Back to Multiple platform build/check report for BioC 3.20: simplified long |
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This page was generated on 2024-08-16 11:41 -0400 (Fri, 16 Aug 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4703 |
palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4440 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4472 |
kjohnson3 | macOS 13.6.5 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4420 |
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4413 |
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 968/2255 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.11.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | ||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | ERROR | skipped | skipped | |||||||||
kjohnson3 | macOS 13.6.5 Ventura / arm64 | OK | OK | OK | OK | ![]() | ||||||||
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | 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: 1.11.0 |
Command: F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.11.0.tar.gz |
StartedAt: 2024-08-16 01:40:54 -0400 (Fri, 16 Aug 2024) |
EndedAt: 2024-08-16 01:46:04 -0400 (Fri, 16 Aug 2024) |
EllapsedTime: 310.7 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.11.0.tar.gz ### ############################################################################## ############################################################################## * using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck' * using R version 4.4.1 (2024-06-14 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 '1.11.0' * 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 var_imp 34.93 1.50 36.44 FSmethod 34.02 2.22 36.38 corr_plot 34.72 1.51 36.26 pred_ensembel 15.51 0.70 11.92 enrichfindP 0.67 0.08 13.38 * 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-3.20-bioc/meat/HPiP.Rcheck/00check.log' for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.20-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 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" 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 106.910419 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 98.660615 final value 94.466823 converged Fitting Repeat 3 # weights: 103 initial value 107.456181 final value 94.113276 converged Fitting Repeat 4 # weights: 103 initial value 99.079943 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 101.725019 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 99.636455 final value 94.466823 converged Fitting Repeat 2 # weights: 305 initial value 95.837927 final value 94.466823 converged Fitting Repeat 3 # weights: 305 initial value 102.324411 final value 94.466823 converged Fitting Repeat 4 # weights: 305 initial value 99.356284 iter 10 value 87.567999 iter 20 value 85.454296 iter 30 value 85.286508 iter 40 value 84.571077 iter 50 value 84.458227 iter 60 value 84.446757 iter 70 value 83.768647 iter 80 value 83.537495 iter 90 value 83.503461 final value 83.503357 converged Fitting Repeat 5 # weights: 305 initial value 98.273556 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 101.020952 iter 10 value 91.668887 iter 20 value 90.521011 iter 30 value 90.258490 iter 40 value 90.254903 final value 90.254775 converged Fitting Repeat 2 # weights: 507 initial value 101.177584 iter 10 value 94.304609 iter 10 value 94.304608 iter 10 value 94.304608 final value 94.304608 converged Fitting Repeat 3 # weights: 507 initial value 96.582606 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 122.462606 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 108.117055 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 98.381065 iter 10 value 94.489403 iter 20 value 94.466919 iter 30 value 91.993972 iter 40 value 91.047188 iter 50 value 90.543859 iter 60 value 90.473083 iter 70 value 86.705470 iter 80 value 85.839641 iter 90 value 83.912201 iter 100 value 83.061738 final value 83.061738 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 103.866229 iter 10 value 94.502212 iter 20 value 94.487632 iter 30 value 94.486891 iter 40 value 93.108580 iter 50 value 91.122440 iter 60 value 90.799175 iter 70 value 90.588862 iter 80 value 90.478468 final value 90.478444 converged Fitting Repeat 3 # weights: 103 initial value 100.685592 iter 10 value 94.400247 iter 20 value 89.136952 iter 30 value 87.561620 iter 40 value 86.301920 iter 50 value 86.221686 iter 60 value 85.637208 iter 70 value 84.307074 iter 80 value 83.771958 iter 90 value 82.726892 iter 100 value 80.651899 final value 80.651899 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 101.789017 iter 10 value 94.483704 iter 20 value 93.097295 iter 30 value 90.117111 iter 40 value 83.322572 iter 50 value 82.670168 iter 60 value 82.641255 iter 70 value 82.639296 iter 80 value 82.638662 final value 82.638641 converged Fitting Repeat 5 # weights: 103 initial value 107.155530 iter 10 value 94.446508 iter 20 value 92.701209 iter 30 value 90.967352 iter 40 value 90.583483 iter 50 value 90.480498 iter 60 value 90.478454 final value 90.478443 converged Fitting Repeat 1 # weights: 305 initial value 104.359515 iter 10 value 94.510815 iter 20 value 84.451645 iter 30 value 83.296933 iter 40 value 82.725421 iter 50 value 82.603339 iter 60 value 82.197323 iter 70 value 80.931663 iter 80 value 79.923601 iter 90 value 79.860567 iter 100 value 79.514251 final value 79.514251 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 104.409956 iter 10 value 91.669444 iter 20 value 83.869179 iter 30 value 81.903387 iter 40 value 80.567338 iter 50 value 80.204257 iter 60 value 80.069403 iter 70 value 79.470763 iter 80 value 79.160857 iter 90 value 79.103368 iter 100 value 78.966386 final value 78.966386 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 109.384533 iter 10 value 94.477778 iter 20 value 86.179938 iter 30 value 83.699898 iter 40 value 83.216371 iter 50 value 80.743566 iter 60 value 79.424546 iter 70 value 79.051713 iter 80 value 78.398545 iter 90 value 78.257675 iter 100 value 78.166099 final value 78.166099 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 102.060206 iter 10 value 93.841598 iter 20 value 87.724339 iter 30 value 86.457614 iter 40 value 85.242631 iter 50 value 83.866781 iter 60 value 81.025826 iter 70 value 79.382669 iter 80 value 79.016004 iter 90 value 78.730681 iter 100 value 78.463871 final value 78.463871 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 123.241276 iter 10 value 94.640292 iter 20 value 92.527715 iter 30 value 88.221658 iter 40 value 87.834325 iter 50 value 85.145512 iter 60 value 83.361020 iter 70 value 82.774257 iter 80 value 82.132161 iter 90 value 81.579470 iter 100 value 80.937777 final value 80.937777 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 125.070446 iter 10 value 94.832896 iter 20 value 90.178947 iter 30 value 83.681593 iter 40 value 82.863586 iter 50 value 82.137315 iter 60 value 81.694849 iter 70 value 81.131723 iter 80 value 79.066378 iter 90 value 78.894575 iter 100 value 78.774199 final value 78.774199 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 111.819086 iter 10 value 95.817814 iter 20 value 93.889268 iter 30 value 91.968237 iter 40 value 87.941919 iter 50 value 82.236007 iter 60 value 81.480882 iter 70 value 80.982684 iter 80 value 80.867372 iter 90 value 79.991593 iter 100 value 79.780989 final value 79.780989 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.150691 iter 10 value 94.570677 iter 20 value 93.449559 iter 30 value 91.526761 iter 40 value 83.790349 iter 50 value 81.170518 iter 60 value 80.304044 iter 70 value 80.103943 iter 80 value 79.556412 iter 90 value 79.145010 iter 100 value 78.911324 final value 78.911324 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 113.311178 iter 10 value 94.504241 iter 20 value 94.361739 iter 30 value 90.557949 iter 40 value 83.731847 iter 50 value 82.555193 iter 60 value 80.911699 iter 70 value 79.293896 iter 80 value 79.046360 iter 90 value 78.867156 iter 100 value 78.811902 final value 78.811902 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 104.535802 iter 10 value 94.660285 iter 20 value 86.949783 iter 30 value 82.246115 iter 40 value 80.554756 iter 50 value 80.275824 iter 60 value 79.255632 iter 70 value 78.724188 iter 80 value 78.239763 iter 90 value 77.935091 iter 100 value 77.767641 final value 77.767641 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.022743 final value 94.485969 converged Fitting Repeat 2 # weights: 103 initial value 100.539761 final value 94.486064 converged Fitting Repeat 3 # weights: 103 initial value 102.789201 final value 94.485830 converged Fitting Repeat 4 # weights: 103 initial value 100.368627 iter 10 value 94.485889 iter 20 value 94.479314 iter 30 value 94.400060 final value 94.400049 converged Fitting Repeat 5 # weights: 103 initial value 99.546063 final value 94.485759 converged Fitting Repeat 1 # weights: 305 initial value 94.618870 iter 10 value 92.101918 iter 20 value 92.087507 iter 30 value 91.767590 iter 40 value 91.758208 final value 91.758119 converged Fitting Repeat 2 # weights: 305 initial value 105.159456 iter 10 value 94.490744 iter 20 value 94.441620 iter 30 value 92.023242 iter 40 value 85.716408 iter 50 value 80.838725 iter 60 value 77.905249 iter 70 value 77.810148 iter 80 value 77.809376 iter 90 value 77.781124 iter 100 value 77.779836 final value 77.779836 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 99.167041 iter 10 value 94.487818 iter 20 value 92.290436 iter 30 value 88.504971 iter 40 value 87.291051 iter 50 value 87.056747 iter 50 value 87.056747 iter 50 value 87.056747 final value 87.056747 converged Fitting Repeat 4 # weights: 305 initial value 98.332298 iter 10 value 94.489457 iter 20 value 94.484265 iter 30 value 91.317291 final value 90.639243 converged Fitting Repeat 5 # weights: 305 initial value 98.077408 iter 10 value 94.489084 iter 20 value 94.298633 iter 30 value 83.903368 iter 40 value 82.289265 iter 50 value 80.437500 iter 60 value 80.180632 iter 70 value 80.179795 final value 80.179712 converged Fitting Repeat 1 # weights: 507 initial value 97.826634 iter 10 value 94.492435 iter 20 value 94.483322 iter 30 value 93.262952 iter 40 value 84.370281 iter 50 value 82.837266 iter 60 value 82.738184 final value 82.737720 converged Fitting Repeat 2 # weights: 507 initial value 104.398643 iter 10 value 94.492573 iter 20 value 92.730965 iter 30 value 84.910553 iter 40 value 82.963857 iter 50 value 82.693188 iter 60 value 81.416865 iter 70 value 81.330621 iter 80 value 81.158271 iter 90 value 80.862019 iter 100 value 80.808384 final value 80.808384 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 120.686641 iter 10 value 92.236069 iter 20 value 92.231250 iter 30 value 92.228199 iter 40 value 92.227657 iter 50 value 92.226532 iter 60 value 92.038153 iter 70 value 92.006556 iter 80 value 92.006165 final value 92.006019 converged Fitting Repeat 4 # weights: 507 initial value 106.861250 iter 10 value 92.287604 iter 20 value 83.655967 iter 30 value 82.414209 iter 40 value 81.945995 iter 50 value 81.937165 iter 60 value 81.934879 iter 70 value 81.933356 iter 80 value 81.868532 iter 90 value 80.295620 iter 100 value 77.143279 final value 77.143279 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 129.577236 iter 10 value 94.474722 iter 20 value 94.340936 iter 30 value 86.725320 iter 40 value 81.990088 iter 50 value 80.981068 iter 60 value 80.622907 iter 70 value 80.622293 iter 70 value 80.622293 final value 80.622293 converged Fitting Repeat 1 # weights: 103 initial value 96.022804 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 98.412086 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 95.642764 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 96.769306 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 99.169356 final value 94.467391 converged Fitting Repeat 1 # weights: 305 initial value 96.495742 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 96.046017 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 104.707706 iter 10 value 92.656395 final value 92.468359 converged Fitting Repeat 4 # weights: 305 initial value 96.563327 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 127.281534 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 131.219795 iter 10 value 87.919897 iter 20 value 82.417072 iter 30 value 81.038136 iter 40 value 80.949600 iter 50 value 80.949538 iter 50 value 80.949538 iter 50 value 80.949538 final value 80.949538 converged Fitting Repeat 2 # weights: 507 initial value 112.325442 final value 94.467391 converged Fitting Repeat 3 # weights: 507 initial value 113.019266 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 114.374606 final value 94.467391 converged Fitting Repeat 5 # weights: 507 initial value 101.572299 iter 10 value 94.467392 iter 10 value 94.467391 iter 10 value 94.467391 final value 94.467391 converged Fitting Repeat 1 # weights: 103 initial value 96.986749 iter 10 value 94.488926 iter 20 value 94.246887 iter 30 value 93.195644 iter 40 value 86.963847 iter 50 value 84.798812 iter 60 value 84.735332 iter 70 value 84.533923 iter 80 value 84.379056 iter 90 value 84.317088 iter 100 value 84.314736 final value 84.314736 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 102.413123 iter 10 value 94.554898 iter 20 value 93.101345 iter 30 value 89.960193 iter 40 value 82.646805 iter 50 value 82.462858 iter 60 value 82.401542 iter 70 value 82.381664 iter 80 value 82.230318 iter 90 value 81.648557 iter 100 value 81.443738 final value 81.443738 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 97.081003 iter 10 value 94.484940 iter 20 value 85.911542 iter 30 value 84.299350 iter 40 value 83.977541 iter 50 value 83.881372 iter 60 value 83.875081 final value 83.875013 converged Fitting Repeat 4 # weights: 103 initial value 105.447376 iter 10 value 94.488832 iter 20 value 87.655840 iter 30 value 85.481212 iter 40 value 83.699823 iter 50 value 82.179446 iter 60 value 82.046174 iter 70 value 81.359300 iter 80 value 81.030066 iter 90 value 80.951507 final value 80.947733 converged Fitting Repeat 5 # weights: 103 initial value 99.664383 iter 10 value 94.474880 iter 20 value 92.287263 iter 30 value 87.605557 iter 40 value 85.566913 iter 50 value 84.060249 iter 60 value 82.200052 iter 70 value 81.432253 iter 80 value 81.234760 iter 90 value 81.206043 final value 81.206028 converged Fitting Repeat 1 # weights: 305 initial value 112.582679 iter 10 value 93.972483 iter 20 value 85.184089 iter 30 value 83.386057 iter 40 value 81.316878 iter 50 value 80.981159 iter 60 value 80.883483 iter 70 value 80.854361 iter 80 value 80.851094 iter 90 value 80.846816 iter 100 value 80.443248 final value 80.443248 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 110.061008 iter 10 value 94.490909 iter 20 value 90.768706 iter 30 value 85.084034 iter 40 value 82.904261 iter 50 value 81.612459 iter 60 value 81.428669 iter 70 value 81.353238 iter 80 value 80.606249 iter 90 value 80.240762 iter 100 value 80.188630 final value 80.188630 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 104.224076 iter 10 value 94.497071 iter 20 value 94.378491 iter 30 value 94.069483 iter 40 value 93.962695 iter 50 value 87.626613 iter 60 value 86.938980 iter 70 value 85.779418 iter 80 value 82.661077 iter 90 value 82.242612 iter 100 value 81.981360 final value 81.981360 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 103.652042 iter 10 value 94.492399 iter 20 value 94.471503 iter 30 value 88.408327 iter 40 value 86.347225 iter 50 value 84.245858 iter 60 value 83.974784 iter 70 value 82.031722 iter 80 value 81.608189 iter 90 value 81.290930 iter 100 value 81.220238 final value 81.220238 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.869134 iter 10 value 92.007954 iter 20 value 84.938508 iter 30 value 84.661186 iter 40 value 84.522127 iter 50 value 84.070747 iter 60 value 82.359205 iter 70 value 81.885759 iter 80 value 81.305461 iter 90 value 81.174887 iter 100 value 80.646102 final value 80.646102 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 130.603500 iter 10 value 94.416786 iter 20 value 94.187303 iter 30 value 86.368503 iter 40 value 83.545868 iter 50 value 82.559958 iter 60 value 82.081102 iter 70 value 81.828419 iter 80 value 81.625944 iter 90 value 81.194389 iter 100 value 80.708324 final value 80.708324 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 105.277772 iter 10 value 94.515458 iter 20 value 94.442579 iter 30 value 90.131881 iter 40 value 88.131155 iter 50 value 85.298181 iter 60 value 84.871592 iter 70 value 82.994812 iter 80 value 82.022717 iter 90 value 81.036118 iter 100 value 80.292489 final value 80.292489 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 112.615156 iter 10 value 94.123060 iter 20 value 88.411295 iter 30 value 85.203419 iter 40 value 84.776746 iter 50 value 84.483252 iter 60 value 84.311567 iter 70 value 84.063662 iter 80 value 83.985000 iter 90 value 83.823887 iter 100 value 83.670170 final value 83.670170 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 105.301083 iter 10 value 94.318112 iter 20 value 88.825769 iter 30 value 87.950177 iter 40 value 86.900450 iter 50 value 86.599307 iter 60 value 84.849763 iter 70 value 82.191651 iter 80 value 81.714985 iter 90 value 81.136363 iter 100 value 81.003271 final value 81.003271 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 104.674426 iter 10 value 94.278751 iter 20 value 92.164343 iter 30 value 87.224176 iter 40 value 83.488670 iter 50 value 82.271486 iter 60 value 81.994981 iter 70 value 81.302855 iter 80 value 80.438255 iter 90 value 80.052818 iter 100 value 79.905559 final value 79.905559 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.162164 final value 94.485851 converged Fitting Repeat 2 # weights: 103 initial value 105.774559 final value 94.485667 converged Fitting Repeat 3 # weights: 103 initial value 103.667039 final value 94.356016 converged Fitting Repeat 4 # weights: 103 initial value 97.267731 iter 10 value 94.485953 iter 20 value 94.484229 final value 94.484215 converged Fitting Repeat 5 # weights: 103 initial value 96.653809 final value 94.485755 converged Fitting Repeat 1 # weights: 305 initial value 99.310958 iter 10 value 94.489246 iter 20 value 94.484114 iter 30 value 94.463958 iter 40 value 85.552453 iter 50 value 82.897103 iter 60 value 82.884417 iter 70 value 82.865945 iter 80 value 81.726876 iter 90 value 81.091748 iter 100 value 81.053675 final value 81.053675 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 95.956126 iter 10 value 87.402321 iter 20 value 87.338717 iter 30 value 85.956135 iter 40 value 85.955979 iter 50 value 85.954163 iter 60 value 85.868539 iter 70 value 85.866679 final value 85.866674 converged Fitting Repeat 3 # weights: 305 initial value 97.553610 iter 10 value 94.102806 iter 20 value 93.938405 iter 30 value 93.936947 iter 40 value 93.936535 iter 50 value 93.935852 iter 60 value 93.935123 iter 70 value 93.925182 iter 80 value 93.847655 iter 90 value 93.792050 iter 100 value 93.791924 final value 93.791924 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 101.291159 iter 10 value 94.491535 iter 20 value 94.278275 iter 30 value 86.049481 iter 40 value 85.238714 iter 50 value 85.218638 final value 85.218502 converged Fitting Repeat 5 # weights: 305 initial value 96.709421 iter 10 value 94.489311 iter 20 value 94.259450 iter 30 value 85.956499 iter 40 value 85.956180 iter 50 value 84.829550 iter 60 value 82.794422 iter 70 value 82.695308 iter 80 value 81.572157 iter 90 value 81.026864 iter 100 value 80.930892 final value 80.930892 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 96.188782 iter 10 value 94.177403 iter 20 value 89.058971 iter 30 value 82.912878 iter 40 value 82.717992 iter 50 value 82.514251 iter 60 value 82.344326 iter 70 value 82.342568 iter 80 value 82.336817 iter 90 value 82.336446 iter 100 value 82.332981 final value 82.332981 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 102.803397 iter 10 value 94.381945 iter 20 value 94.360774 iter 30 value 94.354356 iter 40 value 94.305519 iter 50 value 93.943379 iter 60 value 88.999305 iter 70 value 86.139652 iter 80 value 85.801910 iter 90 value 84.779167 iter 100 value 79.221015 final value 79.221015 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 108.923250 iter 10 value 94.492018 iter 20 value 92.518501 iter 30 value 84.098685 iter 40 value 83.969269 final value 83.967966 converged Fitting Repeat 4 # weights: 507 initial value 96.128493 iter 10 value 94.490903 iter 20 value 92.857455 iter 30 value 86.475676 iter 40 value 82.508667 iter 50 value 82.291989 iter 60 value 82.274283 iter 70 value 82.269992 iter 80 value 82.246675 iter 90 value 82.246534 iter 100 value 82.246241 final value 82.246241 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 105.841971 iter 10 value 94.492902 iter 20 value 93.842077 iter 30 value 86.763252 iter 40 value 84.750619 iter 50 value 84.750249 iter 60 value 84.329098 iter 70 value 83.533458 iter 80 value 83.472157 iter 80 value 83.472157 iter 80 value 83.472157 final value 83.472157 converged Fitting Repeat 1 # weights: 103 initial value 103.261464 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 94.839480 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 95.046980 iter 10 value 92.746701 iter 20 value 86.739808 final value 86.726120 converged Fitting Repeat 4 # weights: 103 initial value 99.834072 final value 94.275362 converged Fitting Repeat 5 # weights: 103 initial value 113.132588 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 111.154674 iter 10 value 94.484354 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 99.491985 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 102.377014 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 97.679448 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 105.253673 iter 10 value 93.443179 iter 20 value 91.942865 iter 30 value 91.773525 iter 40 value 90.950296 iter 50 value 90.946670 final value 90.946667 converged Fitting Repeat 1 # weights: 507 initial value 118.766967 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 100.082052 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 113.322263 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 102.424373 iter 10 value 94.275365 final value 94.275362 converged Fitting Repeat 5 # weights: 507 initial value 104.650904 iter 10 value 94.275367 final value 94.275362 converged Fitting Repeat 1 # weights: 103 initial value 99.113075 iter 10 value 94.588565 iter 20 value 94.487254 iter 30 value 86.695802 iter 40 value 86.341619 iter 50 value 84.702856 iter 60 value 83.643346 iter 70 value 83.588677 iter 80 value 83.581441 final value 83.581423 converged Fitting Repeat 2 # weights: 103 initial value 99.658151 iter 10 value 94.433751 iter 20 value 92.357152 iter 30 value 92.293651 iter 40 value 91.996522 iter 50 value 91.758948 iter 60 value 91.747965 final value 91.747634 converged Fitting Repeat 3 # weights: 103 initial value 96.657606 iter 10 value 94.485463 iter 20 value 87.395916 iter 30 value 86.435772 iter 40 value 85.765781 iter 50 value 85.597611 iter 60 value 84.843353 iter 70 value 83.596494 iter 80 value 83.581383 final value 83.581357 converged Fitting Repeat 4 # weights: 103 initial value 96.988633 iter 10 value 94.495146 iter 20 value 94.310126 iter 30 value 87.817100 iter 40 value 85.796260 iter 50 value 85.391695 iter 60 value 83.930421 iter 70 value 82.832263 iter 80 value 82.647728 final value 82.643794 converged Fitting Repeat 5 # weights: 103 initial value 99.088286 iter 10 value 94.333781 iter 20 value 86.675647 iter 30 value 85.623412 iter 40 value 85.507069 iter 50 value 83.740676 iter 60 value 83.000170 iter 70 value 82.462520 iter 80 value 82.440342 final value 82.440239 converged Fitting Repeat 1 # weights: 305 initial value 113.918055 iter 10 value 94.439210 iter 20 value 90.311368 iter 30 value 88.241818 iter 40 value 87.534625 iter 50 value 86.395948 iter 60 value 84.781707 iter 70 value 83.817696 iter 80 value 82.278962 iter 90 value 81.929446 iter 100 value 81.620509 final value 81.620509 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 103.045931 iter 10 value 91.983599 iter 20 value 86.872380 iter 30 value 85.559552 iter 40 value 82.931346 iter 50 value 82.583274 iter 60 value 82.397070 iter 70 value 82.276332 iter 80 value 82.247629 iter 90 value 82.145083 iter 100 value 81.615754 final value 81.615754 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 104.731663 iter 10 value 94.543880 iter 20 value 94.490889 iter 30 value 94.379109 iter 40 value 90.009356 iter 50 value 86.998040 iter 60 value 85.782239 iter 70 value 83.359893 iter 80 value 82.817413 iter 90 value 82.376242 iter 100 value 81.919700 final value 81.919700 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.090057 iter 10 value 94.511323 iter 20 value 87.964733 iter 30 value 87.104557 iter 40 value 85.641436 iter 50 value 84.576925 iter 60 value 82.746222 iter 70 value 82.659014 iter 80 value 82.624078 iter 90 value 82.469411 iter 100 value 82.432832 final value 82.432832 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 108.516855 iter 10 value 93.868909 iter 20 value 92.143158 iter 30 value 91.717343 iter 40 value 89.142613 iter 50 value 87.576708 iter 60 value 87.075964 iter 70 value 86.131629 iter 80 value 83.950285 iter 90 value 83.539995 iter 100 value 83.347873 final value 83.347873 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 124.033640 iter 10 value 94.302516 iter 20 value 88.118243 iter 30 value 85.967113 iter 40 value 82.074599 iter 50 value 81.627353 iter 60 value 81.462457 iter 70 value 81.315772 iter 80 value 81.227030 iter 90 value 81.188252 iter 100 value 81.144893 final value 81.144893 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 120.687798 iter 10 value 94.276536 iter 20 value 92.541042 iter 30 value 91.812440 iter 40 value 91.243374 iter 50 value 83.169091 iter 60 value 81.621074 iter 70 value 81.365052 iter 80 value 81.337395 iter 90 value 81.290698 iter 100 value 81.279179 final value 81.279179 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 107.078254 iter 10 value 94.613230 iter 20 value 94.265244 iter 30 value 93.030450 iter 40 value 88.027644 iter 50 value 86.753268 iter 60 value 85.770933 iter 70 value 83.550689 iter 80 value 83.197353 iter 90 value 82.892487 iter 100 value 82.227768 final value 82.227768 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.910964 iter 10 value 94.304121 iter 20 value 93.310294 iter 30 value 89.800018 iter 40 value 85.563832 iter 50 value 83.124637 iter 60 value 82.119387 iter 70 value 81.594441 iter 80 value 81.395916 iter 90 value 81.293647 iter 100 value 81.220863 final value 81.220863 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 116.172657 iter 10 value 95.668045 iter 20 value 88.341235 iter 30 value 84.194714 iter 40 value 83.293489 iter 50 value 82.383901 iter 60 value 81.981982 iter 70 value 81.792176 iter 80 value 81.593064 iter 90 value 81.532263 iter 100 value 81.270677 final value 81.270677 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 100.408268 iter 10 value 94.276938 iter 20 value 93.089636 iter 30 value 89.932878 iter 40 value 89.885743 iter 50 value 89.884521 iter 50 value 89.884521 iter 50 value 89.884521 final value 89.884521 converged Fitting Repeat 2 # weights: 103 initial value 101.141610 iter 10 value 94.489377 iter 20 value 94.484222 final value 94.484219 converged Fitting Repeat 3 # weights: 103 initial value 99.877753 iter 10 value 93.111692 iter 20 value 93.110821 iter 20 value 93.110821 iter 20 value 93.110821 final value 93.110821 converged Fitting Repeat 4 # weights: 103 initial value 100.570247 final value 94.485812 converged Fitting Repeat 5 # weights: 103 initial value 99.905846 final value 94.485998 converged Fitting Repeat 1 # weights: 305 initial value 109.492041 iter 10 value 94.488814 iter 20 value 94.356901 iter 30 value 88.515150 iter 40 value 87.815450 iter 50 value 87.813437 iter 60 value 87.812051 final value 87.811475 converged Fitting Repeat 2 # weights: 305 initial value 97.729004 iter 10 value 94.488346 final value 94.484223 converged Fitting Repeat 3 # weights: 305 initial value 96.475128 iter 10 value 93.757153 iter 20 value 93.737367 iter 30 value 93.642626 iter 40 value 93.449534 iter 50 value 93.344686 iter 60 value 93.343572 final value 93.343455 converged Fitting Repeat 4 # weights: 305 initial value 97.663662 iter 10 value 94.488546 iter 20 value 94.481669 iter 30 value 93.339482 iter 40 value 88.476492 iter 50 value 87.735090 iter 60 value 84.352208 iter 70 value 83.634161 iter 80 value 83.252508 iter 90 value 82.396376 iter 100 value 80.787169 final value 80.787169 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 97.920907 iter 10 value 94.280596 iter 20 value 93.772141 iter 30 value 92.114286 iter 40 value 92.107275 iter 50 value 92.097823 final value 92.097812 converged Fitting Repeat 1 # weights: 507 initial value 106.693950 iter 10 value 94.283845 iter 20 value 94.234114 iter 30 value 92.346398 iter 40 value 91.936632 iter 50 value 91.931709 final value 91.931622 converged Fitting Repeat 2 # weights: 507 initial value 99.865595 iter 10 value 94.282929 iter 20 value 94.275534 iter 30 value 87.807495 iter 40 value 86.886776 iter 50 value 84.038967 iter 60 value 83.984033 iter 70 value 83.857551 iter 80 value 83.695004 iter 90 value 83.345309 iter 100 value 83.251957 final value 83.251957 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 98.811974 iter 10 value 94.491869 iter 20 value 93.986083 iter 30 value 86.262351 iter 40 value 86.121632 iter 50 value 85.932939 iter 60 value 85.927680 iter 70 value 85.722812 iter 80 value 83.024673 iter 90 value 81.928360 iter 100 value 81.708668 final value 81.708668 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 106.691103 iter 10 value 94.489808 iter 20 value 94.150454 iter 30 value 89.866930 iter 40 value 88.712195 final value 88.711026 converged Fitting Repeat 5 # weights: 507 initial value 112.506055 iter 10 value 94.236997 iter 20 value 94.234176 iter 30 value 94.229935 iter 40 value 94.229755 iter 50 value 94.229240 iter 60 value 94.228995 iter 70 value 94.228915 iter 80 value 94.035755 iter 90 value 92.108204 iter 100 value 92.099199 final value 92.099199 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.185365 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 95.787221 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 99.255802 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 101.239641 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 104.762812 final value 93.860355 converged Fitting Repeat 1 # weights: 305 initial value 107.166806 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 94.502658 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 108.906513 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 98.701992 iter 10 value 93.356510 iter 20 value 93.341991 iter 20 value 93.341991 iter 20 value 93.341991 final value 93.341991 converged Fitting Repeat 5 # weights: 305 initial value 102.204607 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 94.375183 iter 10 value 93.588180 final value 93.582418 converged Fitting Repeat 2 # weights: 507 initial value 96.717375 final value 94.052910 converged Fitting Repeat 3 # weights: 507 initial value 110.024393 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 110.789961 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 127.258454 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 99.604374 iter 10 value 93.626509 iter 20 value 87.930644 iter 30 value 87.041369 iter 40 value 86.761076 iter 50 value 84.970163 iter 60 value 84.053528 iter 70 value 83.367134 iter 80 value 83.362826 iter 90 value 82.995437 iter 100 value 82.618412 final value 82.618412 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 98.959744 iter 10 value 93.991365 iter 20 value 93.459575 iter 30 value 93.347329 iter 40 value 93.156451 iter 50 value 88.177845 iter 60 value 87.660445 iter 70 value 85.597573 iter 80 value 84.622234 iter 90 value 83.896810 iter 100 value 83.813727 final value 83.813727 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 107.736163 iter 10 value 94.072698 iter 20 value 89.866665 iter 30 value 87.497123 iter 40 value 87.134784 iter 50 value 85.546518 iter 60 value 84.333873 iter 70 value 83.761027 iter 80 value 83.641205 final value 83.640637 converged Fitting Repeat 4 # weights: 103 initial value 104.763721 iter 10 value 94.047774 iter 20 value 92.957247 iter 30 value 84.962527 iter 40 value 83.662903 iter 50 value 83.616791 iter 60 value 83.610565 final value 83.610268 converged Fitting Repeat 5 # weights: 103 initial value 98.552353 iter 10 value 94.055905 iter 20 value 93.788322 iter 30 value 93.247093 iter 40 value 92.937015 iter 50 value 89.207287 iter 60 value 87.201292 iter 70 value 86.808009 iter 80 value 84.766918 iter 90 value 83.393164 iter 100 value 82.892404 final value 82.892404 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 120.237623 iter 10 value 92.367945 iter 20 value 88.192225 iter 30 value 86.623623 iter 40 value 85.148501 iter 50 value 83.556960 iter 60 value 83.190562 iter 70 value 82.894672 iter 80 value 82.593015 iter 90 value 82.359845 iter 100 value 82.330142 final value 82.330142 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 107.520831 iter 10 value 93.832027 iter 20 value 88.257113 iter 30 value 85.405848 iter 40 value 82.989141 iter 50 value 82.074457 iter 60 value 82.005260 iter 70 value 81.923898 iter 80 value 81.907650 iter 80 value 81.907650 final value 81.907650 converged Fitting Repeat 3 # weights: 305 initial value 121.003317 iter 10 value 93.576412 iter 20 value 92.842281 iter 30 value 89.865639 iter 40 value 85.586369 iter 50 value 84.304755 iter 60 value 84.190467 iter 70 value 83.343540 iter 80 value 83.065718 iter 90 value 81.867628 iter 100 value 81.247610 final value 81.247610 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 118.585847 iter 10 value 94.041442 iter 20 value 87.688684 iter 30 value 86.893384 iter 40 value 85.894469 iter 50 value 84.408469 iter 60 value 82.525746 iter 70 value 81.921779 iter 80 value 81.727298 iter 90 value 81.612145 iter 100 value 81.363594 final value 81.363594 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 105.342367 iter 10 value 94.059597 iter 20 value 93.738621 iter 30 value 93.162336 iter 40 value 90.095375 iter 50 value 86.664603 iter 60 value 85.561380 iter 70 value 84.077875 iter 80 value 83.897430 iter 90 value 83.515900 iter 100 value 83.159936 final value 83.159936 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 109.421968 iter 10 value 94.027916 iter 20 value 93.379553 iter 30 value 86.205441 iter 40 value 84.590186 iter 50 value 83.634598 iter 60 value 83.366029 iter 70 value 82.645342 iter 80 value 81.931718 iter 90 value 81.698359 iter 100 value 81.460751 final value 81.460751 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 130.993303 iter 10 value 94.492750 iter 20 value 92.864895 iter 30 value 85.674796 iter 40 value 83.598337 iter 50 value 82.351651 iter 60 value 81.822263 iter 70 value 81.433788 iter 80 value 81.067599 iter 90 value 80.986529 iter 100 value 80.957188 final value 80.957188 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 119.712193 iter 10 value 93.785269 iter 20 value 86.517838 iter 30 value 86.096732 iter 40 value 85.668783 iter 50 value 82.966412 iter 60 value 82.004343 iter 70 value 81.743636 iter 80 value 81.580937 iter 90 value 81.465327 iter 100 value 81.441513 final value 81.441513 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.890469 iter 10 value 94.388418 iter 20 value 93.613966 iter 30 value 87.351963 iter 40 value 84.649322 iter 50 value 83.015142 iter 60 value 82.899616 iter 70 value 82.765910 iter 80 value 82.157633 iter 90 value 81.870622 iter 100 value 81.749153 final value 81.749153 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 119.616086 iter 10 value 92.430616 iter 20 value 88.221681 iter 30 value 85.844544 iter 40 value 85.040943 iter 50 value 83.057622 iter 60 value 82.843506 iter 70 value 82.785590 iter 80 value 82.412416 iter 90 value 81.739500 iter 100 value 81.408638 final value 81.408638 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.531217 final value 94.054851 converged Fitting Repeat 2 # weights: 103 initial value 95.846799 final value 94.054645 converged Fitting Repeat 3 # weights: 103 initial value 98.185252 final value 94.054490 converged Fitting Repeat 4 # weights: 103 initial value 97.037270 iter 10 value 93.659091 iter 10 value 93.659090 iter 10 value 93.659090 final value 93.659090 converged Fitting Repeat 5 # weights: 103 initial value 98.554570 final value 94.054587 converged Fitting Repeat 1 # weights: 305 initial value 100.490920 iter 10 value 88.810469 iter 20 value 83.872352 iter 30 value 83.411068 final value 83.393773 converged Fitting Repeat 2 # weights: 305 initial value 98.722298 iter 10 value 93.767871 iter 20 value 93.552589 iter 30 value 93.342347 iter 40 value 93.339905 iter 50 value 93.308601 iter 60 value 87.255379 iter 70 value 86.577037 iter 80 value 86.542623 final value 86.542520 converged Fitting Repeat 3 # weights: 305 initial value 109.956269 iter 10 value 94.058163 iter 20 value 94.052967 final value 94.052912 converged Fitting Repeat 4 # weights: 305 initial value 99.495440 iter 10 value 94.057425 iter 20 value 92.180521 iter 30 value 89.656961 iter 40 value 89.542430 iter 50 value 87.238610 iter 60 value 87.045945 iter 70 value 86.627860 iter 80 value 86.625980 iter 90 value 86.621805 iter 100 value 86.465702 final value 86.465702 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 95.292168 iter 10 value 94.056960 iter 20 value 93.912029 iter 30 value 89.598683 iter 40 value 86.649243 iter 50 value 86.542276 iter 60 value 86.007366 final value 85.985603 converged Fitting Repeat 1 # weights: 507 initial value 97.531743 iter 10 value 93.590521 iter 20 value 93.321305 iter 30 value 86.770833 iter 40 value 86.328053 iter 50 value 83.201442 iter 60 value 82.207009 iter 70 value 81.765063 iter 80 value 81.326707 iter 90 value 80.975639 iter 100 value 80.567545 final value 80.567545 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 107.252180 iter 10 value 93.590402 iter 20 value 93.191645 iter 30 value 92.960603 iter 40 value 92.946185 iter 50 value 92.924035 iter 60 value 92.921026 iter 70 value 92.920064 final value 92.920042 converged Fitting Repeat 3 # weights: 507 initial value 122.224612 iter 10 value 94.061595 iter 20 value 94.042743 iter 30 value 85.500079 iter 40 value 82.754467 iter 50 value 80.915256 iter 60 value 80.621934 iter 70 value 80.610524 iter 80 value 80.603861 iter 90 value 80.564425 iter 100 value 80.440531 final value 80.440531 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 112.433038 iter 10 value 93.590862 iter 20 value 93.583539 iter 30 value 93.451233 iter 40 value 86.843048 iter 50 value 82.594033 iter 60 value 80.866002 iter 70 value 80.659972 iter 80 value 80.551690 iter 90 value 80.534954 iter 100 value 80.533722 final value 80.533722 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 113.632180 iter 10 value 93.587537 iter 20 value 93.584350 iter 30 value 93.342414 iter 40 value 93.336120 iter 50 value 93.335488 final value 93.335407 converged Fitting Repeat 1 # weights: 103 initial value 98.739655 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 96.477874 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 106.663770 iter 10 value 82.751756 iter 20 value 82.224927 iter 30 value 81.761835 iter 40 value 81.645211 iter 50 value 81.616556 final value 81.616367 converged Fitting Repeat 4 # weights: 103 initial value 110.074264 final value 92.954173 converged Fitting Repeat 5 # weights: 103 initial value 106.318097 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 113.865602 iter 10 value 92.683978 final value 92.677297 converged Fitting Repeat 2 # weights: 305 initial value 100.657175 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 95.450447 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 98.135864 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 103.156564 iter 10 value 93.605237 final value 93.604520 converged Fitting Repeat 1 # weights: 507 initial value 98.764937 final value 94.052910 converged Fitting Repeat 2 # weights: 507 initial value 112.633040 final value 94.052910 converged Fitting Repeat 3 # weights: 507 initial value 96.519981 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 98.579859 iter 10 value 88.360597 iter 20 value 85.980238 iter 30 value 85.911634 iter 40 value 85.594346 iter 50 value 85.284046 iter 60 value 83.885276 iter 70 value 83.824341 iter 80 value 83.821948 final value 83.821894 converged Fitting Repeat 5 # weights: 507 initial value 96.194738 iter 10 value 93.600524 iter 20 value 93.057534 final value 92.954172 converged Fitting Repeat 1 # weights: 103 initial value 101.739263 iter 10 value 88.528014 iter 20 value 85.805332 iter 30 value 85.567626 iter 40 value 85.536427 iter 50 value 85.135518 iter 60 value 85.039701 iter 70 value 84.976758 final value 84.976696 converged Fitting Repeat 2 # weights: 103 initial value 96.884754 iter 10 value 93.829158 iter 20 value 92.842833 iter 30 value 92.804848 iter 40 value 89.767604 iter 50 value 82.604153 iter 60 value 81.919849 iter 70 value 81.190328 iter 80 value 80.820832 iter 90 value 80.679494 iter 100 value 80.332263 final value 80.332263 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 95.978354 iter 10 value 94.007592 iter 20 value 89.697809 iter 30 value 85.249307 iter 40 value 82.174580 iter 50 value 81.094501 iter 60 value 80.643760 iter 70 value 80.219285 iter 80 value 80.187278 final value 80.166515 converged Fitting Repeat 4 # weights: 103 initial value 101.242266 iter 10 value 93.749909 iter 20 value 89.568441 iter 30 value 86.650425 iter 40 value 84.866827 iter 50 value 82.378378 iter 60 value 82.303773 iter 70 value 82.261616 final value 82.260764 converged Fitting Repeat 5 # weights: 103 initial value 95.980049 iter 10 value 94.002463 iter 20 value 93.093150 iter 30 value 92.801144 iter 40 value 87.286222 iter 50 value 83.494332 iter 60 value 82.460766 iter 70 value 81.115761 iter 80 value 80.460536 iter 90 value 80.194912 iter 100 value 80.180559 final value 80.180559 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 104.961538 iter 10 value 95.053932 iter 20 value 93.501363 iter 30 value 89.670479 iter 40 value 82.331581 iter 50 value 81.160799 iter 60 value 80.985644 iter 70 value 80.546091 iter 80 value 80.377845 iter 90 value 79.999628 iter 100 value 79.949261 final value 79.949261 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 105.082250 iter 10 value 94.688895 iter 20 value 83.057379 iter 30 value 81.153847 iter 40 value 80.447253 iter 50 value 80.201940 iter 60 value 79.786044 iter 70 value 79.540245 iter 80 value 79.410251 iter 90 value 79.161111 iter 100 value 79.019019 final value 79.019019 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 109.779751 iter 10 value 92.951874 iter 20 value 88.383132 iter 30 value 82.177861 iter 40 value 80.310437 iter 50 value 79.242643 iter 60 value 78.998868 iter 70 value 78.933550 iter 80 value 78.878891 iter 90 value 78.825511 iter 100 value 78.801420 final value 78.801420 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 103.929121 iter 10 value 94.017183 iter 20 value 93.140948 iter 30 value 91.026194 iter 40 value 86.430344 iter 50 value 84.836281 iter 60 value 81.590778 iter 70 value 80.265272 iter 80 value 79.649129 iter 90 value 79.551625 iter 100 value 79.278234 final value 79.278234 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 108.908181 iter 10 value 93.975848 iter 20 value 83.625937 iter 30 value 82.904761 iter 40 value 80.871614 iter 50 value 80.658990 iter 60 value 80.510092 iter 70 value 80.032930 iter 80 value 79.038823 iter 90 value 78.902228 iter 100 value 78.588214 final value 78.588214 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 102.429527 iter 10 value 89.107260 iter 20 value 82.809432 iter 30 value 81.578689 iter 40 value 80.639347 iter 50 value 79.580431 iter 60 value 79.194354 iter 70 value 78.629803 iter 80 value 78.525768 iter 90 value 78.435396 iter 100 value 78.360740 final value 78.360740 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 111.372336 iter 10 value 96.594808 iter 20 value 94.099850 iter 30 value 85.554142 iter 40 value 84.684606 iter 50 value 82.767548 iter 60 value 81.515441 iter 70 value 80.285238 iter 80 value 79.694793 iter 90 value 79.410649 iter 100 value 79.285467 final value 79.285467 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 105.656164 iter 10 value 94.009233 iter 20 value 91.714188 iter 30 value 85.676101 iter 40 value 83.842807 iter 50 value 79.775578 iter 60 value 78.894269 iter 70 value 78.635172 iter 80 value 78.461053 iter 90 value 78.452739 iter 100 value 78.429937 final value 78.429937 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 116.886549 iter 10 value 94.040241 iter 20 value 92.794000 iter 30 value 84.053910 iter 40 value 82.983619 iter 50 value 81.827447 iter 60 value 81.181372 iter 70 value 80.644342 iter 80 value 79.863283 iter 90 value 79.437690 iter 100 value 79.268683 final value 79.268683 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 133.612222 iter 10 value 93.800278 iter 20 value 83.537592 iter 30 value 81.358125 iter 40 value 80.891551 iter 50 value 80.354574 iter 60 value 79.911015 iter 70 value 79.674529 iter 80 value 79.476323 iter 90 value 79.017992 iter 100 value 78.783996 final value 78.783996 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 98.186680 final value 94.054559 converged Fitting Repeat 2 # weights: 103 initial value 99.509231 iter 10 value 93.185982 iter 20 value 93.184668 iter 30 value 93.184262 iter 30 value 93.184262 iter 30 value 93.184261 final value 93.184261 converged Fitting Repeat 3 # weights: 103 initial value 103.495760 iter 10 value 91.080944 iter 20 value 91.080461 iter 30 value 89.109075 iter 40 value 85.840262 iter 50 value 85.447433 iter 60 value 85.200536 iter 70 value 85.200272 final value 85.200189 converged Fitting Repeat 4 # weights: 103 initial value 96.314366 final value 94.054487 converged Fitting Repeat 5 # weights: 103 initial value 120.787188 iter 10 value 93.837868 iter 20 value 93.836599 iter 30 value 92.168983 iter 40 value 85.231129 iter 50 value 85.219544 iter 60 value 85.217808 iter 70 value 85.217643 final value 85.217614 converged Fitting Repeat 1 # weights: 305 initial value 99.235357 iter 10 value 93.189224 iter 20 value 92.959330 iter 30 value 92.931934 iter 40 value 92.928866 iter 50 value 92.925885 iter 60 value 85.366370 final value 82.288578 converged Fitting Repeat 2 # weights: 305 initial value 114.616909 iter 10 value 94.057793 iter 20 value 92.019686 iter 30 value 91.992829 iter 40 value 91.991962 iter 50 value 91.991097 iter 60 value 91.115974 iter 70 value 89.218289 iter 80 value 89.142599 iter 90 value 89.141547 iter 100 value 89.140169 final value 89.140169 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 97.138898 iter 10 value 90.973281 iter 20 value 86.776360 iter 30 value 86.763428 iter 40 value 83.269144 iter 50 value 82.293669 iter 60 value 82.281949 iter 70 value 82.266449 iter 80 value 82.248812 iter 90 value 81.750312 final value 81.749912 converged Fitting Repeat 4 # weights: 305 initial value 95.753254 iter 10 value 92.740556 iter 20 value 92.733445 iter 30 value 91.806610 iter 40 value 81.704226 iter 50 value 78.279979 iter 60 value 77.513715 iter 70 value 77.370633 iter 80 value 77.053961 iter 90 value 77.049052 iter 100 value 77.048800 final value 77.048800 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 106.849250 iter 10 value 92.662568 iter 20 value 92.653915 iter 30 value 92.650223 final value 92.649787 converged Fitting Repeat 1 # weights: 507 initial value 94.996372 iter 10 value 88.789302 iter 20 value 81.938780 iter 30 value 81.048981 iter 40 value 80.584095 iter 50 value 80.065415 iter 60 value 79.925623 iter 70 value 79.909822 iter 80 value 79.751145 iter 90 value 79.617842 iter 100 value 79.614977 final value 79.614977 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 106.328680 iter 10 value 93.793069 iter 20 value 93.784812 iter 30 value 92.356556 iter 40 value 92.177440 iter 50 value 92.164212 iter 60 value 92.163125 iter 70 value 92.159648 iter 80 value 84.381884 iter 90 value 81.623769 iter 100 value 79.835580 final value 79.835580 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 109.533678 iter 10 value 91.018747 iter 20 value 90.246494 iter 30 value 82.749412 iter 40 value 82.710988 iter 50 value 82.694323 iter 60 value 82.687860 iter 70 value 82.687474 iter 80 value 82.659592 iter 90 value 82.652857 iter 100 value 82.652173 final value 82.652173 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 102.580132 iter 10 value 94.060790 iter 20 value 94.019448 iter 30 value 92.688553 iter 40 value 85.775723 iter 50 value 85.192307 iter 60 value 84.186950 iter 70 value 84.186633 iter 80 value 84.186452 iter 90 value 83.413035 iter 100 value 83.383856 final value 83.383856 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 109.015999 iter 10 value 94.060812 iter 20 value 94.009832 final value 93.836272 converged Fitting Repeat 1 # weights: 305 initial value 142.742679 iter 10 value 117.720057 iter 20 value 117.199264 iter 30 value 117.009899 iter 40 value 117.007792 iter 50 value 111.332887 iter 60 value 105.779927 iter 70 value 104.490740 iter 80 value 103.007159 iter 90 value 101.555294 iter 100 value 101.117740 final value 101.117740 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 156.619450 iter 10 value 117.895762 iter 20 value 117.890984 iter 30 value 111.409913 iter 40 value 105.802165 iter 50 value 105.406049 iter 60 value 105.249920 iter 70 value 104.417764 final value 104.417761 converged Fitting Repeat 3 # weights: 305 initial value 118.317194 iter 10 value 117.574688 iter 20 value 117.573208 iter 30 value 116.955742 iter 40 value 114.212456 iter 50 value 109.171178 iter 60 value 108.498318 iter 70 value 106.311409 iter 80 value 106.297798 iter 90 value 106.293951 iter 100 value 106.290404 final value 106.290404 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 118.482964 iter 10 value 117.871032 iter 20 value 117.695298 iter 30 value 109.708637 iter 40 value 106.778825 final value 106.778717 converged Fitting Repeat 5 # weights: 305 initial value 119.026623 iter 10 value 117.562270 iter 20 value 117.263904 iter 30 value 115.541738 iter 40 value 115.537673 iter 50 value 107.636015 final value 106.943938 converged svmRadial ranger Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases RUNIT TEST PROTOCOL -- Fri Aug 16 01:45:53 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 48.32 2.31 50.01
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 34.02 | 2.22 | 36.38 | |
FreqInteractors | 0.26 | 0.01 | 0.30 | |
calculateAAC | 0.08 | 0.00 | 0.08 | |
calculateAutocor | 0.50 | 0.07 | 0.56 | |
calculateCTDC | 0.06 | 0.01 | 0.08 | |
calculateCTDD | 0.84 | 0.03 | 0.88 | |
calculateCTDT | 0.36 | 0.03 | 0.39 | |
calculateCTriad | 0.41 | 0.04 | 0.43 | |
calculateDC | 0.12 | 0.01 | 0.15 | |
calculateF | 0.44 | 0.03 | 0.47 | |
calculateKSAAP | 0.08 | 0.00 | 0.08 | |
calculateQD_Sm | 2.01 | 0.26 | 2.28 | |
calculateTC | 1.99 | 0.10 | 2.08 | |
calculateTC_Sm | 0.36 | 0.03 | 0.39 | |
corr_plot | 34.72 | 1.51 | 36.26 | |
enrichfindP | 0.67 | 0.08 | 13.38 | |
enrichfind_hp | 0.11 | 0.03 | 1.03 | |
enrichplot | 0.49 | 0.00 | 0.49 | |
filter_missing_values | 0 | 0 | 0 | |
getFASTA | 0.00 | 0.02 | 2.53 | |
getHPI | 0 | 0 | 0 | |
get_negativePPI | 0 | 0 | 0 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0 | 0 | 0 | |
plotPPI | 0.05 | 0.02 | 0.14 | |
pred_ensembel | 15.51 | 0.70 | 11.92 | |
var_imp | 34.93 | 1.50 | 36.44 | |