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 11:06:11 -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 lconway


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: /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_1.4.3.tar.gz
StartedAt: 2023-04-10 20:41:45 -0400 (Mon, 10 Apr 2023)
EndedAt: 2023-04-10 20:47:32 -0400 (Mon, 10 Apr 2023)
EllapsedTime: 346.5 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_1.4.3.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.16-bioc/meat/HPiP.Rcheck’
* using R version 4.2.3 (2023-03-15)
* using platform: x86_64-apple-darwin17.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.4.3’
* 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 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
FSmethod      30.742  1.611  33.718
var_imp       30.582  1.575  32.259
corr_plot     29.698  1.546  31.805
pred_ensembel 11.782  0.782   8.410
enrichfindP    0.315  0.039  51.145
* 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 ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.16-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/4.2/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 version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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 97.456469 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.251205 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.355770 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.550631 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.311744 
final  value 93.109890 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.349143 
iter  10 value 94.112907
final  value 94.112903 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.391109 
iter  10 value 94.112905
iter  10 value 94.112904
iter  10 value 94.112904
final  value 94.112904 
converged
Fitting Repeat 3 

# weights:  305
initial  value 128.762993 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.832597 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.534043 
iter  10 value 94.112912
final  value 94.112903 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.358007 
iter  10 value 94.114061
final  value 94.112903 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.631434 
iter  10 value 87.358032
iter  20 value 86.291480
iter  20 value 86.291480
iter  30 value 86.202195
final  value 86.202176 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.999845 
iter  10 value 93.540030
iter  20 value 91.779604
iter  30 value 91.745630
final  value 91.745549 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.922621 
iter  10 value 93.902526
iter  20 value 93.893780
final  value 93.893766 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.591721 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.105193 
iter  10 value 94.236723
iter  20 value 89.209797
iter  30 value 86.654957
iter  40 value 86.445795
iter  50 value 85.759547
iter  60 value 84.962928
iter  70 value 83.021319
iter  80 value 82.548816
iter  90 value 82.096743
iter 100 value 82.080832
final  value 82.080832 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.155200 
iter  10 value 93.788560
iter  20 value 90.779726
iter  30 value 87.798755
iter  40 value 84.000920
iter  50 value 83.860280
iter  60 value 83.027005
iter  70 value 82.095888
iter  80 value 82.063765
iter  90 value 82.061597
final  value 82.061468 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.523697 
iter  10 value 94.485110
iter  20 value 93.431166
iter  30 value 87.049123
iter  40 value 85.152877
iter  50 value 84.545164
iter  60 value 83.181633
iter  70 value 82.412193
iter  80 value 82.176424
iter  90 value 82.062869
final  value 82.061468 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.450442 
iter  10 value 92.731755
iter  20 value 85.503422
iter  30 value 84.474885
iter  40 value 83.970342
iter  50 value 83.215836
iter  60 value 82.120681
iter  70 value 82.083898
iter  80 value 82.076261
iter  90 value 82.063680
final  value 82.055289 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.306617 
iter  10 value 94.419541
iter  20 value 91.636004
iter  30 value 87.906904
iter  40 value 86.203754
iter  50 value 84.779332
iter  60 value 82.378684
iter  70 value 81.955314
iter  80 value 81.927519
iter  90 value 81.927291
final  value 81.927236 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.726606 
iter  10 value 91.933106
iter  20 value 88.104593
iter  30 value 86.948886
iter  40 value 83.405395
iter  50 value 82.688720
iter  60 value 82.156420
iter  70 value 81.689258
iter  80 value 81.672417
iter  90 value 81.535809
iter 100 value 81.311245
final  value 81.311245 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.474936 
iter  10 value 94.178068
iter  20 value 88.237015
iter  30 value 85.594794
iter  40 value 82.982230
iter  50 value 82.229949
iter  60 value 81.883555
iter  70 value 81.452183
iter  80 value 81.348963
iter  90 value 81.155649
iter 100 value 80.949324
final  value 80.949324 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.178328 
iter  10 value 94.583310
iter  20 value 94.491414
iter  30 value 92.909708
iter  40 value 89.620534
iter  50 value 88.359787
iter  60 value 85.878142
iter  70 value 83.537811
iter  80 value 82.570443
iter  90 value 81.809234
iter 100 value 81.467608
final  value 81.467608 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.277679 
iter  10 value 94.050445
iter  20 value 90.980562
iter  30 value 84.537999
iter  40 value 82.740568
iter  50 value 82.262829
iter  60 value 82.180275
iter  70 value 81.893676
iter  80 value 81.756021
iter  90 value 81.596550
iter 100 value 81.564435
final  value 81.564435 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.760844 
iter  10 value 95.597365
iter  20 value 83.661311
iter  30 value 82.567904
iter  40 value 82.384418
iter  50 value 81.744189
iter  60 value 81.336480
iter  70 value 81.158686
iter  80 value 81.135862
iter  90 value 80.982677
iter 100 value 80.900502
final  value 80.900502 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.369116 
iter  10 value 93.950591
iter  20 value 85.158540
iter  30 value 83.901638
iter  40 value 83.254299
iter  50 value 82.561772
iter  60 value 81.867975
iter  70 value 80.962692
iter  80 value 80.687276
iter  90 value 80.652758
iter 100 value 80.619684
final  value 80.619684 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.101646 
iter  10 value 95.589739
iter  20 value 92.544326
iter  30 value 88.236807
iter  40 value 84.765627
iter  50 value 82.136483
iter  60 value 81.614581
iter  70 value 81.372602
iter  80 value 81.223687
iter  90 value 81.183755
iter 100 value 81.160107
final  value 81.160107 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.988588 
iter  10 value 93.904643
iter  20 value 89.737738
iter  30 value 84.890982
iter  40 value 84.286150
iter  50 value 83.119004
iter  60 value 82.558809
iter  70 value 81.144817
iter  80 value 80.896877
iter  90 value 80.785751
iter 100 value 80.723601
final  value 80.723601 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.722495 
iter  10 value 94.612562
iter  20 value 94.022819
iter  30 value 88.844892
iter  40 value 86.082935
iter  50 value 85.820078
iter  60 value 85.440297
iter  70 value 83.872305
iter  80 value 82.259537
iter  90 value 81.612396
iter 100 value 81.410899
final  value 81.410899 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.839273 
iter  10 value 94.311899
iter  20 value 92.194387
iter  30 value 85.114395
iter  40 value 82.324595
iter  50 value 81.919720
iter  60 value 81.610806
iter  70 value 81.410643
iter  80 value 81.360883
iter  90 value 81.210021
iter 100 value 80.797909
final  value 80.797909 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.206857 
final  value 94.485668 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.342826 
iter  10 value 94.486104
iter  20 value 93.949348
iter  30 value 93.725140
iter  40 value 93.724438
final  value 93.724404 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.307170 
final  value 94.485716 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.891424 
final  value 94.410924 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.682716 
final  value 94.485924 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.319631 
iter  10 value 94.117903
iter  20 value 94.114820
iter  30 value 90.406111
iter  40 value 89.796459
iter  50 value 87.751439
iter  60 value 84.061152
iter  70 value 83.965763
iter  80 value 83.191679
iter  90 value 82.223208
iter 100 value 81.213401
final  value 81.213401 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.648678 
iter  10 value 94.118454
iter  20 value 93.973050
final  value 93.725835 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.476733 
iter  10 value 94.117796
iter  20 value 94.077113
iter  30 value 87.403343
iter  40 value 86.874290
iter  50 value 86.847621
final  value 86.847614 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.952462 
iter  10 value 94.118127
iter  20 value 94.114206
iter  30 value 93.195388
iter  40 value 88.923501
final  value 88.915733 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.328512 
iter  10 value 94.118173
iter  20 value 94.113964
iter  30 value 94.113229
final  value 94.113226 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.147749 
iter  10 value 94.120815
iter  20 value 94.116131
iter  30 value 84.731021
iter  40 value 83.804037
iter  50 value 82.637100
final  value 82.636987 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.072908 
iter  10 value 94.491828
iter  20 value 94.467948
iter  30 value 93.685701
iter  40 value 91.961029
iter  50 value 91.960070
iter  60 value 87.015047
iter  70 value 82.191571
iter  80 value 82.051702
iter  90 value 81.847838
iter 100 value 80.924705
final  value 80.924705 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.275201 
iter  10 value 94.130275
iter  20 value 94.100182
iter  30 value 94.098933
iter  40 value 94.026490
iter  50 value 85.794658
iter  60 value 85.585670
iter  70 value 85.283305
final  value 85.233556 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.262724 
iter  10 value 94.234969
iter  20 value 94.121913
iter  30 value 92.746114
iter  40 value 87.771906
iter  50 value 86.209604
iter  60 value 85.883664
iter  70 value 85.881415
iter  80 value 85.880538
final  value 85.879885 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.562277 
iter  10 value 94.491380
iter  20 value 94.051412
final  value 93.725775 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.135113 
iter  10 value 91.070769
iter  20 value 87.588654
iter  30 value 87.573106
iter  40 value 87.569784
final  value 87.569773 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.590589 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.158728 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.430674 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.753988 
final  value 94.042012 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.058417 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.404395 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.020256 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.912144 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.923259 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.115999 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.133296 
final  value 94.038251 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.910728 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.997857 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.262983 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.123936 
iter  10 value 93.954695
iter  20 value 89.857233
iter  30 value 87.666330
iter  40 value 87.570427
iter  50 value 86.805196
iter  60 value 86.737606
iter  70 value 86.670357
iter  80 value 84.532955
iter  90 value 84.483775
iter 100 value 84.389639
final  value 84.389639 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.460107 
iter  10 value 94.032561
iter  20 value 89.917867
iter  30 value 86.347441
iter  40 value 85.246357
iter  50 value 84.713433
iter  60 value 84.626370
iter  70 value 84.593306
final  value 84.593286 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.677952 
iter  10 value 94.058537
iter  20 value 94.018545
iter  30 value 87.501492
iter  40 value 86.668041
iter  50 value 85.260353
iter  60 value 85.032502
iter  70 value 84.818403
final  value 84.800160 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.483547 
iter  10 value 94.054814
iter  20 value 93.055974
iter  30 value 92.640077
iter  40 value 92.495755
iter  50 value 92.314935
iter  60 value 92.280469
final  value 92.280397 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.645387 
iter  10 value 94.046734
iter  20 value 93.275587
iter  30 value 88.522994
iter  40 value 86.267368
iter  50 value 86.174832
iter  60 value 84.132603
iter  70 value 84.049741
iter  80 value 83.845602
final  value 83.845504 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.151748 
iter  10 value 94.057328
iter  20 value 93.514764
iter  30 value 88.520508
iter  40 value 87.823467
iter  50 value 85.934296
iter  60 value 85.128769
iter  70 value 84.631360
iter  80 value 83.761440
iter  90 value 82.413399
iter 100 value 81.104839
final  value 81.104839 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.331558 
iter  10 value 94.363809
iter  20 value 87.447536
iter  30 value 87.249118
iter  40 value 85.816719
iter  50 value 84.326658
iter  60 value 83.174949
iter  70 value 81.839500
iter  80 value 81.622502
iter  90 value 81.546123
iter 100 value 81.461558
final  value 81.461558 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.986336 
iter  10 value 93.824265
iter  20 value 90.059029
iter  30 value 84.410168
iter  40 value 82.038689
iter  50 value 81.413098
iter  60 value 81.326611
iter  70 value 81.306421
iter  80 value 81.174891
iter  90 value 81.154264
iter 100 value 81.153091
final  value 81.153091 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.796204 
iter  10 value 94.034628
iter  20 value 88.078122
iter  30 value 86.356647
iter  40 value 84.055493
iter  50 value 82.951093
iter  60 value 82.290929
iter  70 value 81.580926
iter  80 value 81.391156
iter  90 value 81.220640
iter 100 value 81.110943
final  value 81.110943 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.859439 
iter  10 value 100.008835
iter  20 value 94.226922
iter  30 value 93.393124
iter  40 value 89.713504
iter  50 value 85.071779
iter  60 value 84.910105
iter  70 value 84.575825
iter  80 value 84.145675
iter  90 value 84.045712
iter 100 value 83.655521
final  value 83.655521 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.296677 
iter  10 value 95.206236
iter  20 value 90.205091
iter  30 value 83.263417
iter  40 value 82.485225
iter  50 value 81.900099
iter  60 value 81.329797
iter  70 value 81.286046
iter  80 value 81.177794
iter  90 value 81.025237
iter 100 value 80.921503
final  value 80.921503 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.635786 
iter  10 value 94.418200
iter  20 value 89.761568
iter  30 value 86.658461
iter  40 value 86.525033
iter  50 value 86.206244
iter  60 value 84.758520
iter  70 value 84.449595
iter  80 value 83.961026
iter  90 value 83.661333
iter 100 value 82.831319
final  value 82.831319 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.002698 
iter  10 value 94.804679
iter  20 value 88.365057
iter  30 value 85.473672
iter  40 value 84.848363
iter  50 value 84.097762
iter  60 value 83.986354
iter  70 value 83.778657
iter  80 value 83.077057
iter  90 value 82.305200
iter 100 value 82.169482
final  value 82.169482 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.964106 
iter  10 value 93.996046
iter  20 value 92.948339
iter  30 value 92.703923
iter  40 value 86.253533
iter  50 value 85.059819
iter  60 value 82.402049
iter  70 value 81.930215
iter  80 value 81.779710
iter  90 value 81.619520
iter 100 value 81.352390
final  value 81.352390 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.194902 
iter  10 value 94.067530
iter  20 value 93.138563
iter  30 value 88.061238
iter  40 value 85.030299
iter  50 value 82.608054
iter  60 value 82.069442
iter  70 value 81.965696
iter  80 value 81.949433
iter  90 value 81.908483
iter 100 value 81.887391
final  value 81.887391 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.086141 
final  value 94.054689 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.012674 
iter  10 value 94.054475
iter  20 value 94.050196
iter  30 value 93.848096
iter  40 value 87.305164
iter  50 value 86.539740
iter  60 value 86.437824
final  value 86.436512 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.674565 
final  value 94.054375 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.603067 
final  value 94.054829 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.803576 
final  value 93.673191 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.797251 
iter  10 value 94.043180
iter  20 value 94.038302
iter  30 value 89.131822
iter  40 value 84.703903
iter  50 value 84.563882
iter  60 value 84.425303
iter  70 value 84.311642
iter  80 value 84.259040
iter  90 value 84.240998
iter 100 value 83.239473
final  value 83.239473 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.150458 
iter  10 value 94.057590
iter  20 value 94.053232
iter  30 value 93.978991
iter  40 value 85.897249
iter  50 value 85.602925
iter  60 value 85.594005
final  value 85.593991 
converged
Fitting Repeat 3 

# weights:  305
initial  value 127.729853 
iter  10 value 94.042931
iter  20 value 94.038487
iter  30 value 94.038273
iter  40 value 93.843904
iter  50 value 86.036805
final  value 86.036800 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.030577 
iter  10 value 94.042534
final  value 94.038301 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.755376 
iter  10 value 94.056506
iter  20 value 93.997141
iter  30 value 85.490854
iter  40 value 85.373161
final  value 85.373153 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.207848 
iter  10 value 94.046909
iter  20 value 94.039356
iter  30 value 90.104096
iter  40 value 87.161651
iter  50 value 86.588298
iter  60 value 85.764835
iter  70 value 84.321680
iter  80 value 82.924515
iter  90 value 82.696167
iter 100 value 82.684874
final  value 82.684874 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.880408 
iter  10 value 93.988372
iter  20 value 93.860968
iter  30 value 93.855181
iter  40 value 93.786075
iter  50 value 93.777981
iter  60 value 93.775580
iter  70 value 92.923398
iter  80 value 86.220345
iter  90 value 85.211799
iter 100 value 84.043397
final  value 84.043397 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.241491 
iter  10 value 93.784099
iter  20 value 93.658145
iter  30 value 93.587756
iter  40 value 92.415505
iter  50 value 92.288246
iter  60 value 92.236631
iter  70 value 92.197042
iter  80 value 92.196469
iter  90 value 92.196401
iter 100 value 92.195759
final  value 92.195759 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.906325 
iter  10 value 94.063794
iter  20 value 93.995920
iter  30 value 88.961916
iter  40 value 85.728762
iter  50 value 85.440205
iter  60 value 85.435559
iter  70 value 82.918295
iter  80 value 82.878148
iter  90 value 82.482217
iter 100 value 82.420184
final  value 82.420184 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.348068 
iter  10 value 93.953779
iter  20 value 86.751751
iter  30 value 86.373124
iter  40 value 86.368814
iter  50 value 86.356523
iter  60 value 85.637923
final  value 85.636473 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.538099 
iter  10 value 90.647111
iter  20 value 87.836316
iter  30 value 87.825153
iter  40 value 87.824716
final  value 87.824710 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.141536 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.788365 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.266564 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.202945 
final  value 93.783647 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.002689 
iter  10 value 94.090484
iter  20 value 93.946906
final  value 93.946831 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.636622 
iter  10 value 94.228679
final  value 94.228678 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.054869 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.759979 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.776012 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.368825 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.784811 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.452306 
iter  10 value 92.740676
iter  20 value 91.444469
iter  30 value 91.436555
final  value 91.436519 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.662253 
iter  10 value 93.607289
final  value 93.607287 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.751549 
iter  10 value 94.264346
iter  20 value 94.204903
final  value 94.204542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.654242 
iter  10 value 94.466871
iter  20 value 93.122715
iter  30 value 87.989121
iter  40 value 85.882931
iter  50 value 84.417979
iter  60 value 84.368385
final  value 84.368301 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.824078 
iter  10 value 94.216674
iter  20 value 85.017966
iter  30 value 84.044056
iter  40 value 83.095457
iter  50 value 81.600786
iter  60 value 81.332703
iter  70 value 81.194871
iter  80 value 81.096570
final  value 81.095867 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.946151 
iter  10 value 94.488570
iter  20 value 94.399845
iter  30 value 87.101762
iter  40 value 84.419473
iter  50 value 83.861574
iter  60 value 83.195704
iter  70 value 82.963432
iter  80 value 82.918466
final  value 82.918420 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.290095 
iter  10 value 94.422418
iter  20 value 93.630299
iter  30 value 88.398618
iter  40 value 83.219262
iter  50 value 82.885046
iter  60 value 82.617779
iter  70 value 81.521425
iter  80 value 81.302554
iter  90 value 81.138509
iter 100 value 81.096463
final  value 81.096463 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.999008 
iter  10 value 94.331034
iter  20 value 92.541912
iter  30 value 91.195270
iter  40 value 90.375153
iter  50 value 90.118120
iter  60 value 90.051548
final  value 90.050868 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.007942 
iter  10 value 92.892624
iter  20 value 90.836181
iter  30 value 87.431673
iter  40 value 84.414525
iter  50 value 81.531370
iter  60 value 80.179955
iter  70 value 79.736074
iter  80 value 79.640266
iter  90 value 79.282899
iter 100 value 79.103783
final  value 79.103783 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.667598 
iter  10 value 91.357141
iter  20 value 90.457770
iter  30 value 89.951007
iter  40 value 89.537994
iter  50 value 89.414779
iter  60 value 88.861748
iter  70 value 87.795064
iter  80 value 84.894835
iter  90 value 84.479496
iter 100 value 83.511609
final  value 83.511609 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.610962 
iter  10 value 94.111369
iter  20 value 90.458337
iter  30 value 87.585225
iter  40 value 84.207578
iter  50 value 83.087567
iter  60 value 82.801458
iter  70 value 82.439000
iter  80 value 81.972605
iter  90 value 81.833557
iter 100 value 81.820289
final  value 81.820289 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.140022 
iter  10 value 91.722835
iter  20 value 90.104064
iter  30 value 89.958448
iter  40 value 84.132072
iter  50 value 83.084330
iter  60 value 82.690778
iter  70 value 82.465787
iter  80 value 81.732175
iter  90 value 81.253541
iter 100 value 79.981727
final  value 79.981727 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.571065 
iter  10 value 91.697952
iter  20 value 87.090472
iter  30 value 86.210610
iter  40 value 84.914251
iter  50 value 83.427076
iter  60 value 82.533600
iter  70 value 81.938574
iter  80 value 81.306947
iter  90 value 81.241307
iter 100 value 81.108970
final  value 81.108970 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.520511 
iter  10 value 94.464466
iter  20 value 91.290876
iter  30 value 88.315737
iter  40 value 84.799074
iter  50 value 81.195069
iter  60 value 80.025024
iter  70 value 79.845963
iter  80 value 79.496791
iter  90 value 79.311493
iter 100 value 79.102644
final  value 79.102644 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.713274 
iter  10 value 94.369592
iter  20 value 90.454445
iter  30 value 85.325986
iter  40 value 83.814737
iter  50 value 82.712115
iter  60 value 80.984697
iter  70 value 79.926631
iter  80 value 79.388678
iter  90 value 79.267385
iter 100 value 79.001106
final  value 79.001106 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.785634 
iter  10 value 94.437994
iter  20 value 90.260620
iter  30 value 85.912316
iter  40 value 84.861123
iter  50 value 82.804159
iter  60 value 81.331809
iter  70 value 80.959309
iter  80 value 80.506785
iter  90 value 79.873442
iter 100 value 79.648176
final  value 79.648176 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 144.315327 
iter  10 value 95.157725
iter  20 value 93.483450
iter  30 value 88.151012
iter  40 value 86.080322
iter  50 value 84.873159
iter  60 value 84.031951
iter  70 value 83.957232
iter  80 value 83.307102
iter  90 value 81.661991
iter 100 value 81.112127
final  value 81.112127 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.339500 
iter  10 value 94.428591
iter  20 value 92.924106
iter  30 value 92.016884
iter  40 value 90.859891
iter  50 value 84.649468
iter  60 value 81.743521
iter  70 value 81.540398
iter  80 value 81.042629
iter  90 value 80.111915
iter 100 value 79.350400
final  value 79.350400 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.943507 
final  value 94.485961 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.486883 
iter  10 value 91.477786
iter  20 value 91.137595
iter  30 value 89.488540
iter  40 value 89.103790
iter  50 value 89.103099
final  value 89.102878 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.196952 
final  value 94.486981 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.024271 
final  value 94.277010 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.526979 
iter  10 value 93.785404
iter  20 value 90.978298
iter  30 value 86.464687
iter  40 value 83.450575
iter  50 value 81.380145
iter  60 value 80.655312
iter  70 value 80.579857
iter  80 value 80.579592
iter  90 value 80.579451
iter  90 value 80.579450
iter  90 value 80.579450
final  value 80.579450 
converged
Fitting Repeat 1 

# weights:  305
initial  value 128.714071 
iter  10 value 94.489421
iter  20 value 94.166599
iter  30 value 84.218251
iter  40 value 83.232042
iter  50 value 83.082930
iter  60 value 82.967660
iter  70 value 82.525869
iter  80 value 81.284192
iter  90 value 79.133458
iter 100 value 78.029927
final  value 78.029927 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.301908 
iter  10 value 94.489372
iter  20 value 94.298705
iter  30 value 94.207061
iter  40 value 94.205848
iter  50 value 93.799620
iter  60 value 85.682806
iter  70 value 85.053528
iter  80 value 85.027682
iter  90 value 85.020850
iter 100 value 85.020492
final  value 85.020492 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.575635 
iter  10 value 94.421681
iter  20 value 86.135619
iter  30 value 85.612270
iter  40 value 85.308058
final  value 85.305743 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.500290 
iter  10 value 94.486814
final  value 94.275662 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.447314 
iter  10 value 94.490356
iter  20 value 94.481224
iter  30 value 85.994723
iter  40 value 84.849998
iter  50 value 84.848799
iter  50 value 84.848799
final  value 84.848799 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.014452 
iter  10 value 91.770580
iter  20 value 89.542805
iter  30 value 89.541463
iter  40 value 89.510537
iter  50 value 88.364447
iter  60 value 88.359950
iter  70 value 87.162994
iter  80 value 87.152368
iter  90 value 87.151788
final  value 87.151425 
converged
Fitting Repeat 2 

# weights:  507
initial  value 139.954000 
iter  10 value 94.285902
iter  20 value 94.278777
iter  30 value 94.278042
iter  40 value 93.943347
iter  50 value 88.613180
iter  60 value 84.060915
iter  70 value 82.767525
iter  80 value 82.635781
iter  90 value 82.599446
iter 100 value 82.598837
final  value 82.598837 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.517468 
iter  10 value 94.488460
iter  20 value 93.831407
iter  30 value 89.676842
iter  40 value 89.671737
iter  50 value 83.112494
iter  60 value 81.578193
iter  70 value 79.819917
iter  80 value 79.790323
iter  90 value 79.751211
iter 100 value 79.749741
final  value 79.749741 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.512008 
iter  10 value 94.489084
iter  20 value 94.484241
iter  30 value 93.809168
iter  40 value 87.765412
iter  50 value 86.379826
iter  60 value 84.807128
iter  70 value 81.145596
iter  80 value 80.848228
final  value 80.847858 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.131828 
iter  10 value 94.283466
iter  20 value 94.278671
iter  30 value 94.277759
iter  40 value 94.277522
iter  50 value 94.250744
iter  60 value 85.439431
iter  70 value 84.833972
iter  80 value 84.819777
iter  90 value 84.322956
iter 100 value 82.386406
final  value 82.386406 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.203318 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.340261 
final  value 93.688363 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.593994 
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.146099 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.033274 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.409863 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.257420 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.159936 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.702171 
iter  10 value 92.098068
iter  20 value 92.088908
final  value 92.088889 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.579807 
iter  10 value 94.356773
iter  20 value 94.313831
final  value 94.313818 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.415206 
iter  10 value 93.421730
iter  20 value 85.679419
iter  30 value 84.186842
iter  40 value 84.185890
iter  40 value 84.185890
iter  40 value 84.185889
final  value 84.185889 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.652531 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.142417 
final  value 94.354395 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.639516 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.396143 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.081687 
iter  10 value 94.488540
iter  20 value 94.097817
iter  30 value 93.746546
iter  40 value 93.362839
iter  50 value 87.340187
iter  60 value 82.713455
iter  70 value 81.410025
iter  80 value 80.649964
iter  90 value 80.346200
iter 100 value 80.224431
final  value 80.224431 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.030146 
iter  10 value 94.487805
iter  20 value 85.960326
iter  30 value 83.660652
iter  40 value 82.872346
iter  50 value 81.689856
iter  60 value 81.578082
final  value 81.573264 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.087380 
iter  10 value 94.486603
iter  20 value 88.627571
iter  30 value 85.828874
iter  40 value 85.660973
iter  50 value 85.358044
iter  60 value 85.274314
iter  70 value 85.075988
iter  80 value 84.872605
iter  90 value 84.855464
final  value 84.855462 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.455636 
iter  10 value 94.489473
iter  20 value 93.243298
iter  30 value 91.270564
iter  40 value 88.391060
iter  50 value 87.086280
iter  60 value 86.551573
iter  70 value 86.446571
iter  80 value 86.413048
iter  90 value 86.391384
final  value 86.391364 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.780101 
iter  10 value 94.077577
iter  20 value 91.804968
iter  30 value 88.034567
iter  40 value 87.252151
iter  50 value 84.819776
iter  60 value 83.728047
iter  70 value 82.972892
iter  80 value 82.315576
iter  90 value 81.774214
iter 100 value 81.589459
final  value 81.589459 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.461585 
iter  10 value 94.522429
iter  20 value 90.259940
iter  30 value 86.048318
iter  40 value 83.128768
iter  50 value 82.056877
iter  60 value 81.079156
iter  70 value 79.952245
iter  80 value 79.663715
iter  90 value 79.147492
iter 100 value 78.594128
final  value 78.594128 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.790705 
iter  10 value 93.055170
iter  20 value 83.581126
iter  30 value 80.918625
iter  40 value 80.142648
iter  50 value 79.521776
iter  60 value 79.272214
iter  70 value 79.079511
iter  80 value 78.695203
iter  90 value 78.577605
iter 100 value 78.568207
final  value 78.568207 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.506877 
iter  10 value 94.175733
iter  20 value 89.597027
iter  30 value 85.183651
iter  40 value 84.051039
iter  50 value 83.266594
iter  60 value 83.046545
iter  70 value 82.608368
iter  80 value 82.201553
iter  90 value 82.050204
iter 100 value 81.117462
final  value 81.117462 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.231865 
iter  10 value 94.713184
iter  20 value 93.856179
iter  30 value 90.218672
iter  40 value 83.732340
iter  50 value 83.585838
iter  60 value 80.988357
iter  70 value 79.560627
iter  80 value 78.585984
iter  90 value 78.380530
iter 100 value 78.270348
final  value 78.270348 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.883628 
iter  10 value 92.460268
iter  20 value 87.752959
iter  30 value 82.276612
iter  40 value 81.740411
iter  50 value 81.367995
iter  60 value 79.802798
iter  70 value 79.318234
iter  80 value 78.944563
iter  90 value 78.624396
iter 100 value 78.572510
final  value 78.572510 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.114323 
iter  10 value 94.901442
iter  20 value 94.219688
iter  30 value 87.080394
iter  40 value 86.741026
iter  50 value 84.833558
iter  60 value 80.478032
iter  70 value 79.960274
iter  80 value 79.601330
iter  90 value 78.865713
iter 100 value 78.376579
final  value 78.376579 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.975025 
iter  10 value 100.352091
iter  20 value 94.079781
iter  30 value 88.290432
iter  40 value 81.908347
iter  50 value 80.909947
iter  60 value 80.424200
iter  70 value 79.698403
iter  80 value 79.486250
iter  90 value 78.910621
iter 100 value 78.633480
final  value 78.633480 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.671422 
iter  10 value 94.004343
iter  20 value 89.774867
iter  30 value 88.152937
iter  40 value 86.055828
iter  50 value 85.071939
iter  60 value 84.498277
iter  70 value 80.934023
iter  80 value 80.230021
iter  90 value 80.018769
iter 100 value 79.899391
final  value 79.899391 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.073842 
iter  10 value 94.509674
iter  20 value 88.206828
iter  30 value 83.269346
iter  40 value 82.312653
iter  50 value 81.809060
iter  60 value 80.429949
iter  70 value 79.258084
iter  80 value 78.946535
iter  90 value 78.748146
iter 100 value 78.549250
final  value 78.549250 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.632793 
iter  10 value 93.285357
iter  20 value 84.647600
iter  30 value 83.832752
iter  40 value 82.745065
iter  50 value 82.253806
iter  60 value 81.421272
iter  70 value 80.937117
iter  80 value 80.053373
iter  90 value 79.653411
iter 100 value 79.315127
final  value 79.315127 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.819126 
iter  10 value 94.485990
iter  20 value 94.484227
iter  20 value 94.484226
iter  20 value 94.484226
final  value 94.484226 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.046131 
final  value 94.485887 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.228451 
final  value 94.485877 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.732193 
final  value 94.485837 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.359964 
final  value 94.486337 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.804293 
iter  10 value 94.489145
iter  20 value 94.484392
final  value 94.484226 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.041036 
iter  10 value 94.359591
iter  20 value 92.786986
iter  30 value 86.352289
iter  40 value 86.333665
iter  50 value 82.791085
iter  60 value 82.752623
iter  70 value 82.750912
final  value 82.750901 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.358363 
iter  10 value 94.488785
iter  20 value 94.484387
final  value 94.484262 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.512754 
iter  10 value 94.200818
iter  20 value 94.194420
iter  30 value 86.094593
iter  40 value 85.242270
iter  50 value 85.227676
iter  60 value 85.227242
final  value 85.227177 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.248879 
iter  10 value 94.500750
iter  20 value 94.495399
iter  30 value 93.671239
iter  40 value 93.635434
iter  50 value 93.631086
iter  60 value 82.214581
iter  70 value 81.347803
iter  80 value 81.262888
iter  90 value 81.123955
iter 100 value 81.115530
final  value 81.115530 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.844020 
iter  10 value 94.510230
iter  20 value 94.449574
iter  30 value 86.430411
iter  40 value 86.329506
iter  50 value 86.151929
iter  60 value 85.229228
iter  70 value 85.187152
iter  80 value 84.708755
iter  90 value 82.139394
iter 100 value 81.212276
final  value 81.212276 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.231373 
iter  10 value 94.491742
iter  20 value 94.433597
iter  30 value 82.848577
iter  40 value 82.698712
iter  50 value 82.315749
iter  60 value 80.498140
iter  70 value 79.876371
iter  80 value 79.847849
iter  90 value 79.845127
iter 100 value 79.844478
final  value 79.844478 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.195965 
iter  10 value 90.006451
iter  20 value 85.257248
iter  30 value 85.230076
iter  40 value 85.206826
iter  50 value 83.935771
iter  60 value 82.912979
iter  70 value 79.909061
iter  80 value 79.287748
iter  90 value 78.877378
iter 100 value 78.693371
final  value 78.693371 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.665073 
iter  10 value 94.375358
iter  20 value 91.604566
iter  30 value 91.585053
iter  40 value 91.584442
iter  50 value 91.582077
iter  60 value 91.580719
iter  70 value 91.580374
iter  80 value 91.578504
iter  90 value 91.578113
iter 100 value 91.577716
final  value 91.577716 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.149011 
iter  10 value 94.493847
iter  20 value 94.486242
iter  30 value 93.897402
iter  40 value 93.580409
iter  50 value 93.579192
iter  60 value 93.561199
iter  70 value 82.820383
iter  80 value 82.816762
iter  90 value 82.292942
final  value 82.283050 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.678104 
final  value 93.810010 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.189874 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.528209 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.746764 
final  value 93.288889 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.852862 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.361071 
final  value 93.810010 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.388395 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.576699 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.588707 
iter  10 value 93.615646
iter  20 value 89.873639
iter  30 value 84.104514
iter  40 value 84.078716
iter  50 value 84.075381
final  value 84.075275 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.448913 
iter  10 value 91.050433
iter  20 value 86.315017
final  value 86.247138 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.713769 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.151033 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.452298 
final  value 93.810010 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.856865 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.765370 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.643548 
iter  10 value 93.538787
iter  20 value 83.564181
iter  30 value 83.403976
iter  40 value 82.981321
iter  50 value 82.927906
final  value 82.927902 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.903512 
iter  10 value 94.104764
iter  20 value 93.453345
iter  30 value 85.007876
iter  40 value 84.251043
iter  50 value 83.759327
iter  60 value 83.694746
iter  70 value 83.408678
iter  80 value 83.376059
final  value 83.376055 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.841138 
iter  10 value 94.067836
iter  20 value 94.034309
iter  30 value 93.148878
iter  40 value 86.630981
iter  50 value 85.519226
iter  60 value 83.345268
iter  70 value 81.909800
iter  80 value 81.303513
iter  90 value 81.008962
iter 100 value 80.502717
final  value 80.502717 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.652263 
iter  10 value 88.150234
iter  20 value 83.792103
iter  30 value 83.150432
iter  40 value 83.042558
iter  50 value 82.928098
final  value 82.927902 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.098020 
iter  10 value 94.057580
iter  20 value 93.999979
iter  30 value 85.663654
iter  40 value 85.378745
iter  50 value 83.633864
iter  60 value 83.443313
iter  70 value 83.378665
final  value 83.376055 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.030155 
iter  10 value 94.038061
iter  20 value 93.577023
iter  30 value 89.512961
iter  40 value 88.051268
iter  50 value 87.062650
iter  60 value 85.841617
iter  70 value 85.485526
iter  80 value 81.593096
iter  90 value 80.552257
iter 100 value 80.299122
final  value 80.299122 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.287442 
iter  10 value 93.788812
iter  20 value 86.900080
iter  30 value 83.952381
iter  40 value 81.757239
iter  50 value 80.631179
iter  60 value 79.838966
iter  70 value 79.729444
iter  80 value 79.530332
iter  90 value 79.466931
iter 100 value 79.427729
final  value 79.427729 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.125668 
iter  10 value 94.034196
iter  20 value 92.881889
iter  30 value 88.212704
iter  40 value 86.041242
iter  50 value 84.670467
iter  60 value 83.523810
iter  70 value 83.226720
iter  80 value 82.853554
iter  90 value 81.657196
iter 100 value 80.899283
final  value 80.899283 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.693112 
iter  10 value 86.329053
iter  20 value 84.067889
iter  30 value 82.775135
iter  40 value 80.931661
iter  50 value 80.344630
iter  60 value 80.096269
iter  70 value 80.024465
iter  80 value 79.808450
iter  90 value 79.531122
iter 100 value 79.293332
final  value 79.293332 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.581501 
iter  10 value 93.063591
iter  20 value 86.466894
iter  30 value 82.487860
iter  40 value 80.380921
iter  50 value 79.616906
iter  60 value 79.107537
iter  70 value 78.946028
iter  80 value 78.846380
iter  90 value 78.808984
iter 100 value 78.803385
final  value 78.803385 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.209051 
iter  10 value 94.415993
iter  20 value 91.862664
iter  30 value 85.665716
iter  40 value 83.843173
iter  50 value 83.024811
iter  60 value 81.792777
iter  70 value 81.510914
iter  80 value 81.154087
iter  90 value 80.723697
iter 100 value 80.539751
final  value 80.539751 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.701707 
iter  10 value 93.913016
iter  20 value 93.588187
iter  30 value 92.430689
iter  40 value 87.217730
iter  50 value 81.725844
iter  60 value 81.166527
iter  70 value 80.423993
iter  80 value 80.327053
iter  90 value 80.136085
iter 100 value 79.635523
final  value 79.635523 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.482173 
iter  10 value 103.147131
iter  20 value 96.412751
iter  30 value 92.137160
iter  40 value 87.844106
iter  50 value 86.033290
iter  60 value 83.631186
iter  70 value 82.113366
iter  80 value 81.658215
iter  90 value 79.765331
iter 100 value 79.537722
final  value 79.537722 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.482671 
iter  10 value 96.759594
iter  20 value 93.690878
iter  30 value 87.330871
iter  40 value 85.687159
iter  50 value 81.424722
iter  60 value 80.248996
iter  70 value 79.433588
iter  80 value 78.886678
iter  90 value 78.809312
iter 100 value 78.784424
final  value 78.784424 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.878868 
iter  10 value 94.268055
iter  20 value 89.179424
iter  30 value 86.757582
iter  40 value 83.568319
iter  50 value 81.308579
iter  60 value 80.271629
iter  70 value 79.471036
iter  80 value 78.967800
iter  90 value 78.762148
iter 100 value 78.670339
final  value 78.670339 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.584480 
final  value 94.054603 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.980534 
final  value 94.054736 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.216008 
final  value 94.054591 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.261969 
final  value 94.054699 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.492270 
iter  10 value 94.054387
iter  20 value 94.052930
iter  30 value 93.356553
iter  40 value 93.316852
final  value 93.315939 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.294774 
iter  10 value 92.805852
iter  20 value 92.780501
iter  30 value 92.778694
iter  40 value 89.922890
iter  50 value 84.256442
iter  60 value 82.267425
iter  70 value 82.237155
iter  80 value 82.233910
iter  90 value 82.229455
iter 100 value 82.228509
final  value 82.228509 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 94.953292 
iter  10 value 94.058183
iter  20 value 92.780761
iter  30 value 92.568588
iter  40 value 90.642041
iter  50 value 83.922433
iter  60 value 83.915997
iter  70 value 82.118219
iter  80 value 82.115636
iter  90 value 82.106654
iter 100 value 81.629192
final  value 81.629192 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.957500 
iter  10 value 93.609443
iter  20 value 92.999957
iter  30 value 82.331205
iter  40 value 81.396376
iter  50 value 79.171594
iter  60 value 78.161035
iter  70 value 77.710370
iter  80 value 77.694231
iter  90 value 77.682279
iter 100 value 77.571747
final  value 77.571747 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.052355 
iter  10 value 93.945320
iter  20 value 93.300189
iter  30 value 87.416672
iter  40 value 84.367024
iter  50 value 81.783955
iter  60 value 80.998263
iter  70 value 80.052864
iter  80 value 79.885043
iter  90 value 79.862846
iter 100 value 79.861966
final  value 79.861966 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.536872 
iter  10 value 94.057190
iter  20 value 93.326674
iter  30 value 87.731549
iter  40 value 85.074004
iter  50 value 85.072374
iter  60 value 85.013247
iter  70 value 84.643293
iter  80 value 82.656419
iter  90 value 81.314333
iter 100 value 81.140358
final  value 81.140358 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.922437 
iter  10 value 93.339041
iter  20 value 93.331229
iter  30 value 93.319406
iter  40 value 93.317188
iter  50 value 89.098173
iter  60 value 85.072834
iter  70 value 84.573079
iter  80 value 83.301269
iter  90 value 83.180250
iter 100 value 83.179927
final  value 83.179927 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.403370 
iter  10 value 93.661150
iter  20 value 90.600503
iter  30 value 90.155991
iter  40 value 90.149609
iter  50 value 89.070246
iter  60 value 83.692727
iter  70 value 81.998872
iter  80 value 80.388349
iter  90 value 79.982102
iter 100 value 79.593271
final  value 79.593271 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.518288 
iter  10 value 94.059375
iter  20 value 93.697868
iter  30 value 86.685092
iter  40 value 86.621931
iter  50 value 86.620969
iter  60 value 86.620064
iter  70 value 86.173168
iter  80 value 81.166377
iter  90 value 79.871273
iter 100 value 78.460513
final  value 78.460513 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.292952 
iter  10 value 92.765998
iter  20 value 92.594758
iter  30 value 86.201337
iter  40 value 85.646632
iter  50 value 85.549451
iter  60 value 85.188103
iter  70 value 85.185752
iter  80 value 85.143374
iter  90 value 85.140763
iter 100 value 85.140509
final  value 85.140509 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.313834 
iter  10 value 89.229954
iter  20 value 85.293122
iter  30 value 85.291677
iter  40 value 85.176844
iter  50 value 85.161566
iter  60 value 85.161155
iter  70 value 85.158377
final  value 85.158314 
converged
Fitting Repeat 1 

# weights:  305
initial  value 131.485618 
iter  10 value 117.708036
iter  20 value 108.123259
iter  30 value 104.699262
iter  40 value 103.837411
iter  50 value 103.152516
iter  60 value 102.636573
iter  70 value 102.253626
iter  80 value 101.804803
iter  90 value 101.457671
iter 100 value 101.400407
final  value 101.400407 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 135.650206 
iter  10 value 116.351420
iter  20 value 108.032955
iter  30 value 107.298395
iter  40 value 106.783176
iter  50 value 103.404730
iter  60 value 101.910094
iter  70 value 101.751212
iter  80 value 101.461723
iter  90 value 101.248490
iter 100 value 100.978609
final  value 100.978609 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 148.116760 
iter  10 value 117.793012
iter  20 value 115.965491
iter  30 value 115.476707
iter  40 value 112.273207
iter  50 value 109.226299
iter  60 value 107.392718
iter  70 value 106.652895
iter  80 value 104.129479
iter  90 value 102.040478
iter 100 value 101.083638
final  value 101.083638 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 137.642882 
iter  10 value 117.863092
iter  20 value 109.468081
iter  30 value 108.661063
iter  40 value 108.370734
iter  50 value 107.242980
iter  60 value 105.375647
iter  70 value 105.038120
iter  80 value 104.943073
iter  90 value 103.489930
iter 100 value 102.076846
final  value 102.076846 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 131.693624 
iter  10 value 117.690961
iter  20 value 108.564841
iter  30 value 107.729320
iter  40 value 105.746763
iter  50 value 105.346342
iter  60 value 105.029100
iter  70 value 105.012552
iter  80 value 104.985547
iter  90 value 104.947813
iter 100 value 103.994881
final  value 103.994881 
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 Apr 10 20:47:22 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 
 36.481   1.625  83.391 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod30.742 1.61133.718
FreqInteractors0.3040.0150.461
calculateAAC0.0530.0080.091
calculateAutocor0.2860.0550.344
calculateCTDC0.0760.0040.081
calculateCTDD0.5470.0410.592
calculateCTDT0.2220.0220.244
calculateCTriad0.3460.0250.372
calculateDC0.0770.0110.088
calculateF0.2710.0230.294
calculateKSAAP0.0850.0100.095
calculateQD_Sm1.7030.1292.023
calculateTC1.6610.1761.845
calculateTC_Sm0.220.010.23
corr_plot29.698 1.54631.805
enrichfindP 0.315 0.03951.145
enrichfind_hp0.0260.0063.439
enrichplot0.2220.0150.238
filter_missing_values0.0010.0000.001
getFASTA0.0810.0144.433
getHPI0.0000.0010.001
get_negativePPI0.0010.0000.002
get_positivePPI000
impute_missing_data0.0020.0010.002
plotPPI0.0660.0030.068
pred_ensembel11.782 0.782 8.410
var_imp30.582 1.57532.259