Back to Multiple platform build/check report for BioC 3.20: simplified long |
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This page was generated on 2024-06-11 15:43 -0400 (Tue, 11 Jun 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 RC (2024-04-16 r86468) -- "Puppy Cup" | 4679 |
palomino4 | Windows Server 2022 Datacenter | x64 | 4.4.0 RC (2024-04-16 r86468 ucrt) -- "Puppy Cup" | 4414 |
merida1 | macOS 12.7.4 Monterey | x86_64 | 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup" | 4441 |
kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup" | 4394 |
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 961/2239 | 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 | |||||||||
palomino4 | 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 | |||||||||
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: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.11.0.tar.gz |
StartedAt: 2024-06-10 22:23:38 -0400 (Mon, 10 Jun 2024) |
EndedAt: 2024-06-10 22:29:20 -0400 (Mon, 10 Jun 2024) |
EllapsedTime: 341.7 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.11.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’ * using R version 4.4.0 Patched (2024-04-24 r86482) * using platform: aarch64-apple-darwin20 * R was compiled by Apple clang version 14.0.0 (clang-1400.0.29.202) GNU Fortran (GCC) 12.2.0 * running under: macOS Ventura 13.6.6 * 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 for sufficient/correct file permissions ... OK * checking whether package ‘HPiP’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... NOTE License stub is invalid DCF. * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... NOTE checkRd: (-1) getHPI.Rd:29: Lost braces 29 | then the Kronecker product is the code{(pm × qn)} block matrix | ^ * checking Rd metadata ... OK * checking Rd cross-references ... 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 54.251 2.380 56.952 corr_plot 53.557 2.485 56.261 FSmethod 43.056 1.630 45.589 pred_ensembel 16.725 0.311 14.372 enrichfindP 0.507 0.074 6.862 * 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 ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log’ for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/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 Patched (2024-04-24 r86482) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: aarch64-apple-darwin20 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > BiocGenerics:::testPackage('HPiP') No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE avNNet Loading required package: ggplot2 Loading required package: lattice Fitting Repeat 1 # weights: 103 initial value 104.906744 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 97.588295 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 95.529148 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 114.794030 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 97.653137 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 109.172266 final value 94.467391 converged Fitting Repeat 2 # weights: 305 initial value 97.475816 final value 94.304608 converged Fitting Repeat 3 # weights: 305 initial value 99.105414 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 122.468599 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 94.898371 iter 10 value 92.183582 iter 20 value 91.169804 iter 30 value 83.683408 iter 40 value 83.621539 iter 50 value 83.597693 final value 83.591261 converged Fitting Repeat 1 # weights: 507 initial value 109.327300 iter 10 value 92.077099 final value 92.074748 converged Fitting Repeat 2 # weights: 507 initial value 96.489752 iter 10 value 84.419201 iter 20 value 83.580295 iter 30 value 83.528294 iter 40 value 83.526332 final value 83.526317 converged Fitting Repeat 3 # weights: 507 initial value 103.047461 iter 10 value 94.478108 iter 20 value 94.467415 final value 94.467392 converged Fitting Repeat 4 # weights: 507 initial value 110.119004 final value 94.467391 converged Fitting Repeat 5 # weights: 507 initial value 116.480965 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 104.369195 iter 10 value 94.303878 iter 20 value 92.352312 iter 30 value 91.844349 iter 40 value 91.578939 iter 50 value 89.154430 iter 60 value 87.440042 iter 70 value 85.934807 iter 80 value 84.730995 iter 90 value 84.229264 iter 100 value 84.210306 final value 84.210306 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 100.743163 iter 10 value 94.488645 iter 20 value 94.138669 iter 30 value 93.603885 iter 40 value 93.504085 iter 50 value 89.353851 iter 60 value 88.703608 iter 70 value 85.383905 iter 80 value 84.389589 iter 90 value 83.847663 iter 100 value 83.279585 final value 83.279585 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 96.322296 iter 10 value 94.474179 iter 20 value 93.360050 iter 30 value 92.551093 iter 40 value 91.945785 iter 50 value 88.796197 iter 60 value 87.242158 iter 70 value 83.947179 iter 80 value 81.839263 iter 90 value 81.776003 final value 81.775987 converged Fitting Repeat 4 # weights: 103 initial value 100.168223 iter 10 value 94.530685 iter 20 value 94.463767 iter 30 value 94.064974 iter 40 value 92.949094 iter 50 value 91.566555 iter 60 value 86.864138 iter 70 value 84.070217 iter 80 value 83.404501 iter 90 value 83.170363 iter 100 value 82.693842 final value 82.693842 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 103.840428 iter 10 value 94.488771 iter 20 value 86.379368 iter 30 value 84.880665 iter 40 value 84.137892 iter 50 value 83.784363 iter 60 value 83.231742 iter 70 value 83.162384 final value 83.162256 converged Fitting Repeat 1 # weights: 305 initial value 118.707223 iter 10 value 94.417043 iter 20 value 91.595820 iter 30 value 91.306267 iter 40 value 88.269683 iter 50 value 85.246987 iter 60 value 83.930422 iter 70 value 82.891805 iter 80 value 82.437035 iter 90 value 82.380450 iter 100 value 82.064917 final value 82.064917 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 104.765522 iter 10 value 94.855717 iter 20 value 89.850295 iter 30 value 85.862107 iter 40 value 84.743752 iter 50 value 83.583785 iter 60 value 82.265520 iter 70 value 81.864860 iter 80 value 81.772629 iter 90 value 81.486893 iter 100 value 81.129170 final value 81.129170 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 123.198765 iter 10 value 94.184306 iter 20 value 92.089438 iter 30 value 84.621665 iter 40 value 84.157234 iter 50 value 83.716380 iter 60 value 82.878736 iter 70 value 82.641751 iter 80 value 82.345894 iter 90 value 82.303386 iter 100 value 81.622404 final value 81.622404 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 106.345197 iter 10 value 88.887469 iter 20 value 87.635407 iter 30 value 85.729399 iter 40 value 83.410836 iter 50 value 82.431956 iter 60 value 82.276765 iter 70 value 82.240941 iter 80 value 82.086014 iter 90 value 81.730931 iter 100 value 81.503256 final value 81.503256 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 110.015399 iter 10 value 94.368062 iter 20 value 92.258209 iter 30 value 91.988213 iter 40 value 85.502451 iter 50 value 84.231309 iter 60 value 83.581915 iter 70 value 81.732245 iter 80 value 81.366887 iter 90 value 80.933513 iter 100 value 80.857791 final value 80.857791 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 119.619925 iter 10 value 96.195806 iter 20 value 94.160904 iter 30 value 87.050846 iter 40 value 84.369851 iter 50 value 84.284443 iter 60 value 83.580710 iter 70 value 82.857495 iter 80 value 82.331235 iter 90 value 81.818244 iter 100 value 81.255676 final value 81.255676 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 114.166548 iter 10 value 94.848982 iter 20 value 92.608753 iter 30 value 84.761091 iter 40 value 83.497940 iter 50 value 81.997971 iter 60 value 81.363639 iter 70 value 80.733598 iter 80 value 80.685252 iter 90 value 80.656107 iter 100 value 80.606043 final value 80.606043 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 122.086420 iter 10 value 94.420426 iter 20 value 90.374978 iter 30 value 83.903983 iter 40 value 82.189684 iter 50 value 81.413408 iter 60 value 81.360950 iter 70 value 80.933088 iter 80 value 80.897823 iter 90 value 80.829925 iter 100 value 80.680874 final value 80.680874 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 110.793990 iter 10 value 93.337948 iter 20 value 85.131294 iter 30 value 83.984414 iter 40 value 83.812868 iter 50 value 82.982909 iter 60 value 82.136033 iter 70 value 81.218931 iter 80 value 81.027709 iter 90 value 80.571411 iter 100 value 80.409202 final value 80.409202 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 132.810861 iter 10 value 94.651952 iter 20 value 86.244109 iter 30 value 84.982804 iter 40 value 84.102267 iter 50 value 83.461647 iter 60 value 82.852949 iter 70 value 82.625419 iter 80 value 81.733393 iter 90 value 81.291628 iter 100 value 80.978625 final value 80.978625 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.918720 iter 10 value 94.485864 iter 20 value 94.484228 iter 30 value 84.603507 iter 40 value 83.580696 final value 83.580685 converged Fitting Repeat 2 # weights: 103 initial value 101.237844 final value 94.485640 converged Fitting Repeat 3 # weights: 103 initial value 103.915716 final value 94.485701 converged Fitting Repeat 4 # weights: 103 initial value 97.205244 final value 94.485733 converged Fitting Repeat 5 # weights: 103 initial value 101.152726 final value 94.486068 converged Fitting Repeat 1 # weights: 305 initial value 103.430768 iter 10 value 94.472128 iter 20 value 92.242890 iter 30 value 92.157968 iter 40 value 92.153130 iter 50 value 91.553461 final value 91.553456 converged Fitting Repeat 2 # weights: 305 initial value 119.964363 iter 10 value 94.489219 iter 20 value 94.136140 iter 30 value 91.662838 iter 40 value 88.931767 iter 50 value 88.914323 iter 60 value 88.816603 iter 70 value 88.337536 iter 80 value 88.030379 iter 90 value 88.026581 iter 100 value 87.629688 final value 87.629688 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 96.463045 iter 10 value 94.487560 iter 20 value 94.446908 iter 30 value 94.444186 iter 40 value 94.345512 iter 50 value 90.771774 iter 60 value 90.529114 iter 70 value 87.556055 iter 80 value 87.429133 iter 90 value 87.396906 iter 100 value 87.396178 final value 87.396178 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 99.130214 iter 10 value 94.488543 iter 20 value 94.484275 iter 30 value 88.684545 iter 40 value 84.223510 iter 50 value 83.867848 iter 60 value 83.860598 iter 70 value 83.733775 iter 80 value 83.580742 iter 80 value 83.580742 final value 83.580742 converged Fitting Repeat 5 # weights: 305 initial value 96.343656 iter 10 value 94.285312 iter 20 value 94.150081 iter 30 value 94.144597 iter 40 value 94.116132 iter 50 value 94.114437 iter 60 value 88.271023 iter 70 value 84.599092 iter 80 value 83.587388 iter 90 value 83.171408 iter 100 value 83.091700 final value 83.091700 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 96.584668 iter 10 value 89.319221 iter 20 value 89.048902 iter 30 value 89.034401 final value 88.808618 converged Fitting Repeat 2 # weights: 507 initial value 105.347703 iter 10 value 93.947571 iter 20 value 93.930541 iter 30 value 93.924691 iter 40 value 91.814112 iter 50 value 91.660651 iter 60 value 91.493902 iter 70 value 91.260844 final value 91.260764 converged Fitting Repeat 3 # weights: 507 initial value 103.239566 iter 10 value 94.491503 iter 20 value 94.485624 iter 30 value 94.351723 iter 40 value 87.756483 iter 50 value 85.346640 iter 60 value 85.136942 iter 70 value 83.319144 iter 80 value 83.060892 iter 90 value 83.037651 iter 100 value 82.977891 final value 82.977891 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 105.194445 iter 10 value 94.096860 iter 20 value 93.644403 iter 30 value 89.406986 iter 40 value 84.104563 iter 50 value 83.444053 iter 60 value 83.440308 iter 70 value 82.541686 iter 80 value 82.511999 iter 90 value 82.511880 iter 100 value 82.506531 final value 82.506531 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 112.372853 iter 10 value 92.080285 iter 20 value 92.067118 iter 30 value 91.232921 iter 40 value 91.082417 iter 50 value 91.037836 iter 60 value 90.989900 iter 70 value 90.989491 iter 80 value 90.523370 iter 90 value 90.255892 iter 100 value 86.683109 final value 86.683109 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.218477 iter 10 value 94.112904 iter 10 value 94.112903 iter 10 value 94.112903 final value 94.112903 converged Fitting Repeat 2 # weights: 103 initial value 100.235680 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 102.574480 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 102.079647 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 101.309002 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 97.712999 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 106.875580 iter 10 value 94.124537 final value 94.065746 converged Fitting Repeat 3 # weights: 305 initial value 105.059941 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 93.461628 iter 10 value 84.719596 iter 20 value 84.396067 iter 30 value 84.387880 iter 30 value 84.387879 iter 30 value 84.387879 final value 84.387879 converged Fitting Repeat 5 # weights: 305 initial value 104.108044 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 96.046016 iter 10 value 94.070517 iter 20 value 93.940239 iter 30 value 93.938225 final value 93.938213 converged Fitting Repeat 2 # weights: 507 initial value 96.564450 iter 10 value 86.233574 iter 20 value 85.822457 iter 30 value 84.848463 iter 40 value 84.569565 iter 40 value 84.569565 iter 40 value 84.569565 final value 84.569565 converged Fitting Repeat 3 # weights: 507 initial value 107.900949 iter 10 value 93.743183 final value 93.743182 converged Fitting Repeat 4 # weights: 507 initial value 113.870916 iter 10 value 94.165117 iter 10 value 94.165117 iter 10 value 94.165117 final value 94.165117 converged Fitting Repeat 5 # weights: 507 initial value 98.318320 iter 10 value 94.112873 iter 20 value 94.045984 final value 94.045978 converged Fitting Repeat 1 # weights: 103 initial value 103.326251 iter 10 value 94.096928 iter 20 value 86.828525 iter 30 value 86.644169 iter 40 value 86.543625 iter 50 value 85.846423 iter 60 value 83.311536 iter 70 value 83.162886 iter 80 value 83.127861 iter 90 value 83.101940 final value 83.098705 converged Fitting Repeat 2 # weights: 103 initial value 96.022900 iter 10 value 94.487946 iter 20 value 94.281960 iter 30 value 94.237419 iter 40 value 94.235278 iter 50 value 93.840713 iter 60 value 91.436075 iter 70 value 88.996484 iter 80 value 88.217690 iter 90 value 84.566880 iter 100 value 84.012076 final value 84.012076 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 99.916643 iter 10 value 94.469311 iter 20 value 90.070205 iter 30 value 87.032816 iter 40 value 86.409290 iter 50 value 86.332347 iter 60 value 83.738161 iter 70 value 83.631208 final value 83.630112 converged Fitting Repeat 4 # weights: 103 initial value 107.120244 iter 10 value 94.467429 iter 20 value 94.202774 iter 30 value 92.464409 iter 40 value 87.355830 iter 50 value 87.117017 iter 60 value 85.532260 iter 70 value 83.130061 iter 80 value 82.766407 iter 90 value 82.672131 iter 100 value 82.498836 final value 82.498836 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 101.583436 iter 10 value 94.441667 iter 20 value 87.929551 iter 30 value 86.926307 iter 40 value 84.008738 iter 50 value 83.698397 iter 60 value 83.680371 iter 70 value 83.666902 iter 70 value 83.666901 final value 83.666901 converged Fitting Repeat 1 # weights: 305 initial value 115.492092 iter 10 value 94.562275 iter 20 value 93.723242 iter 30 value 84.989330 iter 40 value 84.511471 iter 50 value 82.454206 iter 60 value 81.791436 iter 70 value 81.107327 iter 80 value 80.720694 iter 90 value 80.440653 iter 100 value 80.336583 final value 80.336583 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 115.760348 iter 10 value 97.000455 iter 20 value 88.131728 iter 30 value 84.331138 iter 40 value 83.343248 iter 50 value 82.146940 iter 60 value 81.274897 iter 70 value 80.882445 iter 80 value 80.648916 iter 90 value 80.420477 iter 100 value 80.357170 final value 80.357170 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 110.865503 iter 10 value 94.532797 iter 20 value 89.276332 iter 30 value 88.431938 iter 40 value 87.180566 iter 50 value 83.996911 iter 60 value 82.393225 iter 70 value 81.041382 iter 80 value 80.339648 iter 90 value 80.266848 iter 100 value 80.197185 final value 80.197185 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 114.023130 iter 10 value 96.406998 iter 20 value 90.588869 iter 30 value 87.042517 iter 40 value 86.636052 iter 50 value 86.550611 iter 60 value 83.178420 iter 70 value 81.765768 iter 80 value 81.226637 iter 90 value 81.183114 iter 100 value 81.119147 final value 81.119147 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 101.276963 iter 10 value 94.492747 iter 20 value 87.998891 iter 30 value 87.479241 iter 40 value 82.846336 iter 50 value 82.187317 iter 60 value 81.509832 iter 70 value 81.000633 iter 80 value 80.794493 iter 90 value 80.761149 final value 80.759637 converged Fitting Repeat 1 # weights: 507 initial value 110.434875 iter 10 value 93.996979 iter 20 value 84.796911 iter 30 value 83.501391 iter 40 value 81.882454 iter 50 value 81.649185 iter 60 value 81.489013 iter 70 value 81.293353 iter 80 value 81.228539 iter 90 value 80.785502 iter 100 value 80.426542 final value 80.426542 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 104.947214 iter 10 value 94.245525 iter 20 value 86.620452 iter 30 value 86.313355 iter 40 value 84.748297 iter 50 value 83.296491 iter 60 value 83.012235 iter 70 value 82.856003 iter 80 value 82.656158 iter 90 value 82.624319 iter 100 value 82.614318 final value 82.614318 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 104.893885 iter 10 value 94.661907 iter 20 value 89.199839 iter 30 value 88.605972 iter 40 value 86.155230 iter 50 value 82.752557 iter 60 value 82.137302 iter 70 value 81.689237 iter 80 value 81.520160 iter 90 value 81.388826 iter 100 value 81.206160 final value 81.206160 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 151.530822 iter 10 value 98.017851 iter 20 value 97.188791 iter 30 value 92.291399 iter 40 value 86.974945 iter 50 value 84.507692 iter 60 value 83.912499 iter 70 value 82.726058 iter 80 value 81.402087 iter 90 value 80.846991 iter 100 value 80.714044 final value 80.714044 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 107.578173 iter 10 value 94.604708 iter 20 value 91.754691 iter 30 value 83.665558 iter 40 value 81.338582 iter 50 value 81.007802 iter 60 value 80.812724 iter 70 value 80.537643 iter 80 value 80.469712 iter 90 value 80.376737 iter 100 value 80.097418 final value 80.097418 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.099232 iter 10 value 94.485946 iter 20 value 94.484224 final value 94.484216 converged Fitting Repeat 2 # weights: 103 initial value 101.956186 iter 10 value 94.114720 iter 20 value 94.103428 iter 30 value 93.849166 iter 40 value 87.481640 iter 50 value 87.247061 iter 60 value 87.246457 iter 70 value 87.245990 iter 80 value 86.343749 iter 90 value 85.400049 iter 100 value 84.697299 final value 84.697299 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 94.884384 final value 94.485845 converged Fitting Repeat 4 # weights: 103 initial value 96.300995 final value 94.485857 converged Fitting Repeat 5 # weights: 103 initial value 98.524353 final value 94.485891 converged Fitting Repeat 1 # weights: 305 initial value 95.812650 iter 10 value 94.492904 iter 20 value 94.333652 iter 30 value 94.117986 iter 40 value 92.293515 iter 50 value 86.043063 iter 60 value 85.932626 iter 70 value 85.931174 final value 85.931102 converged Fitting Repeat 2 # weights: 305 initial value 96.885058 iter 10 value 94.117659 iter 20 value 94.113567 iter 30 value 94.003498 iter 40 value 93.993936 iter 40 value 93.993936 final value 93.993936 converged Fitting Repeat 3 # weights: 305 initial value 101.046162 iter 10 value 94.489605 iter 20 value 94.471031 iter 30 value 92.665494 iter 40 value 92.529587 iter 50 value 86.295405 iter 60 value 84.113659 iter 60 value 84.113659 final value 82.746871 converged Fitting Repeat 4 # weights: 305 initial value 98.954516 iter 10 value 94.217668 iter 20 value 94.212820 iter 30 value 94.074609 final value 94.046277 converged Fitting Repeat 5 # weights: 305 initial value 103.229774 iter 10 value 94.489041 iter 20 value 94.389551 iter 30 value 88.421839 iter 40 value 87.508953 iter 50 value 84.696166 iter 60 value 84.673017 iter 70 value 84.587361 iter 80 value 82.448859 iter 90 value 81.267387 iter 100 value 81.263853 final value 81.263853 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 110.388584 iter 10 value 94.492632 iter 20 value 94.484379 iter 30 value 94.306455 iter 40 value 87.249524 iter 50 value 86.829808 iter 60 value 84.076513 final value 84.076262 converged Fitting Repeat 2 # weights: 507 initial value 95.604948 iter 10 value 94.121479 iter 20 value 94.096457 iter 30 value 93.779382 iter 40 value 93.712307 iter 50 value 93.712043 iter 50 value 93.712043 iter 50 value 93.712043 final value 93.712043 converged Fitting Repeat 3 # weights: 507 initial value 107.734050 iter 10 value 93.384958 iter 20 value 92.623118 iter 30 value 92.366798 iter 40 value 92.123966 iter 50 value 92.123338 final value 92.123319 converged Fitting Repeat 4 # weights: 507 initial value 112.799541 iter 10 value 94.121829 iter 20 value 94.032580 iter 30 value 87.747051 iter 40 value 85.479459 iter 50 value 83.788714 iter 60 value 81.862850 iter 70 value 80.348646 iter 80 value 80.085416 iter 90 value 80.054562 final value 80.053925 converged Fitting Repeat 5 # weights: 507 initial value 105.322581 iter 10 value 94.492423 iter 20 value 94.431462 iter 30 value 94.130229 final value 94.066132 converged Fitting Repeat 1 # weights: 103 initial value 96.785140 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 95.683959 final value 93.582418 converged Fitting Repeat 3 # weights: 103 initial value 96.099586 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 96.071532 final value 93.582418 converged Fitting Repeat 5 # weights: 103 initial value 101.290402 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 99.698826 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 102.981225 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 106.641759 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 112.135198 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 102.671772 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 104.453449 iter 10 value 85.071614 iter 20 value 83.686926 iter 30 value 83.361222 iter 40 value 82.706810 iter 50 value 82.210020 final value 82.209775 converged Fitting Repeat 2 # weights: 507 initial value 99.494793 final value 94.052910 converged Fitting Repeat 3 # weights: 507 initial value 136.818698 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 110.523093 iter 10 value 93.672976 final value 93.672974 converged Fitting Repeat 5 # weights: 507 initial value 95.283997 iter 10 value 93.095201 iter 20 value 92.940609 final value 92.935232 converged Fitting Repeat 1 # weights: 103 initial value 96.021425 iter 10 value 93.639092 iter 20 value 88.896629 iter 30 value 85.451703 iter 40 value 85.238158 iter 50 value 85.076903 iter 60 value 84.986677 iter 70 value 83.495604 final value 83.494475 converged Fitting Repeat 2 # weights: 103 initial value 100.254996 iter 10 value 94.047906 iter 20 value 93.050823 iter 30 value 89.528362 iter 40 value 83.878413 iter 50 value 80.799554 iter 60 value 80.014342 iter 70 value 79.793445 iter 80 value 79.735602 iter 90 value 79.638675 final value 79.634724 converged Fitting Repeat 3 # weights: 103 initial value 97.596284 iter 10 value 94.012076 iter 20 value 93.183305 iter 30 value 90.832596 iter 40 value 82.187059 iter 50 value 81.924603 iter 60 value 80.620826 iter 70 value 79.792912 iter 80 value 79.646105 iter 90 value 79.634760 final value 79.634724 converged Fitting Repeat 4 # weights: 103 initial value 113.977174 iter 10 value 93.980456 iter 20 value 93.208195 iter 30 value 93.105259 iter 40 value 90.302005 iter 50 value 87.447678 iter 60 value 87.382671 iter 70 value 85.026533 iter 80 value 84.986368 iter 90 value 84.967755 iter 100 value 84.802857 final value 84.802857 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 97.664917 iter 10 value 94.055261 iter 20 value 93.812748 iter 30 value 93.684448 iter 40 value 93.204260 iter 50 value 85.066074 iter 60 value 84.586445 iter 70 value 84.512920 iter 80 value 84.496826 iter 90 value 84.476967 iter 100 value 83.907860 final value 83.907860 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 99.074715 iter 10 value 88.018768 iter 20 value 82.205097 iter 30 value 81.911495 iter 40 value 81.851937 iter 50 value 80.906158 iter 60 value 79.441788 iter 70 value 78.830213 iter 80 value 78.575773 iter 90 value 78.273880 iter 100 value 78.142792 final value 78.142792 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 104.830115 iter 10 value 93.375740 iter 20 value 86.725394 iter 30 value 85.226234 iter 40 value 84.935107 iter 50 value 84.736515 iter 60 value 82.203697 iter 70 value 81.465877 iter 80 value 80.712152 iter 90 value 80.531009 iter 100 value 80.414548 final value 80.414548 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 105.741596 iter 10 value 93.517989 iter 20 value 84.661563 iter 30 value 82.043686 iter 40 value 80.566552 iter 50 value 79.289838 iter 60 value 78.973765 iter 70 value 78.853734 iter 80 value 78.709974 iter 90 value 78.659060 iter 100 value 78.630740 final value 78.630740 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 124.419362 iter 10 value 93.971786 iter 20 value 88.295145 iter 30 value 85.210985 iter 40 value 82.782439 iter 50 value 80.435143 iter 60 value 79.819759 iter 70 value 79.484456 iter 80 value 79.110574 iter 90 value 78.754935 iter 100 value 78.591492 final value 78.591492 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 105.320065 iter 10 value 93.549412 iter 20 value 91.101932 iter 30 value 84.624878 iter 40 value 84.280130 iter 50 value 83.435859 iter 60 value 81.888786 iter 70 value 80.026833 iter 80 value 79.440224 iter 90 value 78.563712 iter 100 value 78.348855 final value 78.348855 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 109.339625 iter 10 value 94.837325 iter 20 value 90.853184 iter 30 value 85.387430 iter 40 value 84.284628 iter 50 value 83.306925 iter 60 value 81.602951 iter 70 value 80.513619 iter 80 value 79.602768 iter 90 value 78.656787 iter 100 value 78.311689 final value 78.311689 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 132.141077 iter 10 value 93.180677 iter 20 value 89.325976 iter 30 value 85.566262 iter 40 value 84.317291 iter 50 value 80.783617 iter 60 value 79.899729 iter 70 value 78.944933 iter 80 value 78.814571 iter 90 value 78.676920 iter 100 value 78.506073 final value 78.506073 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 109.847356 iter 10 value 95.266962 iter 20 value 85.426563 iter 30 value 84.262794 iter 40 value 82.824344 iter 50 value 81.980186 iter 60 value 81.580717 iter 70 value 81.311396 iter 80 value 80.894106 iter 90 value 79.768547 iter 100 value 79.493708 final value 79.493708 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 102.113357 iter 10 value 94.463494 iter 20 value 89.265606 iter 30 value 82.910554 iter 40 value 79.653209 iter 50 value 79.242665 iter 60 value 78.925405 iter 70 value 78.454623 iter 80 value 78.351565 iter 90 value 78.100897 iter 100 value 78.044573 final value 78.044573 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 113.386929 iter 10 value 94.057962 iter 20 value 91.071366 iter 30 value 86.382205 iter 40 value 83.806953 iter 50 value 82.502612 iter 60 value 80.836826 iter 70 value 79.592806 iter 80 value 79.399137 iter 90 value 78.823535 iter 100 value 78.681670 final value 78.681670 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 101.672998 final value 94.054597 converged Fitting Repeat 2 # weights: 103 initial value 105.456538 final value 94.054553 converged Fitting Repeat 3 # weights: 103 initial value 101.502196 iter 10 value 94.054663 iter 20 value 94.052977 iter 30 value 93.587565 final value 93.582786 converged Fitting Repeat 4 # weights: 103 initial value 100.680273 iter 10 value 94.054803 iter 20 value 94.052920 final value 94.052914 converged Fitting Repeat 5 # weights: 103 initial value 116.442226 iter 10 value 93.944473 iter 20 value 92.823750 iter 30 value 88.561640 iter 40 value 85.293759 iter 50 value 84.938753 iter 60 value 82.690843 final value 82.689097 converged Fitting Repeat 1 # weights: 305 initial value 96.350520 iter 10 value 93.370687 iter 20 value 93.367566 iter 30 value 88.296462 iter 40 value 82.807055 iter 50 value 82.795322 iter 60 value 82.790079 iter 70 value 81.737935 iter 80 value 81.378349 iter 90 value 81.309999 iter 100 value 81.300860 final value 81.300860 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 110.080605 iter 10 value 94.057515 iter 20 value 93.986832 iter 30 value 91.812513 iter 40 value 85.138818 iter 50 value 84.450063 iter 60 value 84.401788 iter 70 value 84.391969 iter 80 value 84.390077 iter 90 value 84.389902 iter 100 value 84.389590 final value 84.389590 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 95.159303 iter 10 value 94.057657 iter 20 value 94.041335 iter 30 value 93.160945 iter 40 value 93.116098 iter 50 value 93.114449 iter 60 value 93.114317 iter 70 value 93.113920 final value 93.113801 converged Fitting Repeat 4 # weights: 305 initial value 97.489631 iter 10 value 93.459745 iter 20 value 93.425356 iter 30 value 93.370614 iter 40 value 92.080484 iter 50 value 91.386361 iter 60 value 91.339606 iter 70 value 91.216427 iter 80 value 91.125264 iter 90 value 91.112658 iter 100 value 91.109228 final value 91.109228 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 103.150761 iter 10 value 94.058129 iter 20 value 93.304183 iter 30 value 89.594752 iter 30 value 89.594752 iter 30 value 89.594752 final value 89.594752 converged Fitting Repeat 1 # weights: 507 initial value 98.591417 iter 10 value 92.376446 iter 20 value 92.260448 iter 30 value 91.788388 iter 40 value 91.477721 iter 50 value 91.476887 iter 60 value 91.475639 final value 91.475636 converged Fitting Repeat 2 # weights: 507 initial value 97.775003 iter 10 value 93.878463 iter 20 value 93.877634 iter 30 value 93.876444 iter 40 value 93.873053 final value 93.872938 converged Fitting Repeat 3 # weights: 507 initial value 98.765147 iter 10 value 94.060883 iter 20 value 93.972328 iter 30 value 90.938040 iter 40 value 90.932959 iter 50 value 90.928123 iter 60 value 90.727138 iter 70 value 89.874139 iter 80 value 89.672902 iter 90 value 89.645960 final value 89.645614 converged Fitting Repeat 4 # weights: 507 initial value 107.973072 iter 10 value 93.591415 iter 20 value 93.583387 iter 30 value 86.196560 iter 40 value 84.265826 iter 50 value 79.872214 iter 60 value 79.522036 iter 70 value 79.073768 iter 80 value 78.913269 iter 90 value 78.619119 iter 100 value 78.606507 final value 78.606507 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 108.476669 iter 10 value 94.054670 iter 20 value 92.250628 iter 30 value 85.266980 iter 40 value 83.225057 final value 83.203426 converged Fitting Repeat 1 # weights: 103 initial value 101.394281 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 96.621980 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 102.397550 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 99.136712 final value 93.356643 converged Fitting Repeat 5 # weights: 103 initial value 94.208708 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 95.210965 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 97.396984 iter 10 value 93.915749 final value 93.915746 converged Fitting Repeat 3 # weights: 305 initial value 95.063685 final value 93.893849 converged Fitting Repeat 4 # weights: 305 initial value 121.448790 iter 10 value 93.915746 iter 10 value 93.915746 iter 10 value 93.915746 final value 93.915746 converged Fitting Repeat 5 # weights: 305 initial value 97.752347 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 107.302140 iter 10 value 90.088968 iter 20 value 89.593720 final value 89.593238 converged Fitting Repeat 2 # weights: 507 initial value 93.739553 iter 10 value 89.607230 iter 20 value 89.550611 final value 89.550509 converged Fitting Repeat 3 # weights: 507 initial value 107.920833 iter 10 value 93.390766 iter 20 value 93.273675 iter 30 value 93.273394 final value 93.273392 converged Fitting Repeat 4 # weights: 507 initial value 97.833385 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 102.433655 iter 10 value 93.409697 iter 20 value 93.284593 final value 93.284494 converged Fitting Repeat 1 # weights: 103 initial value 105.633227 iter 10 value 94.054918 iter 20 value 93.771227 iter 30 value 93.517326 iter 40 value 93.363331 iter 50 value 93.225392 iter 60 value 88.327703 iter 70 value 87.641833 iter 80 value 87.217560 iter 90 value 85.357549 iter 100 value 85.060257 final value 85.060257 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 106.604333 iter 10 value 93.965230 iter 20 value 93.445076 iter 30 value 92.833320 iter 40 value 89.415732 iter 50 value 86.526676 iter 60 value 86.395435 iter 70 value 86.269517 iter 80 value 85.534459 iter 90 value 84.873607 final value 84.870573 converged Fitting Repeat 3 # weights: 103 initial value 97.343123 iter 10 value 94.072484 iter 20 value 90.368660 iter 30 value 85.431278 iter 40 value 85.210583 iter 50 value 85.049462 iter 60 value 84.909160 iter 70 value 84.871144 final value 84.870573 converged Fitting Repeat 4 # weights: 103 initial value 101.439709 iter 10 value 93.901405 iter 20 value 89.110859 iter 30 value 85.869326 iter 40 value 85.457596 iter 50 value 85.155825 final value 85.134374 converged Fitting Repeat 5 # weights: 103 initial value 96.302051 iter 10 value 94.141025 iter 20 value 90.262861 iter 30 value 85.555506 iter 40 value 85.385031 iter 50 value 85.182675 iter 60 value 85.136385 final value 85.136312 converged Fitting Repeat 1 # weights: 305 initial value 101.481869 iter 10 value 94.220726 iter 20 value 89.092638 iter 30 value 87.216935 iter 40 value 86.689280 iter 50 value 85.451451 iter 60 value 84.392665 iter 70 value 83.380184 iter 80 value 82.979145 iter 90 value 82.039222 iter 100 value 81.629849 final value 81.629849 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 106.277371 iter 10 value 93.965182 iter 20 value 92.390097 iter 30 value 90.053197 iter 40 value 87.778792 iter 50 value 83.751542 iter 60 value 83.232247 iter 70 value 81.876815 iter 80 value 81.268452 iter 90 value 80.928232 iter 100 value 80.796776 final value 80.796776 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.850842 iter 10 value 94.086840 iter 20 value 90.227104 iter 30 value 89.049373 iter 40 value 87.418884 iter 50 value 84.910258 iter 60 value 84.395490 iter 70 value 83.530163 iter 80 value 81.851134 iter 90 value 81.744947 iter 100 value 81.654676 final value 81.654676 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 138.431875 iter 10 value 94.148221 iter 20 value 94.005629 iter 30 value 93.529310 iter 40 value 93.312351 iter 50 value 88.271014 iter 60 value 88.090613 iter 70 value 87.723566 iter 80 value 85.566981 iter 90 value 84.857421 iter 100 value 83.795462 final value 83.795462 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 108.649159 iter 10 value 94.832549 iter 20 value 94.061781 iter 30 value 91.617617 iter 40 value 87.182617 iter 50 value 85.241428 iter 60 value 83.241069 iter 70 value 82.162419 iter 80 value 81.766227 iter 90 value 81.597611 iter 100 value 81.374506 final value 81.374506 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 116.269343 iter 10 value 94.262095 iter 20 value 92.946340 iter 30 value 88.303799 iter 40 value 83.944061 iter 50 value 82.613302 iter 60 value 81.812318 iter 70 value 81.269314 iter 80 value 81.071221 iter 90 value 81.031511 iter 100 value 80.806779 final value 80.806779 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 110.841331 iter 10 value 95.330422 iter 20 value 90.621535 iter 30 value 88.658803 iter 40 value 84.238138 iter 50 value 82.674467 iter 60 value 82.009917 iter 70 value 81.666510 iter 80 value 81.510155 iter 90 value 81.293568 iter 100 value 80.912975 final value 80.912975 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 106.046631 iter 10 value 93.130655 iter 20 value 92.522647 iter 30 value 88.008116 iter 40 value 85.621481 iter 50 value 84.562065 iter 60 value 83.486653 iter 70 value 83.097462 iter 80 value 82.941108 iter 90 value 82.547966 iter 100 value 81.983137 final value 81.983137 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 110.558789 iter 10 value 94.339416 iter 20 value 93.789439 iter 30 value 90.566003 iter 40 value 85.531895 iter 50 value 83.876330 iter 60 value 83.668390 iter 70 value 83.220899 iter 80 value 82.732681 iter 90 value 81.783821 iter 100 value 81.600534 final value 81.600534 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 104.295714 iter 10 value 95.035568 iter 20 value 94.186121 iter 30 value 93.359979 iter 40 value 91.981785 iter 50 value 86.984454 iter 60 value 85.342919 iter 70 value 85.074492 iter 80 value 84.679093 iter 90 value 83.545620 iter 100 value 82.014451 final value 82.014451 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.473476 final value 94.054633 converged Fitting Repeat 2 # weights: 103 initial value 101.550799 final value 94.054394 converged Fitting Repeat 3 # weights: 103 initial value 106.031205 iter 10 value 94.053893 iter 20 value 93.866364 iter 30 value 93.865649 iter 40 value 93.268935 iter 50 value 93.259075 iter 60 value 93.258833 iter 60 value 93.258832 iter 60 value 93.258832 final value 93.258832 converged Fitting Repeat 4 # weights: 103 initial value 102.813137 final value 94.054550 converged Fitting Repeat 5 # weights: 103 initial value 98.901660 final value 94.054488 converged Fitting Repeat 1 # weights: 305 initial value 96.670871 iter 10 value 94.057908 iter 20 value 92.361863 final value 92.274164 converged Fitting Repeat 2 # weights: 305 initial value 94.929339 iter 10 value 93.184946 iter 20 value 93.183658 final value 93.180669 converged Fitting Repeat 3 # weights: 305 initial value 111.305400 iter 10 value 94.058086 iter 20 value 94.053000 iter 30 value 93.486796 iter 40 value 88.617394 iter 50 value 88.498619 iter 60 value 88.496552 iter 70 value 85.913944 iter 80 value 85.881857 iter 90 value 85.868704 iter 100 value 84.572146 final value 84.572146 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 109.513794 iter 10 value 93.495496 iter 20 value 93.290835 iter 30 value 93.289512 iter 40 value 91.549049 iter 50 value 87.108010 iter 60 value 85.294964 iter 70 value 84.284614 iter 80 value 84.260468 iter 90 value 84.202914 iter 100 value 83.801795 final value 83.801795 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 101.969467 iter 10 value 94.057741 iter 20 value 94.053441 iter 30 value 94.002863 iter 40 value 84.523856 iter 50 value 84.448272 iter 60 value 83.683796 iter 70 value 82.337523 iter 80 value 81.742758 iter 90 value 81.728387 iter 100 value 81.592332 final value 81.592332 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 100.457152 iter 10 value 94.061032 iter 20 value 94.053118 iter 30 value 93.395059 iter 40 value 88.046324 iter 50 value 85.340111 iter 60 value 84.831319 iter 70 value 83.815553 iter 80 value 81.099816 iter 90 value 80.427117 iter 100 value 80.362595 final value 80.362595 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 111.792446 iter 10 value 94.060919 iter 20 value 94.053260 iter 30 value 93.164691 iter 40 value 86.459504 iter 50 value 84.675213 iter 60 value 83.827691 iter 70 value 83.817650 iter 80 value 83.816667 iter 90 value 83.466765 iter 100 value 81.483458 final value 81.483458 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 115.016313 iter 10 value 94.061049 iter 20 value 93.431178 iter 30 value 86.304012 iter 40 value 86.034662 iter 50 value 86.018387 iter 60 value 85.366120 iter 70 value 83.968239 final value 83.924733 converged Fitting Repeat 4 # weights: 507 initial value 103.194940 iter 10 value 93.924426 iter 20 value 93.025390 iter 30 value 86.612310 iter 40 value 85.050806 iter 50 value 83.608154 iter 60 value 82.343046 iter 70 value 82.163064 iter 80 value 81.939237 iter 90 value 81.938270 iter 100 value 81.934478 final value 81.934478 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 99.453122 iter 10 value 93.340117 iter 20 value 93.291809 iter 30 value 93.289844 iter 40 value 93.173205 iter 50 value 84.463103 iter 60 value 82.619672 iter 70 value 81.008177 iter 80 value 80.527837 final value 80.514744 converged Fitting Repeat 1 # weights: 103 initial value 98.534857 final value 94.484210 converged Fitting Repeat 2 # weights: 103 initial value 97.947602 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 95.374618 iter 10 value 94.427051 final value 94.424077 converged Fitting Repeat 4 # weights: 103 initial value 102.819812 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 103.828373 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 95.879127 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 101.841623 final value 94.466823 converged Fitting Repeat 3 # weights: 305 initial value 95.120111 final value 94.046703 converged Fitting Repeat 4 # weights: 305 initial value 101.700161 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 105.206582 iter 10 value 94.323810 iter 10 value 94.323810 iter 10 value 94.323810 final value 94.323810 converged Fitting Repeat 1 # weights: 507 initial value 97.324226 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 111.857264 final value 94.046703 converged Fitting Repeat 3 # weights: 507 initial value 109.701384 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 102.357684 iter 10 value 89.733148 iter 20 value 89.656169 iter 30 value 89.633118 iter 30 value 89.633117 iter 30 value 89.633117 final value 89.633117 converged Fitting Repeat 5 # weights: 507 initial value 102.569585 final value 94.466823 converged Fitting Repeat 1 # weights: 103 initial value 105.025815 iter 10 value 94.131107 iter 20 value 85.590474 iter 30 value 84.536518 iter 40 value 84.314503 iter 50 value 84.137540 iter 60 value 83.451161 iter 70 value 83.327898 final value 83.327696 converged Fitting Repeat 2 # weights: 103 initial value 99.529851 iter 10 value 94.480980 iter 20 value 91.674609 iter 30 value 85.931849 iter 40 value 83.935400 iter 50 value 82.707376 iter 60 value 82.546791 iter 70 value 82.104043 iter 80 value 81.886080 iter 90 value 81.574259 iter 100 value 81.528958 final value 81.528958 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 97.681082 iter 10 value 94.483931 iter 20 value 92.539066 iter 30 value 90.965190 iter 40 value 90.341363 iter 50 value 86.891565 iter 60 value 82.919678 iter 70 value 82.812855 iter 80 value 81.663756 iter 90 value 81.349505 iter 100 value 81.166483 final value 81.166483 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 113.055810 iter 10 value 94.402880 iter 20 value 91.780671 iter 30 value 90.241716 iter 40 value 85.486214 iter 50 value 84.693886 iter 60 value 84.270278 iter 70 value 83.826521 iter 80 value 83.806906 final value 83.805711 converged Fitting Repeat 5 # weights: 103 initial value 96.309286 iter 10 value 94.424876 iter 20 value 85.490048 iter 30 value 85.105710 iter 40 value 83.909056 iter 50 value 83.362875 iter 60 value 83.337349 iter 70 value 83.327709 final value 83.327607 converged Fitting Repeat 1 # weights: 305 initial value 129.534526 iter 10 value 94.690270 iter 20 value 87.806307 iter 30 value 86.525644 iter 40 value 84.703351 iter 50 value 83.496926 iter 60 value 82.847974 iter 70 value 82.601399 iter 80 value 82.419980 iter 90 value 82.305354 iter 100 value 82.175409 final value 82.175409 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.568766 iter 10 value 94.532255 iter 20 value 94.490870 iter 30 value 86.748441 iter 40 value 85.489383 iter 50 value 84.729421 iter 60 value 82.780673 iter 70 value 82.371048 iter 80 value 82.011457 iter 90 value 81.817365 iter 100 value 81.689489 final value 81.689489 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 115.561506 iter 10 value 94.603054 iter 20 value 88.861997 iter 30 value 84.651212 iter 40 value 82.544945 iter 50 value 81.805679 iter 60 value 81.367735 iter 70 value 81.190345 iter 80 value 80.667144 iter 90 value 79.971939 iter 100 value 79.590911 final value 79.590911 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 102.581320 iter 10 value 94.614611 iter 20 value 94.467556 iter 30 value 89.338983 iter 40 value 88.809612 iter 50 value 87.995495 iter 60 value 86.549137 iter 70 value 84.671690 iter 80 value 84.330055 iter 90 value 81.667443 iter 100 value 80.797860 final value 80.797860 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 101.939163 iter 10 value 94.696745 iter 20 value 85.436728 iter 30 value 84.641536 iter 40 value 84.066614 iter 50 value 83.925911 iter 60 value 82.726440 iter 70 value 80.873109 iter 80 value 79.916839 iter 90 value 79.353627 iter 100 value 79.231295 final value 79.231295 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 117.717078 iter 10 value 94.571209 iter 20 value 91.930794 iter 30 value 90.731536 iter 40 value 84.406231 iter 50 value 84.031151 iter 60 value 83.575154 iter 70 value 83.341510 iter 80 value 83.143346 iter 90 value 82.279361 iter 100 value 82.079358 final value 82.079358 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 119.519707 iter 10 value 89.749306 iter 20 value 83.436525 iter 30 value 81.540071 iter 40 value 81.063858 iter 50 value 80.887988 iter 60 value 80.063532 iter 70 value 79.920884 iter 80 value 79.768190 iter 90 value 79.683611 iter 100 value 79.501653 final value 79.501653 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 127.574831 iter 10 value 94.433264 iter 20 value 86.232901 iter 30 value 83.307266 iter 40 value 82.473691 iter 50 value 82.287693 iter 60 value 81.123962 iter 70 value 80.395241 iter 80 value 79.911281 iter 90 value 79.598156 iter 100 value 79.337704 final value 79.337704 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 119.817632 iter 10 value 94.849298 iter 20 value 94.318521 iter 30 value 89.947082 iter 40 value 87.333366 iter 50 value 84.280433 iter 60 value 82.817850 iter 70 value 81.640330 iter 80 value 80.413570 iter 90 value 80.166267 iter 100 value 80.051554 final value 80.051554 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 110.436854 iter 10 value 94.458711 iter 20 value 85.562798 iter 30 value 83.299704 iter 40 value 83.173265 iter 50 value 82.083342 iter 60 value 81.809783 iter 70 value 81.636075 iter 80 value 81.403061 iter 90 value 80.618491 iter 100 value 80.154158 final value 80.154158 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 101.972495 iter 10 value 94.486095 final value 94.484218 converged Fitting Repeat 2 # weights: 103 initial value 97.714039 final value 94.485763 converged Fitting Repeat 3 # weights: 103 initial value 94.728913 final value 94.485997 converged Fitting Repeat 4 # weights: 103 initial value 96.434283 final value 94.485599 converged Fitting Repeat 5 # weights: 103 initial value 99.840618 final value 94.485891 converged Fitting Repeat 1 # weights: 305 initial value 98.589608 iter 10 value 85.709618 iter 20 value 84.902603 iter 30 value 83.690999 iter 40 value 83.358042 iter 50 value 83.112755 iter 60 value 83.106991 iter 70 value 83.106251 final value 83.105601 converged Fitting Repeat 2 # weights: 305 initial value 102.566910 iter 10 value 94.432667 iter 20 value 94.428491 iter 30 value 94.268434 iter 40 value 94.025200 iter 50 value 94.020706 final value 94.019666 converged Fitting Repeat 3 # weights: 305 initial value 105.773110 iter 10 value 94.471820 iter 20 value 94.420177 iter 30 value 83.690675 iter 40 value 83.686504 final value 83.686495 converged Fitting Repeat 4 # weights: 305 initial value 96.621587 iter 10 value 94.471731 iter 20 value 93.397633 iter 30 value 90.354273 iter 40 value 90.329297 iter 50 value 90.144661 iter 60 value 85.676577 iter 70 value 84.816095 iter 80 value 84.778292 iter 90 value 84.775082 iter 100 value 84.769522 final value 84.769522 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 112.836252 iter 10 value 94.490793 iter 20 value 94.486073 iter 30 value 94.218196 iter 40 value 94.025661 iter 50 value 89.342424 iter 60 value 87.421661 iter 70 value 87.308389 iter 80 value 87.307610 final value 87.307582 converged Fitting Repeat 1 # weights: 507 initial value 104.035726 iter 10 value 94.492183 iter 20 value 94.447468 iter 30 value 83.296251 iter 40 value 83.107117 final value 83.107088 converged Fitting Repeat 2 # weights: 507 initial value 116.985302 iter 10 value 95.009969 iter 20 value 94.108874 iter 30 value 94.105260 iter 40 value 94.017033 iter 50 value 93.925633 iter 60 value 93.213355 iter 70 value 92.670867 iter 80 value 92.662186 final value 92.661557 converged Fitting Repeat 3 # weights: 507 initial value 101.677231 iter 10 value 94.475406 iter 20 value 93.759441 iter 30 value 86.200544 iter 40 value 85.844336 iter 50 value 85.705395 final value 85.693644 converged Fitting Repeat 4 # weights: 507 initial value 99.045034 iter 10 value 94.475468 iter 20 value 94.452926 iter 30 value 94.432070 iter 40 value 94.257691 iter 50 value 94.256480 iter 60 value 94.241089 iter 70 value 94.239627 iter 80 value 87.233875 iter 90 value 86.630078 iter 100 value 81.170142 final value 81.170142 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 124.694248 iter 10 value 94.481881 iter 20 value 94.474296 iter 30 value 94.431290 iter 30 value 94.431290 iter 40 value 83.798255 final value 83.687621 converged Fitting Repeat 1 # weights: 305 initial value 134.582375 iter 10 value 117.826124 iter 20 value 109.184603 iter 30 value 105.459857 iter 40 value 105.149999 iter 50 value 104.669635 iter 60 value 103.416120 iter 70 value 102.720303 iter 80 value 102.430564 iter 90 value 102.314594 iter 100 value 101.989649 final value 101.989649 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 151.360436 iter 10 value 117.764421 iter 20 value 107.314260 iter 30 value 105.484880 iter 40 value 105.160561 iter 50 value 104.062216 iter 60 value 103.190219 iter 70 value 103.021909 iter 80 value 102.727041 iter 90 value 101.844567 iter 100 value 101.050155 final value 101.050155 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 137.773787 iter 10 value 117.812305 iter 20 value 113.000559 iter 30 value 106.284928 iter 40 value 105.773070 iter 50 value 103.901248 iter 60 value 102.592869 iter 70 value 102.207108 iter 80 value 101.942905 iter 90 value 101.758178 iter 100 value 101.511886 final value 101.511886 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 141.385759 iter 10 value 117.655007 iter 20 value 117.581960 iter 30 value 115.535715 iter 40 value 112.244490 iter 50 value 110.684130 iter 60 value 106.992988 iter 70 value 103.921612 iter 80 value 103.278216 iter 90 value 102.634503 iter 100 value 102.267267 final value 102.267267 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 143.718345 iter 10 value 117.934471 iter 20 value 117.784704 iter 30 value 116.370957 iter 40 value 108.084450 iter 50 value 107.558925 iter 60 value 106.418442 iter 70 value 105.686435 iter 80 value 105.075612 iter 90 value 102.498660 iter 100 value 101.333548 final value 101.333548 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 -- Mon Jun 10 22:29:09 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 49.445 1.198 50.666
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 43.056 | 1.630 | 45.589 | |
FreqInteractors | 0.266 | 0.013 | 0.279 | |
calculateAAC | 0.045 | 0.007 | 0.052 | |
calculateAutocor | 0.412 | 0.081 | 0.497 | |
calculateCTDC | 0.085 | 0.003 | 0.088 | |
calculateCTDD | 0.607 | 0.022 | 0.631 | |
calculateCTDT | 0.258 | 0.016 | 0.274 | |
calculateCTriad | 0.800 | 0.041 | 0.842 | |
calculateDC | 0.103 | 0.013 | 0.116 | |
calculateF | 0.345 | 0.019 | 0.366 | |
calculateKSAAP | 0.104 | 0.011 | 0.114 | |
calculateQD_Sm | 1.863 | 0.119 | 1.992 | |
calculateTC | 1.717 | 0.168 | 1.891 | |
calculateTC_Sm | 0.388 | 0.030 | 0.422 | |
corr_plot | 53.557 | 2.485 | 56.261 | |
enrichfindP | 0.507 | 0.074 | 6.862 | |
enrichfind_hp | 0.074 | 0.015 | 0.699 | |
enrichplot | 0.400 | 0.009 | 0.411 | |
filter_missing_values | 0.002 | 0.000 | 0.001 | |
getFASTA | 0.091 | 0.014 | 1.308 | |
getHPI | 0.001 | 0.001 | 0.001 | |
get_negativePPI | 0.001 | 0.000 | 0.002 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0.002 | 0.000 | 0.002 | |
plotPPI | 0.080 | 0.004 | 0.084 | |
pred_ensembel | 16.725 | 0.311 | 14.372 | |
var_imp | 54.251 | 2.380 | 56.952 | |