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This page was generated on 2025-10-06 11:41 -0400 (Mon, 06 Oct 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4832
merida1macOS 12.7.5 Montereyx86_644.5.1 RC (2025-06-05 r88288) -- "Great Square Root" 4613
kjohnson1macOS 13.6.6 Venturaarm644.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" 4554
kunpeng2Linux (openEuler 24.03 LTS)aarch64R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" 4585
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 997/2341HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
HPiP 1.14.0  (landing page)
Matineh Rahmatbakhsh
Snapshot Date: 2025-10-02 13:40 -0400 (Thu, 02 Oct 2025)
git_url: https://git.bioconductor.org/packages/HPiP
git_branch: RELEASE_3_21
git_last_commit: e2435b7
git_last_commit_date: 2025-04-15 12:38:30 -0400 (Tue, 15 Apr 2025)
nebbiolo1Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    ERROR  skipped
merida1macOS 12.7.5 Monterey / x86_64  OK    ERROR  skippedskipped
kjohnson1macOS 13.6.6 Ventura / arm64  OK    ERROR  skippedskipped
kunpeng2Linux (openEuler 24.03 LTS) / aarch64  OK    OK    OK  


CHECK results for HPiP on kunpeng2

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.
- See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host.

raw results


Summary

Package: HPiP
Version: 1.14.0
Command: /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.14.0.tar.gz
StartedAt: 2025-10-03 10:18:10 -0000 (Fri, 03 Oct 2025)
EndedAt: 2025-10-03 10:24:55 -0000 (Fri, 03 Oct 2025)
EllapsedTime: 404.4 seconds
RetCode: 0
Status:   OK  
CheckDir: HPiP.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.14.0’
* 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 loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... 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       39.682  0.355  40.118
FSmethod      37.377  0.563  38.021
corr_plot     37.056  0.236  37.335
pred_ensembel 18.648  0.515  17.991
enrichfindP    0.497  0.028  18.831
getFASTA       0.076  0.028   7.741
* 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
  ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.


Installation output

HPiP.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.14.0’
** 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 Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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 103.362733 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.071092 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.715975 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.736694 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.195829 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.178912 
iter  10 value 93.892643
iter  20 value 93.871516
iter  20 value 93.871516
iter  20 value 93.871516
final  value 93.871516 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.861238 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.390611 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.681189 
iter  10 value 92.667685
iter  20 value 92.029306
iter  30 value 86.674387
iter  40 value 85.878934
final  value 85.841270 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.387190 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.846365 
iter  10 value 83.519641
iter  20 value 81.131807
iter  30 value 81.121651
final  value 81.120873 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.330728 
iter  10 value 93.929746
iter  20 value 92.512382
final  value 92.512353 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.801817 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.796927 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.046832 
iter  10 value 93.205814
iter  10 value 93.205814
iter  10 value 93.205814
final  value 93.205814 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.370799 
iter  10 value 93.140561
iter  20 value 89.414505
iter  30 value 89.199207
iter  40 value 89.122140
iter  50 value 89.120063
iter  50 value 89.120063
iter  50 value 89.120063
final  value 89.120063 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.913298 
iter  10 value 94.488795
iter  20 value 94.455186
iter  30 value 94.389525
iter  40 value 94.383482
iter  50 value 94.005393
iter  60 value 85.366216
iter  70 value 84.601658
iter  80 value 82.696921
iter  90 value 81.752308
iter 100 value 81.114011
final  value 81.114011 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.493383 
iter  10 value 92.524263
iter  20 value 88.926312
iter  30 value 85.856920
iter  40 value 85.571031
iter  50 value 83.042006
iter  60 value 82.335103
iter  70 value 82.277874
iter  80 value 82.233923
final  value 82.232219 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.669504 
iter  10 value 94.488553
iter  20 value 93.505203
iter  30 value 93.492507
iter  40 value 85.221551
iter  50 value 84.125052
iter  60 value 82.465433
iter  70 value 81.872843
iter  80 value 81.731741
iter  90 value 81.705031
final  value 81.704165 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.632956 
iter  10 value 94.487277
iter  20 value 93.963339
iter  30 value 93.823778
iter  40 value 84.635573
iter  50 value 83.230580
iter  60 value 82.945802
iter  70 value 81.032127
iter  80 value 80.790743
iter  90 value 80.767977
final  value 80.767746 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.159280 
iter  10 value 94.467508
iter  20 value 93.788507
iter  30 value 86.179068
iter  40 value 82.987346
iter  50 value 79.603940
iter  60 value 78.916217
iter  70 value 78.452299
iter  80 value 78.208950
iter  90 value 77.821306
iter 100 value 77.568428
final  value 77.568428 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 126.494539 
iter  10 value 94.525306
iter  20 value 93.947667
iter  30 value 92.807098
iter  40 value 82.290574
iter  50 value 80.265849
iter  60 value 78.697935
iter  70 value 78.000227
iter  80 value 77.859216
iter  90 value 77.442254
iter 100 value 77.189376
final  value 77.189376 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.793498 
iter  10 value 94.230092
iter  20 value 86.131490
iter  30 value 84.315411
iter  40 value 83.059720
iter  50 value 82.094885
iter  60 value 81.170502
iter  70 value 79.351775
iter  80 value 77.601797
iter  90 value 76.766788
iter 100 value 76.483563
final  value 76.483563 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 115.205472 
iter  10 value 94.902266
iter  20 value 94.476118
iter  30 value 91.694842
iter  40 value 88.847803
iter  50 value 87.906604
iter  60 value 86.249669
iter  70 value 79.877916
iter  80 value 78.189445
iter  90 value 77.719539
iter 100 value 77.315337
final  value 77.315337 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.879005 
iter  10 value 87.620739
iter  20 value 82.994603
iter  30 value 81.929303
iter  40 value 81.687620
iter  50 value 80.536011
iter  60 value 80.139562
iter  70 value 78.721805
iter  80 value 77.902257
iter  90 value 77.192352
iter 100 value 76.978883
final  value 76.978883 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.198258 
iter  10 value 94.257660
iter  20 value 92.964070
iter  30 value 90.336038
iter  40 value 83.785256
iter  50 value 80.427615
iter  60 value 78.089524
iter  70 value 77.683974
iter  80 value 76.980703
iter  90 value 76.793313
iter 100 value 76.645645
final  value 76.645645 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.065446 
iter  10 value 93.379552
iter  20 value 84.066897
iter  30 value 80.642497
iter  40 value 79.718218
iter  50 value 79.241110
iter  60 value 77.067022
iter  70 value 76.178450
iter  80 value 75.949878
iter  90 value 75.670963
iter 100 value 75.615215
final  value 75.615215 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.070292 
iter  10 value 93.762144
iter  20 value 88.249051
iter  30 value 85.040825
iter  40 value 82.895047
iter  50 value 82.444081
iter  60 value 80.629014
iter  70 value 77.971514
iter  80 value 77.211114
iter  90 value 77.013539
iter 100 value 76.743143
final  value 76.743143 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.939156 
iter  10 value 95.013297
iter  20 value 84.173209
iter  30 value 83.960950
iter  40 value 82.446223
iter  50 value 80.728259
iter  60 value 79.537579
iter  70 value 79.190373
iter  80 value 78.705120
iter  90 value 78.667231
iter 100 value 78.569168
final  value 78.569168 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.219035 
iter  10 value 93.717824
iter  20 value 85.202766
iter  30 value 82.688731
iter  40 value 82.153671
iter  50 value 81.868331
iter  60 value 81.028267
iter  70 value 80.670965
iter  80 value 80.393916
iter  90 value 79.240267
iter 100 value 78.029928
final  value 78.029928 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.821643 
final  value 94.487234 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.608536 
final  value 94.485982 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.219416 
iter  10 value 94.485835
iter  20 value 94.477124
iter  30 value 82.692525
iter  40 value 82.632396
iter  50 value 82.605794
iter  60 value 82.602609
iter  70 value 82.599929
iter  80 value 82.585556
iter  90 value 82.479107
iter 100 value 82.478491
final  value 82.478491 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.690917 
final  value 94.487188 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.791941 
final  value 94.485931 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.139030 
iter  10 value 94.489567
iter  20 value 94.484268
final  value 94.484264 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.868038 
iter  10 value 94.489262
iter  20 value 94.256674
iter  30 value 83.956613
iter  40 value 83.267549
iter  50 value 83.262352
iter  60 value 83.261870
iter  70 value 83.016443
iter  80 value 79.326425
iter  90 value 78.039614
iter 100 value 78.038495
final  value 78.038495 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.393448 
iter  10 value 93.304964
final  value 93.304777 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.123607 
iter  10 value 93.626502
iter  20 value 93.625724
iter  30 value 92.553815
iter  40 value 92.545392
iter  40 value 92.545392
iter  40 value 92.545392
final  value 92.545392 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.444677 
iter  10 value 93.305752
iter  20 value 93.302685
iter  30 value 81.445219
iter  40 value 81.441569
iter  50 value 81.092758
iter  60 value 81.046409
final  value 81.045729 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.374009 
iter  10 value 94.488190
iter  20 value 82.276170
iter  30 value 81.118570
final  value 81.118282 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.388436 
iter  10 value 94.363017
iter  20 value 94.357314
iter  30 value 94.353138
iter  40 value 89.453698
iter  50 value 89.064027
final  value 89.063620 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.433650 
iter  10 value 93.818375
iter  20 value 93.815369
iter  30 value 93.787531
iter  40 value 93.781346
iter  50 value 93.689111
iter  60 value 93.687574
iter  70 value 93.445540
iter  80 value 77.541234
iter  90 value 75.013319
iter 100 value 74.484517
final  value 74.484517 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.706173 
iter  10 value 93.781507
iter  20 value 93.779744
iter  30 value 93.701828
iter  40 value 93.700894
iter  50 value 93.686619
iter  60 value 93.536216
final  value 93.536171 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.932317 
iter  10 value 92.299877
iter  20 value 80.467227
iter  30 value 79.470079
iter  40 value 79.089480
iter  50 value 78.330302
iter  60 value 76.762639
iter  70 value 76.292551
iter  80 value 76.186757
iter  90 value 76.184590
final  value 76.183036 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.174086 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.916352 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.586932 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.735188 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.189435 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.798178 
final  value 94.484208 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.669425 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.612952 
final  value 93.783647 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.567259 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.156498 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.713090 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 123.891778 
iter  10 value 94.012863
iter  20 value 94.008781
final  value 94.008684 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.065727 
iter  10 value 94.475796
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.839279 
final  value 93.783647 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.684824 
iter  10 value 94.144793
final  value 94.144496 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.130994 
iter  10 value 94.177208
iter  20 value 93.309049
iter  30 value 85.408313
iter  40 value 82.775980
iter  50 value 82.395554
iter  60 value 81.798748
iter  70 value 80.885740
iter  80 value 80.558706
iter  90 value 80.508664
final  value 80.508635 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.098919 
iter  10 value 94.469298
iter  20 value 94.240788
iter  30 value 94.219913
iter  40 value 94.177398
iter  50 value 90.248226
iter  60 value 84.257472
iter  70 value 83.861508
iter  80 value 83.782123
iter  90 value 82.859807
iter 100 value 82.423475
final  value 82.423475 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.340551 
iter  10 value 94.489012
iter  20 value 94.488591
iter  30 value 94.306029
iter  40 value 93.853749
iter  50 value 90.320273
iter  60 value 88.455702
iter  70 value 87.070671
iter  80 value 83.586178
iter  90 value 80.863743
iter 100 value 80.633578
final  value 80.633578 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.394985 
iter  10 value 94.493904
iter  20 value 94.346285
iter  30 value 94.094035
iter  40 value 94.092558
iter  50 value 94.092044
final  value 94.091465 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.907046 
iter  10 value 94.599055
iter  20 value 94.486498
iter  30 value 93.071153
iter  40 value 90.649099
iter  50 value 87.642655
iter  60 value 82.901746
iter  70 value 80.711949
iter  80 value 80.241499
iter  90 value 80.192230
final  value 80.192208 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.673068 
iter  10 value 93.264934
iter  20 value 82.970345
iter  30 value 81.738597
iter  40 value 81.462569
iter  50 value 80.057272
iter  60 value 79.312492
iter  70 value 79.052063
iter  80 value 78.812164
iter  90 value 78.654883
iter 100 value 78.588510
final  value 78.588510 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.324808 
iter  10 value 93.277587
iter  20 value 84.118098
iter  30 value 83.116760
iter  40 value 82.596407
iter  50 value 82.351207
iter  60 value 81.511632
iter  70 value 80.488852
iter  80 value 80.174060
iter  90 value 79.722541
iter 100 value 79.518421
final  value 79.518421 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.571782 
iter  10 value 94.405463
iter  20 value 94.222671
iter  30 value 86.258519
iter  40 value 84.338623
iter  50 value 83.471065
iter  60 value 82.597589
iter  70 value 82.530761
iter  80 value 82.478783
iter  90 value 81.690403
iter 100 value 79.968768
final  value 79.968768 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 124.044462 
iter  10 value 94.543867
iter  20 value 94.123816
iter  30 value 92.684488
iter  40 value 84.284734
iter  50 value 82.305662
iter  60 value 81.045233
iter  70 value 80.670330
iter  80 value 80.568222
iter  90 value 80.501685
iter 100 value 80.431153
final  value 80.431153 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.185437 
iter  10 value 94.304980
iter  20 value 83.660225
iter  30 value 82.377059
iter  40 value 81.005891
iter  50 value 80.230133
iter  60 value 80.070815
iter  70 value 80.051677
iter  80 value 80.049181
iter  90 value 80.041995
iter 100 value 79.748058
final  value 79.748058 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.374809 
iter  10 value 98.921761
iter  20 value 92.713443
iter  30 value 85.858947
iter  40 value 84.146091
iter  50 value 83.016322
iter  60 value 81.621616
iter  70 value 79.632557
iter  80 value 79.462002
iter  90 value 79.237939
iter 100 value 79.197770
final  value 79.197770 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 125.829331 
iter  10 value 94.220517
iter  20 value 88.048782
iter  30 value 84.300249
iter  40 value 83.140082
iter  50 value 82.548177
iter  60 value 81.024159
iter  70 value 80.470366
iter  80 value 80.279517
iter  90 value 80.230308
iter 100 value 80.136512
final  value 80.136512 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.257943 
iter  10 value 94.468811
iter  20 value 88.913967
iter  30 value 85.019124
iter  40 value 83.428732
iter  50 value 82.945674
iter  60 value 82.301089
iter  70 value 80.071664
iter  80 value 79.547359
iter  90 value 79.213769
iter 100 value 79.054647
final  value 79.054647 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.017162 
iter  10 value 94.650281
iter  20 value 94.379006
iter  30 value 94.138562
iter  40 value 94.082122
iter  50 value 84.460548
iter  60 value 84.207906
iter  70 value 83.761297
iter  80 value 82.310004
iter  90 value 81.068424
iter 100 value 80.104842
final  value 80.104842 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.362723 
iter  10 value 97.715437
iter  20 value 96.687137
iter  30 value 94.074329
iter  40 value 86.563028
iter  50 value 84.494109
iter  60 value 83.475761
iter  70 value 82.601982
iter  80 value 82.090561
iter  90 value 81.289722
iter 100 value 80.226297
final  value 80.226297 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.210425 
final  value 94.215600 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.829297 
final  value 94.485713 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.060787 
iter  10 value 94.486071
iter  10 value 94.486070
iter  10 value 94.486070
final  value 94.486070 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.961960 
final  value 94.485815 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.526956 
iter  10 value 94.485783
iter  20 value 94.479027
iter  30 value 94.028757
iter  40 value 94.027801
iter  50 value 94.026665
iter  60 value 93.277231
iter  70 value 84.863658
iter  80 value 84.861217
iter  90 value 84.566036
iter 100 value 84.563466
final  value 84.563466 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 94.753352 
iter  10 value 94.031490
iter  20 value 94.024709
iter  30 value 86.058831
iter  40 value 85.790091
iter  50 value 83.675750
iter  60 value 83.505018
iter  70 value 83.347248
iter  80 value 83.136344
final  value 83.132127 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.328640 
iter  10 value 94.489144
iter  20 value 94.484649
final  value 94.484646 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.340608 
iter  10 value 94.257701
iter  20 value 94.220831
iter  30 value 94.083023
final  value 93.990132 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.313099 
iter  10 value 94.101845
iter  20 value 93.939022
iter  30 value 92.936873
iter  40 value 88.963465
iter  50 value 87.890254
final  value 87.889861 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.284745 
iter  10 value 94.489499
iter  20 value 94.389803
final  value 94.027280 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.451691 
iter  10 value 94.492448
iter  20 value 94.458673
iter  30 value 83.941587
iter  40 value 83.334041
iter  50 value 82.069876
iter  60 value 80.356384
iter  70 value 79.443923
iter  80 value 79.383870
iter  90 value 79.378457
iter 100 value 79.052492
final  value 79.052492 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.511874 
iter  10 value 94.034944
iter  20 value 94.027388
iter  30 value 94.026815
final  value 94.026771 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.672841 
iter  10 value 94.034885
iter  20 value 93.383037
iter  30 value 83.535706
iter  40 value 83.473805
iter  50 value 83.275514
iter  60 value 83.275109
iter  70 value 83.273865
iter  80 value 83.249162
iter  90 value 82.676731
iter 100 value 82.461975
final  value 82.461975 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.313111 
iter  10 value 93.606603
iter  20 value 93.581180
iter  30 value 85.269502
iter  40 value 84.818278
iter  50 value 84.817143
iter  60 value 84.816106
iter  70 value 84.292246
iter  80 value 80.726631
iter  90 value 80.530756
iter 100 value 80.528951
final  value 80.528951 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.001929 
iter  10 value 94.482623
iter  20 value 94.287897
iter  30 value 94.280943
iter  40 value 94.279837
iter  50 value 94.100549
iter  60 value 93.881559
iter  70 value 93.594601
iter  80 value 93.384065
iter  90 value 93.364292
iter 100 value 93.362000
final  value 93.362000 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.952621 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.949247 
final  value 94.482478 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.599279 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.906931 
iter  10 value 86.625332
final  value 86.622126 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.204779 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.688996 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.854898 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.485379 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.994836 
iter  10 value 86.284266
iter  20 value 85.932647
final  value 85.932643 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.288255 
iter  10 value 87.512927
iter  20 value 85.828500
iter  30 value 83.870210
iter  40 value 83.845060
iter  50 value 83.583533
iter  60 value 83.464918
final  value 83.464842 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.251411 
iter  10 value 94.484208
iter  10 value 94.484208
final  value 94.484208 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.204007 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.294503 
iter  10 value 94.476191
iter  10 value 94.476191
iter  10 value 94.476191
final  value 94.476191 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.260009 
final  value 94.264858 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.713682 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.723029 
iter  10 value 94.486256
iter  20 value 87.531117
iter  30 value 87.012297
iter  40 value 86.728237
iter  50 value 86.667848
iter  60 value 84.761747
iter  70 value 84.715188
iter  80 value 84.686243
iter  90 value 84.671445
final  value 84.670805 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.682780 
iter  10 value 94.467540
iter  20 value 93.965224
iter  30 value 93.779932
iter  40 value 93.026766
iter  50 value 92.313710
iter  60 value 86.395936
iter  70 value 85.141969
iter  80 value 84.756585
iter  90 value 84.337534
iter 100 value 83.768780
final  value 83.768780 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.758315 
iter  10 value 94.491685
iter  20 value 94.304482
iter  30 value 89.934880
iter  40 value 85.333038
iter  50 value 84.823471
iter  60 value 84.816426
iter  70 value 84.816279
iter  70 value 84.816279
iter  70 value 84.816279
final  value 84.816279 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.928191 
iter  10 value 94.481737
iter  20 value 94.035315
iter  30 value 92.438306
iter  40 value 84.915064
iter  50 value 84.498579
iter  60 value 84.107066
iter  70 value 83.815611
iter  80 value 83.710848
final  value 83.710726 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.712858 
iter  10 value 94.488572
iter  20 value 94.330904
iter  30 value 89.316026
iter  40 value 85.624984
iter  50 value 85.348058
iter  60 value 85.281829
iter  70 value 85.240750
iter  80 value 85.223128
final  value 85.222572 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.377589 
iter  10 value 94.534469
iter  20 value 94.408580
iter  30 value 93.190538
iter  40 value 90.876775
iter  50 value 87.041491
iter  60 value 85.339263
iter  70 value 84.126473
iter  80 value 83.124288
iter  90 value 83.052801
iter 100 value 82.942566
final  value 82.942566 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.863464 
iter  10 value 94.233080
iter  20 value 87.040411
iter  30 value 86.013145
iter  40 value 85.081137
iter  50 value 84.945495
iter  60 value 84.781123
iter  70 value 83.999632
iter  80 value 82.884140
iter  90 value 82.642298
iter 100 value 82.331236
final  value 82.331236 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.151643 
iter  10 value 94.554867
iter  20 value 89.722494
iter  30 value 87.786252
iter  40 value 87.119778
iter  50 value 86.389427
iter  60 value 85.100538
iter  70 value 84.990334
iter  80 value 84.937643
iter  90 value 84.272043
iter 100 value 82.589278
final  value 82.589278 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.724769 
iter  10 value 94.589383
iter  20 value 92.154081
iter  30 value 89.783792
iter  40 value 88.102256
iter  50 value 84.181121
iter  60 value 83.347146
iter  70 value 82.933217
iter  80 value 82.709152
iter  90 value 82.586130
iter 100 value 82.573870
final  value 82.573870 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.453801 
iter  10 value 94.497591
iter  20 value 94.270046
iter  30 value 93.745395
iter  40 value 85.957447
iter  50 value 85.712228
iter  60 value 85.499196
iter  70 value 83.646630
iter  80 value 83.462169
iter  90 value 82.711905
iter 100 value 82.247254
final  value 82.247254 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.645390 
iter  10 value 94.490919
iter  20 value 93.678179
iter  30 value 91.472008
iter  40 value 88.998733
iter  50 value 84.293996
iter  60 value 82.787897
iter  70 value 81.970593
iter  80 value 81.898391
iter  90 value 81.886994
iter 100 value 81.828838
final  value 81.828838 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.697276 
iter  10 value 94.605278
iter  20 value 93.858687
iter  30 value 88.339757
iter  40 value 86.218730
iter  50 value 84.269998
iter  60 value 83.511930
iter  70 value 83.031698
iter  80 value 82.063700
iter  90 value 81.676752
iter 100 value 81.443000
final  value 81.443000 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.312037 
iter  10 value 94.458294
iter  20 value 90.260223
iter  30 value 88.211342
iter  40 value 87.382706
iter  50 value 84.688615
iter  60 value 83.785592
iter  70 value 83.032484
iter  80 value 82.509914
iter  90 value 82.396371
iter 100 value 82.254597
final  value 82.254597 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.512117 
iter  10 value 94.433689
iter  20 value 93.170826
iter  30 value 88.124620
iter  40 value 85.961862
iter  50 value 84.756624
iter  60 value 83.971501
iter  70 value 83.586001
iter  80 value 82.857672
iter  90 value 82.245146
iter 100 value 81.825640
final  value 81.825640 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.778308 
iter  10 value 94.463859
iter  20 value 92.935533
iter  30 value 90.231065
iter  40 value 89.106900
iter  50 value 86.068782
iter  60 value 85.688665
iter  70 value 85.108373
iter  80 value 84.655973
iter  90 value 84.451981
iter 100 value 84.337274
final  value 84.337274 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.282179 
final  value 94.485757 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.290768 
final  value 94.485688 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.979357 
final  value 94.485943 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.466334 
iter  10 value 94.471747
iter  20 value 94.468476
iter  30 value 94.467093
final  value 94.466855 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.318548 
final  value 94.485802 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.092241 
iter  10 value 94.488963
iter  20 value 86.186499
final  value 85.937821 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.269630 
iter  10 value 94.489171
iter  20 value 94.346692
iter  30 value 88.628589
iter  40 value 87.941611
iter  50 value 85.963490
iter  60 value 85.959622
iter  70 value 85.953400
iter  80 value 85.949478
iter  90 value 85.759422
iter 100 value 83.510040
final  value 83.510040 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.661645 
iter  10 value 93.951264
iter  20 value 93.925436
iter  30 value 93.868064
iter  40 value 93.863324
iter  50 value 93.862691
iter  60 value 93.860493
final  value 93.860450 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.812211 
iter  10 value 94.488610
iter  20 value 94.421901
iter  30 value 85.940605
iter  40 value 85.933053
iter  50 value 85.932911
final  value 85.932892 
converged
Fitting Repeat 5 

# weights:  305
initial  value 123.964171 
iter  10 value 94.489055
iter  20 value 94.484357
iter  30 value 94.419774
iter  40 value 94.170233
iter  50 value 90.883626
iter  60 value 85.413277
iter  70 value 83.902716
iter  80 value 82.572511
iter  90 value 82.062600
iter 100 value 81.599830
final  value 81.599830 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.826860 
iter  10 value 94.492474
iter  20 value 94.430432
iter  30 value 89.442083
iter  40 value 84.201354
final  value 84.191806 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.396691 
iter  10 value 94.272971
iter  20 value 94.267624
iter  30 value 86.564726
iter  40 value 83.751928
iter  50 value 83.606867
iter  60 value 83.572156
iter  70 value 83.264073
iter  80 value 81.906957
iter  90 value 81.084144
iter 100 value 80.899871
final  value 80.899871 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.151203 
iter  10 value 94.487466
iter  20 value 89.869145
iter  30 value 87.794701
iter  40 value 87.234889
iter  50 value 87.231358
iter  60 value 87.230968
iter  70 value 87.102495
iter  80 value 87.072014
final  value 87.071788 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.151553 
iter  10 value 94.491748
iter  20 value 92.186155
iter  30 value 84.886584
iter  40 value 84.227983
final  value 84.059577 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.440523 
iter  10 value 94.260890
iter  20 value 91.636246
iter  30 value 88.014506
iter  40 value 87.846851
iter  50 value 87.845044
iter  60 value 87.787237
iter  70 value 87.783777
iter  80 value 87.782064
iter  90 value 87.780838
iter  90 value 87.780838
final  value 87.780838 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.375253 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.069790 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.223957 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.314898 
iter  10 value 93.733160
final  value 93.732893 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.011400 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.839233 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.147398 
iter  10 value 90.464626
iter  20 value 90.457006
iter  30 value 90.456951
final  value 90.456939 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.862268 
iter  10 value 92.102082
final  value 91.506173 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.993324 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.634058 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.145521 
iter  10 value 94.008691
final  value 94.008679 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.162366 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.523128 
iter  10 value 93.440660
iter  20 value 87.217897
iter  30 value 85.767753
iter  40 value 85.750155
iter  40 value 85.750154
iter  40 value 85.750154
final  value 85.750154 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.708705 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.063086 
iter  10 value 93.517209
iter  20 value 91.278424
iter  30 value 91.103212
iter  40 value 90.951185
iter  50 value 90.950592
iter  60 value 90.950233
iter  70 value 90.950082
iter  80 value 90.950024
final  value 90.950006 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.635467 
iter  10 value 94.050693
iter  20 value 89.756299
iter  30 value 87.229544
iter  40 value 86.629187
iter  50 value 84.253832
iter  60 value 83.898363
iter  70 value 83.834038
iter  80 value 83.092107
iter  90 value 82.929781
iter 100 value 82.716943
final  value 82.716943 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 107.738167 
iter  10 value 94.055584
iter  20 value 93.822073
iter  30 value 88.289405
iter  40 value 86.619289
iter  50 value 86.470800
iter  60 value 84.371909
iter  70 value 83.813350
iter  80 value 83.225258
iter  90 value 82.767190
iter 100 value 82.660221
final  value 82.660221 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.178367 
iter  10 value 94.067831
iter  20 value 94.056695
iter  30 value 88.243494
iter  40 value 86.651626
iter  50 value 86.277088
iter  60 value 85.718567
iter  70 value 84.144009
iter  80 value 83.933958
iter  90 value 83.662591
iter 100 value 83.109449
final  value 83.109449 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.630061 
iter  10 value 94.040321
iter  20 value 88.174577
iter  30 value 87.161983
iter  40 value 84.776493
iter  50 value 83.933920
iter  60 value 83.528347
iter  70 value 83.043645
iter  80 value 82.906104
iter  90 value 82.846999
iter 100 value 82.738797
final  value 82.738797 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.312425 
iter  10 value 94.062844
iter  20 value 94.013230
iter  30 value 93.820126
iter  40 value 93.804654
iter  50 value 87.059820
iter  60 value 86.563867
iter  70 value 86.133773
iter  80 value 85.595419
iter  90 value 85.424500
iter 100 value 83.611925
final  value 83.611925 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.581570 
iter  10 value 94.168652
iter  20 value 92.944173
iter  30 value 88.021259
iter  40 value 85.113709
iter  50 value 84.541436
iter  60 value 83.395692
iter  70 value 82.356557
iter  80 value 81.785926
iter  90 value 81.702994
iter 100 value 81.692116
final  value 81.692116 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.518710 
iter  10 value 94.096873
iter  20 value 92.121722
iter  30 value 89.011171
iter  40 value 88.659295
iter  50 value 88.269083
iter  60 value 86.563892
iter  70 value 83.228996
iter  80 value 83.022531
iter  90 value 82.756216
iter 100 value 82.578170
final  value 82.578170 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.309333 
iter  10 value 94.108620
iter  20 value 92.092053
iter  30 value 86.059264
iter  40 value 83.976880
iter  50 value 83.698261
iter  60 value 83.347300
iter  70 value 82.963413
iter  80 value 82.739843
iter  90 value 82.661928
iter 100 value 82.654557
final  value 82.654557 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.072954 
iter  10 value 94.013650
iter  20 value 87.035898
iter  30 value 85.691132
iter  40 value 85.217603
iter  50 value 83.678736
iter  60 value 82.389458
iter  70 value 81.887553
iter  80 value 81.777325
iter  90 value 81.699756
iter 100 value 81.574506
final  value 81.574506 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.821101 
iter  10 value 93.995785
iter  20 value 90.783702
iter  30 value 85.744170
iter  40 value 84.255764
iter  50 value 83.583333
iter  60 value 82.850500
iter  70 value 81.976152
iter  80 value 81.878080
iter  90 value 81.755198
iter 100 value 81.671740
final  value 81.671740 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.564261 
iter  10 value 93.819468
iter  20 value 90.303266
iter  30 value 87.415145
iter  40 value 83.822296
iter  50 value 83.678550
iter  60 value 83.588791
iter  70 value 83.422938
iter  80 value 82.936949
iter  90 value 82.544315
iter 100 value 82.458246
final  value 82.458246 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.869396 
iter  10 value 93.507716
iter  20 value 88.419726
iter  30 value 86.586841
iter  40 value 84.422101
iter  50 value 83.096856
iter  60 value 82.377670
iter  70 value 82.246626
iter  80 value 82.174986
iter  90 value 82.032869
iter 100 value 81.648166
final  value 81.648166 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.399050 
iter  10 value 94.638820
iter  20 value 92.462409
iter  30 value 87.745320
iter  40 value 86.217416
iter  50 value 84.294201
iter  60 value 83.127675
iter  70 value 82.798344
iter  80 value 82.267488
iter  90 value 81.859209
iter 100 value 81.824069
final  value 81.824069 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.224622 
iter  10 value 94.112169
iter  20 value 88.648416
iter  30 value 84.928697
iter  40 value 83.904820
iter  50 value 83.517257
iter  60 value 83.078337
iter  70 value 82.062049
iter  80 value 81.691877
iter  90 value 81.529525
iter 100 value 81.455669
final  value 81.455669 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.267467 
iter  10 value 96.192480
iter  20 value 88.122323
iter  30 value 87.054075
iter  40 value 85.831671
iter  50 value 85.429716
iter  60 value 84.828966
iter  70 value 84.185031
iter  80 value 83.821016
iter  90 value 83.610301
iter 100 value 82.962419
final  value 82.962419 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.609467 
final  value 94.054695 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.763305 
final  value 94.054822 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.574817 
final  value 94.054556 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.369276 
final  value 94.054347 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.075616 
final  value 94.054469 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.462409 
iter  10 value 94.058223
iter  20 value 93.750678
iter  30 value 85.316088
iter  40 value 84.804242
iter  50 value 84.653179
iter  60 value 84.022528
iter  70 value 84.017406
iter  80 value 84.000266
iter  90 value 83.997850
iter 100 value 83.800870
final  value 83.800870 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.892368 
iter  10 value 94.057608
iter  20 value 94.052960
iter  30 value 93.953636
iter  40 value 93.765195
iter  50 value 89.848025
iter  60 value 86.837790
iter  70 value 86.798552
iter  80 value 86.795467
final  value 86.795405 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.060603 
iter  10 value 94.013669
iter  20 value 93.888500
iter  30 value 93.794536
iter  40 value 93.785124
final  value 93.785061 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.447599 
iter  10 value 94.057956
iter  20 value 94.053259
iter  30 value 93.825879
final  value 93.809342 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.828794 
iter  10 value 94.057714
iter  20 value 94.052886
iter  30 value 93.873760
iter  40 value 84.785979
iter  50 value 84.669600
iter  60 value 84.623024
iter  70 value 84.583038
iter  80 value 84.196453
iter  90 value 84.059012
iter 100 value 83.819640
final  value 83.819640 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.428433 
iter  10 value 94.038950
iter  20 value 93.970732
iter  30 value 93.969599
final  value 93.969505 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.481295 
iter  10 value 93.819649
iter  20 value 93.764659
iter  30 value 93.761003
iter  40 value 93.758355
iter  50 value 93.757978
final  value 93.756255 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.953664 
iter  10 value 94.061215
iter  20 value 94.018853
iter  30 value 89.398492
iter  40 value 84.880203
iter  50 value 84.857016
final  value 84.856990 
converged
Fitting Repeat 4 

# weights:  507
initial  value 121.478381 
iter  10 value 94.016202
iter  20 value 94.011771
iter  30 value 91.566686
iter  40 value 91.565495
iter  50 value 90.473822
iter  60 value 90.459061
iter  70 value 90.458432
iter  80 value 90.457625
iter  90 value 90.445812
iter 100 value 90.372911
final  value 90.372911 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.311187 
iter  10 value 94.059711
iter  20 value 91.525269
iter  30 value 91.456051
iter  40 value 90.873837
iter  50 value 90.557221
final  value 90.557216 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.300140 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.059148 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.739853 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.050505 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.413189 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.466260 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.783297 
final  value 94.033149 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.587256 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.185250 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.146590 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.568404 
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.553603 
iter  10 value 93.902092
final  value 93.273743 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.215855 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.882919 
iter  10 value 94.008697
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.206105 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.051779 
iter  10 value 93.895070
iter  20 value 89.496149
iter  30 value 87.681967
iter  40 value 84.831360
iter  50 value 83.236440
iter  60 value 82.855974
iter  70 value 82.311678
iter  80 value 82.257427
iter  90 value 82.256251
iter 100 value 82.255792
final  value 82.255792 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.656029 
iter  10 value 93.980226
iter  20 value 88.621648
iter  30 value 85.799185
iter  40 value 84.493615
iter  50 value 83.347191
iter  60 value 82.772792
iter  70 value 82.644401
iter  80 value 82.402066
iter  90 value 82.262688
final  value 82.255791 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.915921 
iter  10 value 94.036658
iter  20 value 92.851686
iter  30 value 92.327034
iter  40 value 89.855252
iter  50 value 89.042536
iter  60 value 87.241502
iter  70 value 85.817717
iter  80 value 84.492703
iter  90 value 83.853150
iter 100 value 83.617725
final  value 83.617725 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.667041 
iter  10 value 93.978385
iter  20 value 87.586276
iter  30 value 86.504578
iter  40 value 86.428124
iter  50 value 85.824473
iter  60 value 84.578543
iter  70 value 83.572243
iter  80 value 82.656293
iter  90 value 82.462413
iter 100 value 82.364460
final  value 82.364460 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.398038 
iter  10 value 94.152893
iter  20 value 94.057046
iter  30 value 94.026666
iter  40 value 93.499569
iter  50 value 90.229271
iter  60 value 88.486773
iter  70 value 86.451390
iter  80 value 85.644013
iter  90 value 85.505745
iter 100 value 85.490117
final  value 85.490117 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.517872 
iter  10 value 94.047541
iter  20 value 93.417360
iter  30 value 92.864411
iter  40 value 88.788317
iter  50 value 86.677530
iter  60 value 85.117588
iter  70 value 84.265494
iter  80 value 82.693347
iter  90 value 82.218624
iter 100 value 81.861643
final  value 81.861643 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.858534 
iter  10 value 93.863534
iter  20 value 89.591312
iter  30 value 86.961334
iter  40 value 85.036861
iter  50 value 83.012902
iter  60 value 81.747891
iter  70 value 81.380884
iter  80 value 81.095327
iter  90 value 80.894626
iter 100 value 80.758751
final  value 80.758751 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.213643 
iter  10 value 94.071163
iter  20 value 93.311048
iter  30 value 89.048280
iter  40 value 87.736724
iter  50 value 86.909960
iter  60 value 84.184645
iter  70 value 82.550708
iter  80 value 82.237294
iter  90 value 81.469988
iter 100 value 81.187595
final  value 81.187595 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.464116 
iter  10 value 93.905898
iter  20 value 93.105696
iter  30 value 92.991177
iter  40 value 89.832001
iter  50 value 89.338911
iter  60 value 88.314627
iter  70 value 87.010294
iter  80 value 85.095920
iter  90 value 84.334406
iter 100 value 83.766114
final  value 83.766114 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.312724 
iter  10 value 94.003819
iter  20 value 91.565825
iter  30 value 87.265636
iter  40 value 84.642319
iter  50 value 82.599327
iter  60 value 81.868660
iter  70 value 81.346807
iter  80 value 81.135400
iter  90 value 80.986790
iter 100 value 80.950468
final  value 80.950468 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.934956 
iter  10 value 93.178858
iter  20 value 90.576066
iter  30 value 86.691200
iter  40 value 84.750145
iter  50 value 83.695485
iter  60 value 83.356234
iter  70 value 83.119213
iter  80 value 81.602246
iter  90 value 81.441893
iter 100 value 81.398885
final  value 81.398885 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 139.239768 
iter  10 value 94.033764
iter  20 value 88.232373
iter  30 value 86.048385
iter  40 value 83.798431
iter  50 value 82.091159
iter  60 value 81.474886
iter  70 value 81.118285
iter  80 value 80.960862
iter  90 value 80.915788
iter 100 value 80.877531
final  value 80.877531 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.813159 
iter  10 value 89.322467
iter  20 value 86.828401
iter  30 value 84.005841
iter  40 value 81.977195
iter  50 value 81.126883
iter  60 value 80.822642
iter  70 value 80.739684
iter  80 value 80.701373
iter  90 value 80.634435
iter 100 value 80.616125
final  value 80.616125 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.454763 
iter  10 value 93.923631
iter  20 value 92.516556
iter  30 value 88.894173
iter  40 value 85.688337
iter  50 value 83.880089
iter  60 value 83.596805
iter  70 value 81.452361
iter  80 value 81.184140
iter  90 value 81.019711
iter 100 value 80.858064
final  value 80.858064 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.363026 
iter  10 value 94.131309
iter  20 value 90.843935
iter  30 value 88.203813
iter  40 value 87.427399
iter  50 value 86.957266
iter  60 value 85.130805
iter  70 value 84.586149
iter  80 value 82.573699
iter  90 value 82.130533
iter 100 value 81.646925
final  value 81.646925 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.971951 
iter  10 value 94.010204
iter  20 value 93.935542
iter  30 value 87.902611
iter  40 value 87.557521
iter  50 value 87.501487
iter  60 value 87.383430
iter  70 value 87.339759
iter  80 value 86.635276
iter  90 value 86.634588
iter 100 value 86.634066
final  value 86.634066 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.092930 
final  value 94.010191 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.926077 
final  value 94.054764 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.333573 
final  value 94.054338 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.813138 
final  value 94.054608 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.830105 
iter  10 value 94.057779
iter  20 value 92.913585
iter  30 value 85.998517
iter  40 value 85.642721
final  value 85.641644 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.003062 
iter  10 value 94.055607
iter  20 value 93.703177
iter  30 value 90.149826
iter  40 value 89.672210
iter  50 value 89.670199
iter  60 value 89.314369
iter  70 value 89.285530
final  value 89.285233 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.990015 
iter  10 value 94.057353
iter  20 value 94.039537
iter  30 value 89.783997
iter  40 value 89.477349
iter  50 value 87.218972
iter  60 value 87.023820
iter  70 value 87.011826
iter  80 value 85.837223
iter  90 value 85.641651
final  value 85.641493 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.686982 
iter  10 value 94.057248
iter  20 value 94.042467
iter  30 value 87.253431
iter  40 value 86.383200
iter  50 value 86.377923
iter  60 value 84.354037
iter  70 value 83.984121
final  value 83.984119 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.659112 
iter  10 value 94.057393
iter  20 value 93.967584
iter  30 value 87.049461
iter  40 value 86.979120
iter  50 value 84.635567
iter  60 value 84.273073
final  value 84.272941 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.075677 
iter  10 value 93.993869
iter  20 value 93.987010
iter  30 value 87.852904
iter  40 value 86.431944
iter  50 value 86.154730
iter  60 value 85.668407
final  value 85.667733 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.499598 
iter  10 value 94.016896
iter  20 value 93.692528
iter  30 value 85.492401
iter  40 value 84.240721
iter  50 value 82.617906
iter  60 value 82.475739
iter  70 value 81.757916
iter  80 value 81.263739
iter  90 value 81.255012
iter  90 value 81.255011
iter  90 value 81.255011
final  value 81.255011 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.578675 
iter  10 value 94.062565
iter  20 value 94.053806
iter  30 value 93.842680
iter  40 value 87.817703
iter  50 value 87.512348
iter  60 value 87.505440
iter  70 value 86.037103
iter  80 value 84.671569
iter  90 value 84.669864
iter 100 value 84.668245
final  value 84.668245 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.148538 
iter  10 value 92.626695
iter  20 value 91.357691
iter  30 value 91.240810
iter  40 value 91.229084
iter  50 value 91.225749
iter  60 value 89.910367
iter  70 value 88.408203
iter  80 value 88.209635
iter  90 value 87.524251
iter 100 value 86.575781
final  value 86.575781 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.683980 
iter  10 value 93.357720
iter  20 value 92.727022
iter  30 value 92.706264
iter  40 value 92.696263
final  value 92.695698 
converged
Fitting Repeat 1 

# weights:  305
initial  value 125.939370 
iter  10 value 108.722417
iter  20 value 108.513029
iter  30 value 108.508808
final  value 108.507382 
converged
Fitting Repeat 2 

# weights:  305
initial  value 141.353167 
iter  10 value 117.749317
iter  20 value 109.954589
iter  30 value 108.533154
iter  40 value 108.328167
iter  50 value 108.300261
iter  60 value 105.601226
iter  70 value 104.116464
final  value 103.974975 
converged
Fitting Repeat 3 

# weights:  305
initial  value 132.556699 
iter  10 value 117.766817
iter  20 value 117.761480
iter  30 value 117.634458
iter  40 value 117.533640
iter  50 value 107.003584
iter  60 value 106.258491
final  value 106.254441 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.809526 
iter  10 value 117.894425
iter  20 value 117.875428
iter  30 value 116.671471
iter  40 value 112.137287
iter  50 value 106.532257
iter  60 value 105.922108
iter  70 value 104.959312
iter  80 value 104.911638
final  value 104.910031 
converged
Fitting Repeat 5 

# weights:  305
initial  value 131.967448 
iter  10 value 117.895613
iter  20 value 117.878280
iter  30 value 115.188900
iter  40 value 112.124616
iter  50 value 107.022806
iter  60 value 107.011103
iter  70 value 107.006051
iter  80 value 105.064287
iter  90 value 104.984085
iter 100 value 104.953357
final  value 104.953357 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri Oct  3 10:24:50 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 
 55.343   1.412 127.946 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod37.377 0.56338.021
FreqInteractors0.2890.0200.310
calculateAAC0.0450.0040.050
calculateAutocor0.6890.0310.724
calculateCTDC0.0950.0000.095
calculateCTDD0.7470.0040.751
calculateCTDT0.2640.0040.268
calculateCTriad0.4670.0000.468
calculateDC0.1260.0040.131
calculateF0.4330.0000.433
calculateKSAAP0.1400.0040.144
calculateQD_Sm2.5880.0202.617
calculateTC2.3210.0322.356
calculateTC_Sm0.3180.0000.318
corr_plot37.056 0.23637.335
enrichfindP 0.497 0.02818.831
enrichfind_hp0.0800.0042.147
enrichplot0.4800.0080.491
filter_missing_values0.0010.0000.002
getFASTA0.0760.0287.741
getHPI0.0010.0000.001
get_negativePPI0.0020.0000.002
get_positivePPI000
impute_missing_data0.0020.0000.002
plotPPI0.0890.0000.089
pred_ensembel18.648 0.51517.991
var_imp39.682 0.35540.118