Back to Multiple platform build/check report for BioC 3.21: simplified long |
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This page was generated on 2025-09-11 11:38 -0400 (Thu, 11 Sep 2025).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4824 |
merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4606 |
kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4547 |
Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X |
Package 997/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.14.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | OK | OK | ![]() | ||||||||
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: HPiP |
Version: 1.14.0 |
Command: /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings HPiP_1.14.0.tar.gz |
StartedAt: 2025-09-11 00:46:56 -0400 (Thu, 11 Sep 2025) |
EndedAt: 2025-09-11 01:02:16 -0400 (Thu, 11 Sep 2025) |
EllapsedTime: 920.2 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings HPiP_1.14.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’ * using R version 4.5.1 (2025-06-13) * 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 ‘1.14.0’ * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘HPiP’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... NOTE License stub is invalid DCF. * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking loading without being on the library search path ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... NOTE checkRd: (-1) getHPI.Rd:29: Lost braces 29 | then the Kronecker product is the code{(pm × qn)} block matrix | ^ * checking Rd metadata ... OK * checking Rd cross-references ... INFO Package unavailable to check Rd xrefs: ‘ftrCOOL’ * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking contents of ‘data’ directory ... OK * checking data for non-ASCII characters ... OK * checking data for ASCII and uncompressed saves ... OK * checking R/sysdata.rda ... OK * checking files in ‘vignettes’ ... OK * checking examples ... OK Examples with CPU (user + system) or elapsed time > 5s user system elapsed var_imp 33.969 0.361 34.333 FSmethod 32.709 0.643 33.354 corr_plot 32.993 0.334 33.328 pred_ensembel 13.282 0.170 12.090 enrichfindP 0.467 0.030 8.148 * 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-3.21-bioc/meat/HPiP.Rcheck/00check.log’ for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.21-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.14.0’ ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root" 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 97.314418 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 104.684952 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 100.926187 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 98.583374 final value 94.484210 converged Fitting Repeat 5 # weights: 103 initial value 97.403068 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 94.136741 iter 10 value 85.232264 iter 20 value 84.402755 iter 30 value 84.348144 final value 84.347930 converged Fitting Repeat 2 # weights: 305 initial value 96.566881 final value 94.387500 converged Fitting Repeat 3 # weights: 305 initial value 100.393235 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 99.502235 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 95.843329 final value 94.354396 converged Fitting Repeat 1 # weights: 507 initial value 98.172538 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 104.064528 iter 10 value 94.387506 final value 94.387500 converged Fitting Repeat 3 # weights: 507 initial value 130.976203 iter 10 value 94.354645 final value 94.354396 converged Fitting Repeat 4 # weights: 507 initial value 97.301068 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 97.421451 iter 10 value 88.707765 iter 20 value 87.181301 iter 30 value 87.169920 final value 87.169492 converged Fitting Repeat 1 # weights: 103 initial value 101.213222 iter 10 value 93.856389 iter 20 value 93.111286 iter 30 value 87.632758 iter 40 value 85.009858 iter 50 value 82.539253 iter 60 value 82.181764 iter 70 value 82.103033 iter 80 value 82.098924 iter 80 value 82.098924 iter 80 value 82.098924 final value 82.098924 converged Fitting Repeat 2 # weights: 103 initial value 100.856988 iter 10 value 94.478604 iter 20 value 93.811943 iter 30 value 90.049194 iter 40 value 87.653092 iter 50 value 87.192875 iter 60 value 83.847093 iter 70 value 82.289606 iter 80 value 81.976449 iter 90 value 81.758634 iter 100 value 81.684500 final value 81.684500 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 97.197134 iter 10 value 94.475411 iter 20 value 88.828326 iter 30 value 87.067072 iter 40 value 83.220633 iter 50 value 82.768221 iter 60 value 82.313694 iter 70 value 82.126369 iter 80 value 82.099393 final value 82.098923 converged Fitting Repeat 4 # weights: 103 initial value 104.170298 iter 10 value 94.446374 iter 20 value 94.105440 iter 30 value 93.932061 iter 40 value 86.318349 iter 50 value 85.493604 iter 60 value 84.894337 iter 70 value 83.034878 iter 80 value 81.047178 iter 90 value 80.986942 iter 100 value 80.766610 final value 80.766610 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 97.228681 iter 10 value 94.492953 iter 20 value 93.345232 iter 30 value 93.088850 iter 40 value 85.674163 iter 50 value 83.808811 iter 60 value 83.265900 iter 70 value 80.700291 iter 80 value 80.685075 iter 90 value 80.647212 iter 100 value 80.524571 final value 80.524571 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 111.628662 iter 10 value 94.481133 iter 20 value 87.939132 iter 30 value 82.768669 iter 40 value 82.515105 iter 50 value 81.975499 iter 60 value 81.905579 iter 70 value 81.839721 iter 80 value 81.629895 iter 90 value 81.394691 iter 100 value 80.444258 final value 80.444258 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 107.173768 iter 10 value 94.505402 iter 20 value 93.941735 iter 30 value 88.301319 iter 40 value 86.868574 iter 50 value 83.968122 iter 60 value 82.298088 iter 70 value 81.593443 iter 80 value 81.071121 iter 90 value 80.534252 iter 100 value 80.350511 final value 80.350511 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 107.314629 iter 10 value 94.534937 iter 20 value 94.131810 iter 30 value 94.006884 iter 40 value 89.325825 iter 50 value 88.784612 iter 60 value 87.569319 iter 70 value 83.707657 iter 80 value 81.119097 iter 90 value 80.500907 iter 100 value 80.167005 final value 80.167005 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 103.413687 iter 10 value 94.233075 iter 20 value 88.917456 iter 30 value 86.528296 iter 40 value 85.523200 iter 50 value 85.230049 iter 60 value 82.113685 iter 70 value 80.782039 iter 80 value 80.559927 iter 90 value 80.519007 iter 100 value 80.040121 final value 80.040121 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 106.764724 iter 10 value 94.305306 iter 20 value 86.708705 iter 30 value 82.758342 iter 40 value 81.297032 iter 50 value 80.955325 iter 60 value 80.354725 iter 70 value 80.125531 iter 80 value 79.959882 iter 90 value 79.456941 iter 100 value 79.249609 final value 79.249609 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 127.181559 iter 10 value 96.544041 iter 20 value 87.480623 iter 30 value 85.113931 iter 40 value 84.466177 iter 50 value 83.963392 iter 60 value 81.038226 iter 70 value 80.091136 iter 80 value 79.939687 iter 90 value 79.844874 iter 100 value 79.785858 final value 79.785858 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 105.858110 iter 10 value 94.763360 iter 20 value 86.156515 iter 30 value 85.666727 iter 40 value 84.602247 iter 50 value 82.451608 iter 60 value 81.304100 iter 70 value 80.605804 iter 80 value 79.606765 iter 90 value 79.157450 iter 100 value 79.067295 final value 79.067295 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 107.776178 iter 10 value 97.619391 iter 20 value 93.623341 iter 30 value 84.957545 iter 40 value 84.436184 iter 50 value 84.003384 iter 60 value 83.914113 iter 70 value 83.818454 iter 80 value 83.423070 iter 90 value 82.220848 iter 100 value 81.083138 final value 81.083138 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 107.522565 iter 10 value 93.956266 iter 20 value 84.609503 iter 30 value 82.448836 iter 40 value 82.006075 iter 50 value 81.219226 iter 60 value 80.641222 iter 70 value 80.263230 iter 80 value 79.961513 iter 90 value 79.679358 iter 100 value 79.321548 final value 79.321548 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 112.564892 iter 10 value 94.523280 iter 20 value 93.643584 iter 30 value 90.775462 iter 40 value 89.649308 iter 50 value 87.700767 iter 60 value 87.046639 iter 70 value 84.400538 iter 80 value 81.289723 iter 90 value 80.866388 iter 100 value 79.862435 final value 79.862435 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.106903 final value 94.485642 converged Fitting Repeat 2 # weights: 103 initial value 96.031078 iter 10 value 94.254787 iter 20 value 92.904226 iter 30 value 84.568218 iter 40 value 83.118511 final value 83.067708 converged Fitting Repeat 3 # weights: 103 initial value 110.296471 iter 10 value 94.485887 iter 20 value 94.484271 final value 94.484205 converged Fitting Repeat 4 # weights: 103 initial value 98.567430 final value 94.486032 converged Fitting Repeat 5 # weights: 103 initial value 98.446257 final value 94.485766 converged Fitting Repeat 1 # weights: 305 initial value 96.293608 iter 10 value 94.488818 iter 20 value 94.484247 iter 30 value 86.764279 iter 40 value 84.467952 iter 50 value 79.639357 iter 60 value 79.221372 iter 70 value 78.913942 iter 80 value 78.913436 iter 90 value 78.913125 iter 90 value 78.913125 final value 78.913125 converged Fitting Repeat 2 # weights: 305 initial value 112.254632 iter 10 value 94.168978 iter 20 value 94.165455 final value 94.165453 converged Fitting Repeat 3 # weights: 305 initial value 98.901528 iter 10 value 94.493752 iter 20 value 94.075864 iter 30 value 94.053608 final value 94.053411 converged Fitting Repeat 4 # weights: 305 initial value 97.559896 iter 10 value 91.324489 iter 20 value 84.369119 iter 30 value 82.000689 iter 40 value 80.852800 iter 50 value 80.848253 iter 60 value 80.639374 iter 70 value 80.595255 iter 80 value 80.586357 iter 90 value 80.575267 iter 100 value 80.571388 final value 80.571388 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 96.079354 iter 10 value 94.359503 iter 20 value 94.133882 iter 30 value 93.883684 iter 40 value 93.883006 final value 93.882912 converged Fitting Repeat 1 # weights: 507 initial value 105.962274 iter 10 value 94.488011 iter 20 value 94.283538 iter 30 value 82.315251 iter 40 value 81.687113 iter 50 value 81.683317 iter 60 value 81.648692 iter 70 value 81.111563 iter 80 value 79.296081 iter 90 value 78.506155 iter 100 value 78.143527 final value 78.143527 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 119.564291 iter 10 value 94.491472 iter 20 value 93.794925 iter 30 value 83.365910 final value 83.336972 converged Fitting Repeat 3 # weights: 507 initial value 95.538813 iter 10 value 92.782218 iter 20 value 86.965060 iter 30 value 86.961771 iter 40 value 85.445416 iter 50 value 83.563198 iter 60 value 83.473088 iter 70 value 83.472032 iter 80 value 83.469058 iter 90 value 83.265117 iter 100 value 80.798626 final value 80.798626 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 103.615922 iter 10 value 94.126480 iter 20 value 94.065181 iter 30 value 94.056899 iter 40 value 93.901921 iter 50 value 83.475943 iter 60 value 79.993838 iter 70 value 78.941505 iter 80 value 78.850624 iter 90 value 78.644692 iter 100 value 78.533505 final value 78.533505 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 113.799482 iter 10 value 94.145979 iter 20 value 94.142330 iter 30 value 94.139206 final value 94.138978 converged Fitting Repeat 1 # weights: 103 initial value 94.495745 iter 10 value 94.052917 final value 94.052911 converged Fitting Repeat 2 # weights: 103 initial value 101.122428 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 126.278194 final value 94.052448 converged Fitting Repeat 4 # weights: 103 initial value 97.930899 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 100.045826 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 103.951644 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 94.609728 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 104.657122 final value 93.962011 converged Fitting Repeat 4 # weights: 305 initial value 100.809135 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 106.329321 iter 10 value 94.033150 iter 10 value 94.033149 iter 10 value 94.033149 final value 94.033149 converged Fitting Repeat 1 # weights: 507 initial value 120.229476 iter 10 value 94.126108 iter 20 value 91.318015 iter 30 value 90.901645 iter 40 value 90.863968 final value 90.863210 converged Fitting Repeat 2 # weights: 507 initial value 110.596147 final value 94.052910 converged Fitting Repeat 3 # weights: 507 initial value 106.809162 iter 10 value 92.961302 iter 20 value 91.824134 iter 20 value 91.824134 iter 30 value 91.760208 iter 40 value 91.726659 final value 91.726481 converged Fitting Repeat 4 # weights: 507 initial value 146.056057 iter 10 value 94.008709 final value 94.008696 converged Fitting Repeat 5 # weights: 507 initial value 94.743909 final value 93.990909 converged Fitting Repeat 1 # weights: 103 initial value 100.426005 iter 10 value 94.109722 iter 20 value 92.051429 iter 30 value 87.656846 iter 40 value 87.468379 iter 50 value 87.202093 iter 60 value 87.096780 iter 70 value 86.169995 iter 80 value 85.589100 iter 90 value 85.557871 iter 100 value 84.994971 final value 84.994971 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 102.151901 iter 10 value 94.119468 iter 20 value 93.895904 iter 30 value 88.399102 iter 40 value 86.888778 iter 50 value 86.012889 iter 60 value 85.583667 iter 70 value 85.198062 final value 85.091699 converged Fitting Repeat 3 # weights: 103 initial value 101.124952 iter 10 value 94.022079 iter 20 value 93.718245 iter 30 value 91.149548 iter 40 value 90.773343 iter 50 value 90.225666 iter 60 value 87.869397 iter 70 value 87.109895 iter 80 value 86.802999 iter 90 value 86.771025 iter 100 value 86.752870 final value 86.752870 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 99.164759 iter 10 value 94.001902 iter 20 value 91.117067 iter 30 value 89.009214 iter 40 value 87.920608 iter 50 value 87.612945 iter 60 value 87.187654 iter 70 value 86.947478 iter 80 value 86.851426 iter 90 value 86.605171 final value 86.596406 converged Fitting Repeat 5 # weights: 103 initial value 103.097694 iter 10 value 94.120193 iter 20 value 94.028838 iter 30 value 93.612452 iter 40 value 92.933777 iter 50 value 91.399716 iter 60 value 91.182972 iter 70 value 88.090650 iter 80 value 86.919455 iter 90 value 86.760270 iter 100 value 86.496033 final value 86.496033 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 120.664490 iter 10 value 94.333156 iter 20 value 94.065934 iter 30 value 92.981200 iter 40 value 88.568353 iter 50 value 87.040807 iter 60 value 86.651248 iter 70 value 85.514067 iter 80 value 84.796056 iter 90 value 84.765302 iter 100 value 84.356167 final value 84.356167 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 113.182711 iter 10 value 94.162768 iter 20 value 94.055637 iter 30 value 93.966780 iter 40 value 93.181663 iter 50 value 88.064500 iter 60 value 85.690365 iter 70 value 84.319632 iter 80 value 84.184262 iter 90 value 83.741044 iter 100 value 83.598988 final value 83.598988 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 101.204251 iter 10 value 94.448666 iter 20 value 92.962092 iter 30 value 88.751009 iter 40 value 87.984531 iter 50 value 87.627331 iter 60 value 87.558484 iter 70 value 87.070714 iter 80 value 85.970418 iter 90 value 84.999270 iter 100 value 83.876631 final value 83.876631 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 105.965345 iter 10 value 94.044199 iter 20 value 92.914872 iter 30 value 89.837578 iter 40 value 88.463510 iter 50 value 87.580923 iter 60 value 87.140940 iter 70 value 87.097994 iter 80 value 87.023773 iter 90 value 85.845350 iter 100 value 85.044797 final value 85.044797 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 103.628275 iter 10 value 94.030405 iter 20 value 92.862743 iter 30 value 92.460511 iter 40 value 92.266191 iter 50 value 89.058429 iter 60 value 87.447369 iter 70 value 86.998941 iter 80 value 86.168232 iter 90 value 85.017016 iter 100 value 84.341039 final value 84.341039 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 122.071878 iter 10 value 94.124336 iter 20 value 89.232614 iter 30 value 88.872030 iter 40 value 88.274886 iter 50 value 86.658285 iter 60 value 85.021719 iter 70 value 84.209266 iter 80 value 83.887337 iter 90 value 83.735903 iter 100 value 83.504469 final value 83.504469 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 104.876965 iter 10 value 94.036026 iter 20 value 91.473286 iter 30 value 88.774189 iter 40 value 87.921174 iter 50 value 86.629908 iter 60 value 85.653001 iter 70 value 84.556834 iter 80 value 84.022804 iter 90 value 83.976933 iter 100 value 83.810654 final value 83.810654 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 122.542243 iter 10 value 94.142120 iter 20 value 94.014109 iter 30 value 93.978526 iter 40 value 93.209161 iter 50 value 89.025019 iter 60 value 87.285746 iter 70 value 86.287343 iter 80 value 86.211633 iter 90 value 85.337891 iter 100 value 84.919153 final value 84.919153 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 104.536617 iter 10 value 93.917698 iter 20 value 88.840126 iter 30 value 87.783781 iter 40 value 87.630943 iter 50 value 84.026352 iter 60 value 83.724793 iter 70 value 83.392651 iter 80 value 83.167390 iter 90 value 83.055515 iter 100 value 82.953253 final value 82.953253 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 117.722040 iter 10 value 94.020796 iter 20 value 89.232076 iter 30 value 86.265357 iter 40 value 84.443717 iter 50 value 84.038220 iter 60 value 83.899504 iter 70 value 83.700439 iter 80 value 83.643939 iter 90 value 83.569371 iter 100 value 83.448735 final value 83.448735 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 94.557632 final value 94.054543 converged Fitting Repeat 2 # weights: 103 initial value 98.165538 iter 10 value 94.054778 iter 20 value 94.052902 iter 30 value 89.761323 iter 40 value 89.578616 final value 89.578543 converged Fitting Repeat 3 # weights: 103 initial value 97.211819 final value 94.054599 converged Fitting Repeat 4 # weights: 103 initial value 102.467140 final value 94.054325 converged Fitting Repeat 5 # weights: 103 initial value 100.561403 final value 94.054536 converged Fitting Repeat 1 # weights: 305 initial value 96.527399 iter 10 value 94.013653 iter 20 value 93.965752 iter 30 value 93.962353 iter 40 value 93.960715 final value 93.960594 converged Fitting Repeat 2 # weights: 305 initial value 115.559987 iter 10 value 94.014342 iter 20 value 93.967577 iter 30 value 93.965063 final value 93.962202 converged Fitting Repeat 3 # weights: 305 initial value 108.095237 iter 10 value 94.057385 iter 20 value 94.052962 iter 30 value 93.929511 iter 40 value 92.709684 iter 50 value 92.645207 iter 60 value 92.505923 iter 70 value 92.504367 final value 92.504269 converged Fitting Repeat 4 # weights: 305 initial value 110.261917 iter 10 value 94.057764 iter 20 value 92.610444 iter 30 value 88.222684 iter 40 value 87.247786 iter 50 value 86.853287 final value 86.797778 converged Fitting Repeat 5 # weights: 305 initial value 101.398689 iter 10 value 94.057396 final value 94.052914 converged Fitting Repeat 1 # weights: 507 initial value 95.188445 iter 10 value 94.015259 iter 20 value 94.000456 iter 30 value 93.962238 iter 40 value 93.961783 iter 50 value 93.961735 iter 60 value 93.960589 iter 70 value 91.456747 iter 80 value 89.077826 iter 90 value 88.964045 iter 100 value 88.765351 final value 88.765351 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 96.867763 iter 10 value 94.016986 iter 20 value 93.969028 iter 30 value 93.893745 iter 40 value 87.941776 iter 50 value 86.281090 iter 60 value 86.278171 iter 70 value 85.681786 iter 80 value 85.455944 iter 90 value 85.362417 iter 100 value 85.248417 final value 85.248417 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 103.538541 iter 10 value 94.016910 iter 20 value 93.978581 iter 30 value 93.960704 iter 40 value 93.960576 final value 93.960575 converged Fitting Repeat 4 # weights: 507 initial value 98.821916 iter 10 value 93.199195 iter 20 value 92.897169 iter 30 value 92.834770 iter 40 value 91.828053 iter 50 value 91.826863 iter 60 value 91.530177 iter 70 value 88.193044 iter 80 value 88.192069 iter 90 value 88.191822 iter 100 value 88.191132 final value 88.191132 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 100.743071 iter 10 value 94.061031 iter 20 value 93.745348 iter 30 value 89.922678 iter 40 value 89.375955 iter 50 value 89.047991 iter 60 value 89.045886 iter 60 value 89.045885 iter 60 value 89.045885 final value 89.045885 converged Fitting Repeat 1 # weights: 103 initial value 98.471453 final value 94.466823 converged Fitting Repeat 2 # weights: 103 initial value 102.748195 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 98.952665 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 119.885130 final value 94.466823 converged Fitting Repeat 5 # weights: 103 initial value 97.419076 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 99.946259 iter 10 value 94.466829 final value 94.466823 converged Fitting Repeat 2 # weights: 305 initial value 96.626944 final value 94.484227 converged Fitting Repeat 3 # weights: 305 initial value 104.525493 final value 94.466823 converged Fitting Repeat 4 # weights: 305 initial value 95.962688 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 100.165552 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 98.147779 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 103.587200 iter 10 value 94.144702 iter 10 value 94.144701 iter 10 value 94.144701 final value 94.144701 converged Fitting Repeat 3 # weights: 507 initial value 114.661588 final value 94.466823 converged Fitting Repeat 4 # weights: 507 initial value 100.690191 iter 10 value 93.103496 final value 93.102857 converged Fitting Repeat 5 # weights: 507 initial value 120.669955 final value 94.466823 converged Fitting Repeat 1 # weights: 103 initial value 97.138096 iter 10 value 94.497271 iter 20 value 91.695344 iter 30 value 91.294165 iter 40 value 91.242880 iter 50 value 87.799443 iter 60 value 85.405613 iter 70 value 84.225077 iter 80 value 83.084997 iter 90 value 82.876819 final value 82.875880 converged Fitting Repeat 2 # weights: 103 initial value 97.802388 iter 10 value 94.471847 iter 20 value 92.929632 iter 30 value 86.248187 iter 40 value 85.248853 iter 50 value 85.106907 iter 60 value 85.075248 iter 70 value 85.042908 iter 80 value 84.252090 iter 90 value 83.206732 iter 100 value 83.173851 final value 83.173851 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 99.810281 iter 10 value 94.531403 iter 20 value 94.488493 iter 30 value 94.287642 iter 40 value 93.422248 iter 50 value 87.284508 iter 60 value 84.856969 iter 70 value 84.434009 iter 80 value 83.913662 iter 90 value 83.775621 iter 100 value 83.767008 final value 83.767008 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 96.727273 iter 10 value 94.485339 iter 20 value 92.268462 iter 30 value 91.201523 iter 40 value 91.134334 iter 50 value 91.103042 iter 60 value 91.066506 iter 70 value 91.066363 final value 91.066266 converged Fitting Repeat 5 # weights: 103 initial value 96.918089 iter 10 value 94.502898 iter 20 value 86.825157 iter 30 value 83.685062 iter 40 value 83.081217 iter 50 value 81.565929 iter 60 value 81.110312 iter 70 value 81.065809 iter 80 value 80.637672 iter 90 value 80.588699 final value 80.588692 converged Fitting Repeat 1 # weights: 305 initial value 107.987601 iter 10 value 94.487292 iter 20 value 88.348110 iter 30 value 86.474635 iter 40 value 85.693538 iter 50 value 85.401490 iter 60 value 85.263465 iter 70 value 85.196355 iter 80 value 85.143238 iter 90 value 85.117606 iter 100 value 84.258240 final value 84.258240 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.460586 iter 10 value 93.701018 iter 20 value 87.783663 iter 30 value 84.288734 iter 40 value 83.527077 iter 50 value 83.286485 iter 60 value 82.878467 iter 70 value 82.029689 iter 80 value 81.006772 iter 90 value 80.894311 iter 100 value 79.735298 final value 79.735298 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.006686 iter 10 value 94.291418 iter 20 value 87.398419 iter 30 value 86.174799 iter 40 value 83.866644 iter 50 value 82.559871 iter 60 value 81.360099 iter 70 value 80.616155 iter 80 value 79.734807 iter 90 value 79.299348 iter 100 value 79.249092 final value 79.249092 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 108.164657 iter 10 value 91.196949 iter 20 value 85.885478 iter 30 value 85.648977 iter 40 value 84.933268 iter 50 value 83.463186 iter 60 value 83.120849 iter 70 value 82.632625 iter 80 value 82.453875 iter 90 value 81.730942 iter 100 value 81.550191 final value 81.550191 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 102.735414 iter 10 value 94.420028 iter 20 value 86.522622 iter 30 value 85.677916 iter 40 value 85.500440 iter 50 value 85.441487 iter 60 value 85.410689 iter 70 value 83.375579 iter 80 value 82.196186 iter 90 value 81.103278 iter 100 value 81.056146 final value 81.056146 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 115.200103 iter 10 value 90.162957 iter 20 value 86.108807 iter 30 value 84.672273 iter 40 value 83.942624 iter 50 value 80.074330 iter 60 value 79.411822 iter 70 value 79.333318 iter 80 value 79.250244 iter 90 value 79.156498 iter 100 value 79.148961 final value 79.148961 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 109.335143 iter 10 value 94.595413 iter 20 value 91.022023 iter 30 value 84.507502 iter 40 value 82.001727 iter 50 value 80.205274 iter 60 value 79.510308 iter 70 value 79.409113 iter 80 value 79.133530 iter 90 value 78.873996 iter 100 value 78.527964 final value 78.527964 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 113.653080 iter 10 value 94.150767 iter 20 value 84.737220 iter 30 value 83.597117 iter 40 value 82.309859 iter 50 value 81.693815 iter 60 value 80.672836 iter 70 value 79.591824 iter 80 value 79.278959 iter 90 value 78.705201 iter 100 value 78.524668 final value 78.524668 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 118.206702 iter 10 value 95.119747 iter 20 value 91.882379 iter 30 value 86.341681 iter 40 value 83.882737 iter 50 value 83.351307 iter 60 value 82.665560 iter 70 value 82.160255 iter 80 value 81.142435 iter 90 value 80.627280 iter 100 value 80.525019 final value 80.525019 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 109.879626 iter 10 value 95.863125 iter 20 value 94.512615 iter 30 value 90.504388 iter 40 value 83.776883 iter 50 value 81.307845 iter 60 value 80.501536 iter 70 value 79.495593 iter 80 value 79.157307 iter 90 value 78.930896 iter 100 value 78.823039 final value 78.823039 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.922653 final value 94.485945 converged Fitting Repeat 2 # weights: 103 initial value 96.535459 final value 94.485759 converged Fitting Repeat 3 # weights: 103 initial value 105.013951 final value 94.485682 converged Fitting Repeat 4 # weights: 103 initial value 101.312600 final value 94.485754 converged Fitting Repeat 5 # weights: 103 initial value 103.975333 final value 94.489696 converged Fitting Repeat 1 # weights: 305 initial value 98.480355 iter 10 value 94.488815 iter 20 value 94.324419 iter 30 value 85.528146 iter 40 value 85.527967 final value 85.527949 converged Fitting Repeat 2 # weights: 305 initial value 99.980941 iter 10 value 92.733707 iter 20 value 92.713671 iter 30 value 92.606240 iter 40 value 92.602461 iter 50 value 92.600695 iter 60 value 92.531841 final value 92.530692 converged Fitting Repeat 3 # weights: 305 initial value 100.589363 iter 10 value 91.711762 iter 20 value 91.697541 iter 30 value 91.697007 iter 40 value 91.696567 iter 50 value 91.694686 final value 91.694082 converged Fitting Repeat 4 # weights: 305 initial value 98.137722 iter 10 value 88.510118 iter 20 value 86.103481 iter 30 value 85.921676 iter 40 value 85.916432 iter 50 value 85.914389 iter 60 value 85.913505 iter 70 value 85.911784 iter 80 value 85.911611 final value 85.911593 converged Fitting Repeat 5 # weights: 305 initial value 107.671009 iter 10 value 94.491187 iter 20 value 94.467954 iter 30 value 87.909534 iter 40 value 86.786523 iter 50 value 86.619218 iter 60 value 85.772965 final value 85.744226 converged Fitting Repeat 1 # weights: 507 initial value 96.461601 iter 10 value 94.495063 iter 20 value 94.486868 iter 30 value 93.736248 iter 40 value 90.813252 iter 50 value 90.804437 final value 90.804225 converged Fitting Repeat 2 # weights: 507 initial value 102.627907 iter 10 value 94.491745 iter 20 value 94.459150 iter 30 value 92.791629 iter 40 value 90.624649 iter 50 value 81.374398 iter 60 value 80.552675 iter 70 value 80.470305 iter 80 value 80.303228 iter 90 value 80.058804 iter 100 value 80.058286 final value 80.058286 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 100.809912 iter 10 value 94.474964 iter 20 value 94.348242 iter 30 value 87.441352 iter 40 value 81.273957 iter 50 value 78.308010 iter 60 value 77.253590 iter 70 value 77.155009 iter 80 value 77.144968 iter 90 value 77.134051 iter 100 value 77.133231 final value 77.133231 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 106.409765 iter 10 value 94.474861 iter 20 value 93.870843 iter 30 value 90.460319 iter 40 value 90.447248 iter 50 value 90.446888 iter 50 value 90.446888 final value 90.446888 converged Fitting Repeat 5 # weights: 507 initial value 108.105657 iter 10 value 94.491598 iter 20 value 94.469464 iter 30 value 92.605890 iter 40 value 92.603633 final value 92.603614 converged Fitting Repeat 1 # weights: 103 initial value 95.959700 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 97.025056 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 97.191164 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 95.809627 iter 10 value 94.253256 final value 94.252921 converged Fitting Repeat 5 # weights: 103 initial value 103.455987 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 100.253051 final value 94.443243 converged Fitting Repeat 2 # weights: 305 initial value 120.264322 iter 10 value 94.536229 iter 20 value 94.484285 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 94.791450 final value 94.443243 converged Fitting Repeat 4 # weights: 305 initial value 98.535659 iter 10 value 94.075416 iter 20 value 93.922750 iter 20 value 93.922749 iter 20 value 93.922749 final value 93.922749 converged Fitting Repeat 5 # weights: 305 initial value 101.641573 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 115.584445 iter 10 value 94.443243 iter 10 value 94.443243 iter 10 value 94.443243 final value 94.443243 converged Fitting Repeat 2 # weights: 507 initial value 127.416126 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 99.348777 iter 10 value 93.638377 iter 20 value 91.664912 iter 30 value 83.355558 iter 40 value 82.747662 iter 50 value 82.733330 final value 82.733272 converged Fitting Repeat 4 # weights: 507 initial value 117.902259 final value 94.443243 converged Fitting Repeat 5 # weights: 507 initial value 118.539022 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 106.788174 iter 10 value 94.425786 iter 20 value 92.863347 iter 30 value 89.140592 iter 40 value 85.927414 iter 50 value 84.252693 iter 60 value 83.561388 iter 70 value 82.672224 iter 80 value 81.101119 iter 90 value 80.460348 iter 100 value 80.457497 final value 80.457497 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 98.648816 iter 10 value 94.472752 iter 20 value 93.300850 iter 30 value 83.475750 iter 40 value 82.619668 iter 50 value 82.352963 iter 60 value 81.900569 final value 81.894449 converged Fitting Repeat 3 # weights: 103 initial value 96.492579 iter 10 value 94.488588 iter 20 value 93.990221 iter 30 value 92.112736 iter 40 value 91.971657 iter 50 value 91.812427 final value 91.806358 converged Fitting Repeat 4 # weights: 103 initial value 97.288882 iter 10 value 94.483483 iter 20 value 94.260980 iter 30 value 94.082137 iter 40 value 93.791612 iter 50 value 91.977058 iter 60 value 87.276018 iter 70 value 86.846985 iter 80 value 83.808018 iter 90 value 82.574358 iter 100 value 82.299047 final value 82.299047 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 99.076575 iter 10 value 94.487363 iter 20 value 90.070178 iter 30 value 86.529532 iter 40 value 85.208526 iter 50 value 83.894954 iter 60 value 83.593806 iter 70 value 82.713587 iter 80 value 82.475101 final value 82.469301 converged Fitting Repeat 1 # weights: 305 initial value 118.448088 iter 10 value 94.385080 iter 20 value 88.822679 iter 30 value 85.829460 iter 40 value 84.091862 iter 50 value 79.685917 iter 60 value 78.881365 iter 70 value 78.739420 iter 80 value 78.715290 iter 90 value 78.701046 iter 100 value 78.696869 final value 78.696869 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 130.291472 iter 10 value 94.484324 iter 20 value 93.796043 iter 30 value 91.834338 iter 40 value 91.546942 iter 50 value 91.257347 iter 60 value 87.125592 iter 70 value 82.872677 iter 80 value 82.159818 iter 90 value 81.556119 iter 100 value 80.656893 final value 80.656893 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 115.657529 iter 10 value 94.456925 iter 20 value 83.663103 iter 30 value 82.452917 iter 40 value 82.315383 iter 50 value 81.655777 iter 60 value 81.304386 iter 70 value 80.844009 iter 80 value 79.956351 iter 90 value 79.689880 iter 100 value 79.542787 final value 79.542787 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 114.237623 iter 10 value 94.512147 iter 20 value 85.747270 iter 30 value 85.300068 iter 40 value 83.557027 iter 50 value 81.763009 iter 60 value 81.246137 iter 70 value 80.856732 iter 80 value 80.753277 iter 90 value 80.533404 iter 100 value 79.618274 final value 79.618274 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 105.612889 iter 10 value 94.603396 iter 20 value 94.348710 iter 30 value 91.721494 iter 40 value 88.247233 iter 50 value 83.689003 iter 60 value 82.986968 iter 70 value 82.864059 iter 80 value 82.476933 iter 90 value 82.285554 iter 100 value 79.904536 final value 79.904536 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 108.909859 iter 10 value 94.759646 iter 20 value 93.367800 iter 30 value 85.936653 iter 40 value 83.029921 iter 50 value 80.731777 iter 60 value 80.037550 iter 70 value 79.820634 iter 80 value 79.535536 iter 90 value 79.483664 iter 100 value 79.326310 final value 79.326310 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 119.283681 iter 10 value 93.097750 iter 20 value 83.733444 iter 30 value 83.141562 iter 40 value 82.036969 iter 50 value 81.322574 iter 60 value 80.001960 iter 70 value 79.420991 iter 80 value 78.943946 iter 90 value 78.704806 iter 100 value 78.520453 final value 78.520453 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 106.584212 iter 10 value 94.458105 iter 20 value 90.348346 iter 30 value 84.032599 iter 40 value 82.201599 iter 50 value 81.818531 iter 60 value 80.578772 iter 70 value 79.253982 iter 80 value 79.012447 iter 90 value 78.843553 iter 100 value 78.784146 final value 78.784146 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 144.069857 iter 10 value 109.185607 iter 20 value 86.697787 iter 30 value 84.481405 iter 40 value 81.763373 iter 50 value 80.633356 iter 60 value 80.182919 iter 70 value 79.950960 iter 80 value 79.283905 iter 90 value 79.002313 iter 100 value 78.857338 final value 78.857338 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 118.254983 iter 10 value 93.985802 iter 20 value 89.394988 iter 30 value 84.802795 iter 40 value 84.373812 iter 50 value 81.606825 iter 60 value 79.561686 iter 70 value 79.440567 iter 80 value 79.275644 iter 90 value 79.075784 iter 100 value 78.880345 final value 78.880345 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 101.662977 iter 10 value 94.485979 iter 20 value 94.484277 iter 30 value 94.320783 iter 40 value 93.724596 iter 50 value 93.688887 iter 60 value 93.688800 iter 60 value 93.688799 iter 60 value 93.688799 final value 93.688799 converged Fitting Repeat 2 # weights: 103 initial value 96.405580 final value 94.486059 converged Fitting Repeat 3 # weights: 103 initial value 99.973692 final value 94.485774 converged Fitting Repeat 4 # weights: 103 initial value 95.930664 final value 94.485756 converged Fitting Repeat 5 # weights: 103 initial value 101.012526 final value 94.485570 converged Fitting Repeat 1 # weights: 305 initial value 94.926469 iter 10 value 94.486926 iter 20 value 94.475620 iter 30 value 88.201026 iter 40 value 82.201462 iter 50 value 82.078232 iter 60 value 82.049436 iter 70 value 81.965411 iter 80 value 81.535067 iter 90 value 81.534557 final value 81.534401 converged Fitting Repeat 2 # weights: 305 initial value 127.553551 iter 10 value 94.448337 iter 20 value 94.443748 iter 30 value 88.410078 iter 40 value 86.331006 iter 50 value 86.310032 iter 60 value 85.848535 iter 70 value 82.870024 iter 80 value 82.705829 iter 90 value 82.670277 iter 100 value 82.670084 final value 82.670084 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 107.008411 iter 10 value 94.489054 final value 94.484408 converged Fitting Repeat 4 # weights: 305 initial value 119.642900 iter 10 value 94.448073 iter 20 value 94.172424 iter 30 value 89.462622 iter 40 value 88.938367 iter 50 value 88.670252 iter 60 value 87.348803 iter 70 value 86.566626 final value 86.564172 converged Fitting Repeat 5 # weights: 305 initial value 99.617532 iter 10 value 94.488745 iter 20 value 94.390612 iter 30 value 82.990368 iter 40 value 80.597103 iter 50 value 80.174722 iter 60 value 79.392673 iter 70 value 77.285279 iter 80 value 77.264896 iter 90 value 77.263661 iter 100 value 77.262945 final value 77.262945 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 97.698107 iter 10 value 83.542961 iter 20 value 82.754286 iter 30 value 81.913489 iter 40 value 81.850764 iter 50 value 81.847028 iter 60 value 81.842943 iter 70 value 81.696791 iter 80 value 81.278491 iter 90 value 81.247817 iter 100 value 80.265428 final value 80.265428 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 104.981002 iter 10 value 94.451037 iter 20 value 94.447171 iter 30 value 94.415164 iter 40 value 90.380603 iter 50 value 89.388305 iter 60 value 85.043534 iter 70 value 81.341726 iter 80 value 80.690335 iter 90 value 80.397224 iter 100 value 80.338752 final value 80.338752 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 95.155720 iter 10 value 89.173535 iter 20 value 89.172605 iter 30 value 84.660988 iter 40 value 84.428986 iter 50 value 84.419894 iter 60 value 84.302438 iter 70 value 84.301508 iter 80 value 84.300750 iter 90 value 84.299232 iter 100 value 84.298955 final value 84.298955 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 120.263183 iter 10 value 94.492692 iter 20 value 94.483974 iter 20 value 94.483974 iter 30 value 87.061993 iter 40 value 86.957098 iter 50 value 83.598185 iter 60 value 83.430087 iter 70 value 83.428784 final value 83.428781 converged Fitting Repeat 5 # weights: 507 initial value 96.545773 iter 10 value 94.402762 iter 20 value 94.271933 iter 30 value 94.085125 iter 40 value 94.084983 iter 50 value 94.084181 iter 60 value 94.083853 iter 60 value 94.083852 iter 60 value 94.083852 final value 94.083852 converged Fitting Repeat 1 # weights: 103 initial value 100.725283 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 100.464263 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 97.613539 final value 93.582418 converged Fitting Repeat 4 # weights: 103 initial value 100.377436 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 99.700388 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 98.483169 iter 10 value 89.243192 iter 20 value 86.210751 iter 30 value 81.481416 iter 40 value 81.196304 iter 50 value 80.817625 final value 80.817248 converged Fitting Repeat 2 # weights: 305 initial value 94.857465 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 108.075578 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 97.402228 iter 10 value 93.604520 iter 10 value 93.604520 iter 10 value 93.604520 final value 93.604520 converged Fitting Repeat 5 # weights: 305 initial value 99.986351 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 103.976773 final value 93.582418 converged Fitting Repeat 2 # weights: 507 initial value 104.379399 iter 10 value 89.630147 iter 20 value 89.621723 final value 89.621672 converged Fitting Repeat 3 # weights: 507 initial value 100.128287 final value 93.582418 converged Fitting Repeat 4 # weights: 507 initial value 100.625246 iter 10 value 90.897930 iter 20 value 83.046572 iter 30 value 81.120974 iter 40 value 80.797404 iter 50 value 80.793375 final value 80.793371 converged Fitting Repeat 5 # weights: 507 initial value 98.556077 final value 93.084594 converged Fitting Repeat 1 # weights: 103 initial value 107.568873 iter 10 value 93.997477 iter 20 value 92.578577 iter 30 value 91.697957 iter 40 value 81.940155 iter 50 value 81.661541 iter 60 value 81.048076 iter 70 value 80.794246 iter 80 value 80.285863 iter 90 value 79.997650 iter 100 value 79.944920 final value 79.944920 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 95.757075 iter 10 value 94.055468 iter 20 value 93.898873 iter 30 value 92.544866 iter 40 value 92.496270 iter 50 value 92.495317 iter 60 value 86.396404 iter 70 value 83.076151 iter 80 value 82.392439 iter 90 value 82.079871 iter 100 value 82.071620 final value 82.071620 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 99.789154 iter 10 value 94.070209 iter 20 value 92.397277 iter 30 value 92.233743 iter 40 value 92.145526 iter 50 value 91.508340 iter 60 value 87.673544 iter 70 value 82.523836 iter 80 value 81.680755 iter 90 value 81.615246 final value 81.615104 converged Fitting Repeat 4 # weights: 103 initial value 99.310131 iter 10 value 93.529552 iter 20 value 87.187913 iter 30 value 82.305819 iter 40 value 82.092710 iter 50 value 82.087809 iter 60 value 82.079631 iter 70 value 82.071772 final value 82.071617 converged Fitting Repeat 5 # weights: 103 initial value 99.961920 iter 10 value 94.055617 iter 20 value 93.502897 iter 30 value 93.061583 iter 40 value 92.502744 iter 50 value 88.570705 iter 60 value 83.325611 iter 70 value 82.378469 iter 80 value 82.089820 iter 90 value 81.271733 iter 100 value 80.669086 final value 80.669086 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 114.102795 iter 10 value 94.196758 iter 20 value 92.330221 iter 30 value 82.855601 iter 40 value 81.733788 iter 50 value 81.347426 iter 60 value 80.426365 iter 70 value 80.039385 iter 80 value 79.769604 iter 90 value 79.645432 iter 100 value 79.598334 final value 79.598334 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 99.689492 iter 10 value 90.473074 iter 20 value 89.718844 iter 30 value 88.326571 iter 40 value 84.144097 iter 50 value 83.227041 iter 60 value 82.775884 iter 70 value 82.654773 iter 80 value 81.548762 iter 90 value 79.487669 iter 100 value 78.900740 final value 78.900740 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 118.012750 iter 10 value 90.319315 iter 20 value 86.138924 iter 30 value 85.142316 iter 40 value 82.410387 iter 50 value 81.476060 iter 60 value 81.117200 iter 70 value 80.616415 iter 80 value 79.739693 iter 90 value 79.459527 iter 100 value 79.055486 final value 79.055486 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 106.586167 iter 10 value 90.605567 iter 20 value 86.622249 iter 30 value 81.010669 iter 40 value 79.431837 iter 50 value 79.097226 iter 60 value 78.903668 iter 70 value 78.777122 iter 80 value 78.730968 iter 90 value 78.654118 iter 100 value 78.599795 final value 78.599795 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 102.640135 iter 10 value 93.792299 iter 20 value 84.269905 iter 30 value 83.201744 iter 40 value 82.178038 iter 50 value 81.347423 iter 60 value 81.066200 iter 70 value 80.421029 iter 80 value 79.881633 iter 90 value 79.681916 iter 100 value 79.030669 final value 79.030669 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 117.527014 iter 10 value 94.597420 iter 20 value 88.101749 iter 30 value 86.408701 iter 40 value 85.443846 iter 50 value 81.950719 iter 60 value 79.643100 iter 70 value 79.175442 iter 80 value 79.102579 iter 90 value 79.022407 iter 100 value 78.993967 final value 78.993967 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 134.549207 iter 10 value 94.061298 iter 20 value 86.666059 iter 30 value 83.167100 iter 40 value 82.362550 iter 50 value 80.856084 iter 60 value 80.293398 iter 70 value 79.744833 iter 80 value 79.629760 iter 90 value 79.030566 iter 100 value 78.635666 final value 78.635666 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 121.295084 iter 10 value 94.774585 iter 20 value 94.078008 iter 30 value 91.093570 iter 40 value 83.129552 iter 50 value 81.512849 iter 60 value 80.625216 iter 70 value 80.353100 iter 80 value 80.059982 iter 90 value 79.348613 iter 100 value 78.845260 final value 78.845260 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 107.119177 iter 10 value 93.949102 iter 20 value 91.414947 iter 30 value 82.028516 iter 40 value 81.069614 iter 50 value 79.860390 iter 60 value 79.757285 iter 70 value 79.669351 iter 80 value 79.587330 iter 90 value 79.240793 iter 100 value 79.059438 final value 79.059438 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 112.505442 iter 10 value 95.363147 iter 20 value 84.917080 iter 30 value 82.148222 iter 40 value 79.719434 iter 50 value 78.680652 iter 60 value 78.372649 iter 70 value 78.246095 iter 80 value 78.198881 iter 90 value 78.110377 iter 100 value 78.048549 final value 78.048549 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 101.091411 iter 10 value 94.055084 final value 94.053115 converged Fitting Repeat 2 # weights: 103 initial value 103.577110 final value 94.054666 converged Fitting Repeat 3 # weights: 103 initial value 95.539316 iter 10 value 94.054704 iter 20 value 94.052920 iter 30 value 83.321233 iter 40 value 82.563018 iter 50 value 82.548807 iter 60 value 82.546687 iter 70 value 81.640329 iter 80 value 81.621138 iter 90 value 81.577994 iter 100 value 80.964105 final value 80.964105 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 100.672620 final value 94.054888 converged Fitting Repeat 5 # weights: 103 initial value 102.565900 final value 94.054572 converged Fitting Repeat 1 # weights: 305 initial value 97.800903 iter 10 value 94.057850 iter 20 value 93.950565 iter 30 value 92.390201 final value 92.390192 converged Fitting Repeat 2 # weights: 305 initial value 97.831099 iter 10 value 94.057734 iter 20 value 93.694786 iter 30 value 84.462467 iter 40 value 84.451686 iter 50 value 84.451499 iter 60 value 82.443057 iter 70 value 82.389277 iter 80 value 82.388485 iter 90 value 81.058793 iter 100 value 80.310471 final value 80.310471 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 127.813969 iter 10 value 94.059062 iter 20 value 94.053813 final value 94.053783 converged Fitting Repeat 4 # weights: 305 initial value 118.715347 iter 10 value 93.587916 iter 20 value 93.583523 final value 93.582685 converged Fitting Repeat 5 # weights: 305 initial value 118.475980 iter 10 value 94.057462 iter 20 value 94.004229 iter 30 value 85.117268 iter 40 value 81.615977 final value 81.615264 converged Fitting Repeat 1 # weights: 507 initial value 108.279520 iter 10 value 92.492073 iter 20 value 92.487194 iter 30 value 91.705442 iter 40 value 90.749465 iter 50 value 90.256676 iter 60 value 89.893360 iter 70 value 89.516321 iter 80 value 89.258174 iter 90 value 89.255433 final value 89.255181 converged Fitting Repeat 2 # weights: 507 initial value 105.537173 iter 10 value 87.160781 iter 20 value 81.623522 iter 30 value 81.402670 iter 40 value 80.966355 iter 50 value 80.944675 iter 60 value 80.938729 iter 70 value 80.937086 iter 80 value 80.135034 iter 90 value 78.596276 iter 100 value 78.560818 final value 78.560818 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 97.529850 iter 10 value 92.450532 iter 20 value 92.396090 iter 30 value 92.311808 iter 40 value 92.308176 final value 92.306837 converged Fitting Repeat 4 # weights: 507 initial value 100.433767 iter 10 value 93.093218 iter 20 value 93.091170 iter 30 value 93.090142 iter 40 value 92.019249 iter 50 value 85.001744 iter 60 value 81.251717 iter 70 value 78.922108 iter 80 value 78.267605 iter 90 value 78.195843 iter 100 value 78.192222 final value 78.192222 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 102.389890 iter 10 value 94.055919 iter 20 value 93.984320 iter 30 value 93.348356 iter 40 value 86.310228 iter 50 value 84.456335 iter 60 value 84.455037 iter 70 value 84.454957 iter 80 value 84.454905 iter 90 value 84.454551 final value 84.454473 converged Fitting Repeat 1 # weights: 305 initial value 128.901616 iter 10 value 117.582867 iter 20 value 114.524614 iter 30 value 108.951092 iter 40 value 107.598443 iter 50 value 106.973265 iter 60 value 106.489027 iter 70 value 106.323030 iter 80 value 105.763755 iter 90 value 103.785957 iter 100 value 103.057388 final value 103.057388 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 167.332223 iter 10 value 117.767359 iter 20 value 115.458870 iter 30 value 114.922054 iter 40 value 114.587947 iter 50 value 114.306398 iter 60 value 111.693999 iter 70 value 105.847873 iter 80 value 102.837617 iter 90 value 101.821326 iter 100 value 101.047965 final value 101.047965 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 126.648184 iter 10 value 113.493345 iter 20 value 106.480379 iter 30 value 106.118860 iter 40 value 105.668683 iter 50 value 104.343702 iter 60 value 103.363344 iter 70 value 101.983025 iter 80 value 101.386303 iter 90 value 101.085500 iter 100 value 100.824213 final value 100.824213 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 130.921020 iter 10 value 117.737434 iter 20 value 110.159686 iter 30 value 108.903573 iter 40 value 108.279682 iter 50 value 105.020908 iter 60 value 104.664367 iter 70 value 104.511102 iter 80 value 104.474607 iter 90 value 103.909604 iter 100 value 102.642496 final value 102.642496 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 124.493162 iter 10 value 117.926356 iter 20 value 116.328678 iter 30 value 115.346952 iter 40 value 108.648554 iter 50 value 105.304948 iter 60 value 103.955690 iter 70 value 102.596547 iter 80 value 101.633330 iter 90 value 101.087555 iter 100 value 100.973930 final value 100.973930 stopped after 100 iterations svmRadial ranger Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases RUNIT TEST PROTOCOL -- Thu Sep 11 00:52:31 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 39.371 0.971 126.388
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 32.709 | 0.643 | 33.354 | |
FreqInteractors | 0.203 | 0.010 | 0.214 | |
calculateAAC | 0.035 | 0.003 | 0.037 | |
calculateAutocor | 0.299 | 0.015 | 0.314 | |
calculateCTDC | 0.07 | 0.00 | 0.07 | |
calculateCTDD | 0.493 | 0.000 | 0.494 | |
calculateCTDT | 0.182 | 0.008 | 0.190 | |
calculateCTriad | 0.380 | 0.020 | 0.401 | |
calculateDC | 0.080 | 0.008 | 0.088 | |
calculateF | 0.294 | 0.002 | 0.297 | |
calculateKSAAP | 0.091 | 0.007 | 0.100 | |
calculateQD_Sm | 1.693 | 0.049 | 1.742 | |
calculateTC | 1.492 | 0.157 | 1.648 | |
calculateTC_Sm | 0.258 | 0.005 | 0.263 | |
corr_plot | 32.993 | 0.334 | 33.328 | |
enrichfindP | 0.467 | 0.030 | 8.148 | |
enrichfind_hp | 0.098 | 0.006 | 1.042 | |
enrichplot | 0.345 | 0.001 | 0.345 | |
filter_missing_values | 0.001 | 0.000 | 0.001 | |
getFASTA | 0.506 | 0.007 | 3.716 | |
getHPI | 0.001 | 0.001 | 0.002 | |
get_negativePPI | 0.002 | 0.002 | 0.004 | |
get_positivePPI | 0.000 | 0.000 | 0.001 | |
impute_missing_data | 0.002 | 0.002 | 0.004 | |
plotPPI | 0.079 | 0.002 | 0.082 | |
pred_ensembel | 13.282 | 0.170 | 12.090 | |
var_imp | 33.969 | 0.361 | 34.333 | |