Matineh Rahmatbakhsh
| Snapshot Date: 2025-12-01 13:40 -0500 (Mon, 01 Dec 2025) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: e6c77ab |
| git_last_commit_date: 2025-11-23 15:13:33 -0500 (Sun, 23 Nov 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2025-12-02 11:35 -0500 (Tue, 02 Dec 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences" | 4866 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4572 |
| 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 994/2328 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.17.1 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | ERROR | |||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.17.1 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.17.1.tar.gz |
| StartedAt: 2025-12-01 20:30:56 -0500 (Mon, 01 Dec 2025) |
| EndedAt: 2025-12-01 20:34:29 -0500 (Mon, 01 Dec 2025) |
| EllapsedTime: 212.7 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: HPiP.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.17.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-11-04 r88984)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 16.0.0 (clang-1600.0.26.6)
GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.8
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.1’
* 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 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 ... WARNING
Codoc mismatches from Rd file 'pred_ensembel.Rd':
pred_ensembel
Code: function(features, gold_standard, classifier = c("avNNet",
"svmRadial", "ranger"), resampling.method = "cv",
ncross = 2, repeats = 2, verboseIter = TRUE, plots =
FALSE, filename = "plots.pdf")
Docs: function(features, gold_standard, classifier = c("avNNet",
"svmRadial", "ranger"), resampling.method = "cv",
ncross = 2, repeats = 2, verboseIter = TRUE, plots =
TRUE, filename = "plots.pdf")
Mismatches in argument default values:
Name: 'plots' Code: FALSE Docs: TRUE
* 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 19.199 0.959 20.814
FSmethod 19.180 0.923 20.928
var_imp 18.571 0.999 20.653
pred_ensembel 6.476 0.106 6.195
enrichfindP 0.201 0.038 15.447
getFASTA 0.031 0.007 5.421
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘runTests.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.6-arm64/Resources/library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.17.1’ ** 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 Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 95.765373
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 98.841247
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 98.003133
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.683031
final value 94.038251
converged
Fitting Repeat 5
# weights: 103
initial value 101.286881
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 126.226412
iter 10 value 94.038251
iter 10 value 94.038251
iter 10 value 94.038251
final value 94.038251
converged
Fitting Repeat 2
# weights: 305
initial value 98.961618
iter 10 value 94.053127
final value 94.052911
converged
Fitting Repeat 3
# weights: 305
initial value 106.737535
final value 94.011561
converged
Fitting Repeat 4
# weights: 305
initial value 98.653945
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 103.078311
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 97.464441
final value 94.038251
converged
Fitting Repeat 2
# weights: 507
initial value 101.917509
final value 94.038251
converged
Fitting Repeat 3
# weights: 507
initial value 97.245021
iter 10 value 94.038251
iter 10 value 94.038251
iter 10 value 94.038251
final value 94.038251
converged
Fitting Repeat 4
# weights: 507
initial value 95.873412
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 136.204420
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 104.127799
iter 10 value 87.305325
iter 20 value 84.582410
iter 30 value 84.051062
iter 40 value 83.824464
iter 50 value 83.641893
iter 60 value 83.615499
final value 83.612559
converged
Fitting Repeat 2
# weights: 103
initial value 97.061630
iter 10 value 93.761473
iter 20 value 88.775602
iter 30 value 87.606282
iter 40 value 86.380090
iter 50 value 83.810620
iter 60 value 83.639591
iter 70 value 83.613548
final value 83.612559
converged
Fitting Repeat 3
# weights: 103
initial value 100.184550
iter 10 value 94.032020
iter 20 value 92.668697
iter 30 value 91.193770
iter 40 value 87.003483
iter 50 value 85.294085
iter 60 value 84.997955
iter 70 value 84.097931
iter 80 value 83.850696
final value 83.850662
converged
Fitting Repeat 4
# weights: 103
initial value 103.809719
iter 10 value 94.055714
iter 20 value 93.161415
iter 30 value 85.205777
iter 40 value 84.570132
iter 50 value 83.565054
iter 60 value 83.114633
iter 70 value 83.035515
iter 80 value 82.790782
iter 90 value 82.498138
iter 100 value 82.493506
final value 82.493506
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 108.982656
iter 10 value 94.194255
iter 20 value 93.788803
iter 30 value 86.529269
iter 40 value 86.228124
iter 50 value 84.255901
iter 60 value 83.615340
iter 70 value 83.612564
final value 83.612562
converged
Fitting Repeat 1
# weights: 305
initial value 103.209357
iter 10 value 92.724398
iter 20 value 85.775204
iter 30 value 84.689234
iter 40 value 84.197508
iter 50 value 83.362016
iter 60 value 82.715498
iter 70 value 82.606189
iter 80 value 82.169845
iter 90 value 81.866921
iter 100 value 81.680870
final value 81.680870
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.711921
iter 10 value 94.128782
iter 20 value 94.057810
iter 30 value 92.637917
iter 40 value 85.867683
iter 50 value 84.484803
iter 60 value 83.008345
iter 70 value 82.378554
iter 80 value 81.679765
iter 90 value 81.231208
iter 100 value 81.137102
final value 81.137102
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.212257
iter 10 value 93.988893
iter 20 value 93.538236
iter 30 value 92.803258
iter 40 value 92.301690
iter 50 value 88.331064
iter 60 value 84.839336
iter 70 value 83.977443
iter 80 value 83.713103
iter 90 value 83.582759
iter 100 value 83.233216
final value 83.233216
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.035915
iter 10 value 94.207283
iter 20 value 87.358561
iter 30 value 84.859347
iter 40 value 83.919137
iter 50 value 82.395638
iter 60 value 81.774278
iter 70 value 81.438085
iter 80 value 81.372534
iter 90 value 81.263954
iter 100 value 81.194432
final value 81.194432
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.513186
iter 10 value 94.119713
iter 20 value 91.047592
iter 30 value 86.764713
iter 40 value 85.101348
iter 50 value 84.696066
iter 60 value 84.130303
iter 70 value 83.726929
iter 80 value 83.518911
iter 90 value 83.308602
iter 100 value 83.207713
final value 83.207713
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.479598
iter 10 value 93.596595
iter 20 value 85.101445
iter 30 value 84.309465
iter 40 value 83.979729
iter 50 value 83.373933
iter 60 value 83.363267
iter 70 value 83.330238
iter 80 value 82.830233
iter 90 value 82.112702
iter 100 value 81.759876
final value 81.759876
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 120.238019
iter 10 value 92.960359
iter 20 value 88.404118
iter 30 value 86.696969
iter 40 value 85.949203
iter 50 value 84.083608
iter 60 value 83.834420
iter 70 value 83.324147
iter 80 value 82.962233
iter 90 value 82.458570
iter 100 value 82.284098
final value 82.284098
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 129.849339
iter 10 value 94.033651
iter 20 value 88.486209
iter 30 value 87.163523
iter 40 value 86.659126
iter 50 value 86.388236
iter 60 value 84.176373
iter 70 value 83.439415
iter 80 value 83.364618
iter 90 value 83.295218
iter 100 value 83.006641
final value 83.006641
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 129.988531
iter 10 value 94.556984
iter 20 value 94.320484
iter 30 value 90.241201
iter 40 value 86.556528
iter 50 value 84.111795
iter 60 value 83.334714
iter 70 value 83.207357
iter 80 value 83.115901
iter 90 value 82.861830
iter 100 value 82.302727
final value 82.302727
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 102.828179
iter 10 value 94.334644
iter 20 value 93.930147
iter 30 value 92.722660
iter 40 value 87.667609
iter 50 value 84.370612
iter 60 value 82.940680
iter 70 value 82.232530
iter 80 value 81.771007
iter 90 value 81.597173
iter 100 value 81.523413
final value 81.523413
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 105.633866
final value 94.054303
converged
Fitting Repeat 2
# weights: 103
initial value 98.750289
final value 94.054722
converged
Fitting Repeat 3
# weights: 103
initial value 104.947606
iter 10 value 94.054540
iter 20 value 94.052932
iter 20 value 94.052932
iter 20 value 94.052932
final value 94.052932
converged
Fitting Repeat 4
# weights: 103
initial value 110.396814
final value 94.054345
converged
Fitting Repeat 5
# weights: 103
initial value 106.223569
iter 10 value 94.054608
iter 20 value 94.052917
iter 30 value 89.859677
iter 40 value 84.368179
iter 50 value 82.534057
iter 60 value 82.072783
iter 70 value 81.959094
iter 80 value 81.957533
iter 90 value 81.956277
iter 100 value 81.956005
final value 81.956005
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 97.297997
iter 10 value 94.044473
iter 20 value 94.039986
final value 94.039882
converged
Fitting Repeat 2
# weights: 305
initial value 96.693210
iter 10 value 94.057668
iter 20 value 94.023688
iter 30 value 92.218402
iter 40 value 92.215770
iter 50 value 92.212141
iter 60 value 92.212047
iter 70 value 92.212021
final value 92.180992
converged
Fitting Repeat 3
# weights: 305
initial value 116.896733
iter 10 value 94.039567
iter 20 value 94.032171
iter 30 value 93.600794
iter 40 value 90.022014
final value 89.944762
converged
Fitting Repeat 4
# weights: 305
initial value 97.150881
iter 10 value 94.042933
iter 20 value 94.039216
iter 30 value 94.011966
iter 30 value 94.011965
iter 30 value 94.011965
final value 94.011965
converged
Fitting Repeat 5
# weights: 305
initial value 99.479713
iter 10 value 94.057705
iter 20 value 93.811532
iter 30 value 84.499308
iter 40 value 84.498934
final value 84.498887
converged
Fitting Repeat 1
# weights: 507
initial value 99.889625
iter 10 value 85.329474
iter 20 value 84.531063
iter 30 value 84.529658
final value 84.529651
converged
Fitting Repeat 2
# weights: 507
initial value 103.164134
iter 10 value 94.060419
iter 20 value 94.017276
iter 30 value 86.143664
iter 40 value 84.504760
iter 50 value 84.493462
iter 60 value 84.483646
iter 70 value 84.482982
iter 80 value 84.482199
iter 90 value 84.481541
iter 100 value 84.478117
final value 84.478117
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 98.757997
iter 10 value 94.058226
iter 20 value 93.837914
iter 30 value 90.603650
final value 90.603648
converged
Fitting Repeat 4
# weights: 507
initial value 96.836164
iter 10 value 89.294909
iter 20 value 83.257819
iter 30 value 82.572204
iter 40 value 82.519703
final value 82.519553
converged
Fitting Repeat 5
# weights: 507
initial value 95.232359
iter 10 value 93.729701
iter 20 value 93.714782
iter 30 value 93.387704
iter 40 value 91.034407
iter 50 value 84.056612
iter 60 value 83.117979
iter 70 value 83.009392
iter 80 value 82.778525
iter 90 value 82.775962
final value 82.774357
converged
Fitting Repeat 1
# weights: 103
initial value 100.009657
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.397502
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 101.953270
iter 10 value 93.304030
iter 20 value 91.420092
iter 30 value 91.323138
final value 91.322960
converged
Fitting Repeat 4
# weights: 103
initial value 97.890921
iter 10 value 93.582418
iter 20 value 93.581472
final value 93.581295
converged
Fitting Repeat 5
# weights: 103
initial value 102.483158
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 96.826998
iter 10 value 93.624728
final value 93.582418
converged
Fitting Repeat 2
# weights: 305
initial value 97.600616
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 103.734472
final value 93.582418
converged
Fitting Repeat 4
# weights: 305
initial value 104.644229
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 97.758992
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 99.617861
iter 10 value 93.258753
iter 20 value 91.183404
iter 30 value 87.029006
iter 40 value 86.539095
iter 50 value 86.530949
final value 86.530903
converged
Fitting Repeat 2
# weights: 507
initial value 96.551835
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 111.060478
iter 10 value 93.594625
final value 93.582418
converged
Fitting Repeat 4
# weights: 507
initial value 105.754936
final value 92.953900
converged
Fitting Repeat 5
# weights: 507
initial value 100.478816
final value 93.582418
converged
Fitting Repeat 1
# weights: 103
initial value 97.543429
iter 10 value 92.741124
iter 20 value 85.498266
iter 30 value 84.476795
iter 40 value 81.006522
iter 50 value 80.521455
iter 60 value 80.290059
final value 80.283362
converged
Fitting Repeat 2
# weights: 103
initial value 102.662865
iter 10 value 94.068229
iter 20 value 93.810774
iter 30 value 91.415976
iter 40 value 87.151616
iter 50 value 84.788559
iter 60 value 83.710184
iter 70 value 83.631596
final value 83.626779
converged
Fitting Repeat 3
# weights: 103
initial value 98.047956
iter 10 value 94.085538
iter 20 value 93.951361
iter 30 value 93.452666
iter 40 value 93.448192
iter 50 value 90.395948
iter 60 value 85.276848
iter 70 value 81.546799
iter 80 value 81.136200
iter 90 value 80.334445
iter 100 value 80.283177
final value 80.283177
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.304922
iter 10 value 93.802817
iter 20 value 93.121013
iter 30 value 91.679855
iter 40 value 86.636085
iter 50 value 85.607467
iter 60 value 83.812147
iter 70 value 82.855693
iter 80 value 82.623198
iter 90 value 82.605230
final value 82.604838
converged
Fitting Repeat 5
# weights: 103
initial value 98.867598
iter 10 value 94.043613
iter 20 value 85.183970
iter 30 value 83.783988
iter 40 value 83.514254
iter 50 value 83.402060
iter 60 value 83.374116
iter 70 value 83.182900
final value 83.182225
converged
Fitting Repeat 1
# weights: 305
initial value 110.630047
iter 10 value 94.091410
iter 20 value 93.944621
iter 30 value 93.465139
iter 40 value 92.632179
iter 50 value 86.856001
iter 60 value 85.540355
iter 70 value 82.258085
iter 80 value 81.487206
iter 90 value 81.120928
iter 100 value 80.529051
final value 80.529051
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 110.517171
iter 10 value 94.100826
iter 20 value 91.453734
iter 30 value 87.565892
iter 40 value 87.372076
iter 50 value 85.130789
iter 60 value 84.414928
iter 70 value 82.105101
iter 80 value 79.990145
iter 90 value 79.534222
iter 100 value 78.961319
final value 78.961319
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 110.339154
iter 10 value 92.899770
iter 20 value 84.946578
iter 30 value 83.858259
iter 40 value 83.454938
iter 50 value 83.351807
iter 60 value 83.130503
iter 70 value 81.712055
iter 80 value 80.968216
iter 90 value 80.627592
iter 100 value 79.970254
final value 79.970254
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.256250
iter 10 value 93.773977
iter 20 value 92.860863
iter 30 value 86.161025
iter 40 value 85.595468
iter 50 value 85.214137
iter 60 value 84.264304
iter 70 value 81.739067
iter 80 value 79.945033
iter 90 value 79.358097
iter 100 value 79.305793
final value 79.305793
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.432739
iter 10 value 94.229156
iter 20 value 91.011135
iter 30 value 84.156061
iter 40 value 82.883039
iter 50 value 82.276704
iter 60 value 81.806809
iter 70 value 81.643062
iter 80 value 81.331062
iter 90 value 81.101374
iter 100 value 80.857615
final value 80.857615
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 127.946773
iter 10 value 95.649942
iter 20 value 92.455224
iter 30 value 86.681422
iter 40 value 82.232002
iter 50 value 81.073445
iter 60 value 80.708586
iter 70 value 80.511350
iter 80 value 80.409820
iter 90 value 80.172653
iter 100 value 79.699740
final value 79.699740
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.365201
iter 10 value 94.657750
iter 20 value 93.516757
iter 30 value 87.674602
iter 40 value 85.247715
iter 50 value 84.103570
iter 60 value 81.760938
iter 70 value 80.995999
iter 80 value 79.821136
iter 90 value 79.284342
iter 100 value 78.926159
final value 78.926159
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 124.491984
iter 10 value 89.587244
iter 20 value 84.545621
iter 30 value 83.579796
iter 40 value 82.158374
iter 50 value 81.890736
iter 60 value 81.316708
iter 70 value 80.930893
iter 80 value 80.367266
iter 90 value 79.904644
iter 100 value 79.588798
final value 79.588798
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 116.725940
iter 10 value 94.038651
iter 20 value 92.355579
iter 30 value 87.740582
iter 40 value 82.175862
iter 50 value 81.434207
iter 60 value 80.341068
iter 70 value 80.085105
iter 80 value 79.885923
iter 90 value 79.391905
iter 100 value 79.154571
final value 79.154571
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.604930
iter 10 value 93.561425
iter 20 value 86.888963
iter 30 value 83.083367
iter 40 value 82.427558
iter 50 value 81.892620
iter 60 value 81.181454
iter 70 value 80.455855
iter 80 value 79.929512
iter 90 value 79.716144
iter 100 value 79.308269
final value 79.308269
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.328207
final value 93.373717
converged
Fitting Repeat 2
# weights: 103
initial value 96.385560
final value 94.054532
converged
Fitting Repeat 3
# weights: 103
initial value 98.211119
iter 10 value 94.101230
iter 20 value 94.095086
iter 30 value 94.055893
final value 94.052915
converged
Fitting Repeat 4
# weights: 103
initial value 103.302952
final value 94.054287
converged
Fitting Repeat 5
# weights: 103
initial value 98.263574
final value 94.054696
converged
Fitting Repeat 1
# weights: 305
initial value 101.717254
iter 10 value 93.901999
iter 20 value 93.711407
iter 30 value 93.706520
final value 93.669971
converged
Fitting Repeat 2
# weights: 305
initial value 95.768614
iter 10 value 94.057878
iter 20 value 94.053190
iter 30 value 85.453199
iter 40 value 82.004387
iter 50 value 80.056889
iter 60 value 80.053193
iter 60 value 80.053193
iter 60 value 80.053193
final value 80.053193
converged
Fitting Repeat 3
# weights: 305
initial value 95.575871
iter 10 value 94.053233
iter 20 value 93.362839
final value 93.356892
converged
Fitting Repeat 4
# weights: 305
initial value 121.095438
iter 10 value 94.059707
iter 20 value 94.054614
iter 30 value 92.711196
iter 40 value 85.273181
iter 50 value 85.269566
iter 60 value 85.186647
iter 70 value 85.177639
iter 80 value 85.175934
iter 90 value 85.175594
iter 90 value 85.175594
iter 90 value 85.175594
final value 85.175594
converged
Fitting Repeat 5
# weights: 305
initial value 97.026736
iter 10 value 93.587309
iter 20 value 92.984629
iter 30 value 92.946409
iter 40 value 92.938881
final value 92.938441
converged
Fitting Repeat 1
# weights: 507
initial value 127.114386
iter 10 value 94.061247
iter 20 value 94.046822
iter 30 value 91.584910
iter 40 value 90.604128
iter 50 value 90.568673
iter 60 value 90.452712
iter 70 value 90.051313
iter 80 value 90.044707
final value 90.044504
converged
Fitting Repeat 2
# weights: 507
initial value 137.864140
iter 10 value 93.617110
iter 20 value 93.611289
iter 30 value 93.605552
iter 40 value 88.998972
iter 50 value 80.969769
iter 60 value 77.842871
iter 70 value 77.694850
iter 80 value 77.624175
iter 90 value 77.600604
iter 100 value 77.598473
final value 77.598473
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 107.277285
iter 10 value 93.219387
iter 20 value 92.570648
iter 30 value 92.564550
iter 40 value 89.930116
iter 50 value 89.124452
iter 60 value 89.020837
final value 89.019863
converged
Fitting Repeat 4
# weights: 507
initial value 94.778371
iter 10 value 83.647605
iter 20 value 83.335303
iter 30 value 83.334343
final value 83.334311
converged
Fitting Repeat 5
# weights: 507
initial value 125.328833
iter 10 value 93.590959
iter 20 value 93.583109
iter 30 value 92.576739
iter 40 value 87.545073
iter 50 value 86.904766
iter 60 value 86.618623
iter 70 value 85.750920
iter 80 value 85.455603
iter 90 value 85.250620
iter 100 value 85.158392
final value 85.158392
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.986922
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 102.028192
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 99.079149
final value 93.809648
converged
Fitting Repeat 4
# weights: 103
initial value 108.179113
final value 94.026542
converged
Fitting Repeat 5
# weights: 103
initial value 111.013240
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 101.547761
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 96.204389
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 95.403197
final value 94.026542
converged
Fitting Repeat 4
# weights: 305
initial value 104.750643
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 98.243044
iter 10 value 93.809665
final value 93.809649
converged
Fitting Repeat 1
# weights: 507
initial value 110.396921
iter 10 value 89.157072
iter 20 value 85.537942
iter 30 value 85.342330
iter 40 value 85.338720
final value 85.338717
converged
Fitting Repeat 2
# weights: 507
initial value 96.238492
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 99.752295
final value 94.026542
converged
Fitting Repeat 4
# weights: 507
initial value 104.888105
final value 94.026542
converged
Fitting Repeat 5
# weights: 507
initial value 98.726439
iter 10 value 92.226658
iter 20 value 90.426265
iter 30 value 90.332488
iter 40 value 90.331241
final value 90.331136
converged
Fitting Repeat 1
# weights: 103
initial value 98.968668
iter 10 value 94.429629
iter 20 value 91.945788
iter 30 value 87.428872
iter 40 value 86.680284
iter 50 value 84.531456
iter 60 value 83.948587
iter 70 value 83.814510
final value 83.812426
converged
Fitting Repeat 2
# weights: 103
initial value 97.194428
iter 10 value 94.414748
iter 20 value 93.048463
iter 30 value 93.000921
iter 40 value 92.997358
iter 50 value 90.415669
iter 60 value 83.371522
iter 70 value 82.302190
iter 80 value 81.827246
iter 90 value 80.998859
iter 100 value 80.419548
final value 80.419548
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 101.589458
iter 10 value 94.731124
iter 20 value 94.488776
iter 30 value 94.210836
iter 40 value 94.139332
iter 50 value 92.317927
iter 60 value 90.255136
iter 70 value 90.120739
iter 80 value 90.087521
final value 90.087378
converged
Fitting Repeat 4
# weights: 103
initial value 103.930915
iter 10 value 94.519056
iter 20 value 93.497695
iter 30 value 93.019455
iter 40 value 92.943951
iter 50 value 85.218835
iter 60 value 82.620430
iter 70 value 81.829783
iter 80 value 80.918369
iter 90 value 80.711804
iter 100 value 80.336742
final value 80.336742
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.272344
iter 10 value 94.494626
iter 20 value 94.294732
iter 30 value 92.768230
iter 40 value 92.384050
iter 50 value 85.701808
iter 60 value 84.052645
iter 70 value 81.182707
iter 80 value 80.848985
iter 90 value 80.390575
iter 100 value 80.352508
final value 80.352508
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 100.617001
iter 10 value 95.030867
iter 20 value 86.446743
iter 30 value 84.079057
iter 40 value 83.667201
iter 50 value 82.784085
iter 60 value 80.984415
iter 70 value 79.834451
iter 80 value 79.664374
iter 90 value 79.604753
iter 100 value 79.483555
final value 79.483555
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 112.857588
iter 10 value 94.260727
iter 20 value 93.395695
iter 30 value 92.990544
iter 40 value 90.781188
iter 50 value 85.506330
iter 60 value 83.642131
iter 70 value 81.832670
iter 80 value 80.666729
iter 90 value 80.246381
iter 100 value 79.522070
final value 79.522070
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.452041
iter 10 value 95.001948
iter 20 value 94.071777
iter 30 value 87.953941
iter 40 value 86.683772
iter 50 value 83.638684
iter 60 value 82.766907
iter 70 value 80.650977
iter 80 value 79.892226
iter 90 value 79.699193
iter 100 value 79.493544
final value 79.493544
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.046692
iter 10 value 94.949167
iter 20 value 91.895294
iter 30 value 85.200793
iter 40 value 83.455079
iter 50 value 82.270242
iter 60 value 81.902077
iter 70 value 80.805245
iter 80 value 79.997492
iter 90 value 79.809339
iter 100 value 79.586607
final value 79.586607
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.360893
iter 10 value 94.251356
iter 20 value 90.514418
iter 30 value 84.987908
iter 40 value 84.163379
iter 50 value 82.628063
iter 60 value 82.407001
iter 70 value 81.592218
iter 80 value 81.028162
iter 90 value 80.759653
iter 100 value 80.406976
final value 80.406976
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.935906
iter 10 value 93.885127
iter 20 value 90.523353
iter 30 value 86.433052
iter 40 value 85.250199
iter 50 value 83.950944
iter 60 value 83.875601
iter 70 value 83.791377
iter 80 value 83.586880
iter 90 value 81.211651
iter 100 value 80.545320
final value 80.545320
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.606937
iter 10 value 94.484158
iter 20 value 88.780933
iter 30 value 85.614753
iter 40 value 84.489889
iter 50 value 83.467470
iter 60 value 82.069540
iter 70 value 80.448251
iter 80 value 79.996357
iter 90 value 79.486146
iter 100 value 79.322048
final value 79.322048
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 116.069711
iter 10 value 95.391270
iter 20 value 93.428216
iter 30 value 86.972414
iter 40 value 84.964310
iter 50 value 83.220092
iter 60 value 81.958680
iter 70 value 81.593979
iter 80 value 81.094649
iter 90 value 79.755915
iter 100 value 79.624383
final value 79.624383
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 102.794132
iter 10 value 93.605402
iter 20 value 93.098062
iter 30 value 88.375169
iter 40 value 86.435371
iter 50 value 85.180331
iter 60 value 82.073205
iter 70 value 80.272467
iter 80 value 79.940950
iter 90 value 79.011650
iter 100 value 78.763770
final value 78.763770
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.724754
iter 10 value 94.468163
iter 20 value 87.603517
iter 30 value 86.036614
iter 40 value 83.486518
iter 50 value 80.640178
iter 60 value 79.005162
iter 70 value 78.760907
iter 80 value 78.542843
iter 90 value 78.437721
iter 100 value 78.372021
final value 78.372021
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.481221
final value 94.028112
converged
Fitting Repeat 2
# weights: 103
initial value 100.836359
final value 94.485726
converged
Fitting Repeat 3
# weights: 103
initial value 95.770620
final value 94.485901
converged
Fitting Repeat 4
# weights: 103
initial value 97.566515
iter 10 value 94.486042
final value 94.484215
converged
Fitting Repeat 5
# weights: 103
initial value 98.834265
final value 94.485838
converged
Fitting Repeat 1
# weights: 305
initial value 98.213291
iter 10 value 94.489233
iter 20 value 94.053577
final value 94.026957
converged
Fitting Repeat 2
# weights: 305
initial value 101.969189
iter 10 value 94.489213
iter 20 value 94.378656
iter 30 value 92.872255
iter 40 value 92.868975
final value 92.868972
converged
Fitting Repeat 3
# weights: 305
initial value 98.956053
iter 10 value 94.084176
iter 20 value 88.857528
iter 30 value 88.850420
iter 40 value 85.714705
iter 50 value 85.332584
iter 60 value 85.332394
iter 70 value 85.330060
iter 70 value 85.330059
final value 85.330059
converged
Fitting Repeat 4
# weights: 305
initial value 107.871879
iter 10 value 94.488677
iter 20 value 93.254373
iter 30 value 92.845724
final value 92.842522
converged
Fitting Repeat 5
# weights: 305
initial value 111.366380
iter 10 value 94.500108
final value 94.495053
converged
Fitting Repeat 1
# weights: 507
initial value 113.243204
iter 10 value 94.487250
iter 20 value 94.287090
iter 30 value 92.888682
iter 40 value 92.873196
iter 50 value 92.860195
iter 60 value 92.856878
iter 70 value 92.853495
iter 80 value 92.851141
iter 90 value 90.970001
iter 100 value 86.070912
final value 86.070912
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.745179
iter 10 value 94.492438
iter 20 value 94.480818
iter 30 value 86.682546
iter 40 value 85.512378
final value 85.512367
converged
Fitting Repeat 3
# weights: 507
initial value 108.328641
iter 10 value 92.736368
iter 20 value 92.407739
iter 30 value 92.403092
iter 40 value 91.320680
iter 50 value 89.750465
iter 60 value 89.567201
iter 70 value 89.558765
iter 80 value 89.557536
iter 90 value 89.557182
iter 100 value 89.556657
final value 89.556657
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 101.119867
iter 10 value 94.490508
final value 94.484395
converged
Fitting Repeat 5
# weights: 507
initial value 96.803551
iter 10 value 94.489739
iter 20 value 93.298695
iter 30 value 92.870815
iter 40 value 92.864993
iter 50 value 85.162798
iter 60 value 81.109535
iter 70 value 79.006231
iter 80 value 78.797894
iter 90 value 78.796451
final value 78.795880
converged
Fitting Repeat 1
# weights: 103
initial value 108.641710
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.246732
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.850513
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 108.031793
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 115.749532
iter 10 value 93.891222
final value 93.837462
converged
Fitting Repeat 1
# weights: 305
initial value 94.955429
iter 10 value 83.199149
iter 20 value 83.122051
final value 83.121885
converged
Fitting Repeat 2
# weights: 305
initial value 114.539225
final value 94.026542
converged
Fitting Repeat 3
# weights: 305
initial value 96.120180
iter 10 value 94.191972
final value 94.191925
converged
Fitting Repeat 4
# weights: 305
initial value 101.126546
final value 94.436782
converged
Fitting Repeat 5
# weights: 305
initial value 105.022688
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 125.127466
final value 94.436782
converged
Fitting Repeat 2
# weights: 507
initial value 98.378155
iter 10 value 88.720885
iter 20 value 80.417946
iter 30 value 78.733045
iter 40 value 78.622343
iter 50 value 78.599743
iter 60 value 78.451032
iter 70 value 78.258659
iter 80 value 78.134865
iter 90 value 78.117736
iter 100 value 78.116834
final value 78.116834
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 112.687571
iter 10 value 94.026523
iter 20 value 93.822792
final value 93.822754
converged
Fitting Repeat 4
# weights: 507
initial value 120.252247
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 113.546511
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 104.387987
iter 10 value 94.442951
iter 20 value 87.846826
iter 30 value 86.835736
iter 40 value 84.763942
iter 50 value 83.567222
iter 60 value 81.969378
iter 70 value 81.562852
iter 80 value 81.443585
iter 90 value 81.375073
iter 100 value 81.250939
final value 81.250939
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.079352
iter 10 value 94.720044
iter 20 value 94.487326
iter 30 value 94.137500
iter 40 value 88.160893
iter 50 value 84.725737
iter 60 value 84.638678
iter 70 value 84.586658
iter 80 value 84.385097
iter 90 value 84.254603
iter 100 value 84.143578
final value 84.143578
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 103.100436
iter 10 value 89.951408
iter 20 value 86.991401
iter 30 value 84.132972
iter 40 value 83.920289
iter 50 value 83.322711
iter 60 value 83.143387
iter 70 value 83.139483
final value 83.139478
converged
Fitting Repeat 4
# weights: 103
initial value 96.595553
iter 10 value 91.861721
iter 20 value 87.277127
iter 30 value 84.673952
iter 40 value 82.510647
iter 50 value 81.502424
iter 60 value 81.411606
iter 70 value 81.238712
final value 81.214691
converged
Fitting Repeat 5
# weights: 103
initial value 96.198521
iter 10 value 94.241668
iter 20 value 93.954304
iter 30 value 90.423878
iter 40 value 86.427290
iter 50 value 84.101697
iter 60 value 83.278507
iter 70 value 81.596810
iter 80 value 81.133636
iter 90 value 80.952883
iter 100 value 80.899454
final value 80.899454
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 106.518928
iter 10 value 94.219696
iter 20 value 85.975448
iter 30 value 84.129137
iter 40 value 83.949755
iter 50 value 83.910041
iter 60 value 83.328599
iter 70 value 82.998574
iter 80 value 82.812464
iter 90 value 81.562795
iter 100 value 80.892520
final value 80.892520
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 115.027744
iter 10 value 94.249796
iter 20 value 94.036929
iter 30 value 93.897523
iter 40 value 87.510762
iter 50 value 85.001124
iter 60 value 84.422619
iter 70 value 82.525147
iter 80 value 81.747007
iter 90 value 81.320539
iter 100 value 80.874719
final value 80.874719
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.681776
iter 10 value 94.437847
iter 20 value 85.533792
iter 30 value 83.337314
iter 40 value 83.288546
iter 50 value 82.676904
iter 60 value 81.039815
iter 70 value 80.466473
iter 80 value 80.157568
iter 90 value 79.968617
iter 100 value 79.925455
final value 79.925455
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 111.834956
iter 10 value 95.429104
iter 20 value 89.794112
iter 30 value 86.262825
iter 40 value 83.260569
iter 50 value 81.397175
iter 60 value 81.098694
iter 70 value 80.858163
iter 80 value 80.709946
iter 90 value 80.534800
iter 100 value 80.368402
final value 80.368402
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.757128
iter 10 value 91.771047
iter 20 value 87.719985
iter 30 value 85.103379
iter 40 value 82.595919
iter 50 value 82.485915
iter 60 value 81.436273
iter 70 value 80.600169
iter 80 value 80.257091
iter 90 value 80.075914
iter 100 value 79.993124
final value 79.993124
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.256969
iter 10 value 86.929178
iter 20 value 84.139086
iter 30 value 83.951123
iter 40 value 83.793431
iter 50 value 82.810286
iter 60 value 81.332596
iter 70 value 80.298775
iter 80 value 79.753945
iter 90 value 79.638479
iter 100 value 79.540609
final value 79.540609
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 128.550789
iter 10 value 96.023778
iter 20 value 88.302887
iter 30 value 85.603412
iter 40 value 84.376422
iter 50 value 82.668582
iter 60 value 81.707420
iter 70 value 81.569937
iter 80 value 81.182655
iter 90 value 80.224508
iter 100 value 80.149354
final value 80.149354
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.814000
iter 10 value 96.119077
iter 20 value 95.251329
iter 30 value 90.006963
iter 40 value 85.953575
iter 50 value 82.632812
iter 60 value 81.941591
iter 70 value 81.233433
iter 80 value 81.005282
iter 90 value 80.480400
iter 100 value 80.081197
final value 80.081197
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.539166
iter 10 value 94.045545
iter 20 value 91.652936
iter 30 value 84.771330
iter 40 value 83.207190
iter 50 value 82.388339
iter 60 value 81.853663
iter 70 value 80.954530
iter 80 value 80.635022
iter 90 value 79.832859
iter 100 value 79.676601
final value 79.676601
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.716932
iter 10 value 94.460674
iter 20 value 88.888254
iter 30 value 85.518420
iter 40 value 83.786475
iter 50 value 82.508980
iter 60 value 82.149139
iter 70 value 81.347462
iter 80 value 81.132443
iter 90 value 80.585857
iter 100 value 80.110845
final value 80.110845
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.060738
final value 94.486114
converged
Fitting Repeat 2
# weights: 103
initial value 101.130628
final value 94.485843
converged
Fitting Repeat 3
# weights: 103
initial value 101.750955
final value 94.485900
converged
Fitting Repeat 4
# weights: 103
initial value 97.064103
final value 93.913489
converged
Fitting Repeat 5
# weights: 103
initial value 111.122347
final value 94.313737
converged
Fitting Repeat 1
# weights: 305
initial value 102.527901
iter 10 value 94.488954
iter 20 value 92.592555
iter 30 value 87.323499
iter 40 value 81.043017
iter 50 value 80.998954
iter 60 value 80.831322
iter 70 value 80.240400
iter 80 value 79.333932
iter 90 value 79.319493
iter 100 value 79.319403
final value 79.319403
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.924763
iter 10 value 94.489167
iter 20 value 94.174603
iter 30 value 91.392908
iter 40 value 91.373441
iter 50 value 91.357895
iter 60 value 91.354058
final value 91.354011
converged
Fitting Repeat 3
# weights: 305
initial value 110.496418
iter 10 value 95.350229
iter 20 value 93.706985
iter 30 value 88.260294
iter 40 value 83.702218
final value 83.686199
converged
Fitting Repeat 4
# weights: 305
initial value 96.974233
iter 10 value 94.031848
iter 20 value 94.027507
iter 30 value 94.027433
iter 40 value 94.027001
final value 94.026995
converged
Fitting Repeat 5
# weights: 305
initial value 96.834672
iter 10 value 87.152536
iter 20 value 86.876727
iter 30 value 84.229553
iter 40 value 84.228608
iter 50 value 84.226752
final value 84.226746
converged
Fitting Repeat 1
# weights: 507
initial value 124.773337
iter 10 value 94.034761
iter 20 value 94.028420
final value 94.027005
converged
Fitting Repeat 2
# weights: 507
initial value 97.290036
iter 10 value 94.034630
iter 20 value 94.029098
final value 93.823095
converged
Fitting Repeat 3
# weights: 507
initial value 105.586868
iter 10 value 93.830994
iter 20 value 93.828033
iter 30 value 93.825360
final value 93.825334
converged
Fitting Repeat 4
# weights: 507
initial value 105.838784
iter 10 value 94.061080
iter 20 value 93.816371
iter 30 value 85.408385
iter 40 value 84.347101
final value 84.346668
converged
Fitting Repeat 5
# weights: 507
initial value 101.954106
iter 10 value 93.986602
iter 20 value 93.921286
iter 30 value 93.880391
iter 40 value 93.861930
iter 50 value 93.861278
iter 60 value 87.018856
iter 70 value 84.093146
iter 80 value 83.732940
iter 90 value 83.211748
iter 100 value 82.847649
final value 82.847649
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.604186
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 102.141119
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.188948
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 94.516512
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.538130
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 96.772429
iter 10 value 94.112905
final value 94.112903
converged
Fitting Repeat 2
# weights: 305
initial value 98.079293
iter 10 value 94.188021
final value 94.112903
converged
Fitting Repeat 3
# weights: 305
initial value 112.024065
iter 10 value 94.275362
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 4
# weights: 305
initial value 99.591794
final value 94.291892
converged
Fitting Repeat 5
# weights: 305
initial value 97.207615
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 109.389515
iter 10 value 93.727123
iter 20 value 93.277831
iter 30 value 88.498833
iter 40 value 81.956343
iter 50 value 81.930111
final value 81.929091
converged
Fitting Repeat 2
# weights: 507
initial value 112.823263
iter 10 value 94.259993
iter 20 value 92.005839
iter 30 value 88.462098
iter 40 value 87.723801
iter 50 value 87.672623
iter 60 value 87.518861
iter 70 value 87.503456
iter 70 value 87.503455
final value 87.503455
converged
Fitting Repeat 3
# weights: 507
initial value 102.173713
final value 94.283324
converged
Fitting Repeat 4
# weights: 507
initial value 95.009803
final value 94.291892
converged
Fitting Repeat 5
# weights: 507
initial value 121.808149
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 101.562138
iter 10 value 95.510460
iter 20 value 93.091595
iter 30 value 84.672159
iter 40 value 84.093893
iter 50 value 83.923536
iter 60 value 83.882878
iter 70 value 83.298061
final value 83.297471
converged
Fitting Repeat 2
# weights: 103
initial value 99.241207
iter 10 value 94.582626
iter 20 value 94.384423
iter 30 value 92.836435
iter 40 value 91.950765
iter 50 value 87.656988
iter 60 value 87.104691
iter 70 value 87.008490
iter 80 value 87.007916
iter 90 value 86.717714
iter 100 value 83.868486
final value 83.868486
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 102.029735
iter 10 value 94.463500
iter 20 value 85.816682
iter 30 value 83.943165
iter 40 value 83.352908
iter 50 value 83.255580
iter 60 value 83.240015
iter 70 value 83.178832
iter 80 value 83.147837
final value 83.147833
converged
Fitting Repeat 4
# weights: 103
initial value 96.444527
iter 10 value 94.541866
iter 20 value 89.642046
iter 30 value 88.972796
iter 40 value 85.749611
iter 50 value 85.089157
iter 60 value 82.861754
iter 70 value 82.735829
iter 80 value 82.734418
iter 90 value 82.734324
iter 100 value 82.734108
final value 82.734108
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 100.422910
iter 10 value 94.362036
iter 20 value 85.752840
iter 30 value 83.915287
iter 40 value 83.119343
iter 50 value 82.342918
iter 60 value 81.725109
iter 70 value 81.688434
final value 81.688433
converged
Fitting Repeat 1
# weights: 305
initial value 104.709458
iter 10 value 94.989152
iter 20 value 87.804822
iter 30 value 84.202856
iter 40 value 83.528164
iter 50 value 83.324947
iter 60 value 82.891421
iter 70 value 81.450298
iter 80 value 80.863373
iter 90 value 80.672592
iter 100 value 80.402551
final value 80.402551
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 116.131606
iter 10 value 94.506534
iter 20 value 93.360549
iter 30 value 86.697629
iter 40 value 84.412774
iter 50 value 82.460234
iter 60 value 82.352385
iter 70 value 82.057356
iter 80 value 81.793191
iter 90 value 81.269382
iter 100 value 80.326228
final value 80.326228
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.616818
iter 10 value 93.627111
iter 20 value 92.054225
iter 30 value 91.036398
iter 40 value 86.438819
iter 50 value 82.824736
iter 60 value 81.413699
iter 70 value 80.885173
iter 80 value 80.187289
iter 90 value 79.544377
iter 100 value 79.245818
final value 79.245818
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.279203
iter 10 value 89.764823
iter 20 value 87.175382
iter 30 value 81.024054
iter 40 value 80.195142
iter 50 value 79.847251
iter 60 value 79.794966
iter 70 value 79.729569
iter 80 value 79.371437
iter 90 value 79.198580
iter 100 value 79.067170
final value 79.067170
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.078471
iter 10 value 95.013540
iter 20 value 94.121595
iter 30 value 88.515006
iter 40 value 84.873683
iter 50 value 84.445926
iter 60 value 84.025910
iter 70 value 83.487057
iter 80 value 82.726791
iter 90 value 80.578706
iter 100 value 80.264371
final value 80.264371
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.432266
iter 10 value 92.557967
iter 20 value 83.375630
iter 30 value 81.471139
iter 40 value 80.485646
iter 50 value 80.171640
iter 60 value 79.724411
iter 70 value 79.274222
iter 80 value 78.876383
iter 90 value 78.325829
iter 100 value 78.249452
final value 78.249452
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.721052
iter 10 value 94.589576
iter 20 value 94.468297
iter 30 value 92.909428
iter 40 value 90.808660
iter 50 value 89.189511
iter 60 value 88.541620
iter 70 value 84.961576
iter 80 value 82.329690
iter 90 value 81.135744
iter 100 value 80.508060
final value 80.508060
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 112.395872
iter 10 value 94.497011
iter 20 value 87.517984
iter 30 value 85.130035
iter 40 value 83.709186
iter 50 value 82.873024
iter 60 value 81.779385
iter 70 value 80.423219
iter 80 value 79.737038
iter 90 value 79.195662
iter 100 value 79.000689
final value 79.000689
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 129.089413
iter 10 value 94.937718
iter 20 value 94.481820
iter 30 value 87.827890
iter 40 value 83.241088
iter 50 value 80.520034
iter 60 value 79.973686
iter 70 value 79.091926
iter 80 value 78.974525
iter 90 value 78.802925
iter 100 value 78.658863
final value 78.658863
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.974994
iter 10 value 94.562722
iter 20 value 92.619630
iter 30 value 87.439768
iter 40 value 84.354007
iter 50 value 84.118441
iter 60 value 83.572726
iter 70 value 83.155049
iter 80 value 82.846899
iter 90 value 82.744944
iter 100 value 82.694623
final value 82.694623
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 104.586600
final value 94.486301
converged
Fitting Repeat 2
# weights: 103
initial value 94.811744
final value 94.485817
converged
Fitting Repeat 3
# weights: 103
initial value 94.992094
iter 10 value 94.331319
final value 94.327562
converged
Fitting Repeat 4
# weights: 103
initial value 104.811959
final value 94.485845
converged
Fitting Repeat 5
# weights: 103
initial value 104.679753
iter 10 value 94.485925
iter 20 value 94.392962
iter 30 value 87.509118
iter 40 value 87.433659
iter 50 value 87.433307
iter 60 value 87.433123
final value 87.433078
converged
Fitting Repeat 1
# weights: 305
initial value 103.869473
iter 10 value 94.296713
iter 20 value 94.292460
final value 94.291979
converged
Fitting Repeat 2
# weights: 305
initial value 103.010867
iter 10 value 94.489140
iter 20 value 94.338795
iter 30 value 90.920862
iter 40 value 90.911735
iter 50 value 90.908412
iter 60 value 90.895168
iter 70 value 90.216068
iter 80 value 80.052148
iter 90 value 79.775916
final value 79.775461
converged
Fitting Repeat 3
# weights: 305
initial value 103.260813
iter 10 value 94.489150
iter 20 value 94.484365
iter 30 value 92.639997
iter 40 value 92.627109
iter 50 value 91.716251
iter 60 value 84.524931
iter 70 value 84.521438
iter 80 value 84.515202
iter 90 value 84.328391
iter 100 value 82.171418
final value 82.171418
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.175875
iter 10 value 94.296848
iter 20 value 94.293968
final value 94.292852
converged
Fitting Repeat 5
# weights: 305
initial value 103.840025
iter 10 value 94.489354
iter 20 value 94.480243
iter 30 value 93.191536
iter 40 value 88.488313
iter 50 value 88.328685
iter 60 value 88.323066
iter 70 value 88.322509
iter 80 value 88.322031
iter 90 value 88.321350
final value 88.321344
converged
Fitting Repeat 1
# weights: 507
initial value 98.551224
iter 10 value 94.300246
iter 20 value 93.115428
iter 30 value 92.627967
iter 40 value 92.515653
iter 50 value 92.510143
final value 92.510129
converged
Fitting Repeat 2
# weights: 507
initial value 109.721504
iter 10 value 94.300185
iter 20 value 94.293169
iter 30 value 94.259942
iter 40 value 92.138914
final value 91.998486
converged
Fitting Repeat 3
# weights: 507
initial value 123.213111
iter 10 value 85.273969
iter 20 value 82.013250
iter 30 value 81.959124
iter 40 value 81.916629
iter 50 value 81.914781
iter 60 value 81.912800
iter 70 value 81.912231
iter 80 value 81.904135
iter 90 value 81.884294
iter 100 value 81.880428
final value 81.880428
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 95.882438
iter 10 value 94.334407
iter 20 value 93.757631
iter 30 value 93.443380
iter 40 value 93.389813
final value 93.389577
converged
Fitting Repeat 5
# weights: 507
initial value 112.320958
iter 10 value 84.548398
iter 20 value 82.561013
iter 30 value 82.559207
iter 40 value 82.555871
iter 50 value 82.554181
final value 82.552717
converged
Fitting Repeat 1
# weights: 507
initial value 133.673435
iter 10 value 117.767044
iter 20 value 116.763222
iter 30 value 113.391046
iter 40 value 109.123980
iter 50 value 108.771245
iter 60 value 108.619415
iter 70 value 107.726844
iter 80 value 107.625060
iter 90 value 107.622519
iter 100 value 107.197756
final value 107.197756
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 151.604736
iter 10 value 117.898288
iter 20 value 117.859803
iter 30 value 117.251962
iter 40 value 112.475245
iter 50 value 112.075270
iter 60 value 112.007317
iter 70 value 111.252657
iter 80 value 106.684517
iter 90 value 102.505410
iter 100 value 101.439684
final value 101.439684
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 127.712756
iter 10 value 117.527522
iter 20 value 117.517944
final value 117.511455
converged
Fitting Repeat 4
# weights: 507
initial value 133.619496
iter 10 value 117.602375
iter 20 value 117.596169
iter 30 value 117.594645
iter 40 value 117.511505
final value 117.500050
converged
Fitting Repeat 5
# weights: 507
initial value 141.443391
iter 10 value 117.898367
iter 20 value 117.869914
iter 30 value 114.409593
iter 40 value 114.324950
iter 50 value 114.324700
final value 114.324677
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 -- Mon Dec 1 20:34:24 2025
***********************************************
Number of test functions: 7
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7
Number of errors: 0
Number of failures: 0
Warning messages:
1: `repeats` has no meaning for this resampling method.
2: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
20.841 0.491 73.702
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 19.180 | 0.923 | 20.928 | |
| FreqInteractors | 0.171 | 0.014 | 0.198 | |
| calculateAAC | 0.013 | 0.002 | 0.016 | |
| calculateAutocor | 0.272 | 0.031 | 0.319 | |
| calculateCTDC | 0.034 | 0.005 | 0.039 | |
| calculateCTDD | 0.160 | 0.007 | 0.169 | |
| calculateCTDT | 0.060 | 0.003 | 0.067 | |
| calculateCTriad | 0.152 | 0.016 | 0.169 | |
| calculateDC | 0.034 | 0.004 | 0.039 | |
| calculateF | 0.107 | 0.008 | 0.121 | |
| calculateKSAAP | 0.034 | 0.004 | 0.043 | |
| calculateQD_Sm | 0.675 | 0.063 | 0.749 | |
| calculateTC | 0.732 | 0.070 | 0.816 | |
| calculateTC_Sm | 0.099 | 0.013 | 0.114 | |
| corr_plot | 19.199 | 0.959 | 20.814 | |
| enrichfindP | 0.201 | 0.038 | 15.447 | |
| enrichfind_hp | 0.014 | 0.003 | 0.992 | |
| enrichplot | 0.175 | 0.008 | 0.186 | |
| filter_missing_values | 0.000 | 0.001 | 0.000 | |
| getFASTA | 0.031 | 0.007 | 5.421 | |
| getHPI | 0.001 | 0.000 | 0.000 | |
| get_negativePPI | 0.000 | 0.000 | 0.001 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.001 | 0.000 | 0.001 | |
| plotPPI | 0.032 | 0.002 | 0.034 | |
| pred_ensembel | 6.476 | 0.106 | 6.195 | |
| var_imp | 18.571 | 0.999 | 20.653 | |