Matineh Rahmatbakhsh
| Snapshot Date: 2026-03-11 13:45 -0400 (Wed, 11 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 -0400 (Sun, 28 Dec 2025) |
| Back to Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-03-12 11:57 -0400 (Thu, 12 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: 2026-03-12 00:32:04 -0400 (Thu, 12 Mar 2026) |
| EndedAt: 2026-03-12 00:46:58 -0400 (Thu, 12 Mar 2026) |
| EllapsedTime: 894.0 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 34.623 0.534 35.168
var_imp 33.741 0.508 34.258
FSmethod 33.033 0.544 33.580
pred_ensembel 13.221 0.145 12.070
enrichfindP 0.541 0.031 9.764
* 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 110.440801
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.318208
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.311712
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 102.003197
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 101.744578
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 96.637567
final value 94.275362
converged
Fitting Repeat 2
# weights: 305
initial value 97.626580
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 96.843671
final value 94.484213
converged
Fitting Repeat 4
# weights: 305
initial value 94.662514
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 107.273124
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 101.337640
iter 10 value 94.045130
final value 94.029451
converged
Fitting Repeat 2
# weights: 507
initial value 107.304866
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 97.505094
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 113.624279
iter 10 value 94.209315
final value 94.209302
converged
Fitting Repeat 5
# weights: 507
initial value 97.286089
iter 10 value 93.535829
iter 20 value 90.568534
iter 30 value 85.637148
iter 40 value 85.627889
final value 85.627851
converged
Fitting Repeat 1
# weights: 103
initial value 101.262639
iter 10 value 94.488527
iter 20 value 94.486668
iter 30 value 94.102564
iter 40 value 92.630259
iter 50 value 90.535674
iter 60 value 89.461462
iter 70 value 84.033664
iter 80 value 82.935418
iter 90 value 82.910119
iter 100 value 82.904506
final value 82.904506
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 105.837461
iter 10 value 94.486774
iter 20 value 94.368005
iter 30 value 86.458395
iter 40 value 86.175986
iter 50 value 86.153786
final value 86.151962
converged
Fitting Repeat 3
# weights: 103
initial value 103.787370
iter 10 value 92.029664
iter 20 value 86.342231
iter 30 value 84.664646
iter 40 value 82.968466
iter 50 value 82.943961
iter 60 value 82.912864
iter 70 value 82.904677
final value 82.904481
converged
Fitting Repeat 4
# weights: 103
initial value 99.559324
iter 10 value 94.326274
iter 20 value 88.138411
iter 30 value 86.299214
iter 40 value 86.174011
iter 50 value 85.708410
iter 60 value 85.500125
iter 70 value 85.500054
final value 85.499541
converged
Fitting Repeat 5
# weights: 103
initial value 96.617590
iter 10 value 93.632762
iter 20 value 87.125633
iter 30 value 86.206644
iter 40 value 85.575996
iter 50 value 85.505207
iter 60 value 85.496587
iter 70 value 85.482533
final value 85.481935
converged
Fitting Repeat 1
# weights: 305
initial value 102.503303
iter 10 value 94.336321
iter 20 value 93.849006
iter 30 value 92.523679
iter 40 value 91.381492
iter 50 value 90.923685
iter 60 value 90.776955
iter 70 value 89.179217
iter 80 value 84.728999
iter 90 value 83.178914
iter 100 value 82.328031
final value 82.328031
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.802000
iter 10 value 94.953731
iter 20 value 94.325202
iter 30 value 91.274059
iter 40 value 85.360988
iter 50 value 85.060540
iter 60 value 84.649039
iter 70 value 84.524045
iter 80 value 84.506295
iter 90 value 84.237612
iter 100 value 83.384211
final value 83.384211
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.506275
iter 10 value 94.006827
iter 20 value 87.157696
iter 30 value 86.772716
iter 40 value 85.520459
iter 50 value 84.255238
iter 60 value 83.130421
iter 70 value 82.004354
iter 80 value 81.242333
iter 90 value 81.158667
iter 100 value 81.099590
final value 81.099590
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 120.483192
iter 10 value 95.487506
iter 20 value 87.182472
iter 30 value 83.012089
iter 40 value 81.859076
iter 50 value 81.402225
iter 60 value 81.285106
iter 70 value 81.186656
iter 80 value 81.180489
iter 90 value 81.160449
iter 100 value 81.104564
final value 81.104564
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.185686
iter 10 value 94.410611
iter 20 value 87.514358
iter 30 value 86.007034
iter 40 value 85.162423
iter 50 value 84.069729
iter 60 value 83.832945
iter 70 value 83.695287
iter 80 value 83.239589
iter 90 value 82.145940
iter 100 value 81.687723
final value 81.687723
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.989056
iter 10 value 91.033002
iter 20 value 84.034358
iter 30 value 83.044636
iter 40 value 82.460715
iter 50 value 82.078237
iter 60 value 81.728715
iter 70 value 81.510295
iter 80 value 81.468357
iter 90 value 81.354229
iter 100 value 81.321597
final value 81.321597
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 122.563890
iter 10 value 94.717652
iter 20 value 89.004376
iter 30 value 87.561115
iter 40 value 87.272318
iter 50 value 87.120362
iter 60 value 86.680043
iter 70 value 84.028443
iter 80 value 82.588474
iter 90 value 82.257380
iter 100 value 81.944489
final value 81.944489
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.817006
iter 10 value 91.361113
iter 20 value 85.929760
iter 30 value 84.532834
iter 40 value 83.636514
iter 50 value 83.469408
iter 60 value 82.787931
iter 70 value 82.124613
iter 80 value 81.952344
iter 90 value 81.887915
iter 100 value 81.609626
final value 81.609626
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.910995
iter 10 value 94.957880
iter 20 value 94.418037
iter 30 value 90.947982
iter 40 value 88.221660
iter 50 value 87.536954
iter 60 value 87.208806
iter 70 value 85.885839
iter 80 value 83.765924
iter 90 value 82.277864
iter 100 value 81.908064
final value 81.908064
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.898561
iter 10 value 94.407281
iter 20 value 88.401164
iter 30 value 86.261575
iter 40 value 85.946501
iter 50 value 85.093204
iter 60 value 84.272763
iter 70 value 83.443693
iter 80 value 82.907146
iter 90 value 82.373267
iter 100 value 82.063389
final value 82.063389
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 108.452699
final value 94.485907
converged
Fitting Repeat 2
# weights: 103
initial value 95.782546
final value 94.486020
converged
Fitting Repeat 3
# weights: 103
initial value 115.986172
final value 94.430218
converged
Fitting Repeat 4
# weights: 103
initial value 100.296672
final value 94.485757
converged
Fitting Repeat 5
# weights: 103
initial value 96.529364
final value 94.485675
converged
Fitting Repeat 1
# weights: 305
initial value 96.424169
iter 10 value 94.280183
iter 20 value 93.964437
iter 30 value 85.708374
iter 40 value 85.706796
final value 85.705763
converged
Fitting Repeat 2
# weights: 305
initial value 105.655497
iter 10 value 94.266328
iter 20 value 94.214433
iter 30 value 94.211802
final value 94.210990
converged
Fitting Repeat 3
# weights: 305
initial value 98.486189
iter 10 value 94.488375
iter 20 value 88.516066
iter 30 value 87.317824
iter 40 value 86.342205
iter 50 value 86.131590
iter 60 value 86.121304
iter 70 value 86.118571
final value 86.118429
converged
Fitting Repeat 4
# weights: 305
initial value 97.478263
iter 10 value 94.280434
iter 20 value 92.718919
iter 30 value 83.991143
iter 40 value 82.628461
iter 50 value 81.441188
iter 60 value 81.412094
iter 70 value 81.382800
final value 81.382796
converged
Fitting Repeat 5
# weights: 305
initial value 96.167936
iter 10 value 94.280528
iter 20 value 94.275474
iter 30 value 88.020930
iter 40 value 86.637158
iter 50 value 85.002545
iter 60 value 84.884895
iter 70 value 84.879107
iter 80 value 84.874625
iter 90 value 84.874461
final value 84.874454
converged
Fitting Repeat 1
# weights: 507
initial value 136.102911
iter 10 value 94.488856
iter 20 value 94.484259
iter 30 value 93.873016
iter 40 value 86.569480
iter 50 value 84.301037
iter 60 value 82.720769
iter 70 value 81.301264
iter 80 value 81.285756
final value 81.285464
converged
Fitting Repeat 2
# weights: 507
initial value 96.671795
iter 10 value 94.284057
iter 20 value 94.277274
iter 30 value 94.082604
iter 40 value 93.712304
iter 50 value 91.735717
iter 60 value 91.105135
iter 70 value 91.103473
iter 80 value 84.830730
iter 90 value 83.354344
iter 100 value 82.793388
final value 82.793388
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 97.895105
iter 10 value 94.437769
iter 20 value 94.434617
iter 30 value 94.321849
iter 40 value 94.265063
iter 50 value 94.061490
final value 94.057394
converged
Fitting Repeat 4
# weights: 507
initial value 100.591193
iter 10 value 94.272843
iter 20 value 94.207450
iter 30 value 85.318004
iter 40 value 83.371958
iter 50 value 82.140664
iter 60 value 82.137394
iter 70 value 81.975979
iter 80 value 81.854469
iter 90 value 81.293582
iter 100 value 80.904251
final value 80.904251
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 97.806854
iter 10 value 94.491788
final value 94.484454
converged
Fitting Repeat 1
# weights: 103
initial value 110.662124
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 105.453318
final value 94.032967
converged
Fitting Repeat 3
# weights: 103
initial value 97.809880
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 101.235065
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.423642
iter 10 value 85.267052
final value 85.264389
converged
Fitting Repeat 1
# weights: 305
initial value 102.316983
iter 10 value 93.714286
iter 10 value 93.714286
iter 10 value 93.714286
final value 93.714286
converged
Fitting Repeat 2
# weights: 305
initial value 97.524940
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 98.909583
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 109.385946
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 96.821819
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 98.473014
iter 10 value 92.804893
iter 20 value 92.621509
iter 30 value 92.347786
iter 40 value 92.338185
iter 50 value 92.249910
final value 92.249640
converged
Fitting Repeat 2
# weights: 507
initial value 98.048821
iter 10 value 93.911744
iter 20 value 93.651974
iter 30 value 93.620402
final value 93.620371
converged
Fitting Repeat 3
# weights: 507
initial value 101.650285
final value 94.032967
converged
Fitting Repeat 4
# weights: 507
initial value 103.271227
iter 10 value 94.032974
final value 94.032967
converged
Fitting Repeat 5
# weights: 507
initial value 100.170518
iter 10 value 93.655105
final value 93.653870
converged
Fitting Repeat 1
# weights: 103
initial value 107.080704
iter 10 value 93.977331
iter 20 value 85.084934
iter 30 value 81.174441
iter 40 value 80.685496
iter 50 value 80.271732
iter 60 value 80.229593
iter 70 value 80.194528
iter 80 value 80.157069
final value 80.156977
converged
Fitting Repeat 2
# weights: 103
initial value 97.282381
iter 10 value 94.056312
iter 20 value 93.779862
iter 30 value 85.559427
iter 40 value 85.245566
iter 50 value 84.926834
iter 60 value 84.416491
iter 70 value 83.718304
iter 80 value 83.419208
iter 90 value 83.390045
final value 83.389996
converged
Fitting Repeat 3
# weights: 103
initial value 111.758198
iter 10 value 93.933322
iter 20 value 89.162059
iter 30 value 87.985230
iter 40 value 87.228591
iter 50 value 86.083481
iter 60 value 84.269336
iter 70 value 80.629586
iter 80 value 80.587491
iter 90 value 80.579087
iter 100 value 80.576347
final value 80.576347
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 99.408186
iter 10 value 94.055720
iter 20 value 82.196119
iter 30 value 81.593185
iter 40 value 81.503258
iter 50 value 81.370537
iter 60 value 80.425336
iter 70 value 80.194405
iter 80 value 80.169015
iter 90 value 80.157118
final value 80.156977
converged
Fitting Repeat 5
# weights: 103
initial value 95.643382
iter 10 value 93.802248
iter 20 value 93.726693
iter 30 value 92.335985
iter 40 value 84.316275
iter 50 value 81.315787
iter 60 value 80.495201
iter 70 value 80.352170
iter 80 value 80.179163
iter 90 value 80.163456
iter 100 value 80.156986
final value 80.156986
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 115.135360
iter 10 value 94.050209
iter 20 value 84.896702
iter 30 value 84.408902
iter 40 value 84.140952
iter 50 value 82.169089
iter 60 value 81.493758
iter 70 value 80.731389
iter 80 value 80.476399
iter 90 value 80.365511
iter 100 value 80.342569
final value 80.342569
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.862983
iter 10 value 93.895368
iter 20 value 90.465013
iter 30 value 86.799870
iter 40 value 84.841393
iter 50 value 81.539341
iter 60 value 80.404113
iter 70 value 80.018532
iter 80 value 79.491107
iter 90 value 79.253643
iter 100 value 78.755802
final value 78.755802
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 116.091970
iter 10 value 94.061535
iter 20 value 92.321908
iter 30 value 86.741509
iter 40 value 82.625387
iter 50 value 81.157457
iter 60 value 80.999867
iter 70 value 79.388499
iter 80 value 79.156177
iter 90 value 79.064619
iter 100 value 79.009258
final value 79.009258
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.852774
iter 10 value 93.987624
iter 20 value 90.822154
iter 30 value 82.002297
iter 40 value 80.632586
iter 50 value 80.497471
iter 60 value 80.456100
iter 70 value 80.430499
iter 80 value 80.363810
iter 90 value 80.343750
iter 100 value 80.026908
final value 80.026908
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.947631
iter 10 value 94.326994
iter 20 value 84.532388
iter 30 value 81.132762
iter 40 value 80.743316
iter 50 value 80.081478
iter 60 value 79.747949
iter 70 value 79.611376
iter 80 value 79.275389
iter 90 value 79.144195
iter 100 value 79.140426
final value 79.140426
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.950107
iter 10 value 95.453634
iter 20 value 85.982545
iter 30 value 81.909604
iter 40 value 80.905410
iter 50 value 79.729968
iter 60 value 79.153460
iter 70 value 78.158676
iter 80 value 77.730771
iter 90 value 77.613342
iter 100 value 77.417034
final value 77.417034
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 135.926788
iter 10 value 94.063262
iter 20 value 92.803548
iter 30 value 92.533090
iter 40 value 81.332339
iter 50 value 80.996691
iter 60 value 79.536415
iter 70 value 78.810516
iter 80 value 78.652209
iter 90 value 78.348020
iter 100 value 78.293930
final value 78.293930
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 102.250932
iter 10 value 94.372374
iter 20 value 91.726755
iter 30 value 84.965786
iter 40 value 82.409143
iter 50 value 79.419061
iter 60 value 78.454790
iter 70 value 77.863773
iter 80 value 77.675635
iter 90 value 77.568097
iter 100 value 77.336969
final value 77.336969
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.828834
iter 10 value 93.621844
iter 20 value 91.423320
iter 30 value 83.628650
iter 40 value 80.730508
iter 50 value 80.309219
iter 60 value 80.215772
iter 70 value 79.925956
iter 80 value 79.274094
iter 90 value 78.346045
iter 100 value 78.001590
final value 78.001590
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 100.993572
iter 10 value 84.022769
iter 20 value 81.744546
iter 30 value 80.997327
iter 40 value 80.904109
iter 50 value 80.399207
iter 60 value 79.143388
iter 70 value 78.203673
iter 80 value 78.032771
iter 90 value 77.668498
iter 100 value 77.449821
final value 77.449821
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.076357
final value 94.054401
converged
Fitting Repeat 2
# weights: 103
initial value 101.997565
final value 94.054447
converged
Fitting Repeat 3
# weights: 103
initial value 115.284493
final value 94.054628
converged
Fitting Repeat 4
# weights: 103
initial value 96.315659
final value 94.054455
converged
Fitting Repeat 5
# weights: 103
initial value 103.635618
final value 94.054571
converged
Fitting Repeat 1
# weights: 305
initial value 99.354094
iter 10 value 94.057245
iter 20 value 93.947946
iter 30 value 93.664189
iter 40 value 93.361557
iter 50 value 83.781243
iter 60 value 83.562371
iter 70 value 83.562138
iter 80 value 83.562114
final value 83.562111
converged
Fitting Repeat 2
# weights: 305
initial value 99.193465
iter 10 value 94.057198
final value 94.052918
converged
Fitting Repeat 3
# weights: 305
initial value 98.373890
iter 10 value 94.057567
iter 20 value 94.053005
iter 30 value 93.479350
final value 84.784497
converged
Fitting Repeat 4
# weights: 305
initial value 103.623327
iter 10 value 94.038269
iter 20 value 92.106600
iter 30 value 88.554267
iter 40 value 84.550117
iter 50 value 84.475895
iter 60 value 84.468265
final value 84.468216
converged
Fitting Repeat 5
# weights: 305
initial value 104.203461
iter 10 value 93.704330
iter 20 value 93.088006
iter 30 value 93.064468
final value 93.053604
converged
Fitting Repeat 1
# weights: 507
initial value 97.730877
iter 10 value 94.042110
iter 20 value 93.311853
iter 30 value 88.236754
iter 40 value 88.211993
iter 50 value 85.645240
iter 60 value 84.935942
iter 70 value 84.930592
iter 80 value 84.929684
iter 90 value 84.928340
iter 100 value 83.585159
final value 83.585159
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 96.448917
iter 10 value 93.573378
iter 20 value 93.559609
iter 30 value 93.453152
iter 40 value 93.372188
iter 50 value 93.353541
iter 60 value 93.351107
final value 93.351059
converged
Fitting Repeat 3
# weights: 507
initial value 99.738454
iter 10 value 94.040795
iter 20 value 94.034665
iter 30 value 92.226911
iter 40 value 82.932568
iter 50 value 80.965246
iter 60 value 80.575360
iter 70 value 79.885534
iter 80 value 79.496391
iter 90 value 77.899709
iter 100 value 76.719375
final value 76.719375
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.069242
iter 10 value 93.674467
iter 20 value 93.668332
iter 30 value 91.877519
iter 40 value 86.403480
iter 50 value 80.051215
iter 60 value 77.912525
iter 70 value 76.427450
iter 80 value 76.030664
iter 90 value 75.928019
iter 100 value 75.917202
final value 75.917202
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 108.090638
iter 10 value 94.041507
iter 20 value 93.996510
iter 30 value 85.430149
iter 40 value 84.136552
iter 50 value 82.255325
final value 81.280517
converged
Fitting Repeat 1
# weights: 103
initial value 95.513132
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.914992
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.016217
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.853632
iter 10 value 94.049149
final value 94.026542
converged
Fitting Repeat 5
# weights: 103
initial value 97.456585
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.707754
final value 94.026542
converged
Fitting Repeat 2
# weights: 305
initial value 99.693830
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 110.305619
iter 10 value 94.026542
iter 10 value 94.026542
iter 10 value 94.026542
final value 94.026542
converged
Fitting Repeat 4
# weights: 305
initial value 96.053826
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 99.767115
final value 94.026542
converged
Fitting Repeat 1
# weights: 507
initial value 103.443516
final value 93.788077
converged
Fitting Repeat 2
# weights: 507
initial value 100.669625
final value 93.974641
converged
Fitting Repeat 3
# weights: 507
initial value 99.718684
iter 10 value 94.470042
iter 20 value 94.026542
iter 20 value 94.026542
iter 20 value 94.026542
final value 94.026542
converged
Fitting Repeat 4
# weights: 507
initial value 112.713629
iter 10 value 93.366836
iter 20 value 84.536445
iter 30 value 84.282180
iter 40 value 84.280655
final value 84.280584
converged
Fitting Repeat 5
# weights: 507
initial value 99.884252
iter 10 value 92.664075
iter 10 value 92.664074
iter 10 value 92.664074
final value 92.664074
converged
Fitting Repeat 1
# weights: 103
initial value 97.360974
iter 10 value 94.487388
iter 20 value 86.010271
iter 30 value 85.005888
iter 40 value 84.878680
iter 50 value 84.825783
final value 84.822896
converged
Fitting Repeat 2
# weights: 103
initial value 102.441689
iter 10 value 94.356055
iter 20 value 90.842482
iter 30 value 85.602559
iter 40 value 83.896977
iter 50 value 82.575566
iter 60 value 81.733025
iter 70 value 81.581144
iter 80 value 81.547478
iter 90 value 81.476048
iter 100 value 81.472677
final value 81.472677
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 107.239356
iter 10 value 94.249529
iter 20 value 86.348656
iter 30 value 85.860053
iter 40 value 85.313298
iter 50 value 84.301378
iter 60 value 84.239905
iter 70 value 84.229556
final value 84.229515
converged
Fitting Repeat 4
# weights: 103
initial value 102.143996
iter 10 value 94.490007
iter 20 value 89.289156
iter 30 value 86.912514
iter 40 value 85.722450
iter 50 value 85.219814
iter 60 value 84.844369
iter 70 value 84.822981
final value 84.822896
converged
Fitting Repeat 5
# weights: 103
initial value 96.156603
iter 10 value 93.921123
iter 20 value 91.953837
iter 30 value 86.536689
iter 40 value 85.231959
iter 50 value 84.236412
iter 60 value 84.229527
final value 84.229515
converged
Fitting Repeat 1
# weights: 305
initial value 100.213211
iter 10 value 93.878463
iter 20 value 92.552638
iter 30 value 88.384167
iter 40 value 88.081848
iter 50 value 87.637504
iter 60 value 85.243935
iter 70 value 83.911748
iter 80 value 83.401007
iter 90 value 83.159390
iter 100 value 81.799800
final value 81.799800
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 136.375545
iter 10 value 94.453540
iter 20 value 86.011154
iter 30 value 84.282108
iter 40 value 82.676437
iter 50 value 81.715033
iter 60 value 81.530812
iter 70 value 81.020323
iter 80 value 80.815213
iter 90 value 80.622882
iter 100 value 80.478106
final value 80.478106
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.751413
iter 10 value 94.456141
iter 20 value 86.807053
iter 30 value 85.079101
iter 40 value 83.546059
iter 50 value 82.192744
iter 60 value 81.346056
iter 70 value 81.136749
iter 80 value 80.756865
iter 90 value 80.257999
iter 100 value 79.953088
final value 79.953088
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.170557
iter 10 value 94.545533
iter 20 value 93.772745
iter 30 value 93.662802
iter 40 value 92.765088
iter 50 value 85.928288
iter 60 value 84.580959
iter 70 value 83.337658
iter 80 value 81.390630
iter 90 value 80.799404
iter 100 value 80.653008
final value 80.653008
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.731113
iter 10 value 94.587189
iter 20 value 88.029326
iter 30 value 85.507074
iter 40 value 84.884847
iter 50 value 83.157622
iter 60 value 81.336947
iter 70 value 80.526777
iter 80 value 80.269923
iter 90 value 80.219732
iter 100 value 80.206894
final value 80.206894
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.136617
iter 10 value 94.600257
iter 20 value 86.643109
iter 30 value 86.453072
iter 40 value 83.812067
iter 50 value 82.771846
iter 60 value 82.374312
iter 70 value 81.891939
iter 80 value 81.820994
iter 90 value 81.178425
iter 100 value 80.929483
final value 80.929483
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.877089
iter 10 value 94.607327
iter 20 value 92.299901
iter 30 value 87.132060
iter 40 value 86.031789
iter 50 value 85.500004
iter 60 value 82.858192
iter 70 value 81.584836
iter 80 value 81.125885
iter 90 value 80.834383
iter 100 value 80.637897
final value 80.637897
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.398757
iter 10 value 94.131706
iter 20 value 84.251636
iter 30 value 83.387655
iter 40 value 83.015813
iter 50 value 82.524842
iter 60 value 81.207350
iter 70 value 80.930782
iter 80 value 80.905465
iter 90 value 80.809462
iter 100 value 80.714291
final value 80.714291
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.015779
iter 10 value 94.005085
iter 20 value 87.427021
iter 30 value 83.038408
iter 40 value 81.557430
iter 50 value 80.935577
iter 60 value 80.286509
iter 70 value 80.034145
iter 80 value 79.979139
iter 90 value 79.811527
iter 100 value 79.596088
final value 79.596088
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.919923
iter 10 value 94.763175
iter 20 value 93.181248
iter 30 value 90.542669
iter 40 value 87.528036
iter 50 value 86.927683
iter 60 value 86.615498
iter 70 value 86.213510
iter 80 value 83.795810
iter 90 value 82.695593
iter 100 value 81.848366
final value 81.848366
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.229726
final value 94.487720
converged
Fitting Repeat 2
# weights: 103
initial value 107.508216
final value 94.485865
converged
Fitting Repeat 3
# weights: 103
initial value 94.524345
final value 94.485884
converged
Fitting Repeat 4
# weights: 103
initial value 97.776727
final value 94.485780
converged
Fitting Repeat 5
# weights: 103
initial value 96.590765
final value 94.449640
converged
Fitting Repeat 1
# weights: 305
initial value 97.373107
iter 10 value 94.486731
iter 20 value 94.319822
final value 93.788331
converged
Fitting Repeat 2
# weights: 305
initial value 98.564665
iter 10 value 94.488998
iter 20 value 94.478319
iter 30 value 94.027163
final value 94.027157
converged
Fitting Repeat 3
# weights: 305
initial value 98.111722
iter 10 value 94.489598
iter 20 value 94.483958
iter 30 value 93.327904
final value 93.321924
converged
Fitting Repeat 4
# weights: 305
initial value 95.918035
iter 10 value 86.572360
iter 20 value 86.509161
iter 30 value 86.186258
iter 40 value 86.185486
iter 50 value 84.542479
iter 60 value 84.056999
iter 70 value 84.049232
iter 80 value 84.049176
iter 90 value 84.048041
final value 84.047908
converged
Fitting Repeat 5
# weights: 305
initial value 103.187355
iter 10 value 94.048493
iter 20 value 93.331967
iter 30 value 93.126953
iter 40 value 93.094420
iter 50 value 91.815318
iter 60 value 84.966098
iter 70 value 82.950945
iter 80 value 82.937695
iter 90 value 82.930569
iter 100 value 82.923289
final value 82.923289
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.506514
iter 10 value 91.884127
iter 20 value 84.216141
iter 30 value 84.114818
iter 40 value 83.942866
iter 50 value 83.898186
iter 60 value 83.896966
iter 70 value 83.893875
iter 80 value 83.893089
final value 83.893058
converged
Fitting Repeat 2
# weights: 507
initial value 104.836906
iter 10 value 93.983378
iter 20 value 93.980400
iter 30 value 93.275709
iter 40 value 93.255718
iter 50 value 93.255327
iter 50 value 93.255326
iter 50 value 93.255326
final value 93.255326
converged
Fitting Repeat 3
# weights: 507
initial value 108.640399
iter 10 value 93.178605
iter 20 value 93.146779
iter 30 value 93.134235
iter 40 value 93.085559
iter 50 value 93.083131
iter 60 value 93.081769
iter 70 value 93.080696
iter 80 value 92.555067
iter 90 value 84.551876
iter 100 value 83.807061
final value 83.807061
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.925598
iter 10 value 94.172961
iter 20 value 94.123613
final value 93.975290
converged
Fitting Repeat 5
# weights: 507
initial value 96.718294
iter 10 value 92.698580
iter 20 value 92.697751
iter 30 value 92.072270
iter 40 value 91.876279
iter 50 value 91.780558
iter 60 value 90.222254
iter 70 value 90.221851
iter 80 value 90.203995
iter 90 value 90.164432
iter 100 value 90.162099
final value 90.162099
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.913888
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 96.777935
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 97.377529
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 96.730073
iter 10 value 91.621321
iter 20 value 91.504781
iter 30 value 88.127319
iter 40 value 80.933073
iter 50 value 79.603062
iter 60 value 79.457561
iter 70 value 79.457349
final value 79.457348
converged
Fitting Repeat 5
# weights: 103
initial value 101.247491
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 124.072656
iter 10 value 93.836066
iter 10 value 93.836066
iter 10 value 93.836066
final value 93.836066
converged
Fitting Repeat 2
# weights: 305
initial value 97.719085
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 110.984828
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 96.102488
final value 93.836066
converged
Fitting Repeat 5
# weights: 305
initial value 100.248297
iter 10 value 93.399741
iter 20 value 93.399021
final value 93.399019
converged
Fitting Repeat 1
# weights: 507
initial value 98.869374
final value 94.052911
converged
Fitting Repeat 2
# weights: 507
initial value 94.391033
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 103.013083
iter 10 value 93.450285
final value 93.450268
converged
Fitting Repeat 4
# weights: 507
initial value 109.512549
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 104.056045
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 102.090481
iter 10 value 94.038374
iter 20 value 90.235256
iter 30 value 89.885603
iter 40 value 89.048799
iter 50 value 83.125798
iter 60 value 82.238172
iter 70 value 81.856793
iter 80 value 81.455652
iter 90 value 80.966909
iter 100 value 80.913759
final value 80.913759
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.032195
iter 10 value 94.042523
iter 20 value 93.778360
iter 30 value 86.139109
iter 40 value 85.500670
iter 50 value 84.101250
iter 60 value 83.100143
iter 70 value 82.857380
iter 80 value 82.782305
iter 90 value 82.777250
final value 82.777242
converged
Fitting Repeat 3
# weights: 103
initial value 119.129854
iter 10 value 94.054890
iter 10 value 94.054889
iter 20 value 90.305119
iter 30 value 83.659607
iter 40 value 82.965323
iter 50 value 82.839689
iter 60 value 82.777300
final value 82.777242
converged
Fitting Repeat 4
# weights: 103
initial value 109.908807
iter 10 value 94.019835
iter 20 value 87.211231
iter 30 value 86.002272
iter 40 value 84.870382
iter 50 value 84.245130
iter 60 value 82.015435
iter 70 value 81.159528
iter 80 value 81.107310
iter 90 value 80.872158
iter 100 value 80.696237
final value 80.696237
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 98.374104
iter 10 value 94.062111
iter 20 value 94.045055
iter 30 value 91.114722
iter 40 value 87.164714
iter 50 value 86.552521
iter 60 value 85.828854
iter 70 value 85.381260
iter 80 value 85.337197
iter 90 value 83.682557
iter 100 value 82.318488
final value 82.318488
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 104.093036
iter 10 value 94.002609
iter 20 value 87.890137
iter 30 value 86.389242
iter 40 value 86.245913
iter 50 value 86.005751
iter 60 value 85.539464
iter 70 value 85.067202
iter 80 value 84.300185
iter 90 value 82.032612
iter 100 value 81.039124
final value 81.039124
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.774607
iter 10 value 93.934664
iter 20 value 87.714516
iter 30 value 85.733085
iter 40 value 84.617250
iter 50 value 83.897220
iter 60 value 82.948680
iter 70 value 82.484489
iter 80 value 81.516616
iter 90 value 80.783180
iter 100 value 80.550809
final value 80.550809
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.480097
iter 10 value 94.373384
iter 20 value 94.083074
iter 30 value 93.711417
iter 40 value 93.130120
iter 50 value 86.612974
iter 60 value 85.640436
iter 70 value 83.842664
iter 80 value 82.888069
iter 90 value 82.746023
iter 100 value 82.396453
final value 82.396453
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 121.803513
iter 10 value 93.868357
iter 20 value 83.531964
iter 30 value 83.013719
iter 40 value 82.909830
iter 50 value 82.765184
iter 60 value 81.562353
iter 70 value 81.364461
iter 80 value 80.989208
iter 90 value 80.837504
iter 100 value 80.575494
final value 80.575494
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 110.317577
iter 10 value 93.877195
iter 20 value 91.817269
iter 30 value 88.804580
iter 40 value 85.444312
iter 50 value 83.129603
iter 60 value 82.769520
iter 70 value 81.424343
iter 80 value 80.691489
iter 90 value 80.478946
iter 100 value 80.168263
final value 80.168263
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 128.859979
iter 10 value 92.529713
iter 20 value 86.351560
iter 30 value 85.774159
iter 40 value 84.821832
iter 50 value 82.705448
iter 60 value 82.190341
iter 70 value 82.084626
iter 80 value 82.001955
iter 90 value 81.562804
iter 100 value 80.851434
final value 80.851434
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 119.820221
iter 10 value 94.005484
iter 20 value 84.966146
iter 30 value 83.477579
iter 40 value 80.626849
iter 50 value 80.025880
iter 60 value 79.483860
iter 70 value 79.097858
iter 80 value 78.964541
iter 90 value 78.872863
iter 100 value 78.783696
final value 78.783696
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.498265
iter 10 value 94.052005
iter 20 value 93.591486
iter 30 value 89.914102
iter 40 value 85.009971
iter 50 value 81.933500
iter 60 value 81.308580
iter 70 value 80.998803
iter 80 value 80.754246
iter 90 value 80.624050
iter 100 value 80.464537
final value 80.464537
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.472775
iter 10 value 94.215758
iter 20 value 87.526120
iter 30 value 85.591967
iter 40 value 85.453893
iter 50 value 85.043933
iter 60 value 83.061695
iter 70 value 82.237338
iter 80 value 81.415077
iter 90 value 81.030269
iter 100 value 80.324782
final value 80.324782
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 120.458986
iter 10 value 97.150816
iter 20 value 94.396999
iter 30 value 94.018558
iter 40 value 93.439244
iter 50 value 91.579703
iter 60 value 87.244221
iter 70 value 83.703773
iter 80 value 81.728237
iter 90 value 81.409706
iter 100 value 80.475149
final value 80.475149
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.371813
final value 94.054508
converged
Fitting Repeat 2
# weights: 103
initial value 99.589697
final value 94.054574
converged
Fitting Repeat 3
# weights: 103
initial value 114.580179
final value 94.054226
converged
Fitting Repeat 4
# weights: 103
initial value 99.627898
final value 94.054510
converged
Fitting Repeat 5
# weights: 103
initial value 95.214720
final value 94.054398
converged
Fitting Repeat 1
# weights: 305
initial value 102.731724
iter 10 value 94.057868
iter 20 value 93.857643
iter 30 value 91.133483
iter 40 value 87.758273
iter 50 value 86.468221
iter 60 value 85.531215
iter 70 value 85.415594
iter 80 value 84.956810
iter 90 value 84.859035
iter 100 value 84.815055
final value 84.815055
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.982978
iter 10 value 93.841141
iter 20 value 93.836447
final value 93.836277
converged
Fitting Repeat 3
# weights: 305
initial value 107.987073
iter 10 value 94.057584
iter 20 value 93.106908
iter 30 value 90.042403
iter 40 value 89.997442
iter 50 value 89.959876
iter 60 value 89.927424
iter 70 value 89.926974
iter 80 value 89.905257
iter 90 value 89.831175
iter 100 value 89.830238
final value 89.830238
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 96.782459
iter 10 value 93.841378
iter 20 value 93.838948
iter 30 value 84.266008
iter 40 value 83.675529
iter 50 value 83.346361
iter 60 value 83.338133
final value 83.338062
converged
Fitting Repeat 5
# weights: 305
initial value 98.797875
iter 10 value 94.058587
iter 20 value 94.053592
iter 20 value 94.053592
iter 20 value 94.053592
final value 94.053592
converged
Fitting Repeat 1
# weights: 507
initial value 96.019997
iter 10 value 89.536017
iter 20 value 86.311634
iter 30 value 86.231212
iter 40 value 83.181505
iter 50 value 83.015500
iter 60 value 82.631966
iter 70 value 82.439548
iter 80 value 82.439322
final value 82.439028
converged
Fitting Repeat 2
# weights: 507
initial value 108.256972
iter 10 value 92.041018
iter 20 value 85.267463
iter 30 value 82.673679
iter 40 value 79.556763
iter 50 value 79.481299
iter 60 value 79.478829
iter 70 value 79.473038
iter 70 value 79.473037
final value 79.473037
converged
Fitting Repeat 3
# weights: 507
initial value 96.597647
iter 10 value 93.690105
iter 20 value 88.061944
iter 30 value 82.918921
iter 40 value 82.465965
iter 50 value 82.335033
iter 60 value 80.510129
iter 70 value 79.959396
iter 80 value 79.912764
iter 90 value 79.531102
iter 100 value 79.494995
final value 79.494995
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 96.716655
iter 10 value 94.059679
iter 20 value 93.583239
iter 30 value 85.979779
iter 40 value 85.941979
final value 85.941973
converged
Fitting Repeat 5
# weights: 507
initial value 98.321304
iter 10 value 94.060297
iter 20 value 93.878597
final value 93.836350
converged
Fitting Repeat 1
# weights: 103
initial value 102.553787
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.800193
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 102.256874
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 100.849039
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 99.999990
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.357234
final value 94.147186
converged
Fitting Repeat 2
# weights: 305
initial value 101.154754
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 102.754566
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 94.938633
iter 10 value 94.275362
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 5
# weights: 305
initial value 105.849076
iter 10 value 94.467431
final value 94.467389
converged
Fitting Repeat 1
# weights: 507
initial value 99.455030
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 110.010287
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 105.736902
final value 94.467391
converged
Fitting Repeat 4
# weights: 507
initial value 99.231455
final value 94.467391
converged
Fitting Repeat 5
# weights: 507
initial value 104.741549
final value 94.467391
converged
Fitting Repeat 1
# weights: 103
initial value 96.910392
iter 10 value 94.484107
iter 20 value 91.560730
iter 30 value 88.849099
iter 40 value 87.369530
iter 50 value 86.827441
iter 60 value 86.566516
iter 70 value 86.384184
iter 80 value 84.049392
iter 90 value 83.988457
final value 83.988414
converged
Fitting Repeat 2
# weights: 103
initial value 104.431421
iter 10 value 94.485256
iter 20 value 92.734504
iter 30 value 88.796051
iter 40 value 84.800008
iter 50 value 83.675059
iter 60 value 82.787536
iter 70 value 82.243577
final value 82.229787
converged
Fitting Repeat 3
# weights: 103
initial value 97.802638
iter 10 value 94.488522
iter 20 value 86.825841
iter 30 value 84.547664
iter 40 value 83.883730
iter 50 value 82.980879
iter 60 value 81.652531
iter 70 value 81.592508
iter 80 value 81.521103
iter 90 value 81.450470
final value 81.437928
converged
Fitting Repeat 4
# weights: 103
initial value 122.911320
iter 10 value 94.360638
iter 20 value 91.087587
iter 30 value 90.615619
iter 40 value 88.049968
iter 50 value 84.925122
iter 60 value 84.583663
iter 70 value 84.380407
iter 80 value 82.757505
iter 90 value 82.468116
iter 100 value 82.451370
final value 82.451370
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 103.160166
iter 10 value 94.469372
iter 20 value 93.500475
iter 30 value 93.473848
iter 40 value 92.860942
iter 50 value 91.199402
iter 60 value 89.443891
iter 70 value 86.274646
iter 80 value 85.585572
iter 90 value 85.171597
iter 100 value 84.523380
final value 84.523380
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 106.208707
iter 10 value 94.379968
iter 20 value 85.929892
iter 30 value 81.981744
iter 40 value 81.698909
iter 50 value 81.274376
iter 60 value 80.694980
iter 70 value 80.396380
iter 80 value 80.257972
iter 90 value 80.118748
iter 100 value 80.062321
final value 80.062321
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.324863
iter 10 value 95.484156
iter 20 value 93.728621
iter 30 value 86.607874
iter 40 value 86.313130
iter 50 value 86.032729
iter 60 value 84.733707
iter 70 value 84.300980
iter 80 value 84.120304
iter 90 value 83.937188
iter 100 value 83.806875
final value 83.806875
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.435826
iter 10 value 94.296350
iter 20 value 84.767720
iter 30 value 84.511613
iter 40 value 83.907294
iter 50 value 82.063953
iter 60 value 80.769549
iter 70 value 80.460628
iter 80 value 80.268580
iter 90 value 80.190183
iter 100 value 80.086895
final value 80.086895
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 116.537465
iter 10 value 94.336619
iter 20 value 88.683829
iter 30 value 85.447677
iter 40 value 83.845391
iter 50 value 81.591997
iter 60 value 81.132562
iter 70 value 80.651639
iter 80 value 80.394951
iter 90 value 79.973163
iter 100 value 79.856819
final value 79.856819
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.748298
iter 10 value 94.676010
iter 20 value 94.396322
iter 30 value 92.892526
iter 40 value 90.908562
iter 50 value 89.148254
iter 60 value 85.464538
iter 70 value 83.330488
iter 80 value 81.924972
iter 90 value 81.000665
iter 100 value 80.639094
final value 80.639094
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.576644
iter 10 value 94.483854
iter 20 value 90.480752
iter 30 value 87.472856
iter 40 value 85.999432
iter 50 value 85.366967
iter 60 value 84.871488
iter 70 value 81.568906
iter 80 value 80.949691
iter 90 value 80.613034
iter 100 value 80.360970
final value 80.360970
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 121.815234
iter 10 value 94.299843
iter 20 value 85.755991
iter 30 value 84.806623
iter 40 value 83.196520
iter 50 value 82.211060
iter 60 value 82.090870
iter 70 value 80.918494
iter 80 value 80.459474
iter 90 value 80.003914
iter 100 value 79.863353
final value 79.863353
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.480711
iter 10 value 93.705010
iter 20 value 90.032042
iter 30 value 87.986367
iter 40 value 87.347462
iter 50 value 83.445788
iter 60 value 80.558267
iter 70 value 79.855291
iter 80 value 79.612292
iter 90 value 79.547809
iter 100 value 79.458282
final value 79.458282
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 129.116776
iter 10 value 94.481394
iter 20 value 89.716208
iter 30 value 88.078243
iter 40 value 86.293358
iter 50 value 85.704957
iter 60 value 84.988397
iter 70 value 84.880814
iter 80 value 84.678224
iter 90 value 84.073544
iter 100 value 82.247189
final value 82.247189
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.432132
iter 10 value 94.388254
iter 20 value 86.384919
iter 30 value 85.123504
iter 40 value 82.725898
iter 50 value 82.224909
iter 60 value 81.858151
iter 70 value 81.123859
iter 80 value 79.894568
iter 90 value 79.527700
iter 100 value 79.416764
final value 79.416764
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.301767
final value 94.485769
converged
Fitting Repeat 2
# weights: 103
initial value 99.677334
final value 94.486099
converged
Fitting Repeat 3
# weights: 103
initial value 94.889113
iter 10 value 93.413696
iter 20 value 93.411190
final value 92.670614
converged
Fitting Repeat 4
# weights: 103
initial value 107.087841
iter 10 value 94.485886
final value 94.485243
converged
Fitting Repeat 5
# weights: 103
initial value 99.185743
final value 94.485957
converged
Fitting Repeat 1
# weights: 305
initial value 100.091394
iter 10 value 94.499823
iter 20 value 93.309367
iter 30 value 90.731982
iter 40 value 90.608518
iter 50 value 90.600024
final value 90.597804
converged
Fitting Repeat 2
# weights: 305
initial value 117.341319
iter 10 value 94.489195
iter 20 value 94.447894
iter 30 value 87.491951
iter 40 value 85.354387
iter 50 value 82.245909
iter 60 value 82.244713
iter 70 value 82.240589
iter 80 value 82.240414
iter 90 value 82.239361
iter 100 value 81.545914
final value 81.545914
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 97.809258
iter 10 value 94.484578
iter 20 value 92.048774
iter 30 value 91.427458
iter 40 value 91.308399
final value 91.308391
converged
Fitting Repeat 4
# weights: 305
initial value 100.551047
iter 10 value 93.306283
iter 20 value 92.679760
iter 30 value 84.866248
iter 40 value 84.706934
iter 50 value 84.703694
final value 84.703074
converged
Fitting Repeat 5
# weights: 305
initial value 103.351251
iter 10 value 94.491499
iter 20 value 94.352010
iter 30 value 88.106483
iter 40 value 87.977665
iter 50 value 86.601010
iter 60 value 86.600567
iter 70 value 86.598747
iter 80 value 85.156008
iter 90 value 83.072752
iter 100 value 82.933804
final value 82.933804
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 98.246713
iter 10 value 94.430840
iter 20 value 94.423963
iter 30 value 94.014821
iter 40 value 85.417998
iter 50 value 85.417410
iter 60 value 85.386847
iter 70 value 85.183893
iter 80 value 85.165008
iter 90 value 85.152760
iter 100 value 84.851183
final value 84.851183
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 98.456013
iter 10 value 94.491908
iter 20 value 94.436836
iter 30 value 93.325317
iter 40 value 93.266252
iter 50 value 92.024818
iter 60 value 90.960319
iter 70 value 84.346310
iter 80 value 83.760149
iter 90 value 82.717615
iter 100 value 81.385472
final value 81.385472
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.290511
iter 10 value 94.490455
iter 20 value 94.421934
iter 30 value 88.399080
iter 40 value 85.978329
iter 50 value 83.471357
iter 60 value 81.244195
iter 70 value 81.106487
iter 80 value 81.022987
iter 90 value 79.768719
iter 100 value 79.359535
final value 79.359535
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.266329
iter 10 value 87.198637
iter 20 value 86.533626
iter 30 value 86.530181
iter 40 value 85.743414
iter 50 value 85.085886
iter 60 value 85.085311
iter 70 value 85.084806
iter 80 value 84.774346
iter 90 value 83.747681
iter 100 value 81.189994
final value 81.189994
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 101.183693
iter 10 value 93.491855
iter 20 value 93.266534
iter 30 value 92.818414
iter 40 value 91.316014
iter 50 value 91.195377
iter 60 value 91.194515
final value 91.194421
converged
Fitting Repeat 1
# weights: 305
initial value 129.174331
iter 10 value 117.895253
iter 20 value 117.703774
iter 30 value 117.607924
iter 40 value 117.558739
iter 50 value 114.026839
iter 60 value 113.941807
iter 70 value 113.929608
iter 80 value 113.833174
iter 90 value 113.824716
iter 100 value 113.814193
final value 113.814193
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 158.474005
iter 10 value 117.895104
iter 20 value 117.890241
iter 30 value 117.610807
final value 117.607787
converged
Fitting Repeat 3
# weights: 305
initial value 120.220169
iter 10 value 117.894831
iter 20 value 117.551431
iter 30 value 107.003795
iter 40 value 107.003124
iter 50 value 106.762037
iter 60 value 106.655429
iter 60 value 106.655429
iter 60 value 106.655429
final value 106.655429
converged
Fitting Repeat 4
# weights: 305
initial value 123.878107
iter 10 value 117.733481
iter 20 value 117.624107
iter 30 value 107.725735
iter 40 value 107.667526
iter 50 value 105.946046
iter 60 value 105.516843
iter 70 value 105.444290
iter 80 value 105.351364
iter 90 value 103.905982
iter 100 value 103.865061
final value 103.865061
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 124.391732
final value 117.894874
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 -- Thu Mar 12 00:37:20 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
39.526 0.856 94.918
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.033 | 0.544 | 33.580 | |
| FreqInteractors | 0.435 | 0.030 | 0.466 | |
| calculateAAC | 0.033 | 0.002 | 0.034 | |
| calculateAutocor | 0.328 | 0.013 | 0.342 | |
| calculateCTDC | 0.074 | 0.000 | 0.074 | |
| calculateCTDD | 0.534 | 0.001 | 0.536 | |
| calculateCTDT | 0.189 | 0.006 | 0.195 | |
| calculateCTriad | 0.353 | 0.008 | 0.362 | |
| calculateDC | 0.083 | 0.001 | 0.085 | |
| calculateF | 0.332 | 0.000 | 0.332 | |
| calculateKSAAP | 0.103 | 0.000 | 0.103 | |
| calculateQD_Sm | 1.708 | 0.021 | 1.729 | |
| calculateTC | 1.549 | 0.020 | 1.571 | |
| calculateTC_Sm | 0.257 | 0.002 | 0.259 | |
| corr_plot | 34.623 | 0.534 | 35.168 | |
| enrichfindP | 0.541 | 0.031 | 9.764 | |
| enrichfind_hp | 0.042 | 0.001 | 0.866 | |
| enrichplot | 0.513 | 0.002 | 0.514 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.406 | 0.027 | 3.777 | |
| getHPI | 0.001 | 0.000 | 0.001 | |
| get_negativePPI | 0.004 | 0.000 | 0.004 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.002 | 0.001 | 0.002 | |
| plotPPI | 0.113 | 0.002 | 0.115 | |
| pred_ensembel | 13.221 | 0.145 | 12.070 | |
| var_imp | 33.741 | 0.508 | 34.258 | |