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This page was generated on 2024-05-04 11:39:21 -0400 (Sat, 04 May 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.3 LTS)x86_644.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" 4753
palomino3Windows Server 2022 Datacenterx644.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" 4486
lconwaymacOS 12.7.1 Montereyx86_644.4.0 beta (2024-04-14 r86421) -- "Puppy Cup" 4519
kunpeng2Linux (openEuler 22.03 LTS-SP1)aarch644.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" 4479
Click on any hostname to see more info about the system (e.g. compilers)      (*) as reported by 'uname -p', except on Windows and Mac OS X

Package 987/2300HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
HPiP 1.10.0  (landing page)
Matineh Rahmatbakhsh
Snapshot Date: 2024-05-03 14:00:19 -0400 (Fri, 03 May 2024)
git_url: https://git.bioconductor.org/packages/HPiP
git_branch: RELEASE_3_19
git_last_commit: 09dc3c1
git_last_commit_date: 2024-04-30 11:37:16 -0400 (Tue, 30 Apr 2024)
nebbiolo1Linux (Ubuntu 22.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino3Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.7.1 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 22.03 LTS-SP1) / aarch64  OK    OK    OK  
kjohnson3macOS 13.6.5 Ventura / arm64see weekly results here

CHECK results for HPiP on lconway


To the developers/maintainers of the HPiP package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.

raw results


Summary

Package: HPiP
Version: 1.10.0
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.10.0.tar.gz
StartedAt: 2024-05-03 22:33:56 -0400 (Fri, 03 May 2024)
EndedAt: 2024-05-03 22:39:18 -0400 (Fri, 03 May 2024)
EllapsedTime: 321.7 seconds
RetCode: 0
Status:   OK  
CheckDir: HPiP.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 beta (2024-04-14 r86421)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.10.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... 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       37.207  2.177  39.941
FSmethod      35.116  1.989  37.567
corr_plot     35.131  1.915  37.405
pred_ensembel 14.793  0.587  11.418
enrichfindP    0.511  0.067  19.623
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.19-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/4.4-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

Tests output

HPiP.Rcheck/tests/runTests.Rout


R version 4.4.0 beta (2024-04-14 r86421) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 96.855511 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.909682 
iter  10 value 94.443243
iter  10 value 94.443243
iter  10 value 94.443243
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.213303 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.372338 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.506322 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.980112 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.470463 
iter  10 value 92.963394
final  value 92.739814 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.634272 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.191575 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.321938 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.891251 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.944036 
iter  10 value 94.383645
final  value 94.383623 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.723619 
iter  10 value 94.385077
iter  20 value 93.738875
iter  30 value 91.865316
iter  40 value 91.823484
iter  50 value 91.823082
final  value 91.823077 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.005611 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.455028 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.313264 
iter  10 value 94.226852
iter  20 value 88.518569
iter  30 value 88.175064
iter  40 value 86.871640
iter  50 value 84.732570
iter  60 value 84.407348
iter  70 value 84.162653
iter  80 value 84.097895
iter  90 value 84.074229
final  value 84.074014 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.285147 
iter  10 value 94.453895
iter  20 value 91.323071
iter  30 value 84.568155
iter  40 value 83.595028
iter  50 value 83.213520
iter  60 value 82.774217
iter  70 value 82.669657
final  value 82.669432 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.733429 
iter  10 value 94.514444
iter  20 value 94.407856
iter  30 value 93.818229
iter  40 value 93.630986
iter  50 value 88.353771
iter  60 value 86.659503
iter  70 value 86.649678
iter  80 value 86.637580
iter  90 value 86.549397
iter 100 value 86.453217
final  value 86.453217 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.695483 
iter  10 value 94.344785
iter  20 value 92.033022
iter  30 value 87.992153
iter  40 value 85.667598
iter  50 value 85.478709
iter  60 value 85.270511
iter  70 value 84.924951
iter  80 value 82.125967
iter  90 value 81.215274
iter 100 value 80.422091
final  value 80.422091 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.661501 
iter  10 value 94.460124
iter  20 value 93.838598
iter  30 value 93.511042
iter  40 value 92.471014
iter  50 value 85.858837
iter  60 value 82.872356
iter  70 value 82.273415
iter  80 value 81.280112
iter  90 value 80.581679
iter 100 value 80.053874
final  value 80.053874 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.480520 
iter  10 value 94.488729
iter  20 value 93.887180
iter  30 value 93.568595
iter  40 value 92.446725
iter  50 value 85.966144
iter  60 value 84.258990
iter  70 value 81.980647
iter  80 value 81.584780
iter  90 value 81.293117
iter 100 value 80.355458
final  value 80.355458 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.682103 
iter  10 value 94.440418
iter  20 value 87.936615
iter  30 value 85.028600
iter  40 value 83.803623
iter  50 value 83.453119
iter  60 value 82.004506
iter  70 value 80.849111
iter  80 value 80.522681
iter  90 value 80.333042
iter 100 value 80.249678
final  value 80.249678 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.692561 
iter  10 value 94.808793
iter  20 value 93.246484
iter  30 value 84.551945
iter  40 value 84.301601
iter  50 value 81.074243
iter  60 value 79.415680
iter  70 value 78.690062
iter  80 value 78.488650
iter  90 value 78.378946
iter 100 value 78.226972
final  value 78.226972 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.923445 
iter  10 value 94.026313
iter  20 value 85.717926
iter  30 value 84.171040
iter  40 value 83.440537
iter  50 value 82.131607
iter  60 value 79.361299
iter  70 value 78.654230
iter  80 value 78.331198
iter  90 value 78.234318
iter 100 value 78.216885
final  value 78.216885 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.717153 
iter  10 value 94.359031
iter  20 value 93.767992
iter  30 value 86.814071
iter  40 value 85.406989
iter  50 value 83.908358
iter  60 value 83.465182
iter  70 value 82.913771
iter  80 value 81.912703
iter  90 value 80.621512
iter 100 value 79.714470
final  value 79.714470 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.898031 
iter  10 value 94.347048
iter  20 value 84.726732
iter  30 value 83.728244
iter  40 value 83.053995
iter  50 value 82.228556
iter  60 value 81.549919
iter  70 value 80.810417
iter  80 value 80.277985
iter  90 value 79.565251
iter 100 value 78.781151
final  value 78.781151 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.838796 
iter  10 value 94.567175
iter  20 value 91.937127
iter  30 value 88.316431
iter  40 value 84.578003
iter  50 value 83.435011
iter  60 value 82.946420
iter  70 value 81.206387
iter  80 value 80.400538
iter  90 value 79.567542
iter 100 value 78.929063
final  value 78.929063 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.802547 
iter  10 value 94.582991
iter  20 value 92.772204
iter  30 value 85.461235
iter  40 value 82.486338
iter  50 value 81.578915
iter  60 value 80.063801
iter  70 value 79.066205
iter  80 value 78.825748
iter  90 value 78.786531
iter 100 value 78.588795
final  value 78.588795 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.005385 
iter  10 value 94.205407
iter  20 value 86.853411
iter  30 value 86.082706
iter  40 value 84.792484
iter  50 value 82.194520
iter  60 value 81.381317
iter  70 value 79.687262
iter  80 value 78.689737
iter  90 value 78.188126
iter 100 value 78.009368
final  value 78.009368 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.547117 
iter  10 value 91.677255
iter  20 value 83.265343
iter  30 value 81.134443
iter  40 value 80.484064
iter  50 value 80.242073
iter  60 value 80.046781
iter  70 value 78.772610
iter  80 value 78.268002
iter  90 value 78.137379
iter 100 value 78.095982
final  value 78.095982 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.120949 
final  value 94.485730 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.353628 
final  value 94.444642 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.181073 
iter  10 value 94.489015
final  value 94.487279 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.938675 
iter  10 value 94.485781
iter  20 value 94.484215
final  value 94.484209 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.604986 
iter  10 value 94.444964
iter  20 value 93.160083
iter  30 value 88.214626
iter  40 value 85.934600
iter  50 value 85.358481
final  value 85.355433 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.458060 
iter  10 value 94.489395
iter  20 value 94.484346
final  value 94.484237 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.042339 
iter  10 value 94.488920
iter  20 value 94.484356
iter  30 value 94.484160
iter  40 value 93.688530
final  value 93.688493 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.419279 
iter  10 value 93.693508
iter  20 value 93.542876
iter  30 value 93.301445
iter  40 value 93.300200
final  value 93.300155 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.029885 
iter  10 value 94.433728
iter  20 value 90.352446
iter  30 value 89.075130
iter  40 value 85.136364
iter  50 value 83.959076
iter  60 value 82.931889
iter  70 value 82.521886
iter  80 value 80.629949
iter  90 value 78.190049
iter 100 value 77.818205
final  value 77.818205 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 94.677918 
iter  10 value 94.489548
iter  20 value 94.400475
iter  30 value 92.259606
iter  40 value 92.210168
final  value 92.209947 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.036335 
iter  10 value 94.492147
iter  20 value 94.484801
iter  30 value 93.921475
iter  40 value 93.688551
final  value 93.688541 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.117817 
iter  10 value 93.941905
iter  20 value 92.741490
iter  30 value 92.738380
iter  40 value 89.777009
iter  50 value 89.388373
iter  60 value 89.379734
iter  70 value 89.378564
iter  80 value 89.376627
iter  90 value 88.203447
iter 100 value 80.021232
final  value 80.021232 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.698775 
iter  10 value 94.451478
iter  20 value 94.002516
iter  30 value 86.652088
iter  40 value 83.342566
iter  50 value 83.340751
iter  60 value 83.123508
final  value 83.119220 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.811028 
iter  10 value 94.451887
iter  20 value 94.443860
final  value 94.443394 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.410115 
iter  10 value 93.305661
iter  20 value 92.700999
final  value 92.700570 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.680452 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.162929 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.953083 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 114.880951 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.836701 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.281058 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.933611 
iter  10 value 93.231692
iter  20 value 93.225338
final  value 93.225316 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.971343 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.544160 
iter  10 value 91.911309
iter  20 value 90.155258
iter  20 value 90.155258
iter  30 value 90.140509
final  value 90.140459 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.227844 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.839799 
iter  10 value 92.748925
final  value 92.706753 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.857713 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.258900 
final  value 93.457887 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.613731 
iter  10 value 93.582419
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.500858 
iter  10 value 93.457889
final  value 93.457887 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.005931 
iter  10 value 94.026792
iter  20 value 88.603761
iter  30 value 87.760304
iter  40 value 87.367955
iter  50 value 86.856847
iter  60 value 84.671194
iter  70 value 84.075109
iter  80 value 84.014804
final  value 84.014760 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.805794 
iter  10 value 93.627400
iter  20 value 86.385827
iter  30 value 84.719005
iter  40 value 84.370959
iter  50 value 84.014946
iter  60 value 83.522041
iter  70 value 83.391896
final  value 83.391457 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.325299 
iter  10 value 94.117695
iter  20 value 94.056391
iter  30 value 93.834514
iter  40 value 93.684798
iter  50 value 93.427798
iter  60 value 84.972714
iter  70 value 83.808838
iter  80 value 82.856978
iter  90 value 82.076195
iter 100 value 81.709012
final  value 81.709012 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.359563 
iter  10 value 94.844362
iter  20 value 94.056856
iter  30 value 93.987206
iter  40 value 93.851931
iter  50 value 93.749554
iter  60 value 84.855538
iter  70 value 84.049669
iter  80 value 83.169728
iter  90 value 82.708664
iter 100 value 82.619916
final  value 82.619916 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.042451 
iter  10 value 93.824878
iter  20 value 85.180189
iter  30 value 84.498524
iter  40 value 84.252395
iter  50 value 83.903508
iter  60 value 82.812495
iter  70 value 82.704880
iter  80 value 82.673761
final  value 82.673753 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.414414 
iter  10 value 94.085960
iter  20 value 86.029085
iter  30 value 84.671758
iter  40 value 83.628473
iter  50 value 82.741410
iter  60 value 81.884660
iter  70 value 81.494048
iter  80 value 80.958162
iter  90 value 80.629771
iter 100 value 80.533592
final  value 80.533592 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.472329 
iter  10 value 93.833917
iter  20 value 91.292879
iter  30 value 87.079881
iter  40 value 86.068395
iter  50 value 82.731932
iter  60 value 81.253468
iter  70 value 81.144023
iter  80 value 80.985774
iter  90 value 80.947913
iter 100 value 80.933016
final  value 80.933016 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.161210 
iter  10 value 94.931349
iter  20 value 85.366435
iter  30 value 84.536939
iter  40 value 83.100189
iter  50 value 82.616009
iter  60 value 82.463060
iter  70 value 81.656531
iter  80 value 81.646892
iter  90 value 81.599824
iter 100 value 81.191936
final  value 81.191936 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.126963 
iter  10 value 93.698298
iter  20 value 87.733735
iter  30 value 87.305193
iter  40 value 86.047827
iter  50 value 81.711894
iter  60 value 81.253825
iter  70 value 81.131566
iter  80 value 81.040060
iter  90 value 80.652288
iter 100 value 80.484007
final  value 80.484007 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.181083 
iter  10 value 94.045097
iter  20 value 90.569563
iter  30 value 86.055601
iter  40 value 85.076268
iter  50 value 83.267467
iter  60 value 82.760537
iter  70 value 82.394143
iter  80 value 82.226811
iter  90 value 82.191087
iter 100 value 81.458802
final  value 81.458802 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.821195 
iter  10 value 94.401165
iter  20 value 91.930427
iter  30 value 85.212592
iter  40 value 84.363964
iter  50 value 83.001446
iter  60 value 81.799179
iter  70 value 81.611409
iter  80 value 81.437287
iter  90 value 81.224943
iter 100 value 80.945036
final  value 80.945036 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 140.972801 
iter  10 value 93.983165
iter  20 value 88.643258
iter  30 value 86.002961
iter  40 value 85.243043
iter  50 value 85.006895
iter  60 value 84.264165
iter  70 value 82.594209
iter  80 value 81.872515
iter  90 value 81.507585
iter 100 value 81.381402
final  value 81.381402 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.884891 
iter  10 value 86.711937
iter  20 value 85.311933
iter  30 value 83.882999
iter  40 value 83.661534
iter  50 value 83.520889
iter  60 value 82.689741
iter  70 value 82.169728
iter  80 value 81.844501
iter  90 value 81.653545
iter 100 value 81.414504
final  value 81.414504 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.050948 
iter  10 value 94.952968
iter  20 value 94.259077
iter  30 value 93.516804
iter  40 value 86.518280
iter  50 value 84.582439
iter  60 value 84.251369
iter  70 value 83.004674
iter  80 value 81.132413
iter  90 value 80.807354
iter 100 value 80.340087
final  value 80.340087 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 137.337401 
iter  10 value 93.320526
iter  20 value 85.982833
iter  30 value 84.245080
iter  40 value 83.647479
iter  50 value 83.080500
iter  60 value 82.661965
iter  70 value 81.764217
iter  80 value 80.827378
iter  90 value 80.610381
iter 100 value 80.537958
final  value 80.537958 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.398437 
final  value 94.054585 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.284079 
iter  10 value 93.941872
iter  20 value 93.584266
iter  30 value 93.583232
final  value 93.583217 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.724149 
final  value 94.036595 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.892460 
final  value 94.054609 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.615692 
iter  10 value 94.054278
iter  20 value 94.052928
final  value 94.052923 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.114809 
iter  10 value 93.587703
iter  20 value 93.013932
iter  30 value 85.245042
iter  40 value 84.055365
iter  50 value 83.059025
iter  60 value 83.042051
iter  70 value 83.016811
iter  80 value 83.016414
iter  90 value 82.963341
iter 100 value 82.868089
final  value 82.868089 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.089892 
iter  10 value 93.587245
iter  20 value 93.583840
iter  30 value 93.334286
iter  40 value 84.910019
iter  50 value 84.641775
iter  60 value 84.637724
iter  70 value 84.418069
iter  80 value 84.404083
iter  90 value 84.217097
iter 100 value 83.080634
final  value 83.080634 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.358968 
iter  10 value 93.840934
iter  20 value 93.837418
iter  30 value 93.440598
iter  40 value 93.344135
final  value 93.342325 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.626706 
iter  10 value 94.057823
iter  20 value 93.758738
iter  30 value 86.433153
iter  40 value 84.546715
iter  50 value 83.949580
iter  60 value 82.395780
iter  70 value 82.014093
iter  80 value 82.013241
final  value 82.012597 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.783827 
iter  10 value 90.421732
iter  20 value 87.418658
iter  30 value 87.202605
iter  40 value 87.166624
iter  50 value 87.165083
iter  60 value 87.161525
iter  70 value 87.156174
iter  80 value 87.155964
iter  90 value 82.982411
iter 100 value 82.395570
final  value 82.395570 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.634520 
iter  10 value 93.912434
iter  20 value 87.453499
iter  30 value 83.609584
iter  40 value 82.294134
iter  50 value 82.146530
iter  60 value 81.526689
iter  70 value 81.371353
iter  80 value 81.351949
final  value 81.351907 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.347401 
iter  10 value 94.059794
iter  20 value 94.047610
iter  30 value 93.358899
iter  40 value 91.191675
iter  50 value 90.264042
iter  60 value 90.263641
iter  70 value 90.017107
iter  80 value 83.511863
iter  90 value 82.866317
iter 100 value 82.858660
final  value 82.858660 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.884158 
iter  10 value 88.563829
iter  20 value 88.507541
iter  30 value 86.393778
iter  40 value 86.390282
iter  50 value 83.224376
iter  60 value 80.858430
iter  70 value 80.234942
iter  80 value 80.023140
iter  90 value 79.983435
iter 100 value 79.814273
final  value 79.814273 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.383935 
iter  10 value 93.590244
iter  20 value 93.584372
iter  30 value 93.569145
final  value 93.568593 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.795055 
iter  10 value 94.061047
iter  20 value 94.052177
iter  30 value 92.446756
iter  40 value 88.050002
iter  50 value 88.047714
iter  60 value 88.044575
iter  70 value 88.043304
iter  80 value 87.951911
iter  90 value 87.260482
iter 100 value 83.128473
final  value 83.128473 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.207109 
iter  10 value 93.109891
final  value 93.109890 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.629282 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.209718 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.476319 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.056300 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.861219 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.429124 
iter  10 value 93.110246
final  value 93.109891 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.754598 
iter  10 value 94.479296
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.241875 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.201159 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.976257 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.079263 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.599487 
iter  10 value 93.109892
final  value 93.109890 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.679573 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.649436 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.930227 
iter  10 value 94.327592
iter  20 value 88.996572
iter  30 value 85.948664
iter  40 value 83.237410
iter  50 value 83.031062
iter  60 value 83.019008
iter  70 value 82.953732
iter  80 value 82.931835
final  value 82.931783 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.070458 
iter  10 value 94.264255
iter  20 value 86.287606
iter  30 value 84.433875
iter  40 value 83.716470
iter  50 value 83.575764
iter  60 value 83.183015
iter  70 value 83.001071
iter  80 value 82.946228
iter  90 value 82.932197
final  value 82.931783 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.310935 
iter  10 value 94.470231
iter  20 value 90.569406
iter  30 value 84.722655
iter  40 value 81.397331
iter  50 value 81.289351
iter  60 value 80.705391
iter  70 value 79.966253
iter  80 value 79.801201
iter  90 value 79.621976
iter 100 value 79.279704
final  value 79.279704 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.906947 
iter  10 value 94.488769
iter  20 value 93.963427
iter  30 value 86.994251
iter  40 value 83.881125
iter  50 value 83.385075
iter  60 value 83.060862
iter  70 value 83.003794
iter  70 value 83.003793
iter  70 value 83.003793
final  value 83.003793 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.366871 
iter  10 value 94.397276
iter  20 value 88.063349
iter  30 value 85.676794
iter  40 value 85.464487
iter  50 value 82.911996
iter  60 value 82.629054
iter  70 value 82.626623
final  value 82.626622 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.572350 
iter  10 value 94.429270
iter  20 value 85.327105
iter  30 value 83.695401
iter  40 value 83.242622
iter  50 value 83.028620
iter  60 value 83.005677
iter  70 value 82.912343
iter  80 value 82.798422
iter  90 value 82.742267
iter 100 value 82.518600
final  value 82.518600 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.204873 
iter  10 value 94.523164
iter  20 value 89.099402
iter  30 value 88.604426
iter  40 value 87.134194
iter  50 value 84.052891
iter  60 value 83.262259
iter  70 value 82.814863
iter  80 value 82.697780
iter  90 value 82.480485
iter 100 value 81.371233
final  value 81.371233 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.626429 
iter  10 value 94.471319
iter  20 value 92.210702
iter  30 value 82.181533
iter  40 value 80.469827
iter  50 value 79.708863
iter  60 value 79.169453
iter  70 value 79.067281
iter  80 value 79.064674
iter  90 value 79.055618
iter 100 value 78.822431
final  value 78.822431 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.159647 
iter  10 value 94.546826
iter  20 value 94.425089
iter  30 value 86.416161
iter  40 value 81.209738
iter  50 value 80.592744
iter  60 value 78.605382
iter  70 value 78.279562
iter  80 value 78.205795
iter  90 value 78.168744
iter 100 value 78.130628
final  value 78.130628 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.404210 
iter  10 value 94.093457
iter  20 value 86.777527
iter  30 value 85.561912
iter  40 value 85.234952
iter  50 value 82.883547
iter  60 value 80.986222
iter  70 value 80.856489
iter  80 value 80.760401
iter  90 value 80.681931
iter 100 value 80.621991
final  value 80.621991 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 152.541947 
iter  10 value 101.817404
iter  20 value 92.668688
iter  30 value 87.894102
iter  40 value 86.068967
iter  50 value 83.158129
iter  60 value 79.594009
iter  70 value 79.030442
iter  80 value 78.440398
iter  90 value 78.233663
iter 100 value 77.995049
final  value 77.995049 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.010322 
iter  10 value 94.664715
iter  20 value 84.568503
iter  30 value 80.788514
iter  40 value 80.309749
iter  50 value 79.813531
iter  60 value 78.576410
iter  70 value 78.208624
iter  80 value 77.843522
iter  90 value 77.510977
iter 100 value 77.412471
final  value 77.412471 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.990153 
iter  10 value 92.888240
iter  20 value 85.552997
iter  30 value 84.115090
iter  40 value 82.628626
iter  50 value 79.707709
iter  60 value 79.068350
iter  70 value 78.867298
iter  80 value 78.717161
iter  90 value 78.249941
iter 100 value 78.024421
final  value 78.024421 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.057604 
iter  10 value 94.701020
iter  20 value 94.309713
iter  30 value 83.530805
iter  40 value 82.810219
iter  50 value 80.478052
iter  60 value 78.344963
iter  70 value 77.905995
iter  80 value 77.722809
iter  90 value 77.652481
iter 100 value 77.628963
final  value 77.628963 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.770518 
iter  10 value 92.524880
iter  20 value 83.801707
iter  30 value 82.497721
iter  40 value 81.643490
iter  50 value 80.032704
iter  60 value 79.480099
iter  70 value 78.450239
iter  80 value 78.006705
iter  90 value 77.860393
iter 100 value 77.690505
final  value 77.690505 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.905536 
final  value 94.486007 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.897714 
iter  10 value 94.485726
iter  20 value 94.484228
final  value 94.484220 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.977466 
iter  10 value 94.485685
iter  20 value 94.375108
iter  30 value 91.391102
iter  40 value 91.387718
final  value 91.387698 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.205446 
final  value 94.486207 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.992711 
final  value 94.485835 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.177639 
iter  10 value 93.731295
iter  20 value 92.871117
iter  30 value 92.865693
iter  40 value 92.634537
iter  50 value 86.586537
iter  60 value 84.147095
iter  70 value 83.924767
iter  80 value 83.889768
iter  90 value 83.889505
iter 100 value 83.888407
final  value 83.888407 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.497332 
iter  10 value 94.488982
iter  20 value 93.678975
iter  30 value 82.802149
iter  40 value 82.781487
final  value 82.781189 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.200671 
iter  10 value 94.315321
iter  20 value 93.367596
iter  30 value 82.838363
iter  40 value 82.658743
iter  50 value 82.655699
iter  60 value 82.650546
iter  70 value 82.298467
iter  80 value 82.092110
iter  90 value 82.091122
iter 100 value 81.511989
final  value 81.511989 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.670177 
iter  10 value 94.489213
iter  20 value 94.352075
iter  30 value 90.348455
iter  40 value 84.442479
iter  50 value 84.278849
iter  60 value 84.274218
iter  70 value 82.372084
iter  80 value 82.226692
final  value 82.225588 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.169341 
iter  10 value 94.488708
iter  20 value 94.368378
iter  30 value 83.147179
iter  40 value 82.484914
iter  50 value 82.415962
iter  60 value 81.936400
iter  70 value 80.415690
iter  80 value 80.411868
iter  90 value 80.406348
iter 100 value 79.985133
final  value 79.985133 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.515711 
iter  10 value 94.475261
iter  20 value 94.468154
iter  30 value 91.703647
iter  40 value 85.653936
iter  50 value 84.524288
iter  60 value 84.511044
iter  70 value 84.008005
iter  80 value 83.877051
iter  90 value 80.104372
iter 100 value 78.508909
final  value 78.508909 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 151.712489 
iter  10 value 94.493754
iter  20 value 94.486106
iter  30 value 88.461236
iter  40 value 82.945753
iter  50 value 82.654730
iter  60 value 82.653980
iter  70 value 82.651589
iter  80 value 82.600341
iter  90 value 82.112010
iter 100 value 81.555150
final  value 81.555150 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.468193 
iter  10 value 94.474864
iter  20 value 94.307779
final  value 94.306457 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.883674 
iter  10 value 91.133496
iter  20 value 90.734038
iter  30 value 90.730007
iter  40 value 90.729015
iter  50 value 90.727225
iter  60 value 89.918247
iter  70 value 81.936653
iter  80 value 81.283326
iter  90 value 81.140815
iter 100 value 81.119956
final  value 81.119956 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.142938 
iter  10 value 92.368779
iter  20 value 91.886534
iter  30 value 88.844077
iter  40 value 82.216509
iter  50 value 79.565196
iter  60 value 77.797815
iter  70 value 77.676573
iter  80 value 77.620952
iter  90 value 77.567436
iter 100 value 77.564945
final  value 77.564945 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.419121 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.588201 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.500607 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.698582 
final  value 94.484207 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.674210 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.080942 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.723090 
iter  10 value 94.427726
iter  10 value 94.427726
iter  10 value 94.427726
final  value 94.427726 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.803956 
final  value 94.427725 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.339211 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.252527 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.252398 
final  value 94.448052 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.202683 
iter  10 value 94.424733
final  value 94.424077 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.846814 
final  value 94.427726 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.252515 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.890687 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.599050 
iter  10 value 94.488543
iter  20 value 94.431295
iter  30 value 92.420309
iter  40 value 91.598889
iter  50 value 85.917379
iter  60 value 85.672228
iter  70 value 85.503925
iter  80 value 85.208610
iter  90 value 85.135080
iter 100 value 85.101371
final  value 85.101371 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.325931 
iter  10 value 94.255726
iter  20 value 90.912442
iter  30 value 88.187004
iter  40 value 86.704435
iter  50 value 86.557198
iter  60 value 86.302991
iter  70 value 84.671029
iter  80 value 83.960042
iter  90 value 83.854625
final  value 83.854462 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.623896 
iter  10 value 94.486419
iter  20 value 93.973898
iter  30 value 89.938966
iter  40 value 87.865514
iter  50 value 87.560785
iter  60 value 86.900696
iter  70 value 86.366300
iter  80 value 84.485487
iter  90 value 84.167941
iter 100 value 83.998927
final  value 83.998927 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.801533 
iter  10 value 94.483479
iter  20 value 94.419574
iter  30 value 94.414416
iter  40 value 94.348575
iter  50 value 87.347600
iter  60 value 86.814194
iter  70 value 86.686505
iter  80 value 86.273503
iter  90 value 84.681065
iter 100 value 84.285258
final  value 84.285258 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.937616 
iter  10 value 94.461377
iter  20 value 89.451805
iter  30 value 86.553538
iter  40 value 84.559024
iter  50 value 84.450312
iter  60 value 84.213272
iter  70 value 84.035020
iter  80 value 83.873904
iter  90 value 83.701907
final  value 83.697907 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.144159 
iter  10 value 94.063286
iter  20 value 88.509706
iter  30 value 87.523057
iter  40 value 87.363160
iter  50 value 87.048769
iter  60 value 86.444767
iter  70 value 83.652656
iter  80 value 83.243228
iter  90 value 82.756728
iter 100 value 82.730575
final  value 82.730575 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.504390 
iter  10 value 94.386646
iter  20 value 88.655055
iter  30 value 87.514587
iter  40 value 85.048464
iter  50 value 84.221310
iter  60 value 84.091829
iter  70 value 83.934590
iter  80 value 83.627217
iter  90 value 83.498990
iter 100 value 83.434311
final  value 83.434311 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.172114 
iter  10 value 97.928942
iter  20 value 95.871102
iter  30 value 94.489145
iter  40 value 94.406353
iter  50 value 93.598846
iter  60 value 87.595925
iter  70 value 87.178621
iter  80 value 86.618794
iter  90 value 85.198615
iter 100 value 84.400876
final  value 84.400876 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.906075 
iter  10 value 94.507089
iter  20 value 93.178798
iter  30 value 89.284760
iter  40 value 88.365771
iter  50 value 87.915609
iter  60 value 87.386783
iter  70 value 87.022852
iter  80 value 86.962774
iter  90 value 86.548070
iter 100 value 84.045944
final  value 84.045944 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.218245 
iter  10 value 94.504894
iter  20 value 94.400217
iter  30 value 93.312028
iter  40 value 92.925643
iter  50 value 87.730934
iter  60 value 86.021037
iter  70 value 85.697575
iter  80 value 85.563223
iter  90 value 83.684943
iter 100 value 82.954352
final  value 82.954352 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.727699 
iter  10 value 96.024676
iter  20 value 94.455775
iter  30 value 92.405499
iter  40 value 85.638090
iter  50 value 84.991367
iter  60 value 84.918143
iter  70 value 84.685177
iter  80 value 84.169422
iter  90 value 83.909660
iter 100 value 83.608542
final  value 83.608542 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.190800 
iter  10 value 94.505543
iter  20 value 90.882497
iter  30 value 88.671245
iter  40 value 87.050875
iter  50 value 85.196763
iter  60 value 84.729058
iter  70 value 84.601014
iter  80 value 84.211292
iter  90 value 83.504598
iter 100 value 83.069318
final  value 83.069318 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.163948 
iter  10 value 94.510653
iter  20 value 92.232017
iter  30 value 90.083789
iter  40 value 87.300430
iter  50 value 87.116401
iter  60 value 85.333002
iter  70 value 84.909633
iter  80 value 84.878352
iter  90 value 84.847009
iter 100 value 84.729545
final  value 84.729545 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.380387 
iter  10 value 94.991184
iter  20 value 94.430635
iter  30 value 89.830522
iter  40 value 88.833308
iter  50 value 87.644583
iter  60 value 86.152814
iter  70 value 85.301871
iter  80 value 84.903855
iter  90 value 84.583646
iter 100 value 83.871934
final  value 83.871934 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.455009 
iter  10 value 94.512844
iter  20 value 94.194256
iter  30 value 87.958043
iter  40 value 86.589537
iter  50 value 85.411828
iter  60 value 84.458537
iter  70 value 83.557947
iter  80 value 83.130554
iter  90 value 82.859665
iter 100 value 82.484731
final  value 82.484731 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.161561 
final  value 94.486053 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.349875 
final  value 94.430569 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.976450 
final  value 94.486006 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.968515 
iter  10 value 94.468593
iter  20 value 94.443843
iter  30 value 94.385809
final  value 94.385714 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.801228 
iter  10 value 94.485832
iter  20 value 94.484270
final  value 94.484215 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.870410 
iter  10 value 94.489289
iter  20 value 94.484251
iter  30 value 90.682041
final  value 90.352772 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.765390 
iter  10 value 94.488949
iter  20 value 94.454334
iter  30 value 85.864114
iter  40 value 85.839480
iter  50 value 85.838689
iter  50 value 85.838689
iter  50 value 85.838689
final  value 85.838689 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.277531 
iter  10 value 94.432901
iter  20 value 94.412889
iter  30 value 89.080731
iter  40 value 87.459101
iter  50 value 85.956071
iter  60 value 85.404385
iter  70 value 85.182875
final  value 85.173104 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.647038 
iter  10 value 94.471900
iter  20 value 94.459103
iter  30 value 92.015525
iter  40 value 87.898798
iter  50 value 87.864578
iter  60 value 87.841126
iter  70 value 87.793919
iter  80 value 87.778061
iter  90 value 87.777422
final  value 87.777412 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.821974 
iter  10 value 94.471433
iter  20 value 94.428196
iter  30 value 87.559678
iter  40 value 84.485934
iter  50 value 82.286523
iter  60 value 81.485724
iter  70 value 80.807458
iter  80 value 80.770309
iter  90 value 80.770265
final  value 80.769724 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.923719 
iter  10 value 94.492266
iter  20 value 94.486963
iter  30 value 94.455109
iter  40 value 94.452656
iter  50 value 92.526064
iter  60 value 87.294342
iter  70 value 87.294100
iter  80 value 85.910382
iter  90 value 85.509621
iter 100 value 85.479491
final  value 85.479491 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.520523 
iter  10 value 94.489061
iter  20 value 94.467639
final  value 94.467300 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.003048 
iter  10 value 93.982874
iter  20 value 93.850554
iter  30 value 90.201637
iter  40 value 90.068665
final  value 90.047633 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.339334 
iter  10 value 94.492498
iter  20 value 94.483860
iter  30 value 93.761400
iter  40 value 91.286743
iter  50 value 91.067566
iter  60 value 91.056966
iter  70 value 86.979392
iter  80 value 86.969059
iter  90 value 86.961219
iter 100 value 86.354432
final  value 86.354432 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.642670 
iter  10 value 94.469960
iter  20 value 94.440623
iter  30 value 89.042893
iter  40 value 87.813567
final  value 87.811288 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.464694 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.355715 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.139483 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.572445 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.125755 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.860601 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.118972 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.471843 
final  value 93.836065 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.475884 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.723612 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 139.939412 
iter  10 value 93.864568
final  value 93.860355 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.307579 
iter  10 value 92.395593
iter  20 value 87.254422
final  value 87.247250 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.101751 
final  value 94.011561 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.619511 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.065951 
iter  10 value 83.014717
iter  20 value 82.658536
iter  30 value 82.543227
iter  40 value 82.541236
iter  50 value 82.540439
final  value 82.540430 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.659862 
iter  10 value 93.772358
iter  20 value 88.611703
iter  30 value 87.636629
iter  40 value 86.745046
iter  50 value 85.967046
iter  60 value 85.453818
iter  70 value 85.255171
iter  80 value 85.235249
final  value 85.234283 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.733636 
iter  10 value 94.056982
iter  20 value 93.960552
iter  30 value 93.854553
iter  40 value 93.842310
iter  50 value 93.840251
iter  60 value 93.839149
iter  60 value 93.839149
final  value 93.839149 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.491704 
iter  10 value 94.064975
iter  20 value 92.412380
iter  30 value 90.670634
iter  40 value 90.548048
iter  50 value 89.189037
iter  60 value 86.817439
iter  70 value 83.650868
iter  80 value 83.114740
iter  90 value 82.985096
iter 100 value 82.775806
final  value 82.775806 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 95.989231 
iter  10 value 93.988102
iter  20 value 93.889877
iter  30 value 93.708537
iter  40 value 92.676272
iter  50 value 86.338051
iter  60 value 85.478019
iter  70 value 84.891086
iter  80 value 83.739602
iter  90 value 83.275702
iter 100 value 82.866190
final  value 82.866190 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.488264 
iter  10 value 93.841161
iter  20 value 89.849272
iter  30 value 88.375085
iter  40 value 87.474089
iter  50 value 86.727430
iter  60 value 86.620298
final  value 86.620260 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.797172 
iter  10 value 93.997148
iter  20 value 87.661896
iter  30 value 86.837773
iter  40 value 86.233266
iter  50 value 84.717842
iter  60 value 82.667254
iter  70 value 82.347014
iter  80 value 81.929739
iter  90 value 81.514344
iter 100 value 80.829731
final  value 80.829731 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.576834 
iter  10 value 93.983132
iter  20 value 90.877291
iter  30 value 87.758771
iter  40 value 83.731961
iter  50 value 82.988174
iter  60 value 82.817051
iter  70 value 82.060764
iter  80 value 81.318520
iter  90 value 81.191417
iter 100 value 81.006134
final  value 81.006134 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.536858 
iter  10 value 93.212706
iter  20 value 89.875508
iter  30 value 85.245585
iter  40 value 84.175722
iter  50 value 83.962781
iter  60 value 83.896580
iter  70 value 83.803653
iter  80 value 83.789066
iter  90 value 83.748930
iter 100 value 83.125935
final  value 83.125935 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.582664 
iter  10 value 94.058303
iter  20 value 92.514759
iter  30 value 92.089914
iter  40 value 91.821287
iter  50 value 91.624835
iter  60 value 90.976361
iter  70 value 86.011768
iter  80 value 82.106877
iter  90 value 81.521918
iter 100 value 81.303466
final  value 81.303466 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.601133 
iter  10 value 93.769877
iter  20 value 87.622814
iter  30 value 86.755194
iter  40 value 84.654062
iter  50 value 83.952922
iter  60 value 83.568436
iter  70 value 83.056524
iter  80 value 82.760586
iter  90 value 82.447159
iter 100 value 81.611830
final  value 81.611830 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.470924 
iter  10 value 94.716274
iter  20 value 94.306055
iter  30 value 87.223851
iter  40 value 85.734043
iter  50 value 83.527743
iter  60 value 82.302905
iter  70 value 81.864163
iter  80 value 81.718799
iter  90 value 81.477828
iter 100 value 81.181515
final  value 81.181515 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.202709 
iter  10 value 94.021443
iter  20 value 91.166311
iter  30 value 87.550345
iter  40 value 87.000773
iter  50 value 82.727187
iter  60 value 81.846875
iter  70 value 81.629045
iter  80 value 81.156393
iter  90 value 80.813192
iter 100 value 80.705627
final  value 80.705627 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.302508 
iter  10 value 94.385560
iter  20 value 93.391870
iter  30 value 87.018225
iter  40 value 86.361104
iter  50 value 84.724161
iter  60 value 82.864192
iter  70 value 82.553741
iter  80 value 82.205551
iter  90 value 81.769369
iter 100 value 81.583278
final  value 81.583278 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.656592 
iter  10 value 94.181475
iter  20 value 90.182189
iter  30 value 85.722930
iter  40 value 83.421901
iter  50 value 82.885183
iter  60 value 82.404227
iter  70 value 81.763927
iter  80 value 81.332646
iter  90 value 81.180347
iter 100 value 80.728483
final  value 80.728483 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.945221 
iter  10 value 93.941022
iter  20 value 89.055282
iter  30 value 88.476151
iter  40 value 86.038514
iter  50 value 84.361250
iter  60 value 83.744158
iter  70 value 83.540673
iter  80 value 83.434944
iter  90 value 83.259378
iter 100 value 82.575193
final  value 82.575193 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 117.327682 
iter  10 value 93.795891
iter  20 value 93.785387
iter  30 value 93.785168
iter  40 value 93.784770
final  value 93.784767 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.103590 
final  value 93.837756 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.428123 
iter  10 value 94.054593
iter  20 value 94.052978
final  value 94.052912 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.867357 
iter  10 value 93.837595
iter  20 value 93.789007
iter  30 value 93.784256
final  value 93.784254 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.416527 
iter  10 value 93.837759
final  value 93.837737 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.553538 
iter  10 value 94.057388
iter  20 value 93.960944
iter  30 value 90.559943
iter  40 value 87.456331
iter  50 value 86.246407
final  value 86.246084 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.413599 
iter  10 value 94.056004
iter  20 value 93.995805
iter  30 value 87.439925
iter  40 value 85.823116
iter  50 value 85.462340
iter  60 value 85.420598
iter  70 value 85.419897
iter  80 value 85.074983
iter  90 value 84.795946
iter 100 value 84.793985
final  value 84.793985 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.032524 
iter  10 value 93.543754
iter  20 value 93.528362
iter  30 value 93.468685
iter  40 value 93.461107
iter  50 value 91.621561
iter  60 value 90.673172
iter  60 value 90.673172
iter  60 value 90.673172
final  value 90.673172 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.148893 
iter  10 value 89.499617
iter  20 value 88.805274
iter  30 value 86.944785
iter  40 value 85.431803
iter  50 value 85.229180
iter  60 value 85.228651
iter  60 value 85.228651
final  value 85.228642 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.253328 
iter  10 value 93.841116
iter  20 value 93.830102
iter  30 value 86.706634
iter  40 value 82.839094
iter  50 value 82.602448
final  value 82.600119 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.704978 
iter  10 value 90.710717
iter  20 value 88.698860
iter  30 value 88.550811
iter  40 value 88.547322
iter  50 value 88.546274
iter  60 value 86.782352
iter  70 value 82.107401
iter  80 value 80.546885
iter  90 value 80.391172
iter 100 value 80.344504
final  value 80.344504 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.911249 
iter  10 value 93.681719
iter  20 value 93.672974
iter  30 value 93.533775
iter  40 value 93.479599
iter  50 value 93.474684
iter  60 value 92.445288
iter  70 value 91.659937
iter  80 value 91.659198
iter  90 value 90.868516
iter 100 value 86.191727
final  value 86.191727 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.116698 
iter  10 value 93.844066
iter  20 value 93.841841
iter  30 value 93.691023
iter  40 value 91.631055
iter  50 value 91.479766
iter  60 value 91.478208
iter  70 value 91.477146
iter  70 value 91.477146
final  value 91.477107 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.176410 
iter  10 value 94.061532
iter  20 value 94.038603
final  value 93.836771 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.314756 
iter  10 value 94.058961
iter  20 value 93.694243
iter  30 value 86.594903
iter  40 value 84.730685
iter  50 value 82.591769
iter  60 value 82.109839
iter  70 value 82.087001
iter  80 value 82.007610
iter  90 value 81.572924
iter 100 value 79.272796
final  value 79.272796 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 121.410164 
iter  10 value 117.895015
iter  20 value 117.789311
iter  30 value 111.577384
iter  40 value 105.502692
iter  50 value 105.299547
iter  60 value 105.296966
iter  70 value 104.260135
iter  80 value 102.810532
iter  90 value 102.655923
iter 100 value 102.236840
final  value 102.236840 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 125.782584 
iter  10 value 117.763942
iter  20 value 117.759526
iter  30 value 114.388405
iter  40 value 111.235011
iter  50 value 111.228042
iter  60 value 111.227502
iter  70 value 106.892753
iter  80 value 105.408042
iter  90 value 105.052889
iter 100 value 104.843168
final  value 104.843168 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 130.837152 
iter  10 value 117.895163
iter  20 value 117.890346
iter  30 value 113.516266
iter  40 value 106.109997
iter  50 value 100.994099
iter  60 value 100.267609
iter  70 value 99.986224
iter  80 value 99.454421
iter  90 value 99.424809
final  value 99.424574 
converged
Fitting Repeat 4 

# weights:  305
initial  value 120.022145 
iter  10 value 117.211124
iter  20 value 115.240965
iter  30 value 115.007390
iter  40 value 114.732198
final  value 114.727272 
converged
Fitting Repeat 5 

# weights:  305
initial  value 125.546258 
iter  10 value 117.895369
iter  20 value 117.890388
final  value 117.890329 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri May  3 22:39:08 2024 
*********************************************** 
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 
 41.901   2.073  50.387 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod35.116 1.98937.567
FreqInteractors0.2740.0160.294
calculateAAC0.0430.0070.051
calculateAutocor0.4020.0800.488
calculateCTDC0.0870.0050.093
calculateCTDD0.6920.0300.731
calculateCTDT0.2590.0110.272
calculateCTriad0.4310.0280.465
calculateDC0.1100.0140.126
calculateF0.3890.0140.408
calculateKSAAP0.1150.0100.126
calculateQD_Sm1.8230.1201.958
calculateTC1.9770.2042.197
calculateTC_Sm0.2920.0180.314
corr_plot35.131 1.91537.405
enrichfindP 0.511 0.06719.623
enrichfind_hp0.0770.0262.035
enrichplot0.4230.0110.443
filter_missing_values0.0010.0000.002
getFASTA0.0750.0124.132
getHPI0.0000.0010.000
get_negativePPI0.0020.0010.002
get_positivePPI0.0000.0000.001
impute_missing_data0.0010.0000.002
plotPPI0.0750.0020.078
pred_ensembel14.793 0.58711.418
var_imp37.207 2.17739.941