Matineh Rahmatbakhsh
| Snapshot Date: 2026-03-02 13:45 -0500 (Mon, 02 Mar 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_22 |
| git_last_commit: 6cf0d22 |
| git_last_commit_date: 2025-12-28 18:31:13 -0500 (Sun, 28 Dec 2025) |
| Back to Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-03-03 11:57 -0500 (Tue, 03 Mar 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4892 |
| 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 1006/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.16.1 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| See other builds for HPiP in R Universe. | ||||||||||||||
|
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: 1.16.1 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz |
| StartedAt: 2026-03-03 00:32:47 -0500 (Tue, 03 Mar 2026) |
| EndedAt: 2026-03-03 00:47:33 -0500 (Tue, 03 Mar 2026) |
| EllapsedTime: 886.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.2 (2025-10-31)
* 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 ‘1.16.1’
* 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 34.783 0.444 35.318
var_imp 33.390 0.723 34.114
FSmethod 33.563 0.435 34.001
pred_ensembel 13.057 0.558 12.338
enrichfindP 0.529 0.041 11.933
* 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-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.16.1’ ** 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 version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 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 101.144713
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.764895
iter 10 value 94.275365
iter 10 value 94.275365
iter 10 value 94.275364
final value 94.275364
converged
Fitting Repeat 3
# weights: 103
initial value 96.490640
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 103.496198
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.715035
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 103.159950
iter 10 value 92.278732
iter 20 value 86.921376
iter 30 value 85.860241
final value 85.860234
converged
Fitting Repeat 2
# weights: 305
initial value 97.799819
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 107.088471
final value 94.275362
converged
Fitting Repeat 4
# weights: 305
initial value 95.607736
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 95.682958
iter 10 value 89.076238
iter 20 value 84.034600
iter 30 value 83.940728
iter 30 value 83.940728
iter 30 value 83.940728
final value 83.940728
converged
Fitting Repeat 1
# weights: 507
initial value 104.582697
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 95.341121
iter 10 value 92.798276
iter 20 value 91.604291
iter 30 value 91.390664
iter 40 value 91.390554
iter 40 value 91.390553
iter 40 value 91.390553
final value 91.390553
converged
Fitting Repeat 3
# weights: 507
initial value 108.431460
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 107.012095
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 95.408822
final value 94.052434
converged
Fitting Repeat 1
# weights: 103
initial value 100.901313
iter 10 value 94.469555
iter 20 value 92.069151
iter 30 value 90.082536
iter 40 value 84.189499
iter 50 value 83.231630
iter 60 value 82.874434
iter 70 value 82.796429
final value 82.795264
converged
Fitting Repeat 2
# weights: 103
initial value 110.312838
iter 10 value 94.491931
iter 20 value 93.940105
iter 30 value 93.914387
iter 40 value 88.865180
iter 50 value 87.467794
iter 60 value 87.302927
iter 70 value 86.407695
iter 80 value 84.664732
iter 90 value 84.655071
iter 100 value 84.650854
final value 84.650854
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 105.891983
iter 10 value 92.779392
iter 20 value 85.363658
iter 30 value 84.384295
iter 40 value 84.358594
iter 50 value 84.347169
iter 60 value 84.281802
final value 84.277458
converged
Fitting Repeat 4
# weights: 103
initial value 96.329528
iter 10 value 94.491903
iter 20 value 94.487987
iter 30 value 94.106523
iter 40 value 90.096240
iter 50 value 89.214063
iter 60 value 86.937818
iter 70 value 86.234186
iter 80 value 85.939824
iter 90 value 85.884029
iter 100 value 85.868417
final value 85.868417
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 104.081177
iter 10 value 94.490755
iter 20 value 94.348655
iter 30 value 91.201833
iter 40 value 86.733707
iter 50 value 84.795007
iter 60 value 84.653209
iter 70 value 84.650875
final value 84.650854
converged
Fitting Repeat 1
# weights: 305
initial value 116.832048
iter 10 value 94.651775
iter 20 value 90.912809
iter 30 value 88.451901
iter 40 value 87.057025
iter 50 value 86.894888
iter 60 value 84.926308
iter 70 value 84.002348
iter 80 value 83.824896
iter 90 value 83.527185
iter 100 value 83.139019
final value 83.139019
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.057475
iter 10 value 94.452592
iter 20 value 89.623507
iter 30 value 84.885608
iter 40 value 84.553399
iter 50 value 84.366807
iter 60 value 83.382793
iter 70 value 82.568550
iter 80 value 82.256085
iter 90 value 82.149266
iter 100 value 82.098776
final value 82.098776
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.549905
iter 10 value 94.379119
iter 20 value 94.152097
iter 30 value 93.992400
iter 40 value 93.775299
iter 50 value 87.299032
iter 60 value 84.295001
iter 70 value 83.083995
iter 80 value 82.163552
iter 90 value 81.901420
iter 100 value 81.653494
final value 81.653494
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.407346
iter 10 value 92.367288
iter 20 value 86.802864
iter 30 value 86.564545
iter 40 value 86.333014
iter 50 value 86.029905
iter 60 value 85.673373
iter 70 value 83.735320
iter 80 value 82.682753
iter 90 value 81.835861
iter 100 value 81.727119
final value 81.727119
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.312778
iter 10 value 91.901412
iter 20 value 84.785160
iter 30 value 84.342272
iter 40 value 84.286420
iter 50 value 83.898949
iter 60 value 83.385814
iter 70 value 82.434304
iter 80 value 82.250076
iter 90 value 82.111817
iter 100 value 81.996355
final value 81.996355
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.407748
iter 10 value 94.382311
iter 20 value 85.204218
iter 30 value 83.104954
iter 40 value 82.867683
iter 50 value 82.657733
iter 60 value 82.433960
iter 70 value 81.884991
iter 80 value 81.501191
iter 90 value 81.351209
iter 100 value 81.322639
final value 81.322639
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.120214
iter 10 value 93.616792
iter 20 value 85.728577
iter 30 value 84.480951
iter 40 value 84.330103
iter 50 value 84.317620
iter 60 value 84.107916
iter 70 value 83.094898
iter 80 value 82.559277
iter 90 value 82.369091
iter 100 value 82.003821
final value 82.003821
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 123.426208
iter 10 value 94.548709
iter 20 value 91.047975
iter 30 value 85.382534
iter 40 value 84.785704
iter 50 value 84.002364
iter 60 value 82.983194
iter 70 value 82.721626
iter 80 value 82.344303
iter 90 value 82.162872
iter 100 value 82.053337
final value 82.053337
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.241583
iter 10 value 94.539247
iter 20 value 87.240860
iter 30 value 86.552295
iter 40 value 85.479189
iter 50 value 84.184662
iter 60 value 83.010374
iter 70 value 81.896682
iter 80 value 81.566044
iter 90 value 81.533600
iter 100 value 81.505764
final value 81.505764
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 127.753331
iter 10 value 93.803388
iter 20 value 87.770011
iter 30 value 84.679029
iter 40 value 84.356732
iter 50 value 82.687062
iter 60 value 82.263249
iter 70 value 82.082258
iter 80 value 81.777717
iter 90 value 81.729239
iter 100 value 81.667090
final value 81.667090
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 106.605823
final value 94.485884
converged
Fitting Repeat 2
# weights: 103
initial value 95.907718
iter 10 value 94.276994
iter 20 value 94.275417
iter 30 value 84.491734
iter 40 value 84.037997
iter 50 value 83.970608
iter 60 value 83.943117
iter 70 value 83.849729
iter 80 value 83.510801
iter 90 value 83.432928
final value 83.415153
converged
Fitting Repeat 3
# weights: 103
initial value 105.195730
iter 10 value 94.485813
iter 20 value 94.294160
iter 30 value 84.638042
iter 40 value 84.629228
iter 50 value 84.628286
iter 60 value 84.626985
final value 84.626924
converged
Fitting Repeat 4
# weights: 103
initial value 96.789018
final value 94.485995
converged
Fitting Repeat 5
# weights: 103
initial value 101.414672
iter 10 value 93.116943
iter 20 value 93.111765
final value 93.110319
converged
Fitting Repeat 1
# weights: 305
initial value 111.265880
iter 10 value 94.280335
iter 20 value 93.959661
iter 30 value 87.318202
iter 40 value 87.317922
final value 87.317917
converged
Fitting Repeat 2
# weights: 305
initial value 110.256879
iter 10 value 94.488965
iter 20 value 94.484226
iter 30 value 94.337408
final value 93.871589
converged
Fitting Repeat 3
# weights: 305
initial value 100.042418
iter 10 value 94.489613
iter 20 value 93.141853
final value 93.111361
converged
Fitting Repeat 4
# weights: 305
initial value 97.493767
iter 10 value 93.825457
iter 20 value 86.750973
iter 30 value 86.715628
iter 40 value 86.712946
iter 50 value 85.372956
iter 60 value 85.187497
iter 70 value 85.162268
iter 80 value 85.161053
iter 90 value 85.134298
iter 100 value 85.051854
final value 85.051854
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.884106
iter 10 value 94.280346
iter 20 value 94.276658
iter 30 value 93.857264
iter 40 value 93.510683
iter 50 value 89.269974
iter 60 value 88.244534
iter 70 value 88.240075
iter 80 value 88.236027
iter 90 value 87.166145
iter 100 value 87.065066
final value 87.065066
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.109008
iter 10 value 94.286624
iter 20 value 94.126725
iter 30 value 87.351066
iter 40 value 84.868016
iter 50 value 84.585785
iter 60 value 84.576263
iter 70 value 84.576068
iter 80 value 84.573983
iter 90 value 84.572847
iter 100 value 84.571321
final value 84.571321
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 96.469451
iter 10 value 93.988045
iter 20 value 93.951062
iter 30 value 88.509206
iter 40 value 85.452507
iter 50 value 85.430135
iter 60 value 85.429465
iter 70 value 85.421061
iter 80 value 85.401545
iter 90 value 85.398794
iter 100 value 85.219391
final value 85.219391
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 121.185390
iter 10 value 93.847541
iter 20 value 93.847096
iter 30 value 93.841068
iter 40 value 93.738437
iter 50 value 84.660292
final value 84.631249
converged
Fitting Repeat 4
# weights: 507
initial value 101.423749
iter 10 value 94.492327
iter 20 value 91.712421
iter 30 value 85.877569
iter 40 value 84.627970
iter 50 value 84.588052
iter 60 value 84.041147
iter 70 value 83.417412
iter 80 value 83.404922
final value 83.404768
converged
Fitting Repeat 5
# weights: 507
initial value 103.419117
iter 10 value 94.092434
iter 20 value 94.085455
final value 94.084775
converged
Fitting Repeat 1
# weights: 103
initial value 95.487695
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.634619
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.169363
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 104.095901
iter 10 value 94.284236
final value 94.275363
converged
Fitting Repeat 5
# weights: 103
initial value 106.631119
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 96.595361
final value 94.275362
converged
Fitting Repeat 2
# weights: 305
initial value 98.179829
iter 10 value 94.424883
iter 20 value 94.275374
final value 94.275363
converged
Fitting Repeat 3
# weights: 305
initial value 115.276519
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 96.033926
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 113.472743
final value 94.275362
converged
Fitting Repeat 1
# weights: 507
initial value 98.584323
final value 94.484216
converged
Fitting Repeat 2
# weights: 507
initial value 99.854207
final value 94.275362
converged
Fitting Repeat 3
# weights: 507
initial value 98.233094
final value 94.275362
converged
Fitting Repeat 4
# weights: 507
initial value 104.213799
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 141.487171
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 103.241861
iter 10 value 94.426048
iter 20 value 91.902764
iter 30 value 91.720935
iter 40 value 91.697271
iter 50 value 91.634179
iter 60 value 91.201440
iter 70 value 90.982061
final value 90.981260
converged
Fitting Repeat 2
# weights: 103
initial value 99.452039
iter 10 value 94.498673
iter 20 value 94.488809
iter 30 value 94.333723
iter 40 value 94.327513
iter 50 value 94.327354
iter 60 value 89.937366
iter 70 value 86.385336
iter 80 value 85.487322
iter 90 value 84.817374
iter 100 value 84.799424
final value 84.799424
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.121868
iter 10 value 94.416768
iter 20 value 90.831143
iter 30 value 90.545741
iter 40 value 90.299880
iter 50 value 87.232470
iter 60 value 85.468616
iter 70 value 84.762683
iter 80 value 84.755602
final value 84.754597
converged
Fitting Repeat 4
# weights: 103
initial value 99.930490
iter 10 value 94.136240
iter 20 value 92.328763
iter 30 value 88.701977
iter 40 value 86.011063
iter 50 value 85.470440
iter 60 value 84.843699
iter 70 value 84.402668
final value 84.370697
converged
Fitting Repeat 5
# weights: 103
initial value 105.075589
iter 10 value 94.435504
iter 20 value 94.324175
iter 30 value 93.792256
iter 40 value 91.174602
iter 50 value 90.358108
iter 60 value 90.253605
final value 90.252078
converged
Fitting Repeat 1
# weights: 305
initial value 104.188002
iter 10 value 94.811344
iter 20 value 91.216663
iter 30 value 88.201096
iter 40 value 86.554147
iter 50 value 85.347744
iter 60 value 84.060152
iter 70 value 82.393599
iter 80 value 81.668447
iter 90 value 81.435691
iter 100 value 81.187594
final value 81.187594
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.728465
iter 10 value 93.329897
iter 20 value 91.589298
iter 30 value 90.392279
iter 40 value 85.522806
iter 50 value 83.061142
iter 60 value 82.746759
iter 70 value 82.591278
iter 80 value 82.517131
iter 90 value 82.383168
iter 100 value 82.326036
final value 82.326036
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 127.109244
iter 10 value 94.462358
iter 20 value 94.268255
iter 30 value 93.093030
iter 40 value 92.942264
iter 50 value 90.859697
iter 60 value 85.581694
iter 70 value 84.016377
iter 80 value 83.575157
iter 90 value 82.726731
iter 100 value 81.865593
final value 81.865593
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 133.163106
iter 10 value 94.453489
iter 20 value 91.844234
iter 30 value 89.365858
iter 40 value 88.494718
iter 50 value 84.210411
iter 60 value 81.876562
iter 70 value 81.355470
iter 80 value 80.767797
iter 90 value 80.613140
iter 100 value 79.896955
final value 79.896955
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 122.581076
iter 10 value 94.340053
iter 20 value 86.602651
iter 30 value 85.668790
iter 40 value 83.637449
iter 50 value 83.300367
iter 60 value 82.523912
iter 70 value 81.922210
iter 80 value 81.697149
iter 90 value 81.539442
iter 100 value 81.527861
final value 81.527861
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.681533
iter 10 value 94.385270
iter 20 value 93.979687
iter 30 value 86.019901
iter 40 value 83.497344
iter 50 value 82.713856
iter 60 value 81.424044
iter 70 value 80.615195
iter 80 value 80.159041
iter 90 value 79.992393
iter 100 value 79.872587
final value 79.872587
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.525335
iter 10 value 94.441617
iter 20 value 85.771498
iter 30 value 82.865539
iter 40 value 81.826583
iter 50 value 80.984365
iter 60 value 80.243434
iter 70 value 80.072274
iter 80 value 79.881909
iter 90 value 79.756739
iter 100 value 79.615109
final value 79.615109
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 134.160975
iter 10 value 94.542170
iter 20 value 91.673226
iter 30 value 88.895356
iter 40 value 87.020450
iter 50 value 86.286891
iter 60 value 85.984668
iter 70 value 84.949449
iter 80 value 84.386464
iter 90 value 83.895998
iter 100 value 83.273869
final value 83.273869
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.852398
iter 10 value 98.282952
iter 20 value 85.366650
iter 30 value 81.924061
iter 40 value 81.491069
iter 50 value 80.195463
iter 60 value 80.049262
iter 70 value 79.909709
iter 80 value 79.700556
iter 90 value 79.487955
iter 100 value 79.276237
final value 79.276237
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 108.770254
iter 10 value 94.526913
iter 20 value 93.938560
iter 30 value 85.837549
iter 40 value 84.041527
iter 50 value 83.014813
iter 60 value 81.011817
iter 70 value 80.420995
iter 80 value 80.096052
iter 90 value 80.049721
iter 100 value 79.876555
final value 79.876555
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.682905
final value 94.486034
converged
Fitting Repeat 2
# weights: 103
initial value 99.641217
final value 94.485826
converged
Fitting Repeat 3
# weights: 103
initial value 96.604947
final value 94.485941
converged
Fitting Repeat 4
# weights: 103
initial value 102.264434
final value 94.254668
converged
Fitting Repeat 5
# weights: 103
initial value 98.784201
iter 10 value 94.485787
iter 20 value 94.484077
iter 30 value 93.965035
iter 40 value 87.593950
final value 87.593841
converged
Fitting Repeat 1
# weights: 305
initial value 101.580683
iter 10 value 94.487953
iter 20 value 87.967028
iter 30 value 87.364279
iter 40 value 87.362487
final value 87.362243
converged
Fitting Repeat 2
# weights: 305
initial value 104.944474
iter 10 value 94.280155
iter 20 value 94.277188
final value 94.276530
converged
Fitting Repeat 3
# weights: 305
initial value 97.503802
iter 10 value 94.488978
iter 20 value 94.272814
iter 30 value 88.161517
iter 40 value 88.157414
iter 50 value 88.149239
iter 60 value 88.147522
iter 70 value 87.229022
iter 80 value 87.200114
final value 87.199398
converged
Fitting Repeat 4
# weights: 305
initial value 102.793197
iter 10 value 94.488876
iter 20 value 94.285326
iter 30 value 90.770054
iter 40 value 90.767064
iter 50 value 90.766661
iter 60 value 90.766174
iter 70 value 90.765092
iter 80 value 90.764582
iter 90 value 88.824949
iter 100 value 88.823362
final value 88.823362
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.212736
iter 10 value 94.488751
iter 20 value 94.463185
iter 30 value 87.528011
iter 40 value 87.249752
iter 50 value 85.105599
final value 85.088323
converged
Fitting Repeat 1
# weights: 507
initial value 97.959355
iter 10 value 93.871321
iter 20 value 93.865323
iter 30 value 85.237923
iter 40 value 82.650253
iter 50 value 82.582755
iter 60 value 82.582452
iter 70 value 81.674587
iter 80 value 81.587120
final value 81.587048
converged
Fitting Repeat 2
# weights: 507
initial value 95.913307
iter 10 value 94.492014
iter 20 value 94.417714
iter 30 value 85.238710
iter 40 value 83.472587
iter 50 value 83.348695
iter 60 value 83.346315
iter 70 value 83.345859
final value 83.345640
converged
Fitting Repeat 3
# weights: 507
initial value 99.263673
iter 10 value 94.332023
iter 20 value 94.295751
iter 30 value 91.431970
iter 40 value 83.725776
iter 50 value 83.242112
iter 60 value 80.531172
iter 70 value 79.647163
iter 80 value 79.464617
iter 90 value 79.230031
iter 100 value 79.091005
final value 79.091005
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 95.005127
iter 10 value 94.484695
iter 20 value 94.169225
iter 30 value 89.314883
iter 40 value 87.881344
iter 50 value 87.879427
iter 60 value 87.463340
iter 70 value 85.456947
iter 80 value 85.454731
iter 90 value 85.452267
iter 100 value 85.052731
final value 85.052731
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 114.314894
iter 10 value 94.055210
iter 20 value 94.048863
final value 94.048572
converged
Fitting Repeat 1
# weights: 103
initial value 95.555419
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 97.127378
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.640244
iter 10 value 93.582418
iter 10 value 93.582418
iter 10 value 93.582418
final value 93.582418
converged
Fitting Repeat 4
# weights: 103
initial value 94.664129
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.104482
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 96.752043
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 101.926122
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 103.578101
iter 10 value 93.407191
iter 20 value 93.387708
final value 93.387664
converged
Fitting Repeat 4
# weights: 305
initial value 107.356341
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 98.393031
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 118.441602
final value 93.582418
converged
Fitting Repeat 2
# weights: 507
initial value 94.738137
iter 10 value 92.696723
iter 20 value 92.647289
iter 30 value 92.646818
iter 40 value 91.924479
final value 91.915973
converged
Fitting Repeat 3
# weights: 507
initial value 109.498356
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 98.621455
final value 93.582418
converged
Fitting Repeat 5
# weights: 507
initial value 108.880036
final value 93.944596
converged
Fitting Repeat 1
# weights: 103
initial value 98.198282
iter 10 value 94.052309
iter 20 value 87.639277
iter 30 value 86.563854
iter 40 value 86.118472
iter 50 value 84.889635
iter 60 value 84.719645
iter 70 value 84.657784
final value 84.640843
converged
Fitting Repeat 2
# weights: 103
initial value 100.227436
iter 10 value 93.400910
iter 20 value 87.061819
iter 30 value 85.013756
iter 40 value 84.138600
iter 50 value 83.748058
iter 60 value 83.642728
iter 70 value 83.214211
iter 80 value 82.945723
iter 90 value 82.742294
iter 100 value 82.727703
final value 82.727703
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 105.418975
iter 10 value 94.055283
iter 20 value 93.375108
iter 30 value 93.044991
iter 40 value 93.025624
iter 50 value 93.014634
iter 60 value 91.059178
iter 70 value 86.359618
iter 80 value 85.681253
iter 90 value 84.459971
iter 100 value 84.162936
final value 84.162936
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.904600
iter 10 value 94.109124
iter 20 value 94.054573
iter 30 value 93.129257
iter 40 value 93.037847
iter 50 value 92.377683
iter 60 value 89.654354
iter 70 value 89.419556
iter 80 value 87.044078
iter 90 value 86.796584
iter 100 value 85.951253
final value 85.951253
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 95.999256
iter 10 value 94.056657
iter 20 value 93.295340
iter 30 value 93.137559
iter 40 value 93.045287
iter 50 value 93.033525
iter 60 value 88.695679
iter 70 value 87.189482
iter 80 value 86.417520
iter 90 value 84.124897
iter 100 value 83.772974
final value 83.772974
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 100.644244
iter 10 value 94.090388
iter 20 value 94.020631
iter 30 value 93.549275
iter 40 value 90.368047
iter 50 value 88.673968
iter 60 value 86.070770
iter 70 value 84.214241
iter 80 value 83.533021
iter 90 value 83.366532
iter 100 value 82.959198
final value 82.959198
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.716318
iter 10 value 94.030792
iter 20 value 92.786132
iter 30 value 89.454373
iter 40 value 86.311876
iter 50 value 84.965798
iter 60 value 84.558047
iter 70 value 83.783028
iter 80 value 83.538866
iter 90 value 83.322748
iter 100 value 83.183722
final value 83.183722
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.531199
iter 10 value 93.277662
iter 20 value 92.415747
iter 30 value 89.364682
iter 40 value 89.049475
iter 50 value 85.745780
iter 60 value 83.143431
iter 70 value 82.624202
iter 80 value 82.241217
iter 90 value 81.965653
iter 100 value 81.929376
final value 81.929376
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.094784
iter 10 value 94.134679
iter 20 value 86.462567
iter 30 value 85.577829
iter 40 value 85.527597
iter 50 value 85.464838
iter 60 value 85.306060
iter 70 value 85.225412
iter 80 value 83.811690
iter 90 value 82.819537
iter 100 value 82.431340
final value 82.431340
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.685774
iter 10 value 94.070625
iter 20 value 92.572042
iter 30 value 88.931703
iter 40 value 87.709984
iter 50 value 86.459107
iter 60 value 84.332419
iter 70 value 83.471765
iter 80 value 83.031629
iter 90 value 82.547558
iter 100 value 82.290290
final value 82.290290
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.025020
iter 10 value 93.923515
iter 20 value 89.043089
iter 30 value 87.784791
iter 40 value 84.755418
iter 50 value 84.345917
iter 60 value 83.914745
iter 70 value 83.536197
iter 80 value 83.184843
iter 90 value 82.892078
iter 100 value 82.761092
final value 82.761092
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.774100
iter 10 value 93.949240
iter 20 value 88.198050
iter 30 value 85.136760
iter 40 value 84.658938
iter 50 value 84.348821
iter 60 value 84.237091
iter 70 value 84.047945
iter 80 value 83.924997
iter 90 value 83.840972
iter 100 value 83.650046
final value 83.650046
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 118.490551
iter 10 value 94.565683
iter 20 value 91.319355
iter 30 value 84.458573
iter 40 value 82.398513
iter 50 value 82.130899
iter 60 value 81.905461
iter 70 value 81.743851
iter 80 value 81.598322
iter 90 value 81.423886
iter 100 value 81.360283
final value 81.360283
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.098892
iter 10 value 93.921614
iter 20 value 93.745067
iter 30 value 92.626285
iter 40 value 85.137797
iter 50 value 82.275573
iter 60 value 81.844494
iter 70 value 81.759311
iter 80 value 81.584071
iter 90 value 81.468976
iter 100 value 81.412340
final value 81.412340
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 136.876512
iter 10 value 95.165961
iter 20 value 93.127630
iter 30 value 87.771537
iter 40 value 87.199379
iter 50 value 85.662182
iter 60 value 84.577188
iter 70 value 84.104343
iter 80 value 82.909428
iter 90 value 81.767670
iter 100 value 81.605833
final value 81.605833
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.119714
iter 10 value 92.863425
iter 20 value 92.862762
iter 30 value 92.862079
final value 92.862056
converged
Fitting Repeat 2
# weights: 103
initial value 99.275371
final value 94.054506
converged
Fitting Repeat 3
# weights: 103
initial value 98.678067
iter 10 value 93.584298
iter 20 value 93.297643
iter 30 value 92.572664
iter 40 value 92.567603
iter 50 value 92.567152
iter 60 value 92.506760
final value 92.506599
converged
Fitting Repeat 4
# weights: 103
initial value 102.079932
iter 10 value 94.054589
iter 20 value 93.625279
iter 30 value 86.418598
final value 85.836485
converged
Fitting Repeat 5
# weights: 103
initial value 101.594000
final value 94.054613
converged
Fitting Repeat 1
# weights: 305
initial value 107.386563
iter 10 value 94.057747
iter 20 value 93.762248
iter 30 value 87.133933
iter 40 value 85.718181
iter 50 value 85.053233
iter 60 value 84.905651
iter 70 value 84.904710
iter 80 value 84.904518
iter 90 value 84.904136
iter 100 value 84.903827
final value 84.903827
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.244261
iter 10 value 94.057456
final value 94.052937
converged
Fitting Repeat 3
# weights: 305
initial value 98.759592
iter 10 value 94.058033
iter 20 value 93.918522
iter 30 value 93.905211
iter 40 value 93.873221
iter 50 value 93.872304
final value 93.872292
converged
Fitting Repeat 4
# weights: 305
initial value 101.021831
iter 10 value 94.057164
iter 20 value 91.916580
iter 30 value 84.840544
iter 40 value 84.387134
iter 50 value 84.219959
iter 60 value 84.219632
iter 70 value 83.651289
iter 80 value 82.808547
iter 90 value 82.700223
iter 100 value 82.643663
final value 82.643663
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 94.751068
iter 10 value 94.055802
iter 20 value 92.867365
final value 92.862110
converged
Fitting Repeat 1
# weights: 507
initial value 148.514424
iter 10 value 94.061362
iter 20 value 94.040815
final value 93.583039
converged
Fitting Repeat 2
# weights: 507
initial value 109.542679
iter 10 value 93.543142
iter 20 value 93.523088
iter 30 value 93.513013
final value 93.512898
converged
Fitting Repeat 3
# weights: 507
initial value 96.751449
iter 10 value 94.036656
iter 20 value 94.035285
iter 30 value 94.026861
iter 40 value 93.267418
iter 50 value 87.777132
iter 60 value 86.647781
iter 70 value 86.638262
final value 86.638249
converged
Fitting Repeat 4
# weights: 507
initial value 102.300459
iter 10 value 93.592306
iter 20 value 93.585080
iter 30 value 93.549669
iter 40 value 90.987132
iter 50 value 89.199787
iter 60 value 89.099899
iter 70 value 89.087616
final value 89.087551
converged
Fitting Repeat 5
# weights: 507
initial value 100.368601
iter 10 value 93.590418
iter 20 value 92.467451
iter 30 value 86.694485
iter 40 value 84.898303
iter 50 value 84.548729
iter 60 value 84.364438
iter 70 value 84.103886
iter 80 value 84.046056
iter 90 value 83.611704
iter 100 value 83.396798
final value 83.396798
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.319673
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 99.467659
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.562023
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.660779
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 110.973258
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 102.193794
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 99.475003
final value 94.467391
converged
Fitting Repeat 3
# weights: 305
initial value 103.324439
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 94.322898
iter 10 value 84.390918
iter 20 value 84.032778
final value 84.032765
converged
Fitting Repeat 5
# weights: 305
initial value 107.012694
iter 10 value 94.016231
iter 20 value 91.019193
final value 91.014706
converged
Fitting Repeat 1
# weights: 507
initial value 111.158773
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 114.350740
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 95.113858
iter 10 value 87.038835
iter 20 value 86.589919
iter 30 value 86.587623
iter 40 value 86.439505
final value 86.439490
converged
Fitting Repeat 4
# weights: 507
initial value 125.118143
final value 94.467391
converged
Fitting Repeat 5
# weights: 507
initial value 102.018105
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 98.087930
iter 10 value 94.488572
final value 94.488553
converged
Fitting Repeat 2
# weights: 103
initial value 98.283992
iter 10 value 94.400564
iter 20 value 87.976507
iter 30 value 85.794813
iter 40 value 84.580866
iter 50 value 84.421553
iter 60 value 84.405049
iter 70 value 84.265183
iter 80 value 84.245931
final value 84.245602
converged
Fitting Repeat 3
# weights: 103
initial value 100.980900
iter 10 value 94.468788
iter 20 value 88.082134
iter 30 value 83.571978
iter 40 value 83.218825
iter 50 value 83.023610
iter 60 value 82.897637
iter 70 value 82.619342
iter 80 value 82.479583
iter 90 value 82.465835
iter 100 value 82.445055
final value 82.445055
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.657343
iter 10 value 94.360072
iter 20 value 94.242488
iter 30 value 94.240905
final value 94.240837
converged
Fitting Repeat 5
# weights: 103
initial value 100.721843
iter 10 value 94.493027
iter 20 value 91.420160
iter 30 value 88.232967
iter 40 value 87.645034
iter 50 value 86.795904
iter 60 value 84.618173
iter 70 value 84.437902
iter 80 value 84.311495
iter 90 value 84.284071
final value 84.283800
converged
Fitting Repeat 1
# weights: 305
initial value 124.915463
iter 10 value 93.748933
iter 20 value 85.538834
iter 30 value 85.420962
iter 40 value 85.349469
iter 50 value 84.557404
iter 60 value 84.333427
iter 70 value 83.493369
iter 80 value 82.033440
iter 90 value 81.595417
iter 100 value 81.349441
final value 81.349441
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.282275
iter 10 value 94.526581
iter 20 value 88.787165
iter 30 value 87.132956
iter 40 value 85.807008
iter 50 value 85.534596
iter 60 value 85.013938
iter 70 value 83.625078
iter 80 value 83.426205
iter 90 value 83.381867
iter 100 value 83.348345
final value 83.348345
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.967477
iter 10 value 94.502456
iter 20 value 93.117257
iter 30 value 84.986779
iter 40 value 83.413235
iter 50 value 82.529454
iter 60 value 81.964786
iter 70 value 81.731615
iter 80 value 81.612203
iter 90 value 81.238197
iter 100 value 80.605280
final value 80.605280
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.974594
iter 10 value 94.509275
iter 20 value 94.470919
iter 30 value 88.391497
iter 40 value 87.869608
iter 50 value 86.148775
iter 60 value 83.103535
iter 70 value 81.566109
iter 80 value 81.468904
iter 90 value 81.253206
iter 100 value 80.698162
final value 80.698162
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.599956
iter 10 value 88.779998
iter 20 value 87.485274
iter 30 value 85.955216
iter 40 value 85.633365
iter 50 value 84.042658
iter 60 value 81.921894
iter 70 value 81.600775
iter 80 value 81.360688
iter 90 value 81.335707
iter 100 value 81.124251
final value 81.124251
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.797351
iter 10 value 94.680599
iter 20 value 88.473326
iter 30 value 86.843680
iter 40 value 85.164761
iter 50 value 82.387470
iter 60 value 81.705832
iter 70 value 81.467639
iter 80 value 81.336754
iter 90 value 81.094370
iter 100 value 80.944227
final value 80.944227
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.690563
iter 10 value 92.066298
iter 20 value 89.017486
iter 30 value 88.452367
iter 40 value 85.928782
iter 50 value 82.640512
iter 60 value 81.348610
iter 70 value 80.660070
iter 80 value 80.481165
iter 90 value 80.347344
iter 100 value 80.276098
final value 80.276098
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.681389
iter 10 value 94.505766
iter 20 value 88.411558
iter 30 value 86.910532
iter 40 value 85.119712
iter 50 value 83.383371
iter 60 value 81.985958
iter 70 value 81.472596
iter 80 value 81.122390
iter 90 value 80.910104
iter 100 value 80.602217
final value 80.602217
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 122.164813
iter 10 value 96.430601
iter 20 value 91.167445
iter 30 value 87.206646
iter 40 value 86.656598
iter 50 value 86.431689
iter 60 value 84.410996
iter 70 value 81.909072
iter 80 value 81.772046
iter 90 value 81.540257
iter 100 value 80.896795
final value 80.896795
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 102.413353
iter 10 value 94.460884
iter 20 value 88.056250
iter 30 value 86.515806
iter 40 value 84.957165
iter 50 value 82.722607
iter 60 value 81.817432
iter 70 value 81.437405
iter 80 value 81.315875
iter 90 value 81.015566
iter 100 value 80.465289
final value 80.465289
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.838731
final value 94.486044
converged
Fitting Repeat 2
# weights: 103
initial value 102.729584
final value 94.485778
converged
Fitting Repeat 3
# weights: 103
initial value 95.370241
final value 94.485875
converged
Fitting Repeat 4
# weights: 103
initial value 104.301958
final value 94.485890
converged
Fitting Repeat 5
# weights: 103
initial value 102.468990
final value 94.485888
converged
Fitting Repeat 1
# weights: 305
initial value 95.803246
iter 10 value 93.706992
iter 20 value 93.682512
iter 30 value 91.557334
iter 40 value 90.211683
iter 50 value 90.060662
iter 60 value 90.060440
iter 70 value 90.059754
iter 80 value 90.059336
iter 90 value 90.056706
iter 100 value 89.996291
final value 89.996291
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 118.208988
iter 10 value 94.489036
iter 20 value 94.484574
iter 30 value 94.328231
final value 94.312500
converged
Fitting Repeat 3
# weights: 305
initial value 100.280682
iter 10 value 94.489068
iter 20 value 94.475990
iter 30 value 93.603537
iter 40 value 84.838693
iter 50 value 83.890584
iter 60 value 83.258507
iter 70 value 82.493733
iter 80 value 80.180846
iter 90 value 79.901182
iter 100 value 79.893842
final value 79.893842
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.319321
iter 10 value 92.039992
iter 20 value 89.618186
iter 30 value 89.605466
iter 40 value 87.769410
iter 50 value 87.665205
iter 60 value 87.664990
iter 70 value 86.737343
iter 80 value 86.730206
iter 90 value 86.730017
final value 86.729420
converged
Fitting Repeat 5
# weights: 305
initial value 112.849593
iter 10 value 93.500232
iter 20 value 93.434095
iter 30 value 93.107995
final value 93.103955
converged
Fitting Repeat 1
# weights: 507
initial value 107.158463
iter 10 value 94.475883
iter 20 value 94.230548
iter 30 value 94.127740
iter 40 value 93.549143
iter 50 value 92.706180
iter 60 value 86.040820
iter 70 value 84.003753
iter 80 value 84.002000
iter 90 value 83.999575
iter 100 value 83.828731
final value 83.828731
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 96.569454
iter 10 value 94.492193
iter 20 value 94.434476
iter 30 value 89.856480
iter 40 value 89.508055
iter 50 value 89.506944
iter 60 value 89.506785
final value 89.506762
converged
Fitting Repeat 3
# weights: 507
initial value 97.544134
iter 10 value 94.492259
iter 20 value 94.477472
iter 30 value 89.337347
iter 40 value 88.859621
final value 88.859042
converged
Fitting Repeat 4
# weights: 507
initial value 101.911584
iter 10 value 94.475583
iter 20 value 94.468303
iter 30 value 94.467537
iter 40 value 94.260449
iter 50 value 94.054727
iter 60 value 93.995633
iter 70 value 93.994416
final value 93.994398
converged
Fitting Repeat 5
# weights: 507
initial value 108.920179
iter 10 value 94.492387
iter 20 value 94.484318
iter 30 value 93.732543
iter 40 value 87.503982
iter 50 value 87.159554
iter 50 value 87.159554
final value 87.159554
converged
Fitting Repeat 1
# weights: 103
initial value 95.660118
final value 93.988095
converged
Fitting Repeat 2
# weights: 103
initial value 100.932235
final value 93.988096
converged
Fitting Repeat 3
# weights: 103
initial value 100.267763
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 96.377063
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 98.111436
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 95.113851
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 116.993876
iter 10 value 94.052910
iter 10 value 94.052910
iter 10 value 94.052910
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 103.839920
iter 10 value 90.302918
iter 20 value 84.107244
iter 30 value 83.945987
iter 40 value 83.945056
iter 50 value 83.943724
iter 60 value 83.941473
iter 70 value 83.935601
iter 80 value 83.917301
iter 90 value 83.809891
iter 100 value 81.077474
final value 81.077474
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.961524
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 95.177203
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 99.223724
final value 94.032967
converged
Fitting Repeat 2
# weights: 507
initial value 97.278385
iter 10 value 93.604520
iter 10 value 93.604520
iter 10 value 93.604520
final value 93.604520
converged
Fitting Repeat 3
# weights: 507
initial value 106.113533
final value 94.032967
converged
Fitting Repeat 4
# weights: 507
initial value 113.863206
final value 93.604520
converged
Fitting Repeat 5
# weights: 507
initial value 106.304715
final value 94.032967
converged
Fitting Repeat 1
# weights: 103
initial value 102.447159
iter 10 value 94.054973
iter 20 value 93.871262
iter 30 value 92.828134
iter 40 value 92.435494
iter 50 value 84.858872
iter 60 value 82.102718
iter 70 value 81.528344
iter 80 value 81.429306
iter 90 value 81.423854
final value 81.421167
converged
Fitting Repeat 2
# weights: 103
initial value 109.427468
iter 10 value 90.302922
iter 20 value 86.918850
iter 30 value 84.381285
iter 40 value 82.267292
iter 50 value 81.598785
iter 60 value 81.486399
iter 70 value 80.934343
iter 80 value 80.873793
final value 80.873645
converged
Fitting Repeat 3
# weights: 103
initial value 101.543568
iter 10 value 94.062384
iter 20 value 94.056779
iter 30 value 93.735249
iter 40 value 91.657529
iter 50 value 84.140429
iter 60 value 81.012027
iter 70 value 80.783325
iter 80 value 79.983890
iter 90 value 79.600061
iter 100 value 79.446990
final value 79.446990
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.737759
iter 10 value 89.157902
iter 20 value 83.837549
iter 30 value 83.328636
iter 40 value 83.230673
iter 50 value 82.036361
iter 60 value 82.008109
final value 82.008025
converged
Fitting Repeat 5
# weights: 103
initial value 110.663551
iter 10 value 94.071948
iter 20 value 94.043099
iter 30 value 89.416810
iter 40 value 84.285330
iter 50 value 83.358974
iter 60 value 82.120065
iter 70 value 81.439908
iter 80 value 81.421276
final value 81.421167
converged
Fitting Repeat 1
# weights: 305
initial value 109.642818
iter 10 value 94.064650
iter 20 value 86.711929
iter 30 value 83.704038
iter 40 value 83.526065
iter 50 value 82.663411
iter 60 value 79.942801
iter 70 value 77.857615
iter 80 value 77.606816
iter 90 value 77.557573
iter 100 value 77.508934
final value 77.508934
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.916055
iter 10 value 94.012322
iter 20 value 87.357252
iter 30 value 85.605214
iter 40 value 84.432622
iter 50 value 84.399843
iter 60 value 84.215931
iter 70 value 83.908560
iter 80 value 79.561490
iter 90 value 79.087509
iter 100 value 78.665591
final value 78.665591
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 123.498506
iter 10 value 93.598120
iter 20 value 91.159556
iter 30 value 88.909956
iter 40 value 87.365154
iter 50 value 85.443114
iter 60 value 80.640502
iter 70 value 78.316656
iter 80 value 77.880753
iter 90 value 77.774722
iter 100 value 77.638156
final value 77.638156
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.058809
iter 10 value 94.186867
iter 20 value 89.027030
iter 30 value 88.149432
iter 40 value 87.805997
iter 50 value 87.495530
iter 60 value 85.944796
iter 70 value 81.232611
iter 80 value 78.638031
iter 90 value 77.307913
iter 100 value 76.800683
final value 76.800683
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.833893
iter 10 value 94.269054
iter 20 value 86.534733
iter 30 value 84.708371
iter 40 value 84.363489
iter 50 value 82.378059
iter 60 value 79.756651
iter 70 value 78.813338
iter 80 value 77.504721
iter 90 value 77.145198
iter 100 value 77.110043
final value 77.110043
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 115.101603
iter 10 value 94.032821
iter 20 value 86.339039
iter 30 value 85.642082
iter 40 value 84.070915
iter 50 value 83.849964
iter 60 value 82.134327
iter 70 value 81.462280
iter 80 value 81.152328
iter 90 value 79.201716
iter 100 value 77.687525
final value 77.687525
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 128.192440
iter 10 value 92.010554
iter 20 value 83.678056
iter 30 value 82.056281
iter 40 value 80.560397
iter 50 value 80.294337
iter 60 value 79.203853
iter 70 value 77.830905
iter 80 value 77.443500
iter 90 value 77.381347
iter 100 value 77.200785
final value 77.200785
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.957007
iter 10 value 93.771376
iter 20 value 92.975081
iter 30 value 85.842903
iter 40 value 81.486393
iter 50 value 79.288074
iter 60 value 77.781640
iter 70 value 77.217717
iter 80 value 77.148342
iter 90 value 77.109906
iter 100 value 77.082495
final value 77.082495
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.315865
iter 10 value 94.512540
iter 20 value 85.179278
iter 30 value 80.825320
iter 40 value 80.305801
iter 50 value 79.686544
iter 60 value 78.086630
iter 70 value 76.628568
iter 80 value 76.436452
iter 90 value 76.314564
iter 100 value 76.186494
final value 76.186494
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.750632
iter 10 value 94.032249
iter 20 value 92.535407
iter 30 value 84.716924
iter 40 value 81.223285
iter 50 value 80.556988
iter 60 value 78.746780
iter 70 value 77.838798
iter 80 value 77.343181
iter 90 value 76.899586
iter 100 value 76.773853
final value 76.773853
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.730621
final value 94.034652
converged
Fitting Repeat 2
# weights: 103
initial value 108.014038
iter 10 value 94.054666
iter 20 value 94.052935
final value 94.052922
converged
Fitting Repeat 3
# weights: 103
initial value 94.926040
final value 94.054487
converged
Fitting Repeat 4
# weights: 103
initial value 99.211646
iter 10 value 94.054684
iter 20 value 94.045981
final value 93.605411
converged
Fitting Repeat 5
# weights: 103
initial value 101.989458
iter 10 value 93.703976
iter 20 value 93.703595
iter 30 value 93.065498
iter 40 value 85.106919
final value 85.106911
converged
Fitting Repeat 1
# weights: 305
initial value 94.132561
iter 10 value 94.057272
iter 20 value 93.948147
iter 30 value 85.534116
iter 40 value 83.950229
iter 50 value 82.658139
iter 60 value 82.652609
iter 70 value 82.647756
iter 80 value 82.158218
iter 90 value 82.157474
iter 100 value 82.156990
final value 82.156990
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 96.724518
iter 10 value 94.038214
iter 20 value 94.033176
iter 30 value 93.504396
iter 40 value 84.669401
iter 50 value 84.662005
iter 60 value 82.126629
iter 70 value 81.215028
iter 80 value 80.921966
iter 90 value 80.921445
iter 100 value 80.920736
final value 80.920736
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.276576
iter 10 value 94.057322
iter 20 value 94.051387
iter 30 value 90.673552
iter 40 value 81.308469
iter 50 value 80.969275
final value 80.967480
converged
Fitting Repeat 4
# weights: 305
initial value 109.869019
iter 10 value 93.992814
iter 20 value 93.812576
iter 30 value 82.381526
iter 40 value 82.330769
final value 82.330523
converged
Fitting Repeat 5
# weights: 305
initial value 108.668612
iter 10 value 94.037954
iter 20 value 91.517733
iter 30 value 82.341975
iter 40 value 82.334092
iter 50 value 82.330390
iter 50 value 82.330389
iter 50 value 82.330389
final value 82.330389
converged
Fitting Repeat 1
# weights: 507
initial value 94.513175
iter 10 value 93.246287
iter 20 value 93.245597
iter 30 value 93.238620
iter 40 value 93.238195
iter 50 value 87.729435
iter 60 value 84.386958
iter 70 value 84.031359
iter 80 value 83.187499
iter 90 value 82.643849
iter 100 value 82.570354
final value 82.570354
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 101.871640
iter 10 value 94.060302
iter 20 value 90.514820
iter 30 value 83.740812
iter 40 value 83.688326
iter 50 value 83.687664
final value 83.686747
converged
Fitting Repeat 3
# weights: 507
initial value 96.421221
iter 10 value 94.058023
iter 20 value 93.556195
iter 30 value 85.254188
iter 40 value 84.880943
iter 50 value 84.840771
iter 60 value 84.837458
final value 84.837383
converged
Fitting Repeat 4
# weights: 507
initial value 102.641211
iter 10 value 94.041264
iter 20 value 93.644514
iter 30 value 93.542684
final value 93.541079
converged
Fitting Repeat 5
# weights: 507
initial value 128.037222
iter 10 value 94.019833
iter 20 value 93.976540
iter 30 value 93.971743
iter 40 value 93.836797
iter 50 value 93.832378
iter 60 value 93.830484
iter 70 value 93.061432
iter 80 value 93.060592
iter 90 value 93.054295
final value 93.053569
converged
Fitting Repeat 1
# weights: 305
initial value 139.489733
iter 10 value 117.892635
iter 20 value 117.890241
iter 30 value 107.695452
iter 40 value 107.542234
iter 50 value 106.334618
iter 60 value 104.439296
iter 70 value 104.429920
iter 80 value 103.894585
iter 90 value 103.243476
iter 100 value 103.238564
final value 103.238564
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 121.855464
iter 10 value 117.733120
iter 20 value 117.730182
final value 117.729475
converged
Fitting Repeat 3
# weights: 305
initial value 121.805824
iter 10 value 117.894646
iter 20 value 117.889826
iter 30 value 111.785672
iter 40 value 103.191780
iter 50 value 100.743231
iter 60 value 100.472983
iter 70 value 100.470187
iter 80 value 100.456963
final value 100.446646
converged
Fitting Repeat 4
# weights: 305
initial value 129.914682
iter 10 value 117.774536
iter 20 value 117.759048
iter 30 value 108.769479
iter 40 value 106.298198
iter 50 value 106.296390
final value 106.296281
converged
Fitting Repeat 5
# weights: 305
initial value 139.779891
iter 10 value 117.895156
iter 20 value 117.837191
iter 30 value 109.328423
iter 40 value 108.562860
iter 50 value 108.539583
iter 60 value 108.408408
final value 108.395105
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 -- Tue Mar 3 00:37:58 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
39.590 1.677 85.181
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.563 | 0.435 | 34.001 | |
| FreqInteractors | 0.447 | 0.027 | 0.474 | |
| calculateAAC | 0.030 | 0.001 | 0.030 | |
| calculateAutocor | 0.297 | 0.015 | 0.313 | |
| calculateCTDC | 0.073 | 0.000 | 0.074 | |
| calculateCTDD | 0.524 | 0.001 | 0.525 | |
| calculateCTDT | 0.194 | 0.010 | 0.203 | |
| calculateCTriad | 0.370 | 0.005 | 0.376 | |
| calculateDC | 0.085 | 0.001 | 0.087 | |
| calculateF | 0.314 | 0.000 | 0.315 | |
| calculateKSAAP | 0.104 | 0.000 | 0.104 | |
| calculateQD_Sm | 1.703 | 0.007 | 1.710 | |
| calculateTC | 1.494 | 0.025 | 1.518 | |
| calculateTC_Sm | 0.252 | 0.001 | 0.252 | |
| corr_plot | 34.783 | 0.444 | 35.318 | |
| enrichfindP | 0.529 | 0.041 | 11.933 | |
| enrichfind_hp | 0.051 | 0.001 | 0.795 | |
| enrichplot | 0.587 | 0.006 | 0.592 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.505 | 0.040 | 3.918 | |
| getHPI | 0.001 | 0.001 | 0.001 | |
| get_negativePPI | 0.003 | 0.000 | 0.003 | |
| get_positivePPI | 0.000 | 0.001 | 0.000 | |
| impute_missing_data | 0.002 | 0.000 | 0.002 | |
| plotPPI | 0.098 | 0.002 | 0.100 | |
| pred_ensembel | 13.057 | 0.558 | 12.338 | |
| var_imp | 33.390 | 0.723 | 34.114 | |