Matineh Rahmatbakhsh
| Snapshot Date: 2026-01-20 13:40 -0500 (Tue, 20 Jan 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: 68bd9a1 |
| git_last_commit_date: 2025-12-28 18:34:02 -0500 (Sun, 28 Dec 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-01-21 11:34 -0500 (Wed, 21 Jan 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences" | 4805 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences" | 4539 |
| 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 1001/2343 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.17.2 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
|
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. |
| Package: HPiP |
| Version: 1.17.2 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.2.tar.gz |
| StartedAt: 2026-01-21 00:30:25 -0500 (Wed, 21 Jan 2026) |
| EndedAt: 2026-01-21 00:45:26 -0500 (Wed, 21 Jan 2026) |
| EllapsedTime: 901.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.2.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-01-15 r89304)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* 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
corr_plot 34.640 0.603 35.244
var_imp 34.503 0.676 35.236
FSmethod 33.046 0.636 33.683
pred_ensembel 13.188 0.360 12.238
enrichfindP 0.562 0.049 12.146
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.17.2’ ** 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)
HPiP.Rcheck/tests/runTests.Rout
R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-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 102.032644
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.678261
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.711306
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 100.446199
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.239447
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.164650
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 98.375684
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 96.310695
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 100.085123
final value 94.305882
converged
Fitting Repeat 5
# weights: 305
initial value 97.078804
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 95.409600
iter 10 value 86.559987
iter 20 value 84.712141
iter 30 value 84.265245
iter 40 value 84.179881
iter 50 value 84.179443
iter 60 value 84.149635
iter 70 value 84.136519
final value 84.136352
converged
Fitting Repeat 2
# weights: 507
initial value 98.502190
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 110.504305
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 119.259233
iter 10 value 89.229898
iter 20 value 88.308595
iter 30 value 88.306345
iter 30 value 88.306345
iter 30 value 88.306345
final value 88.306345
converged
Fitting Repeat 5
# weights: 507
initial value 111.440200
iter 10 value 94.268380
iter 20 value 93.866718
iter 20 value 93.866717
final value 93.866676
converged
Fitting Repeat 1
# weights: 103
initial value 100.509378
iter 10 value 94.487083
iter 20 value 94.336911
iter 30 value 94.314439
final value 94.314164
converged
Fitting Repeat 2
# weights: 103
initial value 101.159112
iter 10 value 94.503774
iter 20 value 91.417352
iter 30 value 87.895564
iter 40 value 86.882054
iter 50 value 86.646206
iter 60 value 85.146851
iter 70 value 84.533162
iter 80 value 83.622633
iter 90 value 83.419843
final value 83.415314
converged
Fitting Repeat 3
# weights: 103
initial value 97.019911
iter 10 value 94.496063
iter 20 value 90.915447
iter 30 value 86.877249
iter 40 value 86.510371
iter 50 value 86.293578
iter 60 value 83.672144
iter 70 value 83.543827
iter 80 value 83.385370
iter 90 value 83.292865
final value 83.286993
converged
Fitting Repeat 4
# weights: 103
initial value 98.624225
iter 10 value 90.708899
iter 20 value 88.998756
iter 30 value 88.666644
iter 40 value 88.489248
iter 50 value 88.079029
iter 60 value 86.395128
iter 70 value 86.297190
iter 80 value 86.272853
final value 86.272831
converged
Fitting Repeat 5
# weights: 103
initial value 103.062577
iter 10 value 94.524416
iter 20 value 94.385764
iter 30 value 93.806443
iter 40 value 92.644209
iter 50 value 87.744006
iter 60 value 86.661756
iter 70 value 86.597520
iter 80 value 84.847068
iter 90 value 84.258968
iter 100 value 84.085599
final value 84.085599
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 104.694462
iter 10 value 94.587795
iter 20 value 93.100143
iter 30 value 87.090872
iter 40 value 86.427002
iter 50 value 86.291851
iter 60 value 84.953044
iter 70 value 83.625788
iter 80 value 82.688992
iter 90 value 82.563138
iter 100 value 82.356461
final value 82.356461
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.573769
iter 10 value 94.454973
iter 20 value 92.235922
iter 30 value 85.907199
iter 40 value 85.745280
iter 50 value 85.481342
iter 60 value 85.256917
iter 70 value 85.024114
iter 80 value 85.016441
iter 90 value 85.011375
iter 100 value 84.983894
final value 84.983894
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.617434
iter 10 value 94.175414
iter 20 value 91.781288
iter 30 value 88.771163
iter 40 value 84.921250
iter 50 value 83.432061
iter 60 value 82.965529
iter 70 value 82.701541
iter 80 value 82.643333
iter 90 value 82.545037
iter 100 value 82.374337
final value 82.374337
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.845210
iter 10 value 94.632848
iter 20 value 94.478217
iter 30 value 93.052145
iter 40 value 91.876737
iter 50 value 91.428318
iter 60 value 90.290406
iter 70 value 86.160189
iter 80 value 83.178956
iter 90 value 82.542860
iter 100 value 82.394657
final value 82.394657
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.420953
iter 10 value 91.730779
iter 20 value 89.466010
iter 30 value 89.074666
iter 40 value 87.081636
iter 50 value 86.195287
iter 60 value 85.686175
iter 70 value 84.755920
iter 80 value 84.498733
iter 90 value 84.294467
iter 100 value 83.627029
final value 83.627029
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 121.878960
iter 10 value 94.427652
iter 20 value 93.421367
iter 30 value 87.240283
iter 40 value 85.054610
iter 50 value 83.693678
iter 60 value 83.350813
iter 70 value 82.792795
iter 80 value 82.659292
iter 90 value 82.621810
iter 100 value 82.583320
final value 82.583320
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 132.131952
iter 10 value 95.463798
iter 20 value 93.882986
iter 30 value 87.619079
iter 40 value 85.706243
iter 50 value 84.267747
iter 60 value 83.437212
iter 70 value 82.560835
iter 80 value 82.406933
iter 90 value 82.260429
iter 100 value 82.165021
final value 82.165021
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.592894
iter 10 value 94.210459
iter 20 value 90.607747
iter 30 value 85.069756
iter 40 value 84.327488
iter 50 value 83.669286
iter 60 value 83.589419
iter 70 value 83.447549
iter 80 value 83.102601
iter 90 value 82.922056
iter 100 value 82.609406
final value 82.609406
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.329765
iter 10 value 94.466065
iter 20 value 90.090502
iter 30 value 87.910802
iter 40 value 86.017613
iter 50 value 85.274220
iter 60 value 83.062667
iter 70 value 82.557058
iter 80 value 82.415597
iter 90 value 82.072441
iter 100 value 82.020394
final value 82.020394
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 114.339070
iter 10 value 93.798336
iter 20 value 88.505268
iter 30 value 85.481835
iter 40 value 83.961359
iter 50 value 83.412303
iter 60 value 83.096132
iter 70 value 82.815881
iter 80 value 82.783723
iter 90 value 82.671069
iter 100 value 82.396948
final value 82.396948
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.867574
final value 94.485812
converged
Fitting Repeat 2
# weights: 103
initial value 104.944899
final value 94.485964
converged
Fitting Repeat 3
# weights: 103
initial value 96.154016
final value 94.486299
converged
Fitting Repeat 4
# weights: 103
initial value 101.022127
final value 94.485745
converged
Fitting Repeat 5
# weights: 103
initial value 107.639406
iter 10 value 94.313787
final value 94.313406
converged
Fitting Repeat 1
# weights: 305
initial value 95.062428
iter 10 value 94.489053
iter 20 value 92.141612
iter 30 value 91.978711
iter 40 value 91.978430
iter 50 value 91.906813
iter 60 value 91.283811
iter 70 value 86.865289
iter 80 value 86.353734
iter 90 value 86.352849
iter 90 value 86.352849
final value 86.352849
converged
Fitting Repeat 2
# weights: 305
initial value 102.663757
iter 10 value 94.471438
iter 20 value 94.467086
final value 94.466918
converged
Fitting Repeat 3
# weights: 305
initial value 102.425897
iter 10 value 94.467470
iter 20 value 94.380810
iter 30 value 94.372523
iter 40 value 94.371944
iter 50 value 91.640246
iter 60 value 88.071688
iter 70 value 87.658299
iter 80 value 87.657327
iter 90 value 87.656928
iter 100 value 87.284398
final value 87.284398
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 119.272922
iter 10 value 94.471997
iter 20 value 94.467402
iter 30 value 94.295631
iter 40 value 92.612079
iter 50 value 86.484907
iter 60 value 85.087384
iter 70 value 84.865172
iter 80 value 84.863191
iter 90 value 84.855574
iter 100 value 84.246821
final value 84.246821
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.594013
iter 10 value 94.489122
iter 20 value 94.392160
iter 30 value 87.095012
iter 40 value 85.610583
iter 50 value 85.595389
iter 60 value 85.593499
final value 85.593489
converged
Fitting Repeat 1
# weights: 507
initial value 103.371700
iter 10 value 94.493131
iter 20 value 94.371376
final value 94.288594
converged
Fitting Repeat 2
# weights: 507
initial value 101.825886
iter 10 value 94.474639
iter 20 value 92.664736
iter 30 value 87.003185
iter 40 value 85.433319
iter 50 value 84.842807
iter 60 value 84.703789
iter 70 value 84.279510
iter 80 value 84.111229
iter 90 value 84.109843
iter 100 value 84.109637
final value 84.109637
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 97.934056
iter 10 value 94.475995
iter 20 value 94.472837
iter 30 value 90.240936
iter 40 value 85.113085
iter 50 value 85.068791
final value 85.063058
converged
Fitting Repeat 4
# weights: 507
initial value 107.927818
iter 10 value 92.617507
iter 20 value 92.615956
iter 30 value 92.610229
iter 40 value 91.940322
iter 50 value 90.871731
iter 60 value 90.762468
iter 70 value 83.749337
iter 80 value 82.887186
iter 90 value 82.878691
iter 100 value 82.782900
final value 82.782900
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 98.868194
iter 10 value 87.333408
iter 20 value 86.232340
iter 30 value 82.976897
iter 40 value 82.802841
iter 50 value 81.605669
iter 60 value 81.435441
iter 70 value 81.425757
iter 80 value 81.371032
iter 90 value 81.369509
iter 100 value 81.366795
final value 81.366795
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.710545
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 100.253874
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.096348
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 100.229051
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 97.477620
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 111.768584
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 94.407219
iter 10 value 93.328639
final value 93.328261
converged
Fitting Repeat 3
# weights: 305
initial value 105.993505
final value 93.473743
converged
Fitting Repeat 4
# weights: 305
initial value 99.210681
iter 10 value 90.353958
iter 20 value 82.793323
iter 30 value 82.784701
final value 82.784679
converged
Fitting Repeat 5
# weights: 305
initial value 102.902883
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 100.616945
iter 10 value 93.797284
iter 20 value 93.340065
iter 30 value 83.883657
iter 40 value 82.568376
iter 50 value 82.561221
iter 60 value 82.560763
iter 70 value 82.560721
iter 70 value 82.560720
final value 82.560716
converged
Fitting Repeat 2
# weights: 507
initial value 98.238004
iter 10 value 93.516039
final value 93.473743
converged
Fitting Repeat 3
# weights: 507
initial value 98.300407
iter 10 value 93.231071
iter 20 value 92.195813
iter 30 value 92.039522
iter 40 value 92.025058
final value 92.025000
converged
Fitting Repeat 4
# weights: 507
initial value 124.465700
iter 10 value 93.714139
final value 93.654456
converged
Fitting Repeat 5
# weights: 507
initial value 104.023301
iter 10 value 93.284524
iter 10 value 93.284524
iter 10 value 93.284524
final value 93.284524
converged
Fitting Repeat 1
# weights: 103
initial value 106.462936
iter 10 value 94.060799
iter 20 value 88.094044
iter 30 value 85.318679
iter 40 value 84.632637
iter 50 value 84.376618
iter 60 value 81.664451
iter 70 value 81.619422
iter 80 value 81.606754
final value 81.606153
converged
Fitting Repeat 2
# weights: 103
initial value 102.653351
iter 10 value 94.064075
iter 20 value 93.983751
iter 30 value 93.525790
iter 40 value 93.429877
iter 50 value 85.971011
iter 60 value 84.414275
iter 70 value 82.472820
iter 80 value 81.320311
iter 90 value 81.048723
iter 100 value 80.971242
final value 80.971242
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 101.503340
iter 10 value 94.058086
final value 94.056059
converged
Fitting Repeat 4
# weights: 103
initial value 96.408515
iter 10 value 94.042561
iter 20 value 93.746756
iter 30 value 93.713645
iter 40 value 93.673448
iter 50 value 91.339991
iter 60 value 83.238452
iter 70 value 81.585773
iter 80 value 81.365624
iter 90 value 81.165912
iter 100 value 81.066987
final value 81.066987
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.930671
iter 10 value 94.054978
iter 20 value 90.614313
iter 30 value 84.048372
iter 40 value 83.524924
iter 50 value 81.828526
iter 60 value 81.678838
iter 70 value 81.575002
iter 80 value 81.524411
final value 81.522936
converged
Fitting Repeat 1
# weights: 305
initial value 108.798488
iter 10 value 87.211128
iter 20 value 81.463744
iter 30 value 81.290310
iter 40 value 80.144345
iter 50 value 79.579192
iter 60 value 79.376026
iter 70 value 79.046357
iter 80 value 79.001644
iter 90 value 78.990013
iter 100 value 78.974701
final value 78.974701
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 107.522749
iter 10 value 94.521451
iter 20 value 93.291339
iter 30 value 86.968453
iter 40 value 83.490676
iter 50 value 81.466879
iter 60 value 80.404618
iter 70 value 80.053458
iter 80 value 80.005045
iter 90 value 79.767435
iter 100 value 79.477942
final value 79.477942
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 114.617562
iter 10 value 93.651764
iter 20 value 93.400334
iter 30 value 83.295057
iter 40 value 82.931311
iter 50 value 81.580137
iter 60 value 81.113625
iter 70 value 81.012430
iter 80 value 80.917825
iter 90 value 80.547501
iter 100 value 79.884300
final value 79.884300
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.141544
iter 10 value 94.044135
iter 20 value 86.987996
iter 30 value 82.738296
iter 40 value 81.353713
iter 50 value 80.469631
iter 60 value 79.338805
iter 70 value 79.154441
iter 80 value 79.022081
iter 90 value 79.007454
iter 100 value 78.993203
final value 78.993203
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 110.224263
iter 10 value 94.489214
iter 20 value 93.592416
iter 30 value 93.268587
iter 40 value 87.127828
iter 50 value 86.077096
iter 60 value 81.790663
iter 70 value 81.469709
iter 80 value 81.347875
iter 90 value 80.935859
iter 100 value 80.824300
final value 80.824300
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 124.513620
iter 10 value 93.999604
iter 20 value 87.483374
iter 30 value 83.741637
iter 40 value 82.461001
iter 50 value 81.029799
iter 60 value 80.325437
iter 70 value 79.974637
iter 80 value 79.848678
iter 90 value 79.680236
iter 100 value 79.358801
final value 79.358801
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 154.328483
iter 10 value 94.627467
iter 20 value 94.362307
iter 30 value 91.403928
iter 40 value 84.635443
iter 50 value 82.071876
iter 60 value 80.933011
iter 70 value 80.597009
iter 80 value 80.424766
iter 90 value 79.970811
iter 100 value 79.435288
final value 79.435288
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 107.904717
iter 10 value 94.431589
iter 20 value 94.121814
iter 30 value 89.971055
iter 40 value 88.925118
iter 50 value 85.365867
iter 60 value 83.025477
iter 70 value 81.363761
iter 80 value 80.421858
iter 90 value 80.284826
iter 100 value 80.128052
final value 80.128052
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 114.186068
iter 10 value 97.123452
iter 20 value 94.718284
iter 30 value 93.694473
iter 40 value 87.440541
iter 50 value 86.284824
iter 60 value 83.947036
iter 70 value 81.732956
iter 80 value 80.341503
iter 90 value 80.136179
iter 100 value 79.927952
final value 79.927952
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.991307
iter 10 value 93.962955
iter 20 value 87.404560
iter 30 value 81.807797
iter 40 value 81.399722
iter 50 value 81.146354
iter 60 value 80.926757
iter 70 value 80.196535
iter 80 value 79.749918
iter 90 value 79.645989
iter 100 value 79.600182
final value 79.600182
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.517677
final value 94.054476
converged
Fitting Repeat 2
# weights: 103
initial value 97.342617
final value 94.054835
converged
Fitting Repeat 3
# weights: 103
initial value 95.060162
final value 94.054393
converged
Fitting Repeat 4
# weights: 103
initial value 102.290283
final value 94.054493
converged
Fitting Repeat 5
# weights: 103
initial value 118.988277
final value 94.054525
converged
Fitting Repeat 1
# weights: 305
initial value 117.555123
iter 10 value 94.058036
iter 20 value 94.029677
iter 30 value 94.026601
iter 40 value 94.025586
iter 50 value 93.772854
iter 60 value 84.113087
iter 70 value 84.101313
iter 80 value 84.093158
iter 90 value 84.080960
iter 100 value 84.080424
final value 84.080424
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.372798
iter 10 value 94.057875
iter 20 value 94.046527
iter 30 value 93.912144
iter 40 value 93.894520
final value 93.894469
converged
Fitting Repeat 3
# weights: 305
initial value 113.828095
iter 10 value 93.335347
iter 20 value 93.332892
iter 30 value 89.088575
iter 40 value 81.466039
iter 50 value 81.448792
iter 60 value 79.967903
iter 70 value 79.514205
iter 80 value 79.467335
iter 90 value 79.358804
iter 100 value 79.355466
final value 79.355466
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.021938
iter 10 value 93.279146
iter 20 value 93.213595
iter 30 value 93.160335
iter 40 value 93.158522
iter 50 value 93.156798
iter 60 value 93.156606
final value 93.156322
converged
Fitting Repeat 5
# weights: 305
initial value 108.339668
iter 10 value 94.072940
iter 20 value 86.908303
iter 30 value 86.648109
iter 40 value 83.153656
iter 50 value 80.403793
iter 60 value 80.393472
iter 70 value 80.392235
iter 80 value 80.390967
final value 80.390966
converged
Fitting Repeat 1
# weights: 507
initial value 115.352201
iter 10 value 94.061069
iter 20 value 94.053048
iter 30 value 93.938270
iter 40 value 91.438360
iter 50 value 89.075593
iter 60 value 89.011221
iter 70 value 87.992469
iter 80 value 82.322447
iter 90 value 81.776894
iter 100 value 81.386514
final value 81.386514
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.481363
iter 10 value 93.336556
iter 20 value 93.330528
iter 30 value 92.575974
iter 40 value 92.522943
iter 50 value 92.522747
iter 60 value 90.810873
iter 70 value 84.341377
iter 80 value 79.998510
iter 90 value 79.953032
iter 100 value 79.844585
final value 79.844585
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 101.155187
iter 10 value 93.959212
iter 20 value 93.956920
iter 30 value 93.643464
iter 40 value 93.293505
iter 50 value 93.168143
iter 60 value 92.587089
iter 70 value 92.562590
final value 92.562533
converged
Fitting Repeat 4
# weights: 507
initial value 112.127403
iter 10 value 94.061039
iter 20 value 94.041018
iter 30 value 92.784401
iter 40 value 90.896743
iter 50 value 90.867867
iter 60 value 90.591953
iter 70 value 90.588399
iter 80 value 89.136819
final value 87.936871
converged
Fitting Repeat 5
# weights: 507
initial value 109.945449
iter 10 value 94.060747
iter 20 value 94.047983
iter 30 value 92.769876
iter 40 value 86.201517
iter 50 value 86.084735
iter 60 value 86.081495
iter 70 value 86.079665
iter 80 value 86.078352
iter 90 value 84.876969
iter 100 value 84.330104
final value 84.330104
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.110642
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.742653
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.586605
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.720398
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 102.795121
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 100.758719
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 107.451728
final value 94.436782
converged
Fitting Repeat 3
# weights: 305
initial value 98.094647
final value 94.214007
converged
Fitting Repeat 4
# weights: 305
initial value 101.946831
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 108.248943
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 112.819308
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 99.192861
final value 94.466823
converged
Fitting Repeat 3
# weights: 507
initial value 104.171140
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 103.230122
final value 94.466823
converged
Fitting Repeat 5
# weights: 507
initial value 95.166592
final value 94.466823
converged
Fitting Repeat 1
# weights: 103
initial value 99.137464
iter 10 value 94.469445
iter 20 value 94.398598
iter 30 value 88.016486
iter 40 value 86.327021
iter 50 value 85.306057
iter 60 value 84.112786
iter 70 value 83.166685
iter 80 value 82.827063
iter 90 value 82.755495
iter 90 value 82.755494
iter 90 value 82.755494
final value 82.755494
converged
Fitting Repeat 2
# weights: 103
initial value 106.978206
iter 10 value 94.428171
iter 20 value 90.589069
iter 30 value 85.929516
iter 40 value 84.799908
iter 50 value 84.023218
iter 60 value 83.287788
iter 70 value 82.998258
iter 80 value 82.756758
final value 82.755494
converged
Fitting Repeat 3
# weights: 103
initial value 103.381185
iter 10 value 94.488840
iter 20 value 93.416198
iter 30 value 89.330175
iter 40 value 88.858431
iter 50 value 88.645061
iter 60 value 84.674347
iter 70 value 83.490332
iter 80 value 83.105574
iter 90 value 82.911421
iter 100 value 82.755758
final value 82.755758
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.058245
iter 10 value 94.488558
iter 20 value 94.478780
iter 30 value 93.107960
iter 40 value 92.687380
iter 50 value 92.542728
iter 60 value 92.473746
iter 70 value 92.342434
iter 80 value 91.412140
iter 90 value 90.846757
iter 100 value 90.445804
final value 90.445804
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 102.949534
iter 10 value 93.298709
iter 20 value 87.370486
iter 30 value 86.307933
iter 40 value 86.174430
iter 50 value 85.978365
iter 60 value 85.840412
iter 70 value 83.628920
iter 80 value 83.508021
iter 90 value 82.910802
iter 100 value 82.779769
final value 82.779769
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 117.722209
iter 10 value 94.459349
iter 20 value 91.175125
iter 30 value 88.309076
iter 40 value 87.929908
iter 50 value 85.712386
iter 60 value 84.481936
iter 70 value 83.478829
iter 80 value 83.088533
iter 90 value 82.927128
iter 100 value 82.726158
final value 82.726158
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 109.081153
iter 10 value 94.464870
iter 20 value 91.253608
iter 30 value 90.775256
iter 40 value 86.749803
iter 50 value 84.320997
iter 60 value 83.802830
iter 70 value 83.599358
iter 80 value 83.495962
iter 90 value 82.373215
iter 100 value 81.980230
final value 81.980230
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 116.284328
iter 10 value 94.507201
iter 20 value 89.391550
iter 30 value 87.232387
iter 40 value 87.019857
iter 50 value 86.515242
iter 60 value 85.484110
iter 70 value 85.108904
iter 80 value 85.065446
iter 90 value 84.827812
iter 100 value 83.473524
final value 83.473524
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 115.439113
iter 10 value 94.329010
iter 20 value 87.818462
iter 30 value 86.067287
iter 40 value 84.415714
iter 50 value 84.296482
iter 60 value 83.934661
iter 70 value 83.405209
iter 80 value 81.950823
iter 90 value 81.379581
iter 100 value 81.209651
final value 81.209651
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 127.113188
iter 10 value 94.468879
iter 20 value 93.436036
iter 30 value 89.124650
iter 40 value 84.679407
iter 50 value 82.629956
iter 60 value 82.476475
iter 70 value 81.959951
iter 80 value 81.557227
iter 90 value 81.511793
iter 100 value 81.467718
final value 81.467718
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.934968
iter 10 value 90.865232
iter 20 value 89.987922
iter 30 value 89.868224
iter 40 value 86.509253
iter 50 value 84.886793
iter 60 value 84.675631
iter 70 value 84.395808
iter 80 value 84.188164
iter 90 value 83.685643
iter 100 value 83.273134
final value 83.273134
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.615061
iter 10 value 95.355497
iter 20 value 89.524355
iter 30 value 84.165718
iter 40 value 83.483590
iter 50 value 83.227804
iter 60 value 83.136888
iter 70 value 82.981835
iter 80 value 82.890594
iter 90 value 82.747565
iter 100 value 82.735256
final value 82.735256
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.360143
iter 10 value 94.497554
iter 20 value 89.738814
iter 30 value 86.500497
iter 40 value 84.677057
iter 50 value 82.688005
iter 60 value 82.389810
iter 70 value 82.043959
iter 80 value 81.840218
iter 90 value 81.777982
iter 100 value 81.748853
final value 81.748853
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.561641
iter 10 value 95.217063
iter 20 value 91.884379
iter 30 value 86.578915
iter 40 value 83.571527
iter 50 value 83.200139
iter 60 value 82.691851
iter 70 value 82.183346
iter 80 value 81.930299
iter 90 value 81.591023
iter 100 value 81.310713
final value 81.310713
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 108.527366
iter 10 value 95.320167
iter 20 value 91.385163
iter 30 value 90.713424
iter 40 value 85.701048
iter 50 value 84.103127
iter 60 value 83.674378
iter 70 value 82.696413
iter 80 value 82.393725
iter 90 value 82.327670
iter 100 value 82.136397
final value 82.136397
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.633717
iter 10 value 94.485823
iter 20 value 94.482413
iter 30 value 93.611290
iter 40 value 91.084295
iter 50 value 90.427082
final value 90.073748
converged
Fitting Repeat 2
# weights: 103
initial value 101.519161
final value 94.485771
converged
Fitting Repeat 3
# weights: 103
initial value 95.158092
final value 94.485869
converged
Fitting Repeat 4
# weights: 103
initial value 106.272341
final value 94.485800
converged
Fitting Repeat 5
# weights: 103
initial value 101.352494
iter 10 value 94.485659
final value 94.484213
converged
Fitting Repeat 1
# weights: 305
initial value 103.074401
iter 10 value 92.261036
iter 20 value 91.067432
iter 30 value 90.670262
iter 40 value 90.659997
iter 50 value 90.659075
iter 60 value 90.655596
iter 70 value 90.648895
iter 80 value 90.431043
iter 90 value 90.043984
iter 100 value 89.292023
final value 89.292023
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.135897
iter 10 value 94.488970
iter 20 value 94.232948
iter 30 value 87.259654
iter 40 value 86.670568
iter 50 value 84.506497
iter 60 value 84.232435
final value 84.220921
converged
Fitting Repeat 3
# weights: 305
initial value 106.011422
iter 10 value 94.484975
iter 20 value 92.298946
iter 30 value 86.668622
iter 40 value 84.275311
iter 50 value 82.323870
iter 60 value 80.897202
iter 70 value 80.745064
iter 80 value 80.673866
final value 80.673837
converged
Fitting Repeat 4
# weights: 305
initial value 101.589478
iter 10 value 94.280304
iter 20 value 94.184465
iter 30 value 94.183344
iter 40 value 94.181179
final value 94.181159
converged
Fitting Repeat 5
# weights: 305
initial value 99.998359
iter 10 value 94.488287
iter 20 value 90.317862
iter 30 value 88.718304
iter 40 value 86.587256
iter 50 value 86.450580
iter 60 value 86.414924
iter 70 value 86.411636
final value 86.411629
converged
Fitting Repeat 1
# weights: 507
initial value 119.331142
iter 10 value 94.493189
iter 20 value 94.480430
iter 30 value 87.014588
iter 40 value 86.401924
iter 50 value 86.401893
iter 60 value 86.401371
iter 70 value 83.357292
iter 80 value 82.379802
iter 90 value 81.616919
iter 100 value 80.917866
final value 80.917866
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.391685
iter 10 value 94.490397
iter 20 value 94.318753
iter 30 value 92.350416
iter 40 value 92.249919
iter 50 value 88.416548
iter 60 value 88.323285
final value 88.322677
converged
Fitting Repeat 3
# weights: 507
initial value 107.240335
iter 10 value 93.434441
iter 20 value 93.355716
iter 30 value 90.546857
iter 40 value 90.482784
iter 50 value 90.082288
iter 60 value 90.076568
iter 70 value 90.074095
iter 80 value 90.073780
iter 90 value 90.056532
iter 100 value 85.589411
final value 85.589411
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 99.698334
iter 10 value 94.393777
iter 20 value 94.387306
iter 30 value 94.302519
iter 40 value 90.133579
iter 50 value 90.126843
iter 60 value 90.122781
iter 70 value 89.992361
iter 80 value 89.941776
iter 90 value 89.793192
iter 100 value 89.757643
final value 89.757643
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.263158
iter 10 value 94.491930
iter 20 value 94.436864
iter 30 value 93.105861
iter 40 value 86.359631
iter 50 value 85.745792
iter 60 value 85.160483
iter 70 value 84.004973
iter 80 value 83.036339
iter 90 value 82.334229
iter 100 value 81.626959
final value 81.626959
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.618784
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.246403
iter 10 value 94.314581
final value 94.312042
converged
Fitting Repeat 3
# weights: 103
initial value 106.848492
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.271341
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.945128
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 101.359913
final value 94.484210
converged
Fitting Repeat 2
# weights: 305
initial value 101.196712
final value 94.466823
converged
Fitting Repeat 3
# weights: 305
initial value 106.383599
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 108.719177
final value 94.088889
converged
Fitting Repeat 5
# weights: 305
initial value 100.210878
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 106.477302
iter 10 value 94.461539
iter 10 value 94.461538
iter 10 value 94.461538
final value 94.461538
converged
Fitting Repeat 2
# weights: 507
initial value 105.512799
final value 94.484210
converged
Fitting Repeat 3
# weights: 507
initial value 100.937738
final value 94.466823
converged
Fitting Repeat 4
# weights: 507
initial value 108.939052
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 105.698848
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 102.357120
iter 10 value 94.489438
iter 20 value 94.488562
iter 30 value 94.365439
iter 40 value 94.135177
iter 50 value 93.536404
iter 60 value 87.106647
iter 70 value 86.107093
iter 80 value 85.544414
iter 90 value 85.361728
iter 100 value 85.329574
final value 85.329574
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.208390
iter 10 value 94.476717
iter 20 value 94.096077
iter 30 value 93.131788
iter 40 value 91.667888
iter 50 value 91.144122
iter 60 value 90.862545
iter 70 value 82.659843
iter 80 value 81.893395
iter 90 value 80.997958
iter 100 value 80.714789
final value 80.714789
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 99.099397
iter 10 value 94.486629
iter 20 value 94.198276
iter 30 value 94.094663
iter 40 value 94.093604
iter 50 value 94.093471
iter 60 value 92.947322
iter 70 value 86.111982
iter 80 value 83.701653
iter 90 value 83.451132
iter 100 value 83.214389
final value 83.214389
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.160568
iter 10 value 94.459443
iter 20 value 93.980797
iter 30 value 92.917919
iter 40 value 92.795423
iter 50 value 84.538885
iter 60 value 82.490748
iter 70 value 81.705067
iter 80 value 81.329969
iter 90 value 81.159936
iter 100 value 80.820187
final value 80.820187
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 105.737698
iter 10 value 94.486710
iter 20 value 94.398645
iter 30 value 91.056971
iter 40 value 87.672671
iter 50 value 83.630819
iter 60 value 83.216575
iter 70 value 82.327707
iter 80 value 81.644601
iter 90 value 80.671337
iter 100 value 80.653776
final value 80.653776
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 127.722480
iter 10 value 94.286644
iter 20 value 92.470603
iter 30 value 92.213033
iter 40 value 89.582562
iter 50 value 83.170021
iter 60 value 82.409707
iter 70 value 82.332401
iter 80 value 82.196440
iter 90 value 81.751039
iter 100 value 81.496016
final value 81.496016
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 107.563675
iter 10 value 94.688151
iter 20 value 88.476076
iter 30 value 85.301749
iter 40 value 83.802654
iter 50 value 83.353661
iter 60 value 81.992350
iter 70 value 81.551911
iter 80 value 81.165058
iter 90 value 80.654936
iter 100 value 80.511328
final value 80.511328
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 114.611372
iter 10 value 94.498504
iter 20 value 94.287161
iter 30 value 90.646643
iter 40 value 87.224549
iter 50 value 85.809523
iter 60 value 85.017015
iter 70 value 84.847667
iter 80 value 84.826171
iter 90 value 84.802633
iter 100 value 84.222839
final value 84.222839
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.588445
iter 10 value 94.697295
iter 20 value 94.508892
iter 30 value 94.130571
iter 40 value 91.317416
iter 50 value 90.166404
iter 60 value 88.830379
iter 70 value 83.959070
iter 80 value 83.569975
iter 90 value 82.961141
iter 100 value 82.386040
final value 82.386040
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.136773
iter 10 value 94.240879
iter 20 value 88.802160
iter 30 value 87.220161
iter 40 value 86.710005
iter 50 value 85.574683
iter 60 value 85.425552
iter 70 value 84.064831
iter 80 value 81.646213
iter 90 value 80.660759
iter 100 value 80.339377
final value 80.339377
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 100.307645
iter 10 value 88.164546
iter 20 value 84.982121
iter 30 value 80.027621
iter 40 value 79.756385
iter 50 value 79.545379
iter 60 value 79.375779
iter 70 value 79.087714
iter 80 value 78.992920
iter 90 value 78.965805
iter 100 value 78.892277
final value 78.892277
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.047337
iter 10 value 94.679739
iter 20 value 93.774968
iter 30 value 88.514893
iter 40 value 88.045472
iter 50 value 84.924259
iter 60 value 83.940253
iter 70 value 82.990241
iter 80 value 82.029092
iter 90 value 81.317006
iter 100 value 80.398440
final value 80.398440
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 125.135627
iter 10 value 94.911813
iter 20 value 94.521726
iter 30 value 94.129693
iter 40 value 87.241415
iter 50 value 86.475746
iter 60 value 85.307802
iter 70 value 82.946408
iter 80 value 82.457951
iter 90 value 82.085996
iter 100 value 81.519900
final value 81.519900
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.071605
iter 10 value 94.890975
iter 20 value 93.382016
iter 30 value 92.336515
iter 40 value 90.639286
iter 50 value 85.170312
iter 60 value 83.302486
iter 70 value 82.877668
iter 80 value 82.292636
iter 90 value 81.622678
iter 100 value 81.040633
final value 81.040633
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 110.483645
iter 10 value 96.521347
iter 20 value 90.516972
iter 30 value 87.676120
iter 40 value 86.849487
iter 50 value 85.669415
iter 60 value 85.108225
iter 70 value 82.562386
iter 80 value 81.834709
iter 90 value 80.932281
iter 100 value 80.517185
final value 80.517185
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.596405
iter 10 value 94.485593
iter 20 value 94.484226
iter 30 value 88.817298
iter 40 value 87.264866
iter 50 value 87.259953
iter 60 value 86.144822
iter 70 value 86.084052
iter 80 value 85.838014
iter 90 value 85.607336
iter 100 value 85.606154
final value 85.606154
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 95.953455
final value 94.486051
converged
Fitting Repeat 3
# weights: 103
initial value 98.266828
final value 94.485646
converged
Fitting Repeat 4
# weights: 103
initial value 96.683909
iter 10 value 94.468682
iter 20 value 94.418835
iter 30 value 93.223700
iter 40 value 93.171451
iter 50 value 93.171114
iter 50 value 93.171113
iter 50 value 93.171113
final value 93.171113
converged
Fitting Repeat 5
# weights: 103
initial value 95.628762
final value 94.321712
converged
Fitting Repeat 1
# weights: 305
initial value 101.170286
iter 10 value 94.488869
iter 20 value 94.475102
iter 30 value 94.133219
iter 40 value 94.057786
final value 94.057680
converged
Fitting Repeat 2
# weights: 305
initial value 96.938258
iter 10 value 94.393612
iter 20 value 87.914995
iter 30 value 87.726161
iter 40 value 87.555492
iter 50 value 85.506759
iter 60 value 84.045875
iter 70 value 81.166913
iter 80 value 80.676028
iter 90 value 80.650202
final value 80.650094
converged
Fitting Repeat 3
# weights: 305
initial value 109.939448
iter 10 value 94.488987
iter 20 value 93.887085
iter 30 value 86.948308
iter 40 value 86.105172
iter 50 value 85.059582
iter 60 value 85.051773
iter 70 value 85.018012
iter 80 value 84.672286
iter 90 value 84.629249
iter 100 value 83.514284
final value 83.514284
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.779568
iter 10 value 94.118576
iter 20 value 94.116944
iter 30 value 94.093209
iter 40 value 94.092502
iter 50 value 94.092317
iter 60 value 93.926284
iter 70 value 93.920406
iter 70 value 93.920406
final value 93.920406
converged
Fitting Repeat 5
# weights: 305
initial value 98.242168
iter 10 value 94.488635
final value 94.484213
converged
Fitting Repeat 1
# weights: 507
initial value 117.467082
iter 10 value 94.493051
final value 94.492251
converged
Fitting Repeat 2
# weights: 507
initial value 103.946982
iter 10 value 94.314183
iter 10 value 94.314182
final value 94.314182
converged
Fitting Repeat 3
# weights: 507
initial value 106.434885
iter 10 value 94.494321
iter 20 value 94.287824
iter 30 value 88.349754
iter 40 value 88.344801
iter 50 value 85.963670
final value 85.783645
converged
Fitting Repeat 4
# weights: 507
initial value 97.230133
iter 10 value 94.269733
iter 20 value 94.268869
iter 30 value 94.263214
final value 94.263196
converged
Fitting Repeat 5
# weights: 507
initial value 95.372233
iter 10 value 90.470877
iter 20 value 89.547354
iter 30 value 89.132445
iter 40 value 88.931180
iter 50 value 87.503152
iter 60 value 84.998402
iter 70 value 84.475032
iter 80 value 84.393324
final value 84.393040
converged
Fitting Repeat 1
# weights: 103
initial value 100.779437
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.862735
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 108.871006
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 94.782037
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 101.982561
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 101.569680
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 113.015484
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 106.921439
final value 93.836065
converged
Fitting Repeat 4
# weights: 305
initial value 96.980204
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 94.930230
iter 10 value 82.016373
iter 20 value 81.991611
final value 81.991354
converged
Fitting Repeat 1
# weights: 507
initial value 110.248397
iter 10 value 93.327629
iter 20 value 87.573008
iter 30 value 86.501582
iter 40 value 86.452885
iter 50 value 86.445550
final value 86.445549
converged
Fitting Repeat 2
# weights: 507
initial value 105.118866
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 111.300883
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 118.124589
iter 10 value 93.433812
final value 93.433810
converged
Fitting Repeat 5
# weights: 507
initial value 105.705476
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 101.570576
iter 10 value 94.069982
iter 20 value 92.932285
iter 30 value 86.345144
iter 40 value 84.774550
iter 50 value 84.628365
iter 60 value 82.322175
iter 70 value 81.954339
iter 80 value 81.631419
iter 90 value 81.591695
iter 100 value 81.588588
final value 81.588588
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 99.037919
iter 10 value 94.058955
iter 20 value 93.959765
iter 30 value 93.892441
iter 40 value 93.891713
iter 50 value 93.890946
iter 60 value 93.771248
iter 70 value 84.018008
iter 80 value 81.401998
iter 90 value 80.901761
iter 100 value 79.560664
final value 79.560664
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.377102
iter 10 value 93.962637
iter 20 value 93.337402
iter 30 value 93.303087
iter 40 value 89.010401
iter 50 value 85.813021
iter 60 value 85.518482
iter 70 value 82.043537
iter 80 value 81.598849
iter 90 value 81.588593
final value 81.588587
converged
Fitting Repeat 4
# weights: 103
initial value 109.105756
iter 10 value 94.056697
iter 20 value 80.767362
iter 30 value 80.245354
iter 40 value 79.817219
iter 50 value 79.513328
final value 79.512218
converged
Fitting Repeat 5
# weights: 103
initial value 105.748851
iter 10 value 93.423863
iter 20 value 83.816273
iter 30 value 82.550894
iter 40 value 80.710784
iter 50 value 80.337323
iter 60 value 79.779643
iter 70 value 79.344102
iter 80 value 79.273752
iter 90 value 79.242339
final value 79.239839
converged
Fitting Repeat 1
# weights: 305
initial value 125.484259
iter 10 value 96.188344
iter 20 value 93.739448
iter 30 value 89.953862
iter 40 value 89.823236
iter 50 value 86.623552
iter 60 value 83.389833
iter 70 value 82.242223
iter 80 value 81.068720
iter 90 value 80.448444
iter 100 value 78.544222
final value 78.544222
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.520403
iter 10 value 94.354438
iter 20 value 84.947572
iter 30 value 80.636537
iter 40 value 80.200159
iter 50 value 80.073439
iter 60 value 79.737122
iter 70 value 79.075063
iter 80 value 78.847575
iter 90 value 78.645237
iter 100 value 78.203367
final value 78.203367
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.116216
iter 10 value 94.123249
iter 20 value 94.009209
iter 30 value 83.919325
iter 40 value 81.681179
iter 50 value 81.049161
iter 60 value 80.698137
iter 70 value 80.496742
iter 80 value 79.683346
iter 90 value 78.722345
iter 100 value 77.863594
final value 77.863594
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.746792
iter 10 value 86.429878
iter 20 value 82.341585
iter 30 value 79.570720
iter 40 value 77.253088
iter 50 value 77.063543
final value 77.038764
converged
Fitting Repeat 5
# weights: 305
initial value 99.431346
iter 10 value 93.967408
iter 20 value 86.627591
iter 30 value 81.649328
iter 40 value 80.540343
iter 50 value 78.535645
iter 60 value 77.330690
iter 70 value 77.218783
iter 80 value 77.120027
iter 90 value 77.085365
iter 100 value 77.074722
final value 77.074722
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.971886
iter 10 value 94.089602
iter 20 value 93.980463
iter 30 value 91.882409
iter 40 value 84.678899
iter 50 value 80.549872
iter 60 value 79.333493
iter 70 value 78.753007
iter 80 value 78.158080
iter 90 value 77.458211
iter 100 value 77.151138
final value 77.151138
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.199037
iter 10 value 94.135011
iter 20 value 86.577328
iter 30 value 82.962737
iter 40 value 82.233761
iter 50 value 80.493370
iter 60 value 79.688180
iter 70 value 79.249113
iter 80 value 79.018262
iter 90 value 78.835626
iter 100 value 78.418075
final value 78.418075
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.310335
iter 10 value 92.039631
iter 20 value 83.027661
iter 30 value 81.464294
iter 40 value 78.361459
iter 50 value 77.570607
iter 60 value 77.272405
iter 70 value 77.030939
iter 80 value 76.827027
iter 90 value 76.505326
iter 100 value 76.451376
final value 76.451376
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.029388
iter 10 value 94.421933
iter 20 value 93.573525
iter 30 value 87.486912
iter 40 value 85.992944
iter 50 value 83.072218
iter 60 value 81.593782
iter 70 value 80.208773
iter 80 value 79.952137
iter 90 value 79.238014
iter 100 value 78.475139
final value 78.475139
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 110.628391
iter 10 value 93.991826
iter 20 value 84.772987
iter 30 value 82.310340
iter 40 value 77.988054
iter 50 value 77.291114
iter 60 value 76.927908
iter 70 value 76.647181
iter 80 value 76.334401
iter 90 value 76.220675
iter 100 value 76.145161
final value 76.145161
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 107.113798
final value 94.054559
converged
Fitting Repeat 2
# weights: 103
initial value 101.998230
final value 94.007700
converged
Fitting Repeat 3
# weights: 103
initial value 98.717759
iter 10 value 89.383793
iter 20 value 87.168396
iter 30 value 86.946539
iter 40 value 86.943277
final value 86.943266
converged
Fitting Repeat 4
# weights: 103
initial value 97.004356
final value 94.054440
converged
Fitting Repeat 5
# weights: 103
initial value 95.618749
iter 10 value 93.837594
iter 20 value 93.754089
iter 30 value 90.572283
iter 40 value 90.459242
iter 40 value 90.459241
iter 40 value 90.459241
final value 90.459241
converged
Fitting Repeat 1
# weights: 305
initial value 102.366606
iter 10 value 94.057544
iter 20 value 94.052953
iter 30 value 81.451894
iter 40 value 81.140860
iter 50 value 80.920416
iter 60 value 80.919723
iter 70 value 79.895199
iter 80 value 79.761511
final value 79.761306
converged
Fitting Repeat 2
# weights: 305
initial value 97.117815
iter 10 value 93.841046
iter 20 value 93.836231
final value 93.836220
converged
Fitting Repeat 3
# weights: 305
initial value 95.163821
iter 10 value 93.841383
iter 20 value 93.838198
iter 30 value 93.837305
final value 93.837291
converged
Fitting Repeat 4
# weights: 305
initial value 94.108724
iter 10 value 93.840834
iter 20 value 93.836274
iter 30 value 84.785984
iter 40 value 81.592052
iter 50 value 81.314538
iter 60 value 81.175032
iter 70 value 81.012004
iter 80 value 81.011436
iter 90 value 79.640664
iter 100 value 79.615923
final value 79.615923
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.819451
iter 10 value 94.057887
iter 20 value 93.972731
iter 30 value 91.994338
iter 40 value 88.721821
iter 50 value 88.597582
iter 60 value 88.593427
iter 70 value 88.552089
iter 80 value 81.445038
iter 90 value 81.292916
iter 100 value 79.564515
final value 79.564515
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.542355
iter 10 value 93.847860
iter 20 value 93.839629
iter 30 value 93.839091
iter 30 value 93.839091
iter 30 value 93.839091
final value 93.839091
converged
Fitting Repeat 2
# weights: 507
initial value 98.805664
iter 10 value 93.844689
iter 20 value 93.837173
iter 30 value 93.282910
iter 40 value 92.137227
final value 92.137164
converged
Fitting Repeat 3
# weights: 507
initial value 105.765346
iter 10 value 94.060766
iter 20 value 88.789724
iter 30 value 82.135504
iter 40 value 79.588828
iter 50 value 77.656194
iter 60 value 75.972080
iter 70 value 75.758745
iter 80 value 75.742776
iter 90 value 75.742483
iter 100 value 75.566916
final value 75.566916
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.282725
iter 10 value 94.014353
iter 20 value 92.387749
iter 30 value 89.178436
iter 40 value 88.883492
iter 50 value 88.883124
final value 88.882889
converged
Fitting Repeat 5
# weights: 507
initial value 104.998516
iter 10 value 94.061315
iter 20 value 89.397594
iter 30 value 82.584727
iter 40 value 82.549901
iter 50 value 79.803352
iter 60 value 79.735632
iter 70 value 79.605746
iter 80 value 78.925804
iter 90 value 76.743128
iter 100 value 76.491121
final value 76.491121
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 133.298424
iter 10 value 117.900553
iter 20 value 117.872632
iter 30 value 110.558865
iter 40 value 108.168289
iter 50 value 107.366044
iter 60 value 106.673654
iter 70 value 106.653435
iter 80 value 106.483310
iter 90 value 105.462552
iter 100 value 105.290583
final value 105.290583
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 128.541099
iter 10 value 117.767451
iter 20 value 117.765579
iter 30 value 117.697370
iter 40 value 117.516505
iter 50 value 117.511780
final value 117.511768
converged
Fitting Repeat 3
# weights: 507
initial value 126.445053
iter 10 value 117.714214
iter 20 value 107.624320
iter 30 value 107.250897
iter 40 value 107.247819
iter 50 value 107.244056
iter 60 value 107.129880
iter 70 value 106.813191
iter 80 value 106.810547
iter 90 value 106.809249
iter 100 value 106.232993
final value 106.232993
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 132.423639
iter 10 value 117.214168
iter 20 value 115.039723
iter 30 value 114.924149
iter 40 value 108.718788
iter 50 value 108.387358
iter 60 value 108.381390
iter 70 value 108.380142
iter 80 value 108.352178
iter 90 value 107.184746
iter 100 value 104.851695
final value 104.851695
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 190.632955
iter 10 value 108.968773
iter 20 value 108.535546
iter 30 value 108.446475
iter 40 value 107.201117
iter 50 value 107.185637
iter 60 value 107.151321
iter 70 value 107.050162
final value 107.047031
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 -- Wed Jan 21 00:35:49 2026
***********************************************
Number of test functions: 7
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7
Number of errors: 0
Number of failures: 0
Warning messages:
1: `repeats` has no meaning for this resampling method.
2: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
41.783 1.961 98.327
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.046 | 0.636 | 33.683 | |
| FreqInteractors | 0.429 | 0.029 | 0.461 | |
| calculateAAC | 0.033 | 0.000 | 0.033 | |
| calculateAutocor | 0.270 | 0.019 | 0.290 | |
| calculateCTDC | 0.077 | 0.000 | 0.077 | |
| calculateCTDD | 0.468 | 0.000 | 0.468 | |
| calculateCTDT | 0.147 | 0.001 | 0.150 | |
| calculateCTriad | 0.417 | 0.007 | 0.424 | |
| calculateDC | 0.088 | 0.006 | 0.095 | |
| calculateF | 0.298 | 0.001 | 0.300 | |
| calculateKSAAP | 0.096 | 0.006 | 0.103 | |
| calculateQD_Sm | 1.809 | 0.027 | 1.836 | |
| calculateTC | 1.480 | 0.144 | 1.624 | |
| calculateTC_Sm | 0.287 | 0.004 | 0.291 | |
| corr_plot | 34.640 | 0.603 | 35.244 | |
| enrichfindP | 0.562 | 0.049 | 12.146 | |
| enrichfind_hp | 0.042 | 0.001 | 2.015 | |
| enrichplot | 0.493 | 0.003 | 0.495 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.501 | 0.012 | 3.462 | |
| getHPI | 0.000 | 0.000 | 0.001 | |
| get_negativePPI | 0.001 | 0.001 | 0.001 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.001 | 0.001 | 0.002 | |
| plotPPI | 0.082 | 0.012 | 0.094 | |
| pred_ensembel | 13.188 | 0.360 | 12.238 | |
| var_imp | 34.503 | 0.676 | 35.236 | |