Back to Multiple platform build/check report for BioC 3.19: simplified long |
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This page was generated on 2024-06-28 17:41 -0400 (Fri, 28 Jun 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4760 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" | 4494 |
merida1 | macOS 12.7.4 Monterey | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4508 |
kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4466 |
palomino7 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4362 |
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 987/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.10.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | ||||||||
merida1 | macOS 12.7.4 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | OK | OK | ![]() | ||||||||
palomino7 | Windows Server 2022 Datacenter / x64 | 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: 1.10.0 |
Command: F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz |
StartedAt: 2024-06-27 02:39:00 -0400 (Thu, 27 Jun 2024) |
EndedAt: 2024-06-27 02:44:02 -0400 (Thu, 27 Jun 2024) |
EllapsedTime: 301.9 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz ### ############################################################################## ############################################################################## * using log directory 'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck' * using R version 4.4.0 (2024-04-24 ucrt) * using platform: x86_64-w64-mingw32 * R was compiled by gcc.exe (GCC) 13.2.0 GNU Fortran (GCC) 13.2.0 * running under: Windows Server 2022 x64 (build 20348) * using session charset: UTF-8 * using option '--no-vignettes' * checking for file 'HPiP/DESCRIPTION' ... OK * checking extension type ... Package * this is package 'HPiP' version '1.10.0' * 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 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 ... NOTE 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 FSmethod 34.18 2.05 36.36 var_imp 33.50 1.52 35.02 corr_plot 33.03 1.79 34.83 pred_ensembel 14.89 0.84 11.45 enrichfindP 0.61 0.07 14.40 * 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: 3 NOTEs See 'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log' for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.19-bioc/R/library' * installing *source* package 'HPiP' ... ** 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 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 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 96.985759 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 95.503323 iter 10 value 93.815818 final value 93.813958 converged Fitting Repeat 3 # weights: 103 initial value 96.086269 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 107.015424 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 96.909605 final value 94.467391 converged Fitting Repeat 1 # weights: 305 initial value 98.980938 iter 10 value 94.465059 iter 20 value 94.052907 final value 94.052435 converged Fitting Repeat 2 # weights: 305 initial value 98.648536 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 100.541320 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 97.765678 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 96.464548 final value 94.052434 converged Fitting Repeat 1 # weights: 507 initial value 95.777684 iter 10 value 94.264859 final value 94.264858 converged Fitting Repeat 2 # weights: 507 initial value 112.880852 final value 94.467391 converged Fitting Repeat 3 # weights: 507 initial value 103.638978 final value 94.484206 converged Fitting Repeat 4 # weights: 507 initial value 99.727656 iter 10 value 94.379748 iter 10 value 94.379747 iter 10 value 94.379747 final value 94.379747 converged Fitting Repeat 5 # weights: 507 initial value 96.360551 iter 10 value 89.867571 iter 20 value 87.132656 iter 30 value 86.630964 iter 40 value 82.754418 iter 50 value 82.425641 final value 82.425477 converged Fitting Repeat 1 # weights: 103 initial value 97.137599 iter 10 value 94.504383 iter 20 value 94.488575 iter 30 value 94.116256 iter 40 value 93.928396 iter 50 value 88.354952 iter 60 value 85.329935 iter 70 value 85.059638 iter 80 value 85.015134 iter 90 value 84.611590 iter 100 value 84.489382 final value 84.489382 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 102.987952 iter 10 value 94.487148 iter 20 value 94.171121 iter 30 value 94.127759 iter 40 value 94.123517 iter 50 value 93.192997 iter 60 value 89.291462 iter 70 value 87.676864 iter 80 value 86.330496 iter 90 value 85.018647 iter 100 value 84.150503 final value 84.150503 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 130.074530 iter 10 value 94.470038 iter 20 value 89.365901 iter 30 value 88.047541 iter 40 value 87.264630 iter 50 value 86.260937 iter 60 value 85.653551 iter 70 value 85.230921 iter 80 value 85.103345 iter 90 value 85.080088 final value 85.078429 converged Fitting Repeat 4 # weights: 103 initial value 112.377681 iter 10 value 94.573486 iter 20 value 93.704654 iter 30 value 87.048148 iter 40 value 86.611469 iter 50 value 86.147011 iter 60 value 85.505017 iter 70 value 85.489840 final value 85.489670 converged Fitting Repeat 5 # weights: 103 initial value 97.103526 iter 10 value 94.488600 iter 20 value 94.390895 iter 30 value 92.240677 iter 40 value 86.725942 iter 50 value 86.401047 iter 60 value 86.259943 iter 70 value 86.199429 iter 80 value 85.431396 iter 90 value 84.107902 iter 100 value 83.839985 final value 83.839985 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 108.910782 iter 10 value 94.644419 iter 20 value 93.703915 iter 30 value 90.858897 iter 40 value 90.568428 iter 50 value 90.160440 iter 60 value 88.407810 iter 70 value 86.648501 iter 80 value 84.937777 iter 90 value 84.455381 iter 100 value 83.615378 final value 83.615378 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 99.115528 iter 10 value 89.021055 iter 20 value 87.132604 iter 30 value 85.788335 iter 40 value 85.068938 iter 50 value 84.926702 iter 60 value 84.199389 iter 70 value 83.921160 iter 80 value 83.854820 iter 90 value 83.601465 iter 100 value 83.470622 final value 83.470622 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 112.136937 iter 10 value 94.251197 iter 20 value 90.256512 iter 30 value 89.126893 iter 40 value 86.790849 iter 50 value 85.236787 iter 60 value 84.923490 iter 70 value 84.914046 iter 80 value 84.899761 iter 90 value 84.721820 iter 100 value 83.543085 final value 83.543085 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 106.391354 iter 10 value 94.486268 iter 20 value 94.381139 iter 30 value 93.093010 iter 40 value 87.864785 iter 50 value 85.927454 iter 60 value 85.427492 iter 70 value 85.026093 iter 80 value 84.712828 iter 90 value 83.795334 iter 100 value 83.073522 final value 83.073522 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 135.856002 iter 10 value 98.680571 iter 20 value 95.970953 iter 30 value 94.497904 iter 40 value 94.329795 iter 50 value 91.866745 iter 60 value 90.478835 iter 70 value 87.991631 iter 80 value 85.716395 iter 90 value 84.090491 iter 100 value 83.529022 final value 83.529022 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 111.452202 iter 10 value 94.501022 iter 20 value 90.110397 iter 30 value 89.304545 iter 40 value 88.946695 iter 50 value 87.171865 iter 60 value 86.236405 iter 70 value 85.602546 iter 80 value 84.920041 iter 90 value 84.376855 iter 100 value 83.603839 final value 83.603839 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 126.526981 iter 10 value 94.190187 iter 20 value 87.183749 iter 30 value 86.441758 iter 40 value 85.447521 iter 50 value 85.207673 iter 60 value 84.996348 iter 70 value 84.432913 iter 80 value 83.551378 iter 90 value 83.122362 iter 100 value 82.715995 final value 82.715995 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 107.260865 iter 10 value 94.257300 iter 20 value 87.514923 iter 30 value 86.209609 iter 40 value 85.023562 iter 50 value 83.127303 iter 60 value 82.857567 iter 70 value 82.576632 iter 80 value 82.529300 iter 90 value 82.496913 iter 100 value 82.479063 final value 82.479063 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 114.129422 iter 10 value 96.168633 iter 20 value 90.907092 iter 30 value 87.014069 iter 40 value 86.544249 iter 50 value 85.167154 iter 60 value 84.871831 iter 70 value 84.113314 iter 80 value 83.103647 iter 90 value 82.838063 iter 100 value 82.336738 final value 82.336738 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 113.202046 iter 10 value 94.657395 iter 20 value 94.393884 iter 30 value 88.961351 iter 40 value 86.676987 iter 50 value 86.044611 iter 60 value 85.064013 iter 70 value 84.746588 iter 80 value 83.715932 iter 90 value 82.671702 iter 100 value 82.329430 final value 82.329430 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.632543 final value 94.485807 converged Fitting Repeat 2 # weights: 103 initial value 95.669968 final value 94.485990 converged Fitting Repeat 3 # weights: 103 initial value 94.871511 final value 94.486052 converged Fitting Repeat 4 # weights: 103 initial value 95.849762 final value 94.485978 converged Fitting Repeat 5 # weights: 103 initial value 94.551378 final value 94.485716 converged Fitting Repeat 1 # weights: 305 initial value 104.917308 iter 10 value 94.472348 iter 20 value 94.468103 final value 94.467414 converged Fitting Repeat 2 # weights: 305 initial value 111.329756 iter 10 value 94.270307 iter 20 value 94.266457 iter 30 value 93.070848 iter 40 value 86.338280 iter 50 value 86.181790 iter 60 value 86.178950 iter 70 value 85.525992 final value 85.523948 converged Fitting Repeat 3 # weights: 305 initial value 102.165747 iter 10 value 94.472734 final value 94.469709 converged Fitting Repeat 4 # weights: 305 initial value 100.987056 iter 10 value 94.489303 iter 20 value 94.314118 iter 30 value 87.422743 iter 40 value 87.320229 iter 50 value 86.643562 iter 60 value 86.107550 iter 70 value 86.106893 final value 86.105726 converged Fitting Repeat 5 # weights: 305 initial value 98.406425 iter 10 value 94.485722 iter 20 value 90.129636 iter 30 value 86.282869 iter 40 value 86.266871 iter 50 value 85.323911 iter 60 value 85.213108 final value 85.211734 converged Fitting Repeat 1 # weights: 507 initial value 118.919955 iter 10 value 94.492568 iter 20 value 94.479696 final value 94.467485 converged Fitting Repeat 2 # weights: 507 initial value 103.909297 iter 10 value 94.491594 iter 20 value 94.467694 iter 30 value 92.421739 iter 40 value 92.307795 iter 50 value 92.108175 iter 60 value 92.105468 iter 70 value 92.105158 final value 92.105066 converged Fitting Repeat 3 # weights: 507 initial value 114.105831 iter 10 value 94.488953 iter 20 value 93.865175 iter 30 value 93.852322 final value 93.851283 converged Fitting Repeat 4 # weights: 507 initial value 105.875755 iter 10 value 94.475596 iter 20 value 94.467741 final value 94.467689 converged Fitting Repeat 5 # weights: 507 initial value 101.928454 iter 10 value 91.178021 iter 20 value 90.752781 iter 30 value 90.475887 iter 40 value 90.443008 iter 50 value 88.475414 iter 60 value 87.539408 iter 70 value 86.438006 iter 80 value 86.432359 iter 90 value 86.426055 iter 100 value 86.338714 final value 86.338714 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 98.113155 final value 94.052911 converged Fitting Repeat 2 # weights: 103 initial value 95.190483 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 98.622078 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 97.328389 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 96.371449 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 98.751902 final value 92.701657 converged Fitting Repeat 2 # weights: 305 initial value 102.941875 final value 93.473743 converged Fitting Repeat 3 # weights: 305 initial value 98.469470 iter 10 value 93.994006 iter 10 value 93.994006 iter 10 value 93.994006 final value 93.994006 converged Fitting Repeat 4 # weights: 305 initial value 103.392713 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 102.822540 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 95.184319 final value 94.052910 converged Fitting Repeat 2 # weights: 507 initial value 98.049432 final value 94.052910 converged Fitting Repeat 3 # weights: 507 initial value 109.571079 iter 10 value 94.052448 iter 10 value 94.052448 iter 10 value 94.052448 final value 94.052448 converged Fitting Repeat 4 # weights: 507 initial value 100.656316 iter 10 value 88.820249 iter 20 value 86.563862 final value 86.563710 converged Fitting Repeat 5 # weights: 507 initial value 104.008505 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 96.509637 iter 10 value 94.065760 iter 20 value 92.271372 iter 30 value 89.739046 iter 40 value 87.100732 iter 50 value 85.494474 iter 60 value 85.135428 iter 70 value 85.073108 iter 80 value 85.062017 final value 85.061926 converged Fitting Repeat 2 # weights: 103 initial value 99.359244 iter 10 value 94.287526 iter 20 value 93.998195 iter 30 value 92.409765 iter 40 value 91.154493 iter 50 value 91.029095 iter 60 value 89.878248 iter 70 value 86.187563 iter 80 value 84.944521 iter 90 value 84.420421 iter 100 value 83.670232 final value 83.670232 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 108.741412 iter 10 value 93.653748 iter 20 value 92.352760 iter 30 value 84.801916 iter 40 value 84.445549 iter 50 value 84.003997 iter 60 value 82.974880 iter 70 value 82.062866 iter 80 value 81.333379 iter 90 value 81.210742 iter 100 value 81.210535 final value 81.210535 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 96.112835 iter 10 value 94.003512 iter 20 value 90.620505 iter 30 value 88.120355 iter 40 value 87.755890 iter 50 value 87.173779 iter 60 value 85.739079 iter 70 value 85.491915 iter 80 value 85.181728 iter 90 value 85.069491 iter 100 value 85.061959 final value 85.061959 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 102.536404 iter 10 value 94.045965 iter 20 value 93.557950 iter 30 value 92.425994 iter 40 value 86.627194 iter 50 value 83.075647 iter 60 value 82.720538 iter 70 value 82.518742 iter 80 value 82.454063 iter 90 value 82.369307 iter 100 value 82.095782 final value 82.095782 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 101.683394 iter 10 value 94.085380 iter 20 value 93.986233 iter 30 value 89.644604 iter 40 value 88.807751 iter 50 value 86.068102 iter 60 value 85.132582 iter 70 value 84.011199 iter 80 value 83.189342 iter 90 value 82.769572 iter 100 value 82.686424 final value 82.686424 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 101.071612 iter 10 value 94.038069 iter 20 value 93.563223 iter 30 value 93.537389 iter 40 value 92.201065 iter 50 value 86.449419 iter 60 value 85.813814 iter 70 value 85.083278 iter 80 value 83.776263 iter 90 value 82.928390 iter 100 value 80.574264 final value 80.574264 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 101.042179 iter 10 value 94.043879 iter 20 value 91.397492 iter 30 value 87.954420 iter 40 value 85.595101 iter 50 value 85.462533 iter 60 value 85.109786 iter 70 value 84.440652 iter 80 value 83.278515 iter 90 value 82.953350 iter 100 value 82.592482 final value 82.592482 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.720622 iter 10 value 93.620575 iter 20 value 92.780473 iter 30 value 85.195150 iter 40 value 84.061824 iter 50 value 82.745167 iter 60 value 81.993452 iter 70 value 80.944937 iter 80 value 80.509223 iter 90 value 80.467714 iter 100 value 80.427215 final value 80.427215 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 114.399444 iter 10 value 94.450700 iter 20 value 91.424737 iter 30 value 90.865815 iter 40 value 90.630347 iter 50 value 88.937368 iter 60 value 84.533047 iter 70 value 83.406588 iter 80 value 81.231523 iter 90 value 80.465139 iter 100 value 80.187617 final value 80.187617 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 103.608192 iter 10 value 93.962315 iter 20 value 93.435453 iter 30 value 93.412175 iter 40 value 92.259046 iter 50 value 88.254695 iter 60 value 85.083219 iter 70 value 84.614538 iter 80 value 84.376775 iter 90 value 83.885092 iter 100 value 82.275836 final value 82.275836 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 115.787650 iter 10 value 91.765165 iter 20 value 85.651341 iter 30 value 85.423674 iter 40 value 84.664714 iter 50 value 83.278047 iter 60 value 83.049788 iter 70 value 82.763215 iter 80 value 82.473329 iter 90 value 81.556403 iter 100 value 81.151866 final value 81.151866 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.500408 iter 10 value 94.243864 iter 20 value 90.173262 iter 30 value 85.506008 iter 40 value 85.069718 iter 50 value 84.150692 iter 60 value 82.094383 iter 70 value 81.104205 iter 80 value 80.969253 iter 90 value 80.699418 iter 100 value 80.463073 final value 80.463073 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 105.067302 iter 10 value 94.241549 iter 20 value 93.365709 iter 30 value 86.816193 iter 40 value 85.533483 iter 50 value 85.238825 iter 60 value 83.857391 iter 70 value 81.399734 iter 80 value 80.514472 iter 90 value 80.056494 iter 100 value 79.914480 final value 79.914480 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 120.017351 iter 10 value 93.588980 iter 20 value 91.369891 iter 30 value 86.560426 iter 40 value 86.362997 iter 50 value 85.416930 iter 60 value 85.118959 iter 70 value 82.900469 iter 80 value 82.414556 iter 90 value 81.767104 iter 100 value 81.340226 final value 81.340226 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 98.849065 final value 94.054456 converged Fitting Repeat 2 # weights: 103 initial value 103.280216 iter 10 value 93.283744 iter 20 value 93.276115 iter 30 value 93.275259 final value 93.274475 converged Fitting Repeat 3 # weights: 103 initial value 103.494922 final value 94.054377 converged Fitting Repeat 4 # weights: 103 initial value 100.955890 iter 10 value 93.330487 iter 20 value 93.328944 iter 30 value 93.328544 iter 40 value 93.286853 iter 50 value 92.205582 iter 60 value 86.107304 iter 70 value 86.101366 iter 80 value 86.093318 iter 90 value 86.092350 iter 100 value 86.088982 final value 86.088982 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 95.330831 final value 94.054682 converged Fitting Repeat 1 # weights: 305 initial value 108.742484 iter 10 value 94.057848 iter 20 value 94.014902 final value 93.328683 converged Fitting Repeat 2 # weights: 305 initial value 103.746287 iter 10 value 94.057661 iter 20 value 94.052942 final value 94.052927 converged Fitting Repeat 3 # weights: 305 initial value 101.132826 iter 10 value 93.333585 iter 20 value 93.331540 iter 30 value 93.328914 iter 40 value 89.805910 iter 50 value 88.078927 iter 60 value 88.067621 iter 70 value 87.207465 iter 80 value 86.340017 iter 90 value 86.159742 iter 100 value 85.953337 final value 85.953337 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 103.760974 iter 10 value 94.011949 iter 20 value 93.960885 iter 30 value 93.958930 iter 40 value 93.874180 iter 50 value 93.871731 iter 60 value 93.354189 iter 70 value 93.291642 iter 80 value 92.098433 iter 90 value 92.093808 final value 92.093686 converged Fitting Repeat 5 # weights: 305 initial value 98.824543 iter 10 value 94.057752 final value 94.052932 converged Fitting Repeat 1 # weights: 507 initial value 96.554339 iter 10 value 93.883833 iter 20 value 93.197985 iter 30 value 93.189059 iter 40 value 93.011184 iter 50 value 92.827498 iter 60 value 92.793767 iter 70 value 92.792551 iter 80 value 92.792135 iter 90 value 92.790203 iter 100 value 92.790124 final value 92.790124 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 100.242533 iter 10 value 93.338472 iter 20 value 93.335290 iter 30 value 93.328664 final value 93.325275 converged Fitting Repeat 3 # weights: 507 initial value 107.776103 iter 10 value 93.337530 iter 20 value 93.335675 iter 30 value 87.636013 iter 40 value 84.404407 iter 50 value 84.134792 iter 60 value 84.028354 iter 70 value 84.027525 iter 80 value 83.015172 iter 90 value 81.020032 iter 100 value 80.340204 final value 80.340204 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 96.471650 iter 10 value 94.060485 iter 20 value 94.057110 iter 30 value 93.910683 iter 40 value 93.410950 iter 50 value 93.294140 final value 93.274867 converged Fitting Repeat 5 # weights: 507 initial value 102.224880 iter 10 value 93.438951 iter 20 value 93.337592 iter 30 value 93.330651 iter 40 value 93.330433 iter 50 value 93.286900 iter 60 value 93.269789 final value 93.269787 converged Fitting Repeat 1 # weights: 103 initial value 104.109440 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 97.303579 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 106.431234 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 102.417432 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 95.751340 iter 10 value 85.842660 iter 20 value 85.840152 final value 85.840146 converged Fitting Repeat 1 # weights: 305 initial value 101.853395 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 100.136442 final value 94.088889 converged Fitting Repeat 3 # weights: 305 initial value 95.110085 iter 10 value 94.469963 final value 94.466832 converged Fitting Repeat 4 # weights: 305 initial value 101.312440 iter 10 value 88.419573 iter 20 value 88.251664 iter 30 value 88.250780 final value 88.250778 converged Fitting Repeat 5 # weights: 305 initial value 100.666058 iter 10 value 94.448481 iter 20 value 94.433727 final value 94.381461 converged Fitting Repeat 1 # weights: 507 initial value 97.572033 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 107.612513 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 103.311498 final value 94.482478 converged Fitting Repeat 4 # weights: 507 initial value 99.995994 iter 10 value 94.430300 final value 94.430236 converged Fitting Repeat 5 # weights: 507 initial value 111.720056 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 98.951566 iter 10 value 94.484449 iter 20 value 88.232764 iter 30 value 86.011868 iter 40 value 85.749816 iter 50 value 85.696021 iter 60 value 85.610548 iter 70 value 85.247980 iter 80 value 85.174479 iter 90 value 85.158805 final value 85.157743 converged Fitting Repeat 2 # weights: 103 initial value 99.377328 iter 10 value 94.518068 iter 20 value 94.486430 iter 30 value 92.570462 iter 40 value 90.774827 iter 50 value 84.494612 iter 60 value 84.134314 iter 70 value 84.085477 iter 80 value 83.792794 iter 90 value 83.380015 iter 100 value 83.369076 final value 83.369076 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 96.742972 iter 10 value 94.470391 iter 20 value 93.216780 iter 30 value 93.123147 iter 40 value 92.828014 iter 50 value 92.777472 iter 60 value 91.572263 iter 70 value 91.321078 iter 80 value 91.309679 final value 91.309676 converged Fitting Repeat 4 # weights: 103 initial value 101.341855 iter 10 value 94.389208 iter 20 value 89.307990 iter 30 value 87.474617 iter 40 value 86.056796 iter 50 value 85.924515 iter 60 value 85.763334 iter 70 value 85.680125 iter 80 value 85.652862 iter 80 value 85.652862 iter 80 value 85.652862 final value 85.652862 converged Fitting Repeat 5 # weights: 103 initial value 109.683917 iter 10 value 94.311779 iter 20 value 88.482677 iter 30 value 85.349777 iter 40 value 84.744114 iter 50 value 84.141462 iter 60 value 83.637838 iter 70 value 83.504911 iter 80 value 83.451365 iter 90 value 83.392216 iter 100 value 83.367835 final value 83.367835 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 110.261583 iter 10 value 94.415819 iter 20 value 92.151172 iter 30 value 89.981287 iter 40 value 85.934530 iter 50 value 84.543349 iter 60 value 84.416443 iter 70 value 84.296560 iter 80 value 83.240516 iter 90 value 82.665545 iter 100 value 82.575804 final value 82.575804 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.144731 iter 10 value 95.895926 iter 20 value 89.897208 iter 30 value 85.993392 iter 40 value 85.039996 iter 50 value 84.096921 iter 60 value 83.159403 iter 70 value 82.808386 iter 80 value 82.749182 iter 90 value 82.685216 iter 100 value 82.624726 final value 82.624726 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 120.544648 iter 10 value 95.405060 iter 20 value 94.362138 iter 30 value 87.119578 iter 40 value 86.635206 iter 50 value 85.790319 iter 60 value 85.483091 iter 70 value 85.226524 iter 80 value 83.743977 iter 90 value 83.290559 iter 100 value 82.988988 final value 82.988988 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 107.597397 iter 10 value 88.364174 iter 20 value 86.556720 iter 30 value 85.748923 iter 40 value 85.469284 iter 50 value 85.418310 iter 60 value 85.366789 iter 70 value 85.120348 iter 80 value 83.554492 iter 90 value 82.850486 iter 100 value 82.347261 final value 82.347261 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 103.561296 iter 10 value 94.625784 iter 20 value 92.044821 iter 30 value 87.960847 iter 40 value 86.820992 iter 50 value 85.624833 iter 60 value 83.780347 iter 70 value 83.494213 iter 80 value 83.386127 iter 90 value 83.181269 iter 100 value 82.992845 final value 82.992845 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 108.260024 iter 10 value 90.424206 iter 20 value 85.848314 iter 30 value 83.325686 iter 40 value 83.143364 iter 50 value 82.465179 iter 60 value 82.444961 iter 70 value 82.407811 iter 80 value 82.388887 iter 90 value 82.375870 iter 100 value 82.298368 final value 82.298368 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 140.595566 iter 10 value 95.249281 iter 20 value 93.712427 iter 30 value 92.532615 iter 40 value 87.147709 iter 50 value 84.047156 iter 60 value 83.111330 iter 70 value 82.878886 iter 80 value 82.546462 iter 90 value 82.331172 iter 100 value 82.272262 final value 82.272262 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 114.588771 iter 10 value 93.862320 iter 20 value 87.424545 iter 30 value 83.454960 iter 40 value 82.489686 iter 50 value 82.341604 iter 60 value 82.143710 iter 70 value 82.121860 iter 80 value 82.112638 iter 90 value 82.028833 iter 100 value 81.908112 final value 81.908112 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 103.733690 iter 10 value 94.832913 iter 20 value 86.364128 iter 30 value 85.870692 iter 40 value 85.387456 iter 50 value 84.595732 iter 60 value 84.130696 iter 70 value 83.466324 iter 80 value 83.026457 iter 90 value 82.559295 iter 100 value 82.480551 final value 82.480551 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 105.052727 iter 10 value 94.602594 iter 20 value 89.702355 iter 30 value 87.740681 iter 40 value 85.693847 iter 50 value 85.241875 iter 60 value 83.663281 iter 70 value 82.967859 iter 80 value 82.768254 iter 90 value 82.625410 iter 100 value 82.490060 final value 82.490060 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 100.373698 final value 94.485749 converged Fitting Repeat 2 # weights: 103 initial value 100.131113 final value 94.486081 converged Fitting Repeat 3 # weights: 103 initial value 96.236120 final value 94.485888 converged Fitting Repeat 4 # weights: 103 initial value 95.347922 final value 94.485544 converged Fitting Repeat 5 # weights: 103 initial value 98.791336 final value 94.486020 converged Fitting Repeat 1 # weights: 305 initial value 104.030330 iter 10 value 94.489531 iter 20 value 94.484342 iter 30 value 94.325853 iter 40 value 94.203670 iter 50 value 91.311465 iter 60 value 87.533744 final value 87.533661 converged Fitting Repeat 2 # weights: 305 initial value 100.188295 iter 10 value 94.359466 iter 20 value 94.354517 iter 30 value 92.376904 iter 40 value 85.327046 iter 50 value 83.269863 iter 60 value 82.903186 iter 70 value 82.620913 iter 80 value 82.605322 iter 90 value 82.583645 iter 100 value 82.557847 final value 82.557847 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 96.271461 iter 10 value 94.489095 iter 20 value 94.217763 iter 30 value 92.224324 iter 40 value 91.290732 final value 91.278460 converged Fitting Repeat 4 # weights: 305 initial value 102.636748 iter 10 value 94.489235 iter 20 value 94.482744 iter 30 value 93.925707 iter 40 value 87.979091 iter 50 value 87.966376 iter 60 value 85.836969 iter 70 value 84.826501 iter 80 value 84.813494 iter 90 value 84.547800 iter 100 value 84.533028 final value 84.533028 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 96.369596 iter 10 value 94.489124 iter 20 value 94.484272 iter 30 value 86.914448 iter 40 value 86.385427 iter 50 value 86.335948 iter 60 value 86.331998 final value 86.331783 converged Fitting Repeat 1 # weights: 507 initial value 98.205030 iter 10 value 94.490743 iter 20 value 94.482613 iter 30 value 88.937083 iter 40 value 87.060467 iter 50 value 86.244522 iter 60 value 84.284227 iter 70 value 84.278753 final value 84.278129 converged Fitting Repeat 2 # weights: 507 initial value 100.563257 iter 10 value 94.492210 iter 20 value 94.464397 iter 30 value 87.158525 iter 40 value 83.759943 iter 50 value 82.135099 iter 60 value 81.542605 iter 70 value 81.464459 iter 80 value 81.120475 iter 90 value 81.014989 iter 100 value 80.970075 final value 80.970075 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 96.817665 iter 10 value 94.492496 iter 20 value 94.484727 iter 30 value 92.216337 iter 40 value 87.865589 iter 50 value 87.824273 iter 60 value 87.785584 iter 70 value 87.734311 iter 80 value 85.911124 iter 90 value 85.484916 iter 100 value 85.046150 final value 85.046150 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 97.963277 iter 10 value 94.491240 iter 20 value 88.105021 iter 30 value 87.518862 iter 40 value 86.489639 iter 50 value 86.467114 iter 60 value 86.467002 iter 70 value 86.459107 iter 80 value 85.408825 iter 90 value 85.379597 iter 100 value 85.379469 final value 85.379469 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 105.326475 iter 10 value 94.492639 iter 20 value 94.461565 iter 30 value 92.588774 iter 40 value 92.588179 iter 40 value 92.588178 iter 40 value 92.588178 final value 92.588178 converged Fitting Repeat 1 # weights: 103 initial value 102.424510 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 99.625474 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 95.066511 final value 94.484207 converged Fitting Repeat 4 # weights: 103 initial value 108.279417 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 97.033048 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 101.567234 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 96.956121 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 94.139296 iter 10 value 90.599074 iter 20 value 90.433077 iter 30 value 90.369813 final value 90.369812 converged Fitting Repeat 4 # weights: 305 initial value 101.140097 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 102.964706 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 97.394927 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 102.235258 iter 10 value 94.482954 iter 10 value 94.482954 iter 10 value 94.482954 final value 94.482954 converged Fitting Repeat 3 # weights: 507 initial value 98.079515 iter 10 value 85.126779 iter 20 value 85.097494 iter 30 value 84.751155 iter 40 value 84.569742 iter 50 value 84.364424 final value 84.351004 converged Fitting Repeat 4 # weights: 507 initial value 103.440546 iter 10 value 94.186667 iter 10 value 94.186667 iter 10 value 94.186667 final value 94.186667 converged Fitting Repeat 5 # weights: 507 initial value 97.955678 iter 10 value 87.196092 iter 20 value 86.464909 final value 86.464077 converged Fitting Repeat 1 # weights: 103 initial value 102.761336 iter 10 value 94.416782 iter 20 value 93.208071 iter 30 value 84.975263 iter 40 value 82.886892 iter 50 value 82.282621 iter 60 value 82.259569 iter 70 value 81.415935 iter 80 value 80.000697 iter 90 value 79.628565 iter 100 value 79.595020 final value 79.595020 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 101.135638 iter 10 value 94.502660 iter 20 value 89.168783 iter 30 value 87.886271 iter 40 value 86.649604 iter 50 value 84.424330 iter 60 value 84.261481 iter 70 value 83.167990 iter 80 value 80.363160 iter 90 value 80.251523 iter 100 value 79.931474 final value 79.931474 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 96.941144 iter 10 value 94.488221 iter 20 value 94.007746 iter 30 value 92.199380 iter 40 value 85.415002 iter 50 value 84.394602 iter 60 value 84.269648 iter 70 value 80.181102 iter 80 value 79.600213 iter 90 value 79.571640 final value 79.557711 converged Fitting Repeat 4 # weights: 103 initial value 98.834025 iter 10 value 94.333726 iter 20 value 94.329063 iter 30 value 92.865813 iter 40 value 85.779477 iter 50 value 82.656090 iter 60 value 82.192373 iter 70 value 81.523370 iter 80 value 81.239654 iter 90 value 81.096470 iter 100 value 80.569711 final value 80.569711 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 104.754691 iter 10 value 94.491173 iter 20 value 86.824872 iter 30 value 86.437630 iter 40 value 86.024819 iter 50 value 83.726850 iter 60 value 82.366312 iter 70 value 82.215697 iter 80 value 82.205801 iter 90 value 82.186816 final value 82.185220 converged Fitting Repeat 1 # weights: 305 initial value 104.777809 iter 10 value 94.572539 iter 20 value 87.227500 iter 30 value 83.510542 iter 40 value 81.691396 iter 50 value 80.254122 iter 60 value 79.930277 iter 70 value 79.805490 iter 80 value 79.782532 iter 90 value 79.711302 iter 100 value 79.306486 final value 79.306486 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 99.458750 iter 10 value 94.509279 iter 20 value 94.160214 iter 30 value 93.868849 iter 40 value 93.136187 iter 50 value 87.492877 iter 60 value 86.651395 iter 70 value 85.498708 iter 80 value 81.059654 iter 90 value 79.349502 iter 100 value 78.942130 final value 78.942130 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 98.436241 iter 10 value 87.158287 iter 20 value 82.739676 iter 30 value 80.311978 iter 40 value 78.917279 iter 50 value 78.377693 iter 60 value 78.233472 iter 70 value 77.979034 iter 80 value 77.891187 iter 90 value 77.878280 iter 100 value 77.876153 final value 77.876153 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 99.413501 iter 10 value 94.121832 iter 20 value 92.868702 iter 30 value 86.643682 iter 40 value 85.821973 iter 50 value 85.548861 iter 60 value 82.719047 iter 70 value 82.234539 iter 80 value 82.097482 iter 90 value 81.167157 iter 100 value 80.217827 final value 80.217827 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 112.512072 iter 10 value 94.420658 iter 20 value 85.972375 iter 30 value 84.571015 iter 40 value 84.373561 iter 50 value 83.087279 iter 60 value 80.323719 iter 70 value 79.451249 iter 80 value 79.192933 iter 90 value 78.935521 iter 100 value 78.544450 final value 78.544450 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 109.220810 iter 10 value 95.602868 iter 20 value 94.037011 iter 30 value 93.899651 iter 40 value 92.922272 iter 50 value 87.261475 iter 60 value 83.177224 iter 70 value 80.181283 iter 80 value 79.245940 iter 90 value 78.677437 iter 100 value 78.438647 final value 78.438647 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 122.105076 iter 10 value 94.506052 iter 20 value 94.326293 iter 30 value 90.067328 iter 40 value 87.664965 iter 50 value 85.199881 iter 60 value 81.171367 iter 70 value 80.039052 iter 80 value 79.304909 iter 90 value 78.741922 iter 100 value 78.587395 final value 78.587395 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 118.584677 iter 10 value 94.365417 iter 20 value 89.329294 iter 30 value 86.161007 iter 40 value 84.873994 iter 50 value 84.652829 iter 60 value 82.135963 iter 70 value 81.588233 iter 80 value 79.898891 iter 90 value 79.210983 iter 100 value 78.886845 final value 78.886845 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 128.793936 iter 10 value 94.954010 iter 20 value 94.258950 iter 30 value 88.008533 iter 40 value 86.859279 iter 50 value 86.105945 iter 60 value 81.433345 iter 70 value 80.233032 iter 80 value 78.661442 iter 90 value 78.020939 iter 100 value 77.826901 final value 77.826901 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 118.605207 iter 10 value 94.843189 iter 20 value 94.095219 iter 30 value 93.472627 iter 40 value 87.566014 iter 50 value 84.417371 iter 60 value 79.737938 iter 70 value 79.373874 iter 80 value 79.062951 iter 90 value 78.505758 iter 100 value 78.274648 final value 78.274648 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 106.658725 iter 10 value 94.485907 iter 10 value 94.485907 iter 10 value 94.485906 final value 94.485906 converged Fitting Repeat 2 # weights: 103 initial value 96.696426 final value 94.485828 converged Fitting Repeat 3 # weights: 103 initial value 96.280425 iter 10 value 88.843260 iter 20 value 85.193227 iter 30 value 85.146585 iter 40 value 85.142815 iter 50 value 85.121714 iter 60 value 84.844654 iter 70 value 84.770416 iter 80 value 84.767622 iter 90 value 84.763648 final value 84.762930 converged Fitting Repeat 4 # weights: 103 initial value 101.524485 iter 10 value 94.277111 iter 20 value 94.186035 iter 30 value 92.163042 iter 40 value 92.162230 final value 92.161873 converged Fitting Repeat 5 # weights: 103 initial value 97.758137 final value 94.277065 converged Fitting Repeat 1 # weights: 305 initial value 110.074911 iter 10 value 94.489216 iter 20 value 94.478107 iter 30 value 88.760359 iter 40 value 86.202862 iter 50 value 84.906791 iter 60 value 84.876201 iter 70 value 84.868930 iter 80 value 84.786293 iter 90 value 82.885295 iter 100 value 82.767151 final value 82.767151 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 104.576425 iter 10 value 93.894200 iter 20 value 93.891903 iter 30 value 89.254784 iter 40 value 88.801202 final value 88.793845 converged Fitting Repeat 3 # weights: 305 initial value 95.752178 iter 10 value 94.489062 iter 20 value 94.351142 iter 30 value 94.240700 iter 40 value 92.794620 iter 50 value 91.985418 iter 60 value 90.832449 iter 70 value 90.675210 iter 70 value 90.675209 iter 70 value 90.675209 final value 90.675209 converged Fitting Repeat 4 # weights: 305 initial value 99.508141 iter 10 value 94.488983 iter 20 value 94.484212 iter 30 value 93.874656 iter 40 value 93.739941 final value 93.739538 converged Fitting Repeat 5 # weights: 305 initial value 108.310819 iter 10 value 94.170270 iter 20 value 93.795214 iter 30 value 92.902389 iter 40 value 92.874401 iter 50 value 92.871492 iter 60 value 92.871285 iter 70 value 92.871027 final value 92.870925 converged Fitting Repeat 1 # weights: 507 initial value 115.804455 iter 10 value 94.486546 iter 20 value 94.366174 iter 30 value 84.660245 iter 40 value 82.647288 iter 50 value 82.462224 iter 60 value 82.431950 final value 82.430212 converged Fitting Repeat 2 # weights: 507 initial value 116.703133 iter 10 value 94.331739 iter 20 value 94.328018 iter 30 value 83.958046 iter 40 value 83.580524 iter 50 value 83.223123 iter 60 value 83.204980 iter 70 value 82.397717 iter 80 value 81.045960 iter 90 value 80.990790 iter 100 value 80.990483 final value 80.990483 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 101.207558 iter 10 value 93.880332 iter 20 value 93.875148 iter 30 value 93.772632 iter 40 value 93.754070 iter 50 value 93.753505 iter 60 value 93.751857 iter 70 value 93.737853 iter 80 value 93.221682 iter 90 value 84.521155 iter 100 value 83.404673 final value 83.404673 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 103.351851 iter 10 value 93.823136 iter 20 value 93.780887 iter 30 value 88.147593 iter 40 value 86.874434 iter 50 value 86.832676 iter 60 value 86.729309 iter 70 value 86.619874 iter 80 value 86.540554 iter 90 value 86.372798 iter 100 value 86.332727 final value 86.332727 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 116.301910 iter 10 value 94.492978 iter 20 value 94.452033 iter 30 value 90.789806 iter 40 value 87.341612 iter 50 value 87.299721 iter 60 value 85.438571 iter 70 value 85.305729 iter 80 value 85.305027 final value 85.305026 converged Fitting Repeat 1 # weights: 103 initial value 99.938309 final value 94.052878 converged Fitting Repeat 2 # weights: 103 initial value 95.752369 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 99.735077 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 96.233273 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 97.984703 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 95.280150 iter 10 value 89.845074 iter 20 value 81.909958 iter 30 value 79.494765 iter 40 value 79.147633 iter 50 value 79.117885 iter 60 value 78.194895 final value 78.194863 converged Fitting Repeat 2 # weights: 305 initial value 104.056820 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 109.918678 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 101.958934 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 97.662584 final value 94.032967 converged Fitting Repeat 1 # weights: 507 initial value 113.659926 iter 10 value 94.001767 iter 20 value 93.674745 iter 30 value 93.578708 final value 93.578654 converged Fitting Repeat 2 # weights: 507 initial value 101.978537 iter 10 value 91.253389 iter 20 value 89.336393 iter 30 value 89.335036 iter 40 value 89.334969 final value 89.334957 converged Fitting Repeat 3 # weights: 507 initial value 129.611112 final value 94.032967 converged Fitting Repeat 4 # weights: 507 initial value 95.933107 iter 10 value 91.077750 iter 20 value 85.867984 iter 30 value 85.858909 final value 85.858892 converged Fitting Repeat 5 # weights: 507 initial value 120.772863 iter 10 value 93.426574 iter 10 value 93.426573 iter 10 value 93.426573 final value 93.426573 converged Fitting Repeat 1 # weights: 103 initial value 100.296953 iter 10 value 94.027865 iter 20 value 93.439493 iter 30 value 93.178420 iter 40 value 92.117679 iter 50 value 83.474436 iter 60 value 80.128963 iter 70 value 80.034003 iter 80 value 79.969608 iter 90 value 79.505904 iter 100 value 78.454428 final value 78.454428 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 97.612163 iter 10 value 94.058144 iter 20 value 93.183675 iter 30 value 86.067505 iter 40 value 85.542100 iter 50 value 85.243915 iter 60 value 84.671948 iter 70 value 80.282806 iter 80 value 80.275282 final value 80.275146 converged Fitting Repeat 3 # weights: 103 initial value 98.397497 iter 10 value 86.499427 iter 20 value 82.025871 iter 30 value 81.253344 iter 40 value 79.966557 iter 50 value 79.618518 iter 60 value 79.153803 iter 70 value 79.110628 final value 79.110625 converged Fitting Repeat 4 # weights: 103 initial value 105.667161 iter 10 value 93.924208 iter 20 value 81.478009 iter 30 value 80.485095 iter 40 value 79.616821 iter 50 value 79.329321 final value 79.329224 converged Fitting Repeat 5 # weights: 103 initial value 99.665670 iter 10 value 94.005936 iter 20 value 83.032157 iter 30 value 80.853857 iter 40 value 80.257170 iter 50 value 79.558123 iter 60 value 79.110642 final value 79.110625 converged Fitting Repeat 1 # weights: 305 initial value 120.239342 iter 10 value 90.729597 iter 20 value 81.588306 iter 30 value 79.441110 iter 40 value 78.315823 iter 50 value 77.442877 iter 60 value 76.816347 iter 70 value 76.638314 iter 80 value 76.290631 iter 90 value 75.984847 iter 100 value 75.781126 final value 75.781126 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 99.520347 iter 10 value 94.709907 iter 20 value 85.825618 iter 30 value 85.120928 iter 40 value 84.859088 iter 50 value 79.620677 iter 60 value 77.165948 iter 70 value 76.470324 iter 80 value 76.315073 iter 90 value 76.221928 iter 100 value 75.812556 final value 75.812556 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 99.187405 iter 10 value 93.929113 iter 20 value 86.043884 iter 30 value 83.999975 iter 40 value 79.394207 iter 50 value 78.616569 iter 60 value 78.347612 iter 70 value 76.942797 iter 80 value 76.185397 iter 90 value 76.006768 iter 100 value 75.873035 final value 75.873035 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 117.612519 iter 10 value 93.033170 iter 20 value 81.259033 iter 30 value 80.840633 iter 40 value 80.555760 iter 50 value 80.273469 iter 60 value 79.227579 iter 70 value 79.125463 iter 80 value 78.564117 iter 90 value 77.672885 iter 100 value 77.477441 final value 77.477441 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 117.626516 iter 10 value 92.824476 iter 20 value 89.680851 iter 30 value 88.803347 iter 40 value 86.309573 iter 50 value 80.752951 iter 60 value 80.506130 iter 70 value 79.544240 iter 80 value 78.169031 iter 90 value 77.941585 iter 100 value 76.972301 final value 76.972301 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 116.908227 iter 10 value 94.092712 iter 20 value 86.238199 iter 30 value 85.407499 iter 40 value 85.198765 iter 50 value 81.085791 iter 60 value 78.307182 iter 70 value 76.970632 iter 80 value 76.244384 iter 90 value 76.209788 iter 100 value 76.169001 final value 76.169001 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 122.808660 iter 10 value 94.354078 iter 20 value 83.672432 iter 30 value 82.048960 iter 40 value 81.317795 iter 50 value 80.820529 iter 60 value 79.605630 iter 70 value 79.234954 iter 80 value 79.077327 iter 90 value 78.146716 iter 100 value 76.617517 final value 76.617517 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 112.259616 iter 10 value 93.854964 iter 20 value 91.316223 iter 30 value 89.994329 iter 40 value 83.374523 iter 50 value 82.212310 iter 60 value 80.296789 iter 70 value 77.861713 iter 80 value 77.644267 iter 90 value 77.425293 iter 100 value 77.244965 final value 77.244965 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 110.383151 iter 10 value 93.969010 iter 20 value 86.944458 iter 30 value 85.381305 iter 40 value 84.255337 iter 50 value 80.602817 iter 60 value 78.408748 iter 70 value 77.269175 iter 80 value 76.506533 iter 90 value 75.929822 iter 100 value 75.524079 final value 75.524079 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 110.390541 iter 10 value 95.632821 iter 20 value 83.326979 iter 30 value 81.666801 iter 40 value 80.369271 iter 50 value 78.272274 iter 60 value 78.036650 iter 70 value 77.516205 iter 80 value 77.428675 iter 90 value 77.321149 iter 100 value 77.139411 final value 77.139411 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 101.587793 final value 94.054535 converged Fitting Repeat 2 # weights: 103 initial value 101.288962 final value 94.054583 converged Fitting Repeat 3 # weights: 103 initial value 110.450071 final value 94.034696 converged Fitting Repeat 4 # weights: 103 initial value 101.631827 final value 94.054554 converged Fitting Repeat 5 # weights: 103 initial value 103.093169 final value 94.054885 converged Fitting Repeat 1 # weights: 305 initial value 104.899268 iter 10 value 94.057953 iter 20 value 94.044716 iter 30 value 84.378428 iter 40 value 82.872682 iter 50 value 80.549606 final value 80.546822 converged Fitting Repeat 2 # weights: 305 initial value 98.499267 iter 10 value 94.000020 iter 20 value 93.894900 iter 30 value 93.894011 iter 30 value 93.894010 iter 30 value 93.894010 final value 93.894010 converged Fitting Repeat 3 # weights: 305 initial value 99.371241 iter 10 value 94.037176 iter 20 value 93.938536 iter 30 value 92.103175 iter 40 value 91.953605 iter 50 value 91.953181 iter 60 value 80.390917 iter 70 value 78.771598 iter 80 value 78.651850 iter 90 value 78.651672 final value 78.651609 converged Fitting Repeat 4 # weights: 305 initial value 98.605246 iter 10 value 91.164211 iter 20 value 84.131726 iter 30 value 84.123250 iter 40 value 84.094898 iter 50 value 83.287745 iter 60 value 80.596526 iter 70 value 77.770023 iter 80 value 77.750262 iter 90 value 77.749350 iter 100 value 77.739559 final value 77.739559 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 113.622015 iter 10 value 94.059001 iter 20 value 94.035864 iter 30 value 90.903642 iter 40 value 90.826069 iter 50 value 80.476565 iter 60 value 80.386320 iter 70 value 78.879129 iter 80 value 78.560330 iter 90 value 78.455665 iter 100 value 78.449964 final value 78.449964 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 98.648293 iter 10 value 94.057868 iter 20 value 88.169917 iter 30 value 85.446843 iter 40 value 85.444507 iter 50 value 84.232721 iter 60 value 80.106091 iter 70 value 80.094770 iter 80 value 79.404262 iter 90 value 79.312235 iter 100 value 79.310133 final value 79.310133 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 101.319858 iter 10 value 94.041025 iter 20 value 94.033018 iter 30 value 93.975607 iter 40 value 92.680344 final value 92.665803 converged Fitting Repeat 3 # weights: 507 initial value 97.899249 iter 10 value 93.831529 iter 20 value 93.819151 iter 30 value 92.990879 iter 40 value 85.824866 iter 50 value 85.047879 iter 60 value 83.854023 iter 70 value 83.853354 iter 80 value 83.849205 iter 90 value 83.848803 iter 100 value 83.760865 final value 83.760865 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 106.527417 iter 10 value 94.041322 iter 20 value 94.038952 iter 30 value 94.020561 iter 40 value 93.796124 iter 50 value 93.270205 iter 60 value 93.107303 iter 70 value 93.086442 iter 80 value 93.082846 iter 90 value 93.052681 iter 100 value 91.483627 final value 91.483627 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 107.298526 iter 10 value 90.597763 iter 20 value 90.477227 iter 30 value 89.242613 iter 40 value 89.137639 iter 50 value 85.742149 iter 60 value 85.211737 iter 70 value 85.102613 iter 80 value 85.088416 iter 90 value 85.087008 iter 100 value 85.003788 final value 85.003788 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 148.476224 iter 10 value 117.767160 iter 20 value 117.761992 iter 30 value 117.761485 iter 40 value 117.761140 iter 50 value 115.513908 iter 60 value 107.971363 iter 70 value 107.910393 final value 107.910308 converged Fitting Repeat 2 # weights: 507 initial value 135.690584 iter 10 value 117.767074 iter 20 value 117.725905 iter 30 value 107.614240 iter 40 value 106.825337 iter 50 value 106.784126 iter 60 value 106.764492 final value 106.764266 converged Fitting Repeat 3 # weights: 507 initial value 141.731115 iter 10 value 117.766963 iter 20 value 117.759688 final value 117.759643 converged Fitting Repeat 4 # weights: 507 initial value 136.563803 iter 10 value 117.766714 iter 20 value 117.743254 iter 30 value 115.616511 iter 40 value 107.003617 final value 107.002639 converged Fitting Repeat 5 # weights: 507 initial value 136.422792 iter 10 value 117.898339 iter 20 value 117.864523 iter 30 value 107.876732 iter 40 value 107.010165 iter 50 value 107.009748 iter 60 value 107.007810 iter 70 value 107.004737 iter 80 value 105.768111 iter 90 value 105.346562 iter 100 value 105.326843 final value 105.326843 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 Jun 27 02:43:52 2024 *********************************************** 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 45.68 1.87 47.89
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 34.18 | 2.05 | 36.36 | |
FreqInteractors | 0.29 | 0.02 | 0.38 | |
calculateAAC | 0.02 | 0.03 | 0.05 | |
calculateAutocor | 0.42 | 0.14 | 0.61 | |
calculateCTDC | 0.09 | 0.00 | 0.09 | |
calculateCTDD | 0.75 | 0.08 | 0.85 | |
calculateCTDT | 0.33 | 0.00 | 0.33 | |
calculateCTriad | 0.41 | 0.00 | 0.40 | |
calculateDC | 0.10 | 0.03 | 0.14 | |
calculateF | 0.49 | 0.00 | 0.50 | |
calculateKSAAP | 0.11 | 0.00 | 0.11 | |
calculateQD_Sm | 2.28 | 0.20 | 2.49 | |
calculateTC | 1.83 | 0.11 | 1.93 | |
calculateTC_Sm | 0.36 | 0.02 | 0.38 | |
corr_plot | 33.03 | 1.79 | 34.83 | |
enrichfindP | 0.61 | 0.07 | 14.40 | |
enrichfind_hp | 0.11 | 0.00 | 1.02 | |
enrichplot | 0.29 | 0.03 | 0.33 | |
filter_missing_values | 0 | 0 | 0 | |
getFASTA | 0.04 | 0.00 | 2.36 | |
getHPI | 0 | 0 | 0 | |
get_negativePPI | 0 | 0 | 0 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0 | 0 | 0 | |
plotPPI | 0.06 | 0.01 | 0.10 | |
pred_ensembel | 14.89 | 0.84 | 11.45 | |
var_imp | 33.50 | 1.52 | 35.02 | |