Back to Multiple platform build/check report for BioC 3.22:   simplified   long
ABCDEFG[H]IJKLMNOPQRSTUVWXYZ

This page was generated on 2025-08-09 12:08 -0400 (Sat, 09 Aug 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.2 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4818
palomino8Windows Server 2022 Datacenterx644.5.1 (2025-06-13 ucrt) -- "Great Square Root" 4553
lconwaymacOS 12.7.1 Montereyx86_644.5.1 (2025-06-13) -- "Great Square Root" 4595
kjohnson3macOS 13.7.1 Venturaarm644.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" 4537
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 987/2317HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
HPiP 1.15.0  (landing page)
Matineh Rahmatbakhsh
Snapshot Date: 2025-08-08 13:45 -0400 (Fri, 08 Aug 2025)
git_url: https://git.bioconductor.org/packages/HPiP
git_branch: devel
git_last_commit: b0c624c
git_last_commit_date: 2025-04-15 12:38:30 -0400 (Tue, 15 Apr 2025)
nebbiolo2Linux (Ubuntu 24.04.2 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino8Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.7.1 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson3macOS 13.7.1 Ventura / arm64  OK    OK    OK    OK  UNNEEDED, same version is already published


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: 1.15.0
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_1.15.0.tar.gz
StartedAt: 2025-08-08 21:39:22 -0400 (Fri, 08 Aug 2025)
EndedAt: 2025-08-08 21:45:42 -0400 (Fri, 08 Aug 2025)
EllapsedTime: 380.2 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_1.15.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.1 (2025-06-13)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.15.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       35.827  2.083  38.507
corr_plot     33.665  1.875  35.919
FSmethod      33.582  1.839  35.764
pred_ensembel 13.964  0.451  12.456
enrichfindP    0.467  0.057   8.220
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.


Installation output

HPiP.Rcheck/00install.out

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.15.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

Tests output

HPiP.Rcheck/tests/runTests.Rout


R version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 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 99.904149 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.542288 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.161190 
iter  10 value 93.836066
iter  10 value 93.836066
iter  10 value 93.836066
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.335446 
iter  10 value 94.043243
iter  10 value 94.043243
iter  10 value 94.043243
final  value 94.043243 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.098513 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.384403 
iter  10 value 94.043246
final  value 94.043243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 132.646726 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.366558 
final  value 94.017143 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.285579 
final  value 94.043243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.463978 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.461515 
iter  10 value 92.361775
iter  20 value 91.588269
final  value 91.587993 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.547288 
final  value 94.043243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.501674 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.583521 
final  value 92.190657 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.812637 
final  value 94.043243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.616116 
iter  10 value 94.007032
iter  20 value 92.256826
iter  30 value 85.928791
iter  40 value 84.516525
iter  50 value 82.491723
iter  60 value 80.269222
iter  70 value 79.622687
iter  80 value 78.898798
iter  90 value 78.714374
final  value 78.711494 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.998283 
iter  10 value 93.916121
iter  20 value 83.011107
iter  30 value 81.645118
iter  40 value 81.278562
iter  50 value 80.188346
iter  60 value 80.051459
final  value 80.051018 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.394110 
iter  10 value 94.057369
iter  20 value 85.614831
iter  30 value 82.467420
iter  40 value 82.359096
iter  50 value 81.446336
iter  60 value 80.293943
iter  70 value 79.742242
iter  80 value 79.633280
final  value 79.632894 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.069943 
iter  10 value 94.050910
iter  20 value 92.109562
iter  30 value 87.672792
iter  40 value 81.739555
iter  50 value 80.723345
iter  60 value 80.191441
iter  70 value 80.052375
final  value 80.051018 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.608036 
iter  10 value 94.038886
iter  20 value 89.121864
iter  30 value 85.982263
iter  40 value 84.061623
iter  50 value 83.618005
iter  60 value 83.204125
iter  70 value 83.029860
iter  80 value 81.764919
iter  90 value 80.501762
iter 100 value 79.818215
final  value 79.818215 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.078116 
iter  10 value 95.285200
iter  20 value 83.651977
iter  30 value 82.030922
iter  40 value 81.143474
iter  50 value 80.558749
iter  60 value 78.709941
iter  70 value 78.677356
iter  80 value 78.672189
iter  90 value 78.600715
iter 100 value 78.260576
final  value 78.260576 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.670240 
iter  10 value 93.980860
iter  20 value 88.033103
iter  30 value 82.275950
iter  40 value 79.757986
iter  50 value 78.984231
iter  60 value 77.940620
iter  70 value 77.611726
iter  80 value 77.325717
iter  90 value 77.091763
iter 100 value 77.014654
final  value 77.014654 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.359270 
iter  10 value 93.804846
iter  20 value 91.800192
iter  30 value 86.021437
iter  40 value 83.923670
iter  50 value 80.963941
iter  60 value 79.529208
iter  70 value 79.237267
iter  80 value 78.873496
iter  90 value 78.798769
iter 100 value 78.552425
final  value 78.552425 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.637426 
iter  10 value 94.020474
iter  20 value 91.884702
iter  30 value 91.296043
iter  40 value 88.994288
iter  50 value 80.473761
iter  60 value 78.144499
iter  70 value 77.442087
iter  80 value 77.188612
iter  90 value 77.075280
iter 100 value 77.057418
final  value 77.057418 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.861526 
iter  10 value 94.060418
iter  20 value 93.148815
iter  30 value 83.880382
iter  40 value 81.621666
iter  50 value 81.187776
iter  60 value 80.783891
iter  70 value 80.401530
iter  80 value 79.817186
iter  90 value 79.628904
iter 100 value 79.563808
final  value 79.563808 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.261763 
iter  10 value 93.998964
iter  20 value 89.309306
iter  30 value 82.615541
iter  40 value 80.118714
iter  50 value 79.475342
iter  60 value 78.380330
iter  70 value 77.991387
iter  80 value 77.808389
iter  90 value 77.371551
iter 100 value 77.061786
final  value 77.061786 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.091116 
iter  10 value 95.365197
iter  20 value 94.086946
iter  30 value 94.049320
iter  40 value 87.803836
iter  50 value 84.615103
iter  60 value 83.902929
iter  70 value 83.226721
iter  80 value 82.920607
iter  90 value 82.513488
iter 100 value 79.989079
final  value 79.989079 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.915169 
iter  10 value 91.903719
iter  20 value 86.406124
iter  30 value 79.458951
iter  40 value 78.181025
iter  50 value 77.688033
iter  60 value 77.592751
iter  70 value 77.363003
iter  80 value 77.294620
iter  90 value 77.136475
iter 100 value 77.040014
final  value 77.040014 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.788497 
iter  10 value 94.091231
iter  20 value 92.139522
iter  30 value 87.601999
iter  40 value 80.885139
iter  50 value 78.997793
iter  60 value 78.293867
iter  70 value 77.748844
iter  80 value 77.439043
iter  90 value 77.212114
iter 100 value 77.103267
final  value 77.103267 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.682961 
iter  10 value 93.974080
iter  20 value 89.450256
iter  30 value 86.956585
iter  40 value 83.284743
iter  50 value 81.868089
iter  60 value 78.902227
iter  70 value 78.045513
iter  80 value 77.428736
iter  90 value 77.190446
iter 100 value 77.046524
final  value 77.046524 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.418783 
final  value 94.054631 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.868838 
final  value 94.054545 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.180395 
final  value 94.054634 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.163596 
iter  10 value 94.054365
iter  20 value 94.052935
final  value 94.052914 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.916424 
final  value 94.054584 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.059954 
iter  10 value 94.048335
iter  20 value 93.845622
iter  30 value 85.391492
iter  40 value 81.920917
iter  50 value 81.920276
final  value 81.920275 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.937261 
iter  10 value 94.057631
iter  20 value 94.052917
iter  30 value 82.394026
iter  40 value 81.688453
iter  50 value 81.676563
iter  60 value 81.663760
final  value 81.663455 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.922780 
iter  10 value 94.047895
iter  20 value 94.043351
iter  30 value 94.043194
iter  40 value 91.167133
iter  50 value 90.786081
iter  60 value 90.785367
iter  70 value 90.785046
iter  80 value 90.715064
iter  90 value 90.604300
iter 100 value 90.386901
final  value 90.386901 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.337826 
iter  10 value 93.959634
iter  20 value 93.907787
iter  30 value 81.091908
iter  40 value 80.944020
final  value 80.943797 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.570089 
iter  10 value 93.950159
iter  20 value 85.699870
iter  30 value 82.558191
iter  40 value 81.962447
iter  50 value 81.899008
iter  60 value 81.830717
iter  70 value 81.761636
iter  80 value 80.968394
iter  90 value 80.962591
iter 100 value 80.950714
final  value 80.950714 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.924006 
iter  10 value 94.060956
iter  20 value 94.054284
iter  30 value 94.051116
iter  40 value 93.998161
iter  50 value 91.753569
iter  60 value 84.003420
iter  70 value 83.277375
iter  80 value 82.705321
iter  90 value 82.612949
iter 100 value 82.553855
final  value 82.553855 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.706714 
iter  10 value 94.061753
iter  20 value 94.032028
iter  30 value 93.062706
iter  40 value 85.245351
iter  50 value 83.457978
iter  60 value 81.423141
iter  70 value 81.244312
iter  80 value 81.239340
iter  90 value 81.238320
iter 100 value 78.933717
final  value 78.933717 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.375106 
iter  10 value 94.036091
iter  20 value 93.794463
iter  30 value 93.537489
iter  40 value 93.534588
iter  50 value 93.510788
iter  60 value 91.060485
iter  70 value 82.771092
iter  80 value 82.729273
iter  90 value 82.214869
iter 100 value 82.124882
final  value 82.124882 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.900940 
iter  10 value 94.060824
iter  20 value 93.310964
iter  30 value 82.879893
iter  40 value 82.877647
iter  50 value 82.875660
iter  60 value 82.601388
iter  70 value 82.569208
iter  80 value 82.352415
iter  90 value 78.946265
iter 100 value 77.773217
final  value 77.773217 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.041464 
iter  10 value 91.794166
iter  20 value 89.422678
iter  30 value 89.402325
iter  40 value 89.364668
iter  50 value 89.359027
iter  60 value 79.846569
iter  70 value 77.801311
iter  80 value 77.646926
iter  90 value 77.605239
iter 100 value 77.472449
final  value 77.472449 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.405930 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.677216 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.899119 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.421269 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 118.214961 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.206920 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 132.236198 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.512813 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.318177 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 133.505966 
iter  10 value 94.026543
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  507
initial  value 123.094926 
final  value 94.433545 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.369333 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.876046 
iter  10 value 90.485770
iter  20 value 89.843543
iter  30 value 89.705319
iter  40 value 89.679107
final  value 89.678936 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.905001 
iter  10 value 92.077084
iter  20 value 91.199058
iter  30 value 91.198092
final  value 91.198086 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.058493 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.729580 
iter  10 value 94.497044
iter  20 value 94.167275
iter  30 value 94.130642
iter  40 value 94.025295
iter  50 value 93.757197
iter  60 value 93.695470
iter  70 value 87.996176
iter  80 value 86.140883
iter  90 value 85.810494
iter 100 value 83.900294
final  value 83.900294 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.754603 
iter  10 value 94.358726
iter  20 value 86.700707
iter  30 value 86.398561
iter  40 value 85.004855
iter  50 value 83.861079
iter  60 value 83.559019
iter  70 value 83.247444
iter  80 value 83.109578
iter  90 value 83.038101
iter 100 value 83.027998
final  value 83.027998 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.961810 
iter  10 value 92.463475
iter  20 value 87.505011
iter  30 value 85.767704
iter  40 value 85.359141
iter  50 value 83.932818
iter  60 value 83.651156
iter  70 value 83.239596
final  value 83.211874 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.935074 
iter  10 value 94.486616
iter  20 value 93.976082
iter  30 value 93.751892
iter  40 value 93.749549
iter  50 value 93.682145
iter  60 value 93.671261
iter  70 value 90.556895
iter  80 value 85.009262
iter  90 value 84.863187
iter 100 value 84.787123
final  value 84.787123 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 108.138879 
iter  10 value 94.979532
iter  20 value 94.490132
iter  30 value 93.803717
iter  40 value 93.307678
iter  50 value 90.049956
iter  60 value 85.826592
iter  70 value 85.031235
iter  80 value 84.167620
iter  90 value 84.069718
iter 100 value 83.916557
final  value 83.916557 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 112.398130 
iter  10 value 94.469832
iter  20 value 93.731724
iter  30 value 93.194481
iter  40 value 86.036518
iter  50 value 84.386388
iter  60 value 84.053777
iter  70 value 83.281932
iter  80 value 82.196179
iter  90 value 81.829114
iter 100 value 81.780229
final  value 81.780229 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 118.847992 
iter  10 value 94.415479
iter  20 value 93.821884
iter  30 value 93.736508
iter  40 value 93.453630
iter  50 value 92.050891
iter  60 value 86.361211
iter  70 value 85.043194
iter  80 value 84.012679
iter  90 value 82.999493
iter 100 value 82.691520
final  value 82.691520 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.852727 
iter  10 value 94.285941
iter  20 value 93.565625
iter  30 value 90.131465
iter  40 value 87.487790
iter  50 value 85.073939
iter  60 value 84.469515
iter  70 value 83.404038
iter  80 value 83.158174
iter  90 value 82.760487
iter 100 value 82.505931
final  value 82.505931 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.376670 
iter  10 value 94.308885
iter  20 value 93.737839
iter  30 value 93.562538
iter  40 value 87.337827
iter  50 value 86.117914
iter  60 value 84.410604
iter  70 value 82.538633
iter  80 value 82.005013
iter  90 value 81.807193
iter 100 value 81.642583
final  value 81.642583 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.255382 
iter  10 value 93.869551
iter  20 value 93.740934
iter  30 value 93.012969
iter  40 value 85.512288
iter  50 value 84.626777
iter  60 value 83.954499
iter  70 value 83.590078
iter  80 value 82.791516
iter  90 value 82.297738
iter 100 value 82.181770
final  value 82.181770 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 132.814651 
iter  10 value 95.603806
iter  20 value 91.620749
iter  30 value 86.426571
iter  40 value 84.986136
iter  50 value 84.611631
iter  60 value 84.432321
iter  70 value 84.165117
iter  80 value 83.962936
iter  90 value 83.670896
iter 100 value 82.879625
final  value 82.879625 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.215348 
iter  10 value 94.494678
iter  20 value 94.273298
iter  30 value 86.266234
iter  40 value 85.889653
iter  50 value 85.392440
iter  60 value 84.094176
iter  70 value 82.975413
iter  80 value 82.777263
iter  90 value 82.615229
iter 100 value 82.552773
final  value 82.552773 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.652461 
iter  10 value 92.338817
iter  20 value 91.110087
iter  30 value 87.799902
iter  40 value 86.516429
iter  50 value 85.627747
iter  60 value 84.708163
iter  70 value 84.093857
iter  80 value 83.901927
iter  90 value 83.828029
iter 100 value 83.442093
final  value 83.442093 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.729244 
iter  10 value 94.567365
iter  20 value 89.529126
iter  30 value 87.963506
iter  40 value 87.538731
iter  50 value 87.176798
iter  60 value 86.863623
iter  70 value 84.812880
iter  80 value 83.939793
iter  90 value 82.853657
iter 100 value 82.236271
final  value 82.236271 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.575836 
iter  10 value 94.066515
iter  20 value 88.276205
iter  30 value 86.341886
iter  40 value 85.603661
iter  50 value 85.203319
iter  60 value 84.685639
iter  70 value 83.968451
iter  80 value 83.709264
iter  90 value 83.107354
iter 100 value 82.764809
final  value 82.764809 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 117.323732 
iter  10 value 94.630392
iter  20 value 94.603650
iter  30 value 94.486266
final  value 94.484218 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.371540 
iter  10 value 94.485853
iter  20 value 94.342535
iter  30 value 88.743238
iter  40 value 88.411995
iter  50 value 88.398686
iter  60 value 88.384755
iter  70 value 87.894307
iter  80 value 87.177340
final  value 87.177338 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.031958 
final  value 94.485623 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.219365 
final  value 94.485747 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.746315 
iter  10 value 94.485843
iter  20 value 94.484250
final  value 94.484215 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.977665 
iter  10 value 94.491016
iter  20 value 94.484701
final  value 94.484302 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.251345 
iter  10 value 94.489151
iter  20 value 94.428361
iter  30 value 87.947284
iter  40 value 85.599149
iter  50 value 85.382965
iter  60 value 85.380334
iter  70 value 85.378656
final  value 85.378279 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.186569 
iter  10 value 88.473058
iter  20 value 87.226534
final  value 87.224080 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.687456 
iter  10 value 94.489214
iter  20 value 94.484230
iter  30 value 94.321999
iter  40 value 93.640905
final  value 93.640903 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.150099 
iter  10 value 94.488761
iter  20 value 92.061783
iter  30 value 92.031655
iter  40 value 91.508033
iter  50 value 88.403847
iter  60 value 87.457751
final  value 87.382609 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.938263 
iter  10 value 94.154102
iter  20 value 94.152211
iter  30 value 94.145678
iter  40 value 94.102876
iter  50 value 93.555538
iter  60 value 93.488419
iter  70 value 93.486004
iter  80 value 93.482635
iter  90 value 93.473159
iter 100 value 93.390857
final  value 93.390857 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.953719 
iter  10 value 91.911095
iter  20 value 85.399858
iter  30 value 85.182708
iter  40 value 84.179320
iter  50 value 84.175895
iter  60 value 83.692278
iter  70 value 83.651158
iter  80 value 83.211695
iter  90 value 82.441134
iter 100 value 82.316579
final  value 82.316579 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.504476 
iter  10 value 93.600240
iter  20 value 93.584872
iter  30 value 93.579488
iter  40 value 93.213934
iter  50 value 92.321424
iter  60 value 92.320323
iter  70 value 92.311132
final  value 92.310991 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.958915 
iter  10 value 94.034920
iter  20 value 94.028302
final  value 94.027683 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.462360 
iter  10 value 87.342527
iter  20 value 86.605852
iter  30 value 86.596233
iter  40 value 86.537975
iter  50 value 86.533559
iter  60 value 86.476171
iter  70 value 86.277187
iter  80 value 85.310319
iter  90 value 84.790793
iter 100 value 84.669022
final  value 84.669022 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.221774 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.211509 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.380911 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.140707 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.575627 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.232397 
iter  10 value 93.016715
iter  20 value 87.142115
iter  30 value 86.100958
iter  40 value 86.099607
final  value 86.099605 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.839905 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.353585 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.376544 
iter  10 value 85.557144
iter  20 value 83.931899
iter  30 value 83.584722
iter  40 value 83.575960
iter  40 value 83.575960
final  value 83.575960 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.734935 
iter  10 value 93.724711
iter  10 value 93.724711
iter  10 value 93.724711
final  value 93.724711 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.337192 
iter  10 value 94.179692
final  value 93.946237 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.536762 
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.841260 
iter  10 value 93.491549
iter  20 value 92.824798
iter  30 value 92.815736
final  value 92.815715 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.579609 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.260776 
iter  10 value 86.079913
iter  20 value 84.238990
iter  30 value 84.189291
final  value 84.189285 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.697348 
iter  10 value 93.676171
iter  20 value 88.055346
iter  30 value 87.164092
iter  40 value 86.148788
iter  50 value 85.571312
iter  60 value 85.402397
iter  70 value 85.374819
iter  80 value 84.784341
iter  90 value 84.456206
final  value 84.455512 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.062934 
iter  10 value 93.452627
iter  20 value 86.637768
iter  30 value 85.661072
iter  40 value 85.429492
iter  50 value 84.817022
iter  60 value 84.467178
iter  70 value 84.457038
iter  70 value 84.457037
iter  70 value 84.457037
final  value 84.457037 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.204029 
iter  10 value 94.055665
iter  20 value 93.940827
iter  30 value 91.115921
iter  40 value 86.787784
iter  50 value 84.435963
iter  60 value 83.752162
final  value 83.750479 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.247008 
iter  10 value 94.046783
iter  20 value 93.466782
iter  30 value 91.094585
iter  40 value 89.334155
iter  50 value 84.382419
iter  60 value 82.848106
iter  70 value 82.574558
iter  80 value 81.704801
iter  90 value 81.186670
iter 100 value 81.000201
final  value 81.000201 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 109.001909 
iter  10 value 94.051550
iter  20 value 89.113277
iter  30 value 86.063248
iter  40 value 84.947856
iter  50 value 84.605349
iter  60 value 84.481716
iter  70 value 84.458666
final  value 84.457662 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.870421 
iter  10 value 94.083566
iter  20 value 86.468754
iter  30 value 85.510089
iter  40 value 85.313520
iter  50 value 83.949629
iter  60 value 83.082745
iter  70 value 82.459142
iter  80 value 82.339383
iter  90 value 81.884388
iter 100 value 81.542611
final  value 81.542611 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.801960 
iter  10 value 89.554731
iter  20 value 86.362905
iter  30 value 85.967018
iter  40 value 85.200071
iter  50 value 84.852351
iter  60 value 84.715598
iter  70 value 84.023505
iter  80 value 83.071832
iter  90 value 81.476724
iter 100 value 80.625681
final  value 80.625681 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.763404 
iter  10 value 94.071514
iter  20 value 93.901552
iter  30 value 87.737148
iter  40 value 85.158756
iter  50 value 81.643839
iter  60 value 80.355916
iter  70 value 80.233404
iter  80 value 80.081588
iter  90 value 79.981767
iter 100 value 79.971814
final  value 79.971814 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.635782 
iter  10 value 94.012383
iter  20 value 85.698576
iter  30 value 85.193930
iter  40 value 84.883757
iter  50 value 83.974802
iter  60 value 82.626368
iter  70 value 80.861145
iter  80 value 80.508231
iter  90 value 80.190063
iter 100 value 79.879351
final  value 79.879351 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.410253 
iter  10 value 94.056494
iter  20 value 86.661709
iter  30 value 85.434326
iter  40 value 84.910949
iter  50 value 82.800789
iter  60 value 80.984079
iter  70 value 80.633578
iter  80 value 80.479057
iter  90 value 80.211237
iter 100 value 79.593098
final  value 79.593098 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.085533 
iter  10 value 94.144315
iter  20 value 93.393640
iter  30 value 86.158300
iter  40 value 84.861216
iter  50 value 82.854811
iter  60 value 81.119280
iter  70 value 80.383678
iter  80 value 80.346767
iter  90 value 80.162396
iter 100 value 79.943004
final  value 79.943004 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.071415 
iter  10 value 94.202997
iter  20 value 93.959617
iter  30 value 85.488320
iter  40 value 85.253500
iter  50 value 84.477237
iter  60 value 81.819461
iter  70 value 81.555933
iter  80 value 81.073552
iter  90 value 79.694757
iter 100 value 79.255188
final  value 79.255188 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.489753 
iter  10 value 95.645192
iter  20 value 91.251972
iter  30 value 82.920848
iter  40 value 80.901957
iter  50 value 79.411634
iter  60 value 79.312578
iter  70 value 79.108004
iter  80 value 79.085607
iter  90 value 79.075768
iter 100 value 79.027997
final  value 79.027997 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.549446 
iter  10 value 93.802133
iter  20 value 93.112251
iter  30 value 91.820658
iter  40 value 87.111517
iter  50 value 85.016502
iter  60 value 81.778093
iter  70 value 80.941649
iter  80 value 80.537361
iter  90 value 80.317130
iter 100 value 79.958171
final  value 79.958171 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.673866 
iter  10 value 95.695156
iter  20 value 92.878002
iter  30 value 86.297955
iter  40 value 84.410091
iter  50 value 82.272849
iter  60 value 81.823375
iter  70 value 81.615196
iter  80 value 81.044415
iter  90 value 80.881551
iter 100 value 80.487324
final  value 80.487324 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.306600 
final  value 94.054574 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.259669 
iter  10 value 88.482588
iter  20 value 85.802291
final  value 85.802217 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.504823 
final  value 94.010121 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.843179 
final  value 94.054501 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.988372 
final  value 94.054489 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.973243 
iter  10 value 94.067603
iter  20 value 94.062006
iter  30 value 86.499190
iter  40 value 85.088924
iter  50 value 85.081457
iter  60 value 85.078429
final  value 85.078111 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.846604 
iter  10 value 94.057656
iter  20 value 93.419821
iter  30 value 87.798335
iter  40 value 87.340591
iter  50 value 87.330913
final  value 87.330903 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.968548 
iter  10 value 94.013551
iter  20 value 93.570476
iter  30 value 86.943933
iter  40 value 86.935733
iter  50 value 85.087353
iter  60 value 85.077832
final  value 85.077747 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.419721 
iter  10 value 94.057439
iter  20 value 94.051781
iter  30 value 86.975017
iter  40 value 86.609347
iter  50 value 84.988287
iter  60 value 84.984957
iter  70 value 84.945115
iter  80 value 84.939817
iter  90 value 84.622581
iter 100 value 84.537393
final  value 84.537393 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.394710 
iter  10 value 93.899024
iter  20 value 93.881534
final  value 93.865610 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.151582 
iter  10 value 94.061088
iter  20 value 94.042032
iter  30 value 92.265691
iter  40 value 87.908045
iter  50 value 86.446978
iter  60 value 86.216436
iter  70 value 86.209365
iter  80 value 83.981989
iter  90 value 82.686723
iter 100 value 82.682374
final  value 82.682374 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.549979 
iter  10 value 93.971270
iter  20 value 93.962793
iter  30 value 85.997330
iter  40 value 83.792041
iter  50 value 83.789689
iter  60 value 83.630456
iter  70 value 83.618374
iter  80 value 83.617710
final  value 83.617378 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.745359 
iter  10 value 94.016820
iter  20 value 94.010072
final  value 94.009572 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.266248 
iter  10 value 93.213734
iter  20 value 93.026788
iter  30 value 92.140793
iter  40 value 92.121611
iter  50 value 92.109279
final  value 92.108915 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.974452 
iter  10 value 85.319872
iter  20 value 84.089175
iter  30 value 83.777605
iter  40 value 83.142721
iter  50 value 83.007606
iter  60 value 83.003289
iter  70 value 83.003006
iter  80 value 82.921007
iter  90 value 81.744782
iter 100 value 80.010214
final  value 80.010214 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.832237 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.836703 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.678701 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.345687 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.210491 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.956174 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.436360 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.620928 
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.063293 
iter  10 value 94.038286
iter  20 value 88.360965
iter  30 value 88.212123
final  value 88.212121 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.432076 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.305140 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.552605 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.306819 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.340026 
final  value 93.936782 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.421091 
iter  10 value 94.321437
final  value 94.321429 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.683838 
iter  10 value 94.456570
iter  20 value 86.741298
iter  30 value 84.897521
iter  40 value 84.601126
iter  50 value 84.527888
iter  60 value 84.358110
iter  70 value 84.149988
final  value 84.141204 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.163200 
iter  10 value 94.475032
iter  20 value 94.000569
iter  30 value 88.746432
iter  40 value 87.912191
iter  50 value 83.831460
iter  60 value 83.648325
iter  70 value 82.448931
iter  80 value 82.248046
iter  90 value 82.027059
iter 100 value 82.024818
final  value 82.024818 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.615422 
iter  10 value 94.297475
iter  20 value 94.178805
iter  30 value 85.339743
iter  40 value 84.278219
iter  50 value 84.086137
iter  60 value 83.770466
iter  70 value 83.737886
final  value 83.737883 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.370226 
iter  10 value 94.462699
iter  20 value 93.475758
iter  30 value 89.508312
iter  40 value 88.235765
iter  50 value 86.510664
iter  60 value 84.570834
iter  70 value 82.601155
iter  80 value 82.066442
iter  90 value 82.025935
iter 100 value 82.024830
final  value 82.024830 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.451793 
iter  10 value 94.474345
iter  20 value 91.038015
iter  30 value 85.013930
iter  40 value 84.532345
iter  50 value 84.355547
iter  60 value 84.194069
iter  70 value 84.144043
iter  80 value 84.141763
iter  90 value 84.140830
iter  90 value 84.140830
iter  90 value 84.140830
final  value 84.140830 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.470372 
iter  10 value 94.430920
iter  20 value 90.701118
iter  30 value 85.696927
iter  40 value 84.633313
iter  50 value 83.919342
iter  60 value 83.373136
iter  70 value 82.723818
iter  80 value 81.881994
iter  90 value 81.712228
iter 100 value 81.471470
final  value 81.471470 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.354593 
iter  10 value 94.121536
iter  20 value 92.719563
iter  30 value 87.684566
iter  40 value 86.597422
iter  50 value 84.383481
iter  60 value 83.388352
iter  70 value 81.955678
iter  80 value 81.437637
iter  90 value 81.219718
iter 100 value 81.115360
final  value 81.115360 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.520233 
iter  10 value 94.643224
iter  20 value 94.518849
iter  30 value 84.959251
iter  40 value 84.151411
iter  50 value 83.829869
iter  60 value 83.651067
iter  70 value 82.424048
iter  80 value 81.840615
iter  90 value 81.524571
iter 100 value 81.337277
final  value 81.337277 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.272857 
iter  10 value 94.426945
iter  20 value 86.643280
iter  30 value 84.735141
iter  40 value 84.250877
iter  50 value 84.046391
iter  60 value 83.853004
iter  70 value 83.295032
iter  80 value 82.286712
iter  90 value 81.349479
iter 100 value 81.191019
final  value 81.191019 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.515325 
iter  10 value 94.486917
iter  20 value 93.951713
iter  30 value 90.789447
iter  40 value 90.557930
iter  50 value 89.720930
iter  60 value 84.859173
iter  70 value 83.011612
iter  80 value 82.315697
iter  90 value 82.197156
iter 100 value 81.848792
final  value 81.848792 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.264086 
iter  10 value 94.545759
iter  20 value 88.892381
iter  30 value 87.632011
iter  40 value 85.827633
iter  50 value 84.509554
iter  60 value 84.225296
iter  70 value 83.870898
iter  80 value 83.769816
iter  90 value 82.640773
iter 100 value 82.457419
final  value 82.457419 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.384773 
iter  10 value 95.015547
iter  20 value 90.553009
iter  30 value 86.373311
iter  40 value 85.746427
iter  50 value 84.457519
iter  60 value 82.260196
iter  70 value 81.335157
iter  80 value 81.116279
iter  90 value 80.816904
iter 100 value 80.630091
final  value 80.630091 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.976423 
iter  10 value 94.240419
iter  20 value 86.070324
iter  30 value 84.011937
iter  40 value 82.398311
iter  50 value 81.780565
iter  60 value 81.630107
iter  70 value 81.501156
iter  80 value 81.381894
iter  90 value 81.124534
iter 100 value 81.102919
final  value 81.102919 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.228378 
iter  10 value 94.593521
iter  20 value 88.245963
iter  30 value 87.191338
iter  40 value 85.299017
iter  50 value 83.548298
iter  60 value 82.662190
iter  70 value 82.283481
iter  80 value 82.225081
iter  90 value 81.876163
iter 100 value 81.837699
final  value 81.837699 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 142.413229 
iter  10 value 96.126102
iter  20 value 94.475425
iter  30 value 93.527668
iter  40 value 89.456145
iter  50 value 86.075730
iter  60 value 83.597001
iter  70 value 82.747476
iter  80 value 82.605828
iter  90 value 82.220795
iter 100 value 81.511970
final  value 81.511970 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.221355 
iter  10 value 94.485912
final  value 94.485762 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.744141 
final  value 94.485902 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.384338 
final  value 94.485674 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.601244 
final  value 94.485906 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.315493 
iter  10 value 94.485980
iter  20 value 94.484256
final  value 94.484215 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.905097 
iter  10 value 94.484678
iter  20 value 88.128464
iter  30 value 84.186146
iter  40 value 82.069161
iter  50 value 81.881317
final  value 81.879942 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.918936 
iter  10 value 94.488852
iter  20 value 94.477269
iter  30 value 93.240103
iter  40 value 93.220807
iter  50 value 91.801132
iter  60 value 82.795465
iter  70 value 82.764631
iter  80 value 81.987048
iter  90 value 81.212592
iter 100 value 80.374945
final  value 80.374945 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.870578 
iter  10 value 94.493362
iter  20 value 94.470810
iter  30 value 85.670697
iter  40 value 85.663454
iter  50 value 85.661012
iter  60 value 85.570635
iter  70 value 84.213185
iter  80 value 84.210260
iter  90 value 83.168231
iter 100 value 81.065943
final  value 81.065943 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.993316 
iter  10 value 94.525018
iter  20 value 94.411725
iter  30 value 92.341502
iter  40 value 92.309290
iter  50 value 91.553017
iter  60 value 91.542413
iter  70 value 91.534760
iter  80 value 91.434396
iter  90 value 91.397234
iter 100 value 91.392532
final  value 91.392532 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.977072 
iter  10 value 93.863979
iter  20 value 93.823197
iter  30 value 85.791981
iter  40 value 85.285523
iter  50 value 85.285418
iter  60 value 85.285205
final  value 85.285201 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.822317 
iter  10 value 94.492292
iter  20 value 94.457288
iter  30 value 90.819205
iter  40 value 86.922725
iter  50 value 82.802568
iter  60 value 82.463128
iter  70 value 82.371910
final  value 82.371003 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.083651 
iter  10 value 94.467358
iter  20 value 94.362047
iter  30 value 94.361320
iter  40 value 94.356005
iter  50 value 92.357337
iter  60 value 84.439552
iter  70 value 83.890666
iter  80 value 83.231321
iter  90 value 83.043487
iter 100 value 81.112024
final  value 81.112024 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.492082 
iter  10 value 94.492310
iter  20 value 94.484282
iter  30 value 89.392541
final  value 89.392201 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.449875 
iter  10 value 94.362259
iter  20 value 94.354513
final  value 94.354447 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.668162 
iter  10 value 94.054982
iter  20 value 94.049099
iter  30 value 94.048925
iter  40 value 90.657423
iter  50 value 87.133723
iter  60 value 83.937298
final  value 83.937296 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.266634 
iter  10 value 89.894497
iter  20 value 88.223699
iter  30 value 88.124156
iter  40 value 88.107567
final  value 88.107560 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.442735 
final  value 94.305880 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.757324 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.392424 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.424376 
iter  10 value 94.113855
final  value 94.112570 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.431977 
final  value 94.428839 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.767895 
final  value 94.322897 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.272119 
final  value 94.322897 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.035273 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.495067 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.600327 
iter  10 value 94.275572
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.580110 
iter  10 value 94.289216
iter  10 value 94.289216
iter  10 value 94.289216
final  value 94.289216 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.399536 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.414046 
iter  10 value 90.308433
iter  20 value 90.295092
final  value 90.295083 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.361654 
iter  10 value 87.508419
iter  20 value 86.384247
final  value 86.384048 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.619698 
iter  10 value 94.254306
iter  20 value 88.430369
iter  30 value 84.958706
iter  40 value 83.709439
iter  50 value 83.204480
iter  60 value 82.837425
iter  70 value 82.688145
iter  80 value 82.442010
iter  90 value 82.074844
iter 100 value 82.066627
final  value 82.066627 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.136777 
iter  10 value 93.961257
iter  20 value 90.784405
iter  30 value 88.396147
iter  40 value 85.760480
iter  50 value 85.442809
iter  60 value 83.054663
iter  70 value 82.663066
iter  80 value 82.648501
final  value 82.648498 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.414706 
iter  10 value 94.486104
iter  20 value 94.050695
iter  30 value 93.006518
iter  40 value 92.728404
iter  50 value 90.473865
iter  60 value 86.171541
iter  70 value 84.676645
iter  80 value 84.596172
iter  90 value 84.549369
iter 100 value 84.531128
final  value 84.531128 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.521056 
iter  10 value 94.489159
iter  20 value 94.485897
iter  30 value 88.696654
iter  40 value 88.237553
iter  50 value 85.993421
iter  60 value 83.401637
iter  70 value 83.331040
iter  80 value 83.274766
final  value 83.273719 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.609230 
iter  10 value 93.176789
iter  20 value 88.326358
iter  30 value 85.080970
iter  40 value 84.715381
iter  50 value 84.535318
iter  60 value 84.530325
final  value 84.529818 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.892917 
iter  10 value 94.481926
iter  20 value 89.874970
iter  30 value 85.451372
iter  40 value 84.318704
iter  50 value 82.158355
iter  60 value 80.755411
iter  70 value 80.386472
iter  80 value 80.338260
iter  90 value 79.747307
iter 100 value 79.418687
final  value 79.418687 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.319067 
iter  10 value 95.277446
iter  20 value 91.942377
iter  30 value 85.974908
iter  40 value 85.122079
iter  50 value 83.645160
iter  60 value 82.534712
iter  70 value 80.933143
iter  80 value 80.447326
iter  90 value 79.788315
iter 100 value 79.265432
final  value 79.265432 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.734807 
iter  10 value 94.310258
iter  20 value 89.581235
iter  30 value 84.489989
iter  40 value 83.480781
iter  50 value 81.691830
iter  60 value 80.740379
iter  70 value 79.737008
iter  80 value 79.643275
iter  90 value 79.599190
iter 100 value 79.586924
final  value 79.586924 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.858948 
iter  10 value 94.423398
iter  20 value 91.639102
iter  30 value 90.905132
iter  40 value 86.616124
iter  50 value 84.571056
iter  60 value 82.787064
iter  70 value 81.891179
iter  80 value 81.060022
iter  90 value 80.376533
iter 100 value 79.618900
final  value 79.618900 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.269904 
iter  10 value 94.507161
iter  20 value 94.197952
iter  30 value 89.629883
iter  40 value 89.092123
iter  50 value 88.193997
iter  60 value 86.431933
iter  70 value 85.793035
iter  80 value 85.604648
iter  90 value 85.593914
iter 100 value 82.445119
final  value 82.445119 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.195851 
iter  10 value 94.792015
iter  20 value 87.857603
iter  30 value 82.888124
iter  40 value 82.113984
iter  50 value 81.515007
iter  60 value 81.366068
iter  70 value 80.748735
iter  80 value 80.043432
iter  90 value 79.866043
iter 100 value 79.587517
final  value 79.587517 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.155144 
iter  10 value 94.140885
iter  20 value 86.684403
iter  30 value 84.046734
iter  40 value 80.577339
iter  50 value 80.029895
iter  60 value 79.538801
iter  70 value 79.488093
iter  80 value 79.420527
iter  90 value 79.189620
iter 100 value 78.812306
final  value 78.812306 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.917132 
iter  10 value 94.667724
iter  20 value 93.937231
iter  30 value 92.108470
iter  40 value 91.168980
iter  50 value 89.907438
iter  60 value 87.381741
iter  70 value 84.434061
iter  80 value 82.360093
iter  90 value 81.515387
iter 100 value 81.123035
final  value 81.123035 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.179857 
iter  10 value 94.471012
iter  20 value 88.531948
iter  30 value 85.995944
iter  40 value 82.493298
iter  50 value 80.981328
iter  60 value 80.272757
iter  70 value 80.077659
iter  80 value 79.757128
iter  90 value 79.563712
iter 100 value 79.466686
final  value 79.466686 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.920970 
iter  10 value 94.688895
iter  20 value 94.310235
iter  30 value 91.562617
iter  40 value 87.208192
iter  50 value 84.528370
iter  60 value 82.435673
iter  70 value 79.909463
iter  80 value 79.386254
iter  90 value 79.063524
iter 100 value 78.867784
final  value 78.867784 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.313534 
iter  10 value 94.485673
final  value 94.484220 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.480341 
iter  10 value 94.486028
iter  20 value 94.484222
iter  30 value 94.120884
iter  40 value 94.112837
final  value 94.112823 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.262209 
iter  10 value 94.485869
iter  20 value 94.305965
iter  30 value 91.197769
iter  40 value 91.171940
iter  50 value 90.194823
iter  60 value 89.331024
iter  70 value 89.255792
iter  80 value 89.251431
iter  90 value 87.549658
iter 100 value 87.233190
final  value 87.233190 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.509023 
final  value 94.485745 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.220721 
final  value 94.485816 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.748212 
iter  10 value 94.359242
iter  20 value 94.355882
final  value 94.355796 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.242418 
iter  10 value 94.489153
iter  20 value 94.484219
iter  20 value 94.484218
iter  20 value 94.484218
final  value 94.484218 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.498569 
iter  10 value 94.488833
iter  20 value 94.484230
final  value 94.354680 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.912371 
iter  10 value 94.327764
iter  20 value 89.714984
iter  30 value 87.260586
iter  40 value 86.450813
iter  50 value 86.378451
iter  50 value 86.378451
iter  50 value 86.378451
final  value 86.378451 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.972283 
iter  10 value 94.489258
iter  20 value 94.302525
iter  30 value 92.898825
iter  40 value 90.584457
iter  50 value 90.546068
iter  60 value 90.545911
iter  70 value 90.509170
iter  80 value 90.026849
iter  90 value 89.429224
iter 100 value 89.251692
final  value 89.251692 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.687372 
iter  10 value 94.361904
iter  20 value 92.330003
iter  30 value 81.639640
iter  40 value 81.631129
iter  50 value 81.620956
iter  60 value 81.613041
iter  70 value 81.525356
iter  80 value 80.177571
iter  90 value 80.005881
iter 100 value 80.005177
final  value 80.005177 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.448114 
iter  10 value 94.489205
iter  20 value 91.961028
iter  30 value 85.671424
iter  40 value 85.661962
iter  50 value 85.648376
iter  60 value 85.546364
iter  70 value 85.544401
iter  80 value 85.406575
iter  90 value 85.331611
iter 100 value 85.331413
final  value 85.331413 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.004442 
iter  10 value 94.492111
iter  20 value 94.484535
iter  30 value 94.067907
iter  40 value 90.078247
iter  50 value 89.952028
iter  60 value 87.224082
final  value 86.055141 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.710430 
iter  10 value 94.491484
iter  20 value 94.369535
iter  30 value 89.030911
iter  40 value 83.594640
final  value 83.594449 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.870826 
iter  10 value 94.492609
iter  20 value 94.483779
iter  30 value 85.005351
iter  40 value 84.752235
iter  50 value 84.750307
iter  60 value 84.051641
iter  70 value 83.904752
iter  80 value 83.458293
final  value 83.458265 
converged
Fitting Repeat 1 

# weights:  507
initial  value 129.393698 
iter  10 value 117.688441
iter  20 value 117.686305
iter  30 value 117.539904
iter  40 value 117.539498
iter  50 value 117.537997
iter  60 value 112.366086
iter  70 value 105.444626
iter  80 value 104.794344
iter  90 value 104.747321
iter 100 value 101.931127
final  value 101.931127 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.576885 
iter  10 value 117.767062
iter  20 value 117.759117
iter  30 value 117.520080
iter  40 value 114.904989
iter  50 value 112.080041
iter  60 value 111.987071
iter  70 value 110.813096
iter  80 value 110.517568
iter  90 value 110.489552
iter 100 value 105.577500
final  value 105.577500 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 140.105258 
iter  10 value 117.131149
iter  20 value 117.103842
iter  30 value 111.744098
iter  40 value 108.430546
iter  50 value 108.426163
iter  60 value 108.413840
iter  70 value 108.413224
iter  80 value 108.092837
final  value 108.092609 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.395216 
iter  10 value 117.767458
iter  20 value 117.743882
iter  30 value 117.728773
iter  40 value 117.728631
iter  50 value 117.728591
iter  60 value 117.728528
iter  70 value 117.728467
iter  80 value 115.598112
iter  90 value 106.944418
iter 100 value 106.649963
final  value 106.649963 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.359161 
iter  10 value 117.898063
iter  20 value 117.890285
iter  30 value 107.706854
iter  40 value 107.002344
iter  50 value 106.779352
iter  60 value 106.779016
iter  70 value 106.777350
iter  80 value 106.655642
final  value 106.655576 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri Aug  8 21:45:31 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 43.079   1.741 126.097 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod33.582 1.83935.764
FreqInteractors0.2560.0130.272
calculateAAC0.0390.0100.049
calculateAutocor0.3630.0700.438
calculateCTDC0.0840.0060.090
calculateCTDD0.6510.0220.677
calculateCTDT0.2230.0110.236
calculateCTriad0.3780.0400.423
calculateDC0.1030.0110.116
calculateF0.3640.0130.378
calculateKSAAP0.1020.0090.111
calculateQD_Sm1.7390.1241.883
calculateTC2.0110.1652.198
calculateTC_Sm0.2350.0150.252
corr_plot33.665 1.87535.919
enrichfindP0.4670.0578.220
enrichfind_hp0.0570.0221.011
enrichplot0.4050.0100.417
filter_missing_values0.0010.0000.001
getFASTA0.0680.0113.009
getHPI0.0000.0000.001
get_negativePPI0.0010.0000.001
get_positivePPI0.0010.0000.000
impute_missing_data0.0010.0000.001
plotPPI0.0720.0030.075
pred_ensembel13.964 0.45112.456
var_imp35.827 2.08338.507