 82.286656
iter  60 value 82.274184
final  value 82.274178 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.602193 
iter  10 value 90.951653
iter  20 value 87.859899
iter  30 value 87.189126
iter  40 value 84.619337
iter  50 value 83.125756
iter  60 value 83.073176
iter  70 value 83.070275
iter  80 value 83.069509
iter  90 value 83.069089
final  value 83.068985 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.918321 
iter  10 value 94.064018
iter  20 value 93.937635
iter  30 value 90.157579
iter  40 value 85.602813
iter  50 value 84.946402
iter  60 value 84.117331
iter  70 value 82.152724
iter  80 value 80.433227
iter  90 value 80.193069
final  value 80.135004 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.706321 
iter  10 value 92.673567
iter  20 value 85.936564
iter  30 value 85.357352
iter  40 value 85.119354
iter  50 value 84.866745
iter  60 value 84.470672
final  value 84.470604 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.404541 
iter  10 value 94.049693
iter  20 value 85.883053
iter  30 value 85.216087
iter  40 value 84.604752
iter  50 value 83.889201
iter  60 value 82.655382
iter  70 value 82.093411
iter  80 value 80.218806
iter  90 value 79.543006
iter 100 value 79.155820
final  value 79.155820 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.246956 
iter  10 value 94.111398
iter  20 value 92.841837
iter  30 value 91.791511
iter  40 value 89.873814
iter  50 value 83.143751
iter  60 value 80.251419
iter  70 value 79.655853
iter  80 value 79.340217
iter  90 value 79.304174
iter 100 value 79.281201
final  value 79.281201 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.329683 
iter  10 value 93.687447
iter  20 value 89.421545
iter  30 value 87.843724
iter  40 value 85.158458
iter  50 value 81.360623
iter  60 value 80.966684
iter  70 value 80.480226
iter  80 value 79.587021
iter  90 value 79.419054
iter 100 value 79.179541
final  value 79.179541 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.891040 
iter  10 value 94.948069
iter  20 value 85.841807
iter  30 value 85.095782
iter  40 value 83.815014
iter  50 value 82.619550
iter  60 value 82.148107
iter  70 value 80.369390
iter  80 value 79.947206
iter  90 value 79.763798
iter 100 value 79.373086
final  value 79.373086 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.034358 
iter  10 value 94.017243
iter  20 value 89.659739
iter  30 value 83.784820
iter  40 value 82.863264
iter  50 value 81.748244
iter  60 value 80.285838
iter  70 value 79.034370
iter  80 value 78.855114
iter  90 value 78.826523
iter 100 value 78.820745
final  value 78.820745 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.155629 
iter  10 value 94.088865
iter  20 value 92.600634
iter  30 value 84.836775
iter  40 value 83.830570
iter  50 value 83.076516
iter  60 value 81.965783
iter  70 value 81.906682
iter  80 value 81.661364
iter  90 value 81.097398
iter 100 value 79.787171
final  value 79.787171 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.080164 
iter  10 value 93.890795
iter  20 value 85.559075
iter  30 value 82.322000
iter  40 value 80.509723
iter  50 value 80.134882
iter  60 value 79.330709
iter  70 value 79.145464
iter  80 value 79.117742
iter  90 value 79.061935
iter 100 value 78.972507
final  value 78.972507 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.800601 
iter  10 value 95.015826
iter  20 value 93.783261
iter  30 value 92.347337
iter  40 value 88.348538
iter  50 value 82.222319
iter  60 value 81.115344
iter  70 value 79.706957
iter  80 value 79.034716
iter  90 value 78.747873
iter 100 value 78.513167
final  value 78.513167 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.501152 
iter  10 value 94.137879
iter  20 value 93.963662
iter  30 value 90.476325
iter  40 value 88.858806
iter  50 value 83.568720
iter  60 value 81.726886
iter  70 value 81.069941
iter  80 value 80.849650
iter  90 value 80.535138
iter 100 value 79.935683
final  value 79.935683 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.876970 
iter  10 value 94.086402
iter  20 value 93.501825
iter  30 value 88.215849
iter  40 value 85.387046
iter  50 value 83.198375
iter  60 value 82.562105
iter  70 value 81.923158
iter  80 value 81.094700
iter  90 value 81.052318
iter 100 value 80.687907
final  value 80.687907 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.159129 
iter  10 value 90.075994
iter  20 value 90.071840
iter  30 value 90.039573
iter  40 value 90.018800
iter  50 value 90.011597
iter  60 value 90.011439
iter  70 value 90.010670
final  value 90.009872 
converged
Fitting Repeat 2 

# weights:  103
initial  value 115.420579 
iter  10 value 93.715895
iter  20 value 93.469491
iter  30 value 83.118335
iter  40 value 82.335222
iter  50 value 82.333183
iter  60 value 82.332874
final  value 82.332824 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.114046 
final  value 94.054458 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.307979 
final  value 94.054583 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.352895 
final  value 94.054431 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.241917 
iter  10 value 94.043433
iter  20 value 94.038816
iter  30 value 93.775800
iter  40 value 90.670072
final  value 90.670057 
converged
Fitting Repeat 2 

# weights:  305
initial  value 119.506289 
iter  10 value 94.057831
iter  20 value 94.034813
iter  30 value 84.893992
iter  40 value 83.896769
iter  50 value 83.723778
iter  60 value 83.718684
iter  70 value 83.713800
iter  80 value 83.393941
iter  90 value 83.081904
iter 100 value 82.015139
final  value 82.015139 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.347339 
iter  10 value 93.611871
iter  20 value 93.546952
iter  30 value 84.046072
final  value 83.911982 
converged
Fitting Repeat 4 

# weights:  305
initial  value 119.962035 
iter  10 value 94.057732
iter  20 value 93.536459
iter  30 value 86.603194
iter  40 value 84.831046
iter  50 value 84.795136
iter  60 value 84.604078
iter  70 value 84.573644
iter  80 value 84.572905
iter  90 value 84.571793
final  value 84.571378 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.720620 
iter  10 value 93.633337
iter  20 value 90.638535
iter  30 value 89.812036
iter  40 value 89.565260
iter  50 value 89.222305
iter  60 value 89.220310
iter  70 value 89.219851
final  value 89.219667 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.348487 
iter  10 value 94.058161
iter  20 value 92.551795
iter  30 value 88.179108
iter  40 value 87.239583
final  value 87.167242 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.166371 
iter  10 value 93.976949
iter  20 value 93.890604
final  value 93.870561 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.368048 
iter  10 value 94.060816
iter  20 value 94.052809
iter  30 value 83.929293
final  value 83.912246 
converged
Fitting Repeat 4 

# weights:  507
initial  value 93.379427 
iter  10 value 90.474500
final  value 90.458698 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.356438 
iter  10 value 93.722474
iter  20 value 93.693695
iter  30 value 93.630029
iter  40 value 83.936883
iter  50 value 83.905040
iter  60 value 83.903835
iter  60 value 83.903835
iter  60 value 83.903835
final  value 83.903835 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.032039 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.452619 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.392994 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.992812 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.529167 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.222439 
iter  10 value 89.044696
iter  20 value 88.380657
iter  30 value 88.296873
iter  40 value 84.315426
iter  50 value 84.309631
final  value 84.309319 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.093219 
iter  10 value 93.563621
iter  20 value 86.521851
iter  30 value 83.304010
iter  40 value 83.235273
iter  50 value 82.941202
iter  60 value 82.883818
final  value 82.883697 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.874647 
iter  10 value 87.333293
iter  20 value 87.283812
iter  20 value 87.283811
iter  20 value 87.283811
final  value 87.283811 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.901781 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.218699 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.178604 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.397153 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.944948 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.891310 
iter  10 value 94.312066
final  value 94.312042 
converged
Fitting Repeat 5 

# weights:  507
initial  value 137.090058 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.905711 
iter  10 value 94.375024
iter  20 value 86.765426
iter  30 value 86.371828
iter  40 value 85.443322
iter  50 value 85.398014
iter  60 value 85.354483
final  value 85.354475 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.936087 
iter  10 value 94.484229
iter  20 value 92.628219
iter  30 value 88.515320
iter  40 value 86.491429
iter  50 value 85.886867
iter  60 value 85.466794
iter  70 value 85.354506
final  value 85.354478 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.985087 
iter  10 value 94.500446
iter  20 value 94.029545
iter  30 value 86.478430
iter  40 value 86.220023
iter  50 value 85.530464
iter  60 value 83.491692
iter  70 value 82.390048
iter  80 value 82.279196
iter  90 value 82.187759
final  value 82.177987 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.939323 
iter  10 value 94.488575
iter  20 value 94.487181
iter  30 value 94.227333
iter  40 value 85.650427
iter  50 value 84.136233
iter  60 value 83.297235
iter  70 value 82.869039
iter  80 value 82.518776
iter  90 value 82.286351
iter 100 value 82.273573
final  value 82.273573 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 111.734385 
iter  10 value 94.568435
iter  20 value 94.449542
iter  30 value 90.748251
iter  40 value 86.106117
iter  50 value 85.929931
iter  60 value 85.772952
iter  70 value 85.178361
iter  80 value 85.001274
iter  90 value 84.964692
final  value 84.964685 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.920740 
iter  10 value 94.690854
iter  20 value 88.951271
iter  30 value 87.175181
iter  40 value 85.921857
iter  50 value 85.262410
iter  60 value 83.421246
iter  70 value 81.788390
iter  80 value 81.328106
iter  90 value 81.079407
iter 100 value 80.948125
final  value 80.948125 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.705948 
iter  10 value 96.093912
iter  20 value 91.517251
iter  30 value 88.219472
iter  40 value 86.303522
iter  50 value 85.628314
iter  60 value 85.049856
iter  70 value 84.940045
final  value 84.940041 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.992212 
iter  10 value 94.559480
iter  20 value 88.842250
iter  30 value 87.441130
iter  40 value 86.495369
iter  50 value 85.627628
iter  60 value 84.565382
iter  70 value 83.350752
iter  80 value 82.502096
iter  90 value 82.062234
iter 100 value 81.516239
final  value 81.516239 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.823736 
iter  10 value 86.712669
iter  20 value 86.319911
iter  30 value 86.069804
iter  40 value 85.882883
iter  50 value 84.784207
iter  60 value 84.433683
iter  70 value 84.295602
iter  80 value 83.863558
iter  90 value 82.758425
iter 100 value 82.615677
final  value 82.615677 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.335392 
iter  10 value 92.911683
iter  20 value 86.696830
iter  30 value 86.068985
iter  40 value 85.704714
iter  50 value 85.155562
iter  60 value 84.984506
iter  70 value 84.946806
iter  80 value 84.820049
iter  90 value 83.354736
iter 100 value 83.021262
final  value 83.021262 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.061054 
iter  10 value 94.020867
iter  20 value 88.148244
iter  30 value 85.137631
iter  40 value 84.966355
iter  50 value 83.900335
iter  60 value 81.967464
iter  70 value 81.670001
iter  80 value 81.391700
iter  90 value 81.045665
iter 100 value 80.803308
final  value 80.803308 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.432375 
iter  10 value 94.537637
iter  20 value 94.394120
iter  30 value 93.063820
iter  40 value 85.271249
iter  50 value 84.599722
iter  60 value 84.400584
iter  70 value 84.211249
iter  80 value 84.041578
iter  90 value 83.982751
iter 100 value 83.583972
final  value 83.583972 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.580912 
iter  10 value 94.632725
iter  20 value 94.208489
iter  30 value 87.466706
iter  40 value 87.145963
iter  50 value 85.209172
iter  60 value 83.069287
iter  70 value 82.753499
iter  80 value 82.510983
iter  90 value 81.889986
iter 100 value 81.288273
final  value 81.288273 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.748239 
iter  10 value 91.379164
iter  20 value 87.624676
iter  30 value 85.175900
iter  40 value 81.795534
iter  50 value 81.423176
iter  60 value 81.251836
iter  70 value 80.917445
iter  80 value 80.802282
iter  90 value 80.644019
iter 100 value 80.539841
final  value 80.539841 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.000207 
iter  10 value 94.732151
iter  20 value 87.655230
iter  30 value 83.985541
iter  40 value 83.317718
iter  50 value 82.661437
iter  60 value 81.830325
iter  70 value 81.211795
iter  80 value 81.124032
iter  90 value 81.075886
iter 100 value 81.049539
final  value 81.049539 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.591649 
final  value 94.485819 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.711537 
final  value 94.485948 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.900415 
final  value 94.485863 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.869782 
iter  10 value 94.486439
final  value 94.484573 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.807146 
final  value 94.486513 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.498216 
iter  10 value 94.489157
iter  20 value 94.354524
iter  30 value 94.287445
iter  40 value 92.789949
final  value 92.789940 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.334568 
iter  10 value 91.926525
iter  20 value 86.313991
iter  30 value 85.916125
iter  40 value 85.405188
final  value 85.404946 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.690665 
iter  10 value 94.489226
iter  20 value 94.484357
iter  30 value 91.996519
iter  40 value 85.231305
iter  50 value 85.228931
final  value 85.228192 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.999076 
iter  10 value 94.489430
iter  20 value 94.484237
final  value 94.484230 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.260941 
iter  10 value 94.489567
iter  20 value 94.484863
iter  30 value 94.056616
iter  40 value 93.114737
iter  50 value 91.063509
iter  60 value 85.521381
iter  70 value 85.512696
iter  80 value 85.500399
iter  90 value 85.494682
iter 100 value 84.642282
final  value 84.642282 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.678379 
iter  10 value 94.492760
iter  20 value 94.478637
iter  30 value 87.857468
iter  40 value 84.766339
iter  50 value 84.762814
final  value 84.762780 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.736682 
iter  10 value 94.493126
iter  20 value 94.341539
iter  30 value 88.194823
iter  40 value 84.898834
final  value 84.748532 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.355853 
iter  10 value 94.491803
iter  20 value 94.427360
iter  30 value 94.031403
final  value 94.031247 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.566272 
iter  10 value 94.492758
iter  20 value 94.412160
iter  30 value 93.085915
iter  40 value 86.980277
iter  50 value 86.595195
iter  60 value 86.575789
iter  70 value 86.573738
iter  80 value 84.930955
iter  90 value 84.747903
iter  90 value 84.747903
iter  90 value 84.747903
final  value 84.747903 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.199584 
iter  10 value 93.308946
iter  20 value 93.213859
iter  30 value 90.487740
iter  40 value 88.206411
iter  50 value 86.157899
iter  60 value 86.151854
final  value 86.151390 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.952994 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.243917 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.754685 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.674778 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.386723 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.693091 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.695029 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.886526 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.294000 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.235567 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.477351 
iter  10 value 94.038796
final  value 94.030550 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.801876 
iter  10 value 94.032967
iter  10 value 94.032967
iter  10 value 94.032967
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.077221 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.496553 
iter  10 value 94.053312
final  value 94.052917 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.072304 
iter  10 value 93.921217
final  value 93.921212 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.662497 
iter  10 value 94.055084
iter  20 value 89.133314
iter  30 value 86.488512
iter  40 value 84.684883
iter  50 value 83.749545
iter  60 value 82.883124
iter  70 value 82.593509
iter  80 value 82.569316
final  value 82.562388 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.333610 
iter  10 value 94.071864
iter  20 value 93.927648
iter  30 value 93.732783
iter  40 value 88.908297
iter  50 value 85.886366
iter  60 value 84.704553
iter  70 value 83.368007
iter  80 value 82.622446
iter  90 value 82.578751
iter 100 value 82.571005
final  value 82.571005 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.308951 
iter  10 value 94.087969
iter  20 value 94.045937
iter  30 value 90.877698
iter  40 value 87.598854
iter  50 value 87.174087
iter  60 value 86.642878
iter  70 value 85.740157
iter  80 value 85.448854
iter  90 value 85.048019
iter 100 value 84.596167
final  value 84.596167 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.155776 
iter  10 value 94.056139
iter  20 value 88.699226
iter  30 value 87.678647
iter  40 value 87.213390
iter  50 value 87.184695
final  value 87.184691 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.561851 
iter  10 value 94.055811
iter  20 value 89.739631
iter  30 value 88.150190
iter  40 value 86.881736
iter  50 value 84.289490
iter  60 value 83.768826
iter  70 value 83.055942
iter  80 value 82.745645
iter  90 value 82.570519
final  value 82.570262 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.476033 
iter  10 value 94.020265
iter  20 value 88.971691
iter  30 value 86.201902
iter  40 value 84.944605
iter  50 value 83.975688
iter  60 value 82.446614
iter  70 value 81.823919
iter  80 value 81.746286
iter  90 value 81.646803
iter 100 value 81.625249
final  value 81.625249 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.541942 
iter  10 value 94.388624
iter  20 value 89.011725
iter  30 value 87.039606
iter  40 value 86.841561
iter  50 value 86.017577
iter  60 value 84.591305
iter  70 value 82.545115
iter  80 value 81.847335
iter  90 value 81.587631
iter 100 value 81.407457
final  value 81.407457 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.984246 
iter  10 value 94.343890
iter  20 value 94.054751
iter  30 value 90.127612
iter  40 value 87.717403
iter  50 value 87.347687
iter  60 value 87.269719
iter  70 value 87.146903
iter  80 value 86.819372
iter  90 value 85.288908
iter 100 value 84.106865
final  value 84.106865 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 115.735014 
iter  10 value 94.055407
iter  20 value 92.962423
iter  30 value 89.330230
iter  40 value 88.307287
iter  50 value 87.549250
iter  60 value 87.329323
iter  70 value 86.074466
iter  80 value 83.078286
iter  90 value 82.316385
iter 100 value 82.121737
final  value 82.121737 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.500156 
iter  10 value 93.977822
iter  20 value 90.317735
iter  30 value 89.089176
iter  40 value 86.997784
iter  50 value 84.945104
iter  60 value 83.829110
iter  70 value 82.692593
iter  80 value 82.016286
iter  90 value 81.842042
iter 100 value 81.571283
final  value 81.571283 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.184851 
iter  10 value 94.658367
iter  20 value 93.515668
iter  30 value 87.927332
iter  40 value 85.545688
iter  50 value 85.007290
iter  60 value 84.880021
iter  70 value 84.176226
iter  80 value 83.796389
iter  90 value 83.515181
iter 100 value 83.048729
final  value 83.048729 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.498522 
iter  10 value 94.080339
iter  20 value 93.324281
iter  30 value 88.885171
iter  40 value 88.686433
iter  50 value 87.986835
iter  60 value 86.799549
iter  70 value 86.575397
iter  80 value 86.494911
iter  90 value 85.433565
iter 100 value 84.749339
final  value 84.749339 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.321429 
iter  10 value 94.383637
iter  20 value 90.596766
iter  30 value 87.314586
iter  40 value 86.949374
iter  50 value 86.176987
iter  60 value 85.053255
iter  70 value 83.884592
iter  80 value 82.254544
iter  90 value 81.615858
iter 100 value 81.244630
final  value 81.244630 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 136.769798 
iter  10 value 94.622244
iter  20 value 93.748995
iter  30 value 88.564235
iter  40 value 87.939936
iter  50 value 87.775803
iter  60 value 87.285158
iter  70 value 84.752238
iter  80 value 82.778543
iter  90 value 82.076756
iter 100 value 81.790641
final  value 81.790641 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.124319 
iter  10 value 94.174055
iter  20 value 88.608942
iter  30 value 87.079028
iter  40 value 85.610749
iter  50 value 84.594036
iter  60 value 84.144364
iter  70 value 83.725119
iter  80 value 83.264536
iter  90 value 82.998243
iter 100 value 82.533952
final  value 82.533952 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.516138 
iter  10 value 87.612130
iter  20 value 87.361995
iter  30 value 86.111967
iter  40 value 85.698107
iter  50 value 85.305791
iter  60 value 85.298620
final  value 85.298172 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.381353 
iter  10 value 94.054433
iter  20 value 94.009695
iter  30 value 91.615221
iter  40 value 89.093692
iter  50 value 86.843749
iter  60 value 85.988375
iter  70 value 85.977536
final  value 85.976632 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.224023 
final  value 94.034321 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.917980 
final  value 94.034555 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.963800 
final  value 94.034353 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.508418 
iter  10 value 94.056866
iter  20 value 89.362480
iter  30 value 87.514043
iter  40 value 87.503556
iter  50 value 86.411078
iter  60 value 84.430083
iter  70 value 84.394783
iter  80 value 84.394433
iter  90 value 84.393878
iter 100 value 84.298774
final  value 84.298774 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.311129 
iter  10 value 94.057924
iter  20 value 94.053454
iter  30 value 92.051698
iter  40 value 87.959200
iter  50 value 86.111510
iter  60 value 85.586623
final  value 85.586239 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.634245 
iter  10 value 94.057778
iter  20 value 94.052839
iter  30 value 93.994889
iter  40 value 88.207367
iter  50 value 85.219669
iter  60 value 82.386801
iter  70 value 81.589196
iter  80 value 81.438860
iter  90 value 81.379311
iter 100 value 81.273476
final  value 81.273476 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.461973 
iter  10 value 94.037961
iter  20 value 93.886151
iter  30 value 93.864087
iter  40 value 93.863850
iter  50 value 93.407668
iter  60 value 93.088020
iter  70 value 92.881553
iter  80 value 90.056440
iter  90 value 86.471080
iter 100 value 85.500068
final  value 85.500068 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.456395 
iter  10 value 94.057647
iter  20 value 94.036093
iter  30 value 93.049493
iter  40 value 91.693964
iter  50 value 87.086039
iter  60 value 87.056529
iter  70 value 87.002071
iter  80 value 86.996299
final  value 86.996208 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.754680 
iter  10 value 94.023911
iter  20 value 93.923873
iter  30 value 93.907101
iter  40 value 93.748484
iter  50 value 86.607254
iter  60 value 84.459252
iter  70 value 83.798959
iter  80 value 82.598815
iter  90 value 82.033569
iter 100 value 81.850328
final  value 81.850328 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.432681 
iter  10 value 94.061846
iter  20 value 94.053669
iter  30 value 93.810182
iter  30 value 93.810181
iter  30 value 93.810181
final  value 93.810181 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.735297 
iter  10 value 94.069264
iter  20 value 87.844770
iter  30 value 85.723271
iter  40 value 85.713671
iter  50 value 85.710498
final  value 85.709231 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.093849 
iter  10 value 94.062063
iter  20 value 94.011800
iter  30 value 91.672954
iter  40 value 90.456947
iter  50 value 90.435451
iter  60 value 90.434578
iter  70 value 90.432711
iter  80 value 90.411803
iter  90 value 90.404526
iter 100 value 90.207620
final  value 90.207620 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.325182 
iter  10 value 94.061270
iter  20 value 93.245837
iter  30 value 87.332610
iter  40 value 87.331299
iter  50 value 87.268734
iter  60 value 87.266558
iter  70 value 87.264296
iter  80 value 87.084531
final  value 87.082129 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.138249 
iter  10 value 117.763486
iter  20 value 116.915435
iter  30 value 103.373234
iter  40 value 102.545212
iter  50 value 101.625525
iter  60 value 101.501718
final  value 101.501437 
converged
Fitting Repeat 2 

# weights:  305
initial  value 123.047132 
iter  10 value 117.763994
iter  20 value 116.282225
iter  30 value 105.548507
iter  40 value 105.522815
iter  50 value 105.522593
iter  60 value 105.354811
iter  70 value 105.238312
iter  80 value 105.208663
iter  90 value 105.174693
iter 100 value 105.174593
final  value 105.174593 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 128.611354 
iter  10 value 117.894842
iter  20 value 117.726926
iter  30 value 107.280830
iter  40 value 106.872339
iter  50 value 106.866525
final  value 106.866520 
converged
Fitting Repeat 4 

# weights:  305
initial  value 126.177716 
iter  10 value 117.895245
iter  20 value 111.959794
final  value 108.529094 
converged
Fitting Repeat 5 

# weights:  305
initial  value 121.972657 
iter  10 value 108.759834
iter  20 value 105.070059
iter  30 value 105.060286
final  value 105.059913 
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 -- Mon Apr 10 21:25:07 2023 
*********************************************** 
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 
 41.197   1.643  83.615 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod33.480 0.53534.017
FreqInteractors0.2770.0200.297
calculateAAC0.0370.0020.040
calculateAutocor0.3170.0080.325
calculateCTDC0.0880.0000.088
calculateCTDD0.6400.0040.645
calculateCTDT0.2290.0000.229
calculateCTriad0.3490.0080.356
calculateDC0.0770.0080.086
calculateF0.3090.0000.310
calculateKSAAP0.0880.0000.088
calculateQD_Sm1.7110.0081.719
calculateTC1.4600.0561.517
calculateTC_Sm0.2950.0000.296
corr_plot33.107 0.56433.672
enrichfindP 0.438 0.06053.618
enrichfind_hp0.0490.0043.055
enrichplot0.2750.0430.318
filter_missing_values0.0010.0000.001
getFASTA0.1200.0245.184
getHPI0.0010.0000.002
get_negativePPI0.0040.0000.003
get_positivePPI000
impute_missing_data0.0030.0000.003
plotPPI0.1220.0120.270
pred_ensembel15.258 0.69512.477
var_imp34.805 0.76835.574