Back to Multiple platform build/check report for BioC 3.19: simplified long |
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This page was generated on 2024-05-04 11:36:40 -0400 (Sat, 04 May 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4753 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" | 4486 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 beta (2024-04-14 r86421) -- "Puppy Cup" | 4519 |
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4479 |
Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X |
Package 987/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.10.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | ||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
kjohnson3 | macOS 13.6.5 Ventura / arm64 | see weekly results here | ||||||||||||
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: HPiP |
Version: 1.10.0 |
Command: /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings HPiP_1.10.0.tar.gz |
StartedAt: 2024-05-04 00:08:57 -0400 (Sat, 04 May 2024) |
EndedAt: 2024-05-04 00:22:40 -0400 (Sat, 04 May 2024) |
EllapsedTime: 822.5 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings HPiP_1.10.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’ * using R version 4.4.0 beta (2024-04-15 r86425) * using platform: x86_64-pc-linux-gnu * R was compiled by gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 * running under: Ubuntu 22.04.4 LTS * using session charset: UTF-8 * checking for file ‘HPiP/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘HPiP’ version ‘1.10.0’ * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘HPiP’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... NOTE License stub is invalid DCF. * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking loading without being on the library search path ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... NOTE checkRd: (-1) getHPI.Rd:29: Lost braces 29 | then the Kronecker product is the code{(pm × qn)} block matrix | ^ * checking Rd metadata ... OK * checking Rd cross-references ... 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 36.442 0.931 37.374 FSmethod 34.787 0.653 35.439 corr_plot 34.502 0.296 34.799 pred_ensembel 13.473 0.657 10.880 enrichfindP 0.458 0.042 12.046 * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘runTests.R’ OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking re-building of vignette outputs ... OK * checking PDF version of manual ... OK * DONE Status: 3 NOTEs See ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’ for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.19-bioc/R/site-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 beta (2024-04-15 r86425) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > BiocGenerics:::testPackage('HPiP') No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE avNNet Loading required package: ggplot2 Loading required package: lattice Fitting Repeat 1 # weights: 103 initial value 97.785550 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 99.315168 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 100.150639 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 102.856934 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 96.189374 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 98.821412 iter 10 value 92.147252 iter 20 value 91.348044 iter 30 value 90.414313 final value 90.234101 converged Fitting Repeat 2 # weights: 305 initial value 119.617973 iter 10 value 94.466823 iter 10 value 94.466823 iter 10 value 94.466823 final value 94.466823 converged Fitting Repeat 3 # weights: 305 initial value 103.489970 iter 10 value 93.448109 iter 20 value 88.949584 iter 30 value 88.709498 final value 88.707699 converged Fitting Repeat 4 # weights: 305 initial value 98.686729 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 97.673333 iter 10 value 94.169911 iter 20 value 93.735989 final value 93.735903 converged Fitting Repeat 1 # weights: 507 initial value 120.224303 iter 10 value 93.116790 final value 93.102857 converged Fitting Repeat 2 # weights: 507 initial value 146.036678 iter 10 value 93.797016 iter 20 value 93.617120 final value 93.617022 converged Fitting Repeat 3 # weights: 507 initial value 100.941142 iter 10 value 93.520342 final value 80.136336 converged Fitting Repeat 4 # weights: 507 initial value 101.764792 final value 94.466822 converged Fitting Repeat 5 # weights: 507 initial value 105.146697 final value 94.466823 converged Fitting Repeat 1 # weights: 103 initial value 103.448403 iter 10 value 94.431357 iter 20 value 85.373597 iter 30 value 81.959253 iter 40 value 80.240221 iter 50 value 79.564039 iter 60 value 79.140229 iter 70 value 78.763194 iter 80 value 78.069938 iter 90 value 77.549743 iter 100 value 77.546502 final value 77.546502 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 103.183432 iter 10 value 94.489612 iter 20 value 93.381886 iter 30 value 82.314957 iter 40 value 81.957744 iter 50 value 81.357797 iter 60 value 81.230683 iter 70 value 81.036882 iter 80 value 81.007647 final value 81.005617 converged Fitting Repeat 3 # weights: 103 initial value 98.120577 iter 10 value 94.487397 iter 20 value 94.335367 iter 30 value 93.733077 iter 40 value 85.293805 iter 50 value 85.011067 iter 60 value 83.791461 iter 70 value 81.667835 iter 80 value 81.155180 iter 90 value 80.987065 iter 100 value 80.971014 final value 80.971014 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 102.388691 iter 10 value 91.925520 iter 20 value 85.545368 iter 30 value 84.499235 iter 40 value 82.077470 iter 50 value 81.604144 iter 60 value 81.329741 iter 70 value 81.120575 iter 80 value 81.008181 final value 81.005618 converged Fitting Repeat 5 # weights: 103 initial value 99.360838 iter 10 value 94.488113 iter 20 value 87.221410 iter 30 value 83.170061 iter 40 value 82.881753 iter 50 value 81.151684 iter 60 value 81.025794 iter 70 value 81.005623 final value 81.005617 converged Fitting Repeat 1 # weights: 305 initial value 100.037879 iter 10 value 94.366347 iter 20 value 91.473790 iter 30 value 86.719406 iter 40 value 86.122587 iter 50 value 83.541801 iter 60 value 81.413388 iter 70 value 80.500824 iter 80 value 80.288277 iter 90 value 80.150185 iter 100 value 80.096014 final value 80.096014 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.133080 iter 10 value 93.591824 iter 20 value 85.995978 iter 30 value 85.242523 iter 40 value 83.706811 iter 50 value 83.145737 iter 60 value 79.557900 iter 70 value 78.373171 iter 80 value 77.821422 iter 90 value 77.121924 iter 100 value 76.705504 final value 76.705504 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.625416 iter 10 value 94.486819 iter 20 value 93.745033 iter 30 value 91.571718 iter 40 value 81.843704 iter 50 value 80.885675 iter 60 value 80.540167 iter 70 value 79.455783 iter 80 value 79.416575 iter 90 value 79.139260 iter 100 value 78.284915 final value 78.284915 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 105.215796 iter 10 value 94.698193 iter 20 value 89.547312 iter 30 value 82.597336 iter 40 value 81.364016 iter 50 value 81.059062 iter 60 value 80.821366 iter 70 value 80.143442 iter 80 value 77.895180 iter 90 value 77.739205 iter 100 value 77.449166 final value 77.449166 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 117.260495 iter 10 value 97.163425 iter 20 value 92.599725 iter 30 value 84.534935 iter 40 value 82.133142 iter 50 value 78.602173 iter 60 value 76.786270 iter 70 value 76.622975 iter 80 value 76.405343 iter 90 value 76.161409 iter 100 value 75.835399 final value 75.835399 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 109.059618 iter 10 value 94.839184 iter 20 value 85.054761 iter 30 value 84.358135 iter 40 value 79.829625 iter 50 value 77.949367 iter 60 value 77.681817 iter 70 value 76.835169 iter 80 value 76.560161 iter 90 value 75.968045 iter 100 value 75.637860 final value 75.637860 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 133.085540 iter 10 value 95.539242 iter 20 value 86.264761 iter 30 value 82.715461 iter 40 value 81.445114 iter 50 value 80.755209 iter 60 value 80.721832 iter 70 value 80.535699 iter 80 value 79.867647 iter 90 value 78.135269 iter 100 value 76.999419 final value 76.999419 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 103.466910 iter 10 value 95.039437 iter 20 value 94.300138 iter 30 value 92.680945 iter 40 value 86.176399 iter 50 value 82.829291 iter 60 value 82.580260 iter 70 value 80.454820 iter 80 value 78.859868 iter 90 value 77.870797 iter 100 value 77.600703 final value 77.600703 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 112.590008 iter 10 value 94.507475 iter 20 value 94.333671 iter 30 value 88.086426 iter 40 value 81.330555 iter 50 value 79.427353 iter 60 value 78.609831 iter 70 value 78.071651 iter 80 value 76.903512 iter 90 value 76.397327 iter 100 value 75.977227 final value 75.977227 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 114.526986 iter 10 value 94.659693 iter 20 value 92.428777 iter 30 value 90.478896 iter 40 value 86.615964 iter 50 value 86.193897 iter 60 value 85.099786 iter 70 value 84.772302 iter 80 value 82.988539 iter 90 value 81.446024 iter 100 value 80.613914 final value 80.613914 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.363143 iter 10 value 92.403813 iter 20 value 91.571470 iter 30 value 91.571296 iter 40 value 85.857015 iter 50 value 82.735246 iter 60 value 82.630481 iter 70 value 81.913012 iter 80 value 81.761113 iter 90 value 81.760568 iter 100 value 81.757263 final value 81.757263 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 97.129008 iter 10 value 94.468496 iter 20 value 87.058903 iter 30 value 86.111364 iter 40 value 86.052766 iter 50 value 84.271255 iter 60 value 84.232094 iter 70 value 84.135985 iter 80 value 83.990737 iter 90 value 83.990408 iter 100 value 83.989685 final value 83.989685 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 102.566134 final value 94.485899 converged Fitting Repeat 4 # weights: 103 initial value 107.581571 final value 94.485683 converged Fitting Repeat 5 # weights: 103 initial value 96.434140 final value 94.485806 converged Fitting Repeat 1 # weights: 305 initial value 99.380857 iter 10 value 92.681854 iter 20 value 90.158672 iter 30 value 90.156972 iter 40 value 90.154960 iter 50 value 90.131970 iter 60 value 90.033554 iter 70 value 88.851647 iter 80 value 88.844324 final value 88.844208 converged Fitting Repeat 2 # weights: 305 initial value 107.256318 iter 10 value 94.471492 iter 20 value 94.467208 iter 30 value 84.862729 iter 40 value 82.462673 iter 50 value 82.278037 iter 60 value 80.652919 iter 70 value 79.825408 iter 80 value 79.818836 iter 90 value 79.818576 iter 90 value 79.818576 iter 90 value 79.818576 final value 79.818576 converged Fitting Repeat 3 # weights: 305 initial value 99.675378 iter 10 value 94.471576 iter 20 value 94.413788 iter 30 value 80.170903 iter 40 value 80.130966 iter 50 value 80.111388 iter 60 value 79.959128 iter 70 value 79.767651 iter 80 value 79.765284 iter 90 value 79.765245 iter 90 value 79.765245 iter 90 value 79.765245 final value 79.765245 converged Fitting Repeat 4 # weights: 305 initial value 104.168852 iter 10 value 94.489435 iter 20 value 94.453502 iter 30 value 87.917286 iter 40 value 87.847657 iter 50 value 87.584327 iter 60 value 85.346330 iter 70 value 83.471701 iter 80 value 82.890971 final value 82.851504 converged Fitting Repeat 5 # weights: 305 initial value 106.226632 iter 10 value 94.471894 iter 20 value 94.440376 iter 30 value 89.592567 final value 89.074009 converged Fitting Repeat 1 # weights: 507 initial value 97.228215 iter 10 value 85.187923 iter 20 value 84.641230 iter 30 value 79.842741 iter 40 value 79.825852 iter 50 value 79.818794 iter 60 value 79.569069 iter 70 value 76.115604 iter 80 value 75.136818 iter 90 value 75.115890 iter 100 value 75.019534 final value 75.019534 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 107.592095 iter 10 value 94.474497 iter 20 value 85.600721 iter 30 value 82.220119 final value 82.216438 converged Fitting Repeat 3 # weights: 507 initial value 113.704618 iter 10 value 94.452086 iter 20 value 94.448281 iter 30 value 94.300089 iter 40 value 93.603236 iter 50 value 86.549498 iter 60 value 86.250642 iter 70 value 86.246549 iter 80 value 86.245213 iter 90 value 85.580774 iter 100 value 85.116689 final value 85.116689 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 110.108126 iter 10 value 94.247105 iter 20 value 94.236848 iter 30 value 92.851943 iter 40 value 89.958128 iter 50 value 89.613106 iter 60 value 89.515133 iter 70 value 89.511907 iter 80 value 89.510579 iter 90 value 86.007562 iter 100 value 84.543545 final value 84.543545 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 99.121714 iter 10 value 94.474757 iter 20 value 93.693595 iter 30 value 85.565291 iter 40 value 84.897094 iter 50 value 84.749199 iter 60 value 84.746907 final value 84.746855 converged Fitting Repeat 1 # weights: 103 initial value 97.160778 final value 93.320225 converged Fitting Repeat 2 # weights: 103 initial value 94.691568 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 94.593595 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 98.489879 iter 10 value 94.112904 iter 10 value 94.112904 iter 10 value 94.112904 final value 94.112904 converged Fitting Repeat 5 # weights: 103 initial value 97.337938 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 105.003465 iter 10 value 94.484211 iter 10 value 94.484211 iter 10 value 94.484211 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 100.063536 iter 10 value 94.112904 iter 10 value 94.112904 iter 10 value 94.112904 final value 94.112904 converged Fitting Repeat 3 # weights: 305 initial value 100.512336 iter 10 value 85.831948 iter 20 value 81.159190 iter 30 value 80.762929 iter 40 value 80.718975 iter 50 value 80.710866 final value 80.704738 converged Fitting Repeat 4 # weights: 305 initial value 108.651631 iter 10 value 94.112905 final value 94.112903 converged Fitting Repeat 5 # weights: 305 initial value 111.994434 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 94.574464 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 97.194561 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 100.059120 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 107.870183 iter 10 value 94.112905 final value 94.112903 converged Fitting Repeat 5 # weights: 507 initial value 109.414917 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 106.319402 iter 10 value 94.586269 iter 20 value 94.488593 iter 30 value 92.205706 iter 40 value 91.056543 iter 50 value 83.183886 iter 60 value 81.653465 iter 70 value 80.980888 iter 80 value 79.602143 iter 90 value 79.211525 iter 100 value 78.430181 final value 78.430181 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 102.312853 iter 10 value 94.482279 iter 20 value 83.691499 iter 30 value 80.473690 iter 40 value 79.712877 iter 50 value 79.312878 iter 60 value 79.205483 iter 70 value 78.464320 iter 80 value 78.405889 iter 90 value 78.401434 final value 78.401428 converged Fitting Repeat 3 # weights: 103 initial value 103.696187 iter 10 value 94.489007 iter 20 value 93.807034 iter 30 value 93.176625 iter 40 value 93.007945 iter 50 value 92.991211 iter 60 value 86.663501 iter 70 value 84.665459 iter 80 value 82.163170 iter 90 value 81.862869 iter 100 value 81.850943 final value 81.850943 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 102.897536 iter 10 value 94.470860 iter 20 value 85.312127 iter 30 value 81.505605 iter 40 value 80.522063 iter 50 value 79.787008 iter 60 value 79.516481 iter 70 value 79.255580 iter 80 value 79.140862 iter 90 value 78.577826 iter 100 value 78.402304 final value 78.402304 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 97.866486 iter 10 value 94.275995 iter 20 value 93.008652 iter 30 value 91.838446 iter 40 value 85.698252 iter 50 value 84.834460 iter 60 value 83.222017 iter 70 value 81.572581 iter 80 value 81.323805 iter 90 value 81.282050 iter 100 value 81.281261 final value 81.281261 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 101.430831 iter 10 value 93.770342 iter 20 value 82.713802 iter 30 value 81.854046 iter 40 value 81.152570 iter 50 value 80.903387 iter 60 value 80.650135 iter 70 value 80.096209 iter 80 value 79.567005 iter 90 value 78.568506 iter 100 value 77.861383 final value 77.861383 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 106.357895 iter 10 value 93.788755 iter 20 value 82.703296 iter 30 value 80.795400 iter 40 value 79.651705 iter 50 value 79.209622 iter 60 value 77.790759 iter 70 value 77.417874 iter 80 value 77.386545 iter 90 value 77.380900 iter 100 value 77.378816 final value 77.378816 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 112.812234 iter 10 value 95.188084 iter 20 value 94.077472 iter 30 value 90.436160 iter 40 value 83.960815 iter 50 value 83.569357 iter 60 value 83.124716 iter 70 value 81.437982 iter 80 value 79.575722 iter 90 value 77.965676 iter 100 value 77.562016 final value 77.562016 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 108.393380 iter 10 value 92.830050 iter 20 value 85.547370 iter 30 value 82.449015 iter 40 value 79.907101 iter 50 value 78.521772 iter 60 value 77.964194 iter 70 value 77.756956 iter 80 value 77.706299 iter 90 value 77.672074 iter 100 value 77.659742 final value 77.659742 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 108.833937 iter 10 value 94.379826 iter 20 value 92.754077 iter 30 value 82.735681 iter 40 value 82.692041 iter 50 value 82.327174 iter 60 value 80.327473 iter 70 value 78.681386 iter 80 value 78.110458 iter 90 value 78.028026 iter 100 value 77.998812 final value 77.998812 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 122.952161 iter 10 value 94.587211 iter 20 value 92.688448 iter 30 value 90.378000 iter 40 value 88.510202 iter 50 value 83.800953 iter 60 value 81.573799 iter 70 value 80.742176 iter 80 value 79.600307 iter 90 value 77.986169 iter 100 value 77.694169 final value 77.694169 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 103.640142 iter 10 value 92.865506 iter 20 value 89.523915 iter 30 value 83.955426 iter 40 value 81.100001 iter 50 value 80.221582 iter 60 value 79.035273 iter 70 value 77.854108 iter 80 value 76.969130 iter 90 value 76.759562 iter 100 value 76.634138 final value 76.634138 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 135.083880 iter 10 value 94.217388 iter 20 value 89.201749 iter 30 value 82.395537 iter 40 value 81.864916 iter 50 value 81.244247 iter 60 value 79.675327 iter 70 value 78.708476 iter 80 value 78.174215 iter 90 value 77.798799 iter 100 value 77.714466 final value 77.714466 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.157647 iter 10 value 93.014435 iter 20 value 90.126028 iter 30 value 84.237417 iter 40 value 80.003251 iter 50 value 79.029021 iter 60 value 78.256211 iter 70 value 77.574080 iter 80 value 77.476281 iter 90 value 76.916527 iter 100 value 76.693184 final value 76.693184 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 106.110134 iter 10 value 91.884299 iter 20 value 84.013139 iter 30 value 82.328607 iter 40 value 81.371966 iter 50 value 81.044890 iter 60 value 78.605064 iter 70 value 77.834910 iter 80 value 77.564686 iter 90 value 77.372905 iter 100 value 77.290699 final value 77.290699 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.995990 final value 94.486004 converged Fitting Repeat 2 # weights: 103 initial value 95.988183 final value 94.485779 converged Fitting Repeat 3 # weights: 103 initial value 98.442173 iter 10 value 89.804682 iter 20 value 81.335410 iter 30 value 80.832074 iter 40 value 80.672335 iter 50 value 80.671004 iter 60 value 80.670001 final value 80.669758 converged Fitting Repeat 4 # weights: 103 initial value 106.276021 iter 10 value 94.486020 iter 20 value 94.484240 iter 30 value 93.209940 final value 92.679976 converged Fitting Repeat 5 # weights: 103 initial value 97.330404 iter 10 value 94.114699 iter 20 value 94.112191 iter 30 value 92.623384 iter 40 value 92.619747 final value 92.619746 converged Fitting Repeat 1 # weights: 305 initial value 104.503849 iter 10 value 94.489096 iter 20 value 94.484246 iter 30 value 94.199424 iter 40 value 92.680400 iter 40 value 92.680400 iter 40 value 92.680400 final value 92.680400 converged Fitting Repeat 2 # weights: 305 initial value 99.360262 iter 10 value 94.489404 iter 20 value 94.484247 iter 30 value 82.676848 iter 40 value 81.246830 iter 50 value 81.233798 iter 60 value 81.169644 iter 60 value 81.169643 iter 60 value 81.169643 final value 81.169643 converged Fitting Repeat 3 # weights: 305 initial value 94.854837 final value 94.489745 converged Fitting Repeat 4 # weights: 305 initial value 98.477641 iter 10 value 94.118715 iter 20 value 94.116417 iter 30 value 92.923278 iter 40 value 92.682930 iter 50 value 92.680739 iter 60 value 92.631169 final value 92.620091 converged Fitting Repeat 5 # weights: 305 initial value 120.920136 iter 10 value 94.489405 iter 20 value 93.334633 iter 30 value 85.653150 iter 40 value 85.649550 iter 40 value 85.649550 iter 40 value 85.649550 final value 85.649550 converged Fitting Repeat 1 # weights: 507 initial value 108.010191 iter 10 value 94.493214 iter 20 value 91.287451 iter 30 value 80.634325 iter 40 value 78.565092 iter 50 value 78.312481 iter 60 value 77.955646 iter 70 value 77.912540 final value 77.912213 converged Fitting Repeat 2 # weights: 507 initial value 129.170419 iter 10 value 94.121710 iter 20 value 94.114322 final value 92.897166 converged Fitting Repeat 3 # weights: 507 initial value 103.503017 iter 10 value 91.362595 iter 20 value 88.677802 iter 30 value 88.668805 iter 40 value 88.668253 iter 50 value 87.575046 iter 60 value 87.554655 iter 70 value 87.551960 iter 80 value 87.312344 iter 90 value 87.298223 iter 100 value 82.909399 final value 82.909399 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 95.505658 iter 10 value 94.120814 iter 20 value 94.113707 iter 30 value 92.654836 final value 92.619539 converged Fitting Repeat 5 # weights: 507 initial value 103.626448 iter 10 value 92.905357 iter 20 value 92.900158 iter 30 value 92.354870 iter 40 value 89.621670 iter 50 value 80.101987 iter 60 value 78.351648 iter 70 value 77.963009 iter 80 value 77.926019 iter 90 value 77.869619 iter 100 value 77.766259 final value 77.766259 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 103.865669 final value 93.991525 converged Fitting Repeat 2 # weights: 103 initial value 101.695829 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 103.339534 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 101.090788 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 99.674907 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 99.866131 iter 10 value 94.034684 final value 94.032967 converged Fitting Repeat 2 # weights: 305 initial value 103.263179 iter 10 value 92.475121 iter 20 value 92.462301 iter 30 value 92.462217 final value 92.462212 converged Fitting Repeat 3 # weights: 305 initial value 104.999273 final value 94.008696 converged Fitting Repeat 4 # weights: 305 initial value 103.088898 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 98.486542 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 104.940828 iter 10 value 94.022863 iter 20 value 90.174859 iter 30 value 87.036097 final value 87.035863 converged Fitting Repeat 2 # weights: 507 initial value 107.056681 iter 10 value 94.087455 final value 94.050155 converged Fitting Repeat 3 # weights: 507 initial value 104.646782 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 101.834733 final value 94.032967 converged Fitting Repeat 5 # weights: 507 initial value 112.913716 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 95.446668 iter 10 value 93.531351 iter 20 value 88.017500 iter 30 value 86.378609 iter 40 value 85.497096 iter 50 value 85.314284 iter 60 value 85.296690 iter 70 value 85.267822 final value 85.263488 converged Fitting Repeat 2 # weights: 103 initial value 108.227923 iter 10 value 94.049611 iter 20 value 90.444203 iter 30 value 90.036556 iter 40 value 88.054218 iter 50 value 86.024059 iter 60 value 85.956105 iter 70 value 85.457099 iter 80 value 85.325494 iter 90 value 85.264366 final value 85.263488 converged Fitting Repeat 3 # weights: 103 initial value 100.989855 iter 10 value 94.069592 iter 20 value 90.846436 iter 30 value 88.471235 iter 40 value 86.267065 iter 50 value 84.337337 iter 60 value 83.897257 iter 70 value 83.453548 iter 80 value 83.286346 iter 90 value 83.201536 iter 100 value 83.151606 final value 83.151606 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 100.468028 iter 10 value 93.987419 iter 20 value 89.123793 iter 30 value 87.681450 iter 40 value 87.113648 iter 50 value 85.937667 iter 60 value 85.676623 iter 70 value 85.599456 iter 80 value 85.554763 final value 85.554195 converged Fitting Repeat 5 # weights: 103 initial value 99.622316 iter 10 value 94.059837 iter 20 value 93.981925 iter 30 value 89.167503 iter 40 value 87.656523 iter 50 value 85.852620 iter 60 value 85.383888 iter 70 value 85.309151 iter 80 value 85.305312 iter 90 value 85.277876 iter 100 value 85.265973 final value 85.265973 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 104.830124 iter 10 value 94.421862 iter 20 value 94.067385 iter 30 value 86.637185 iter 40 value 86.225258 iter 50 value 85.780365 iter 60 value 83.741263 iter 70 value 83.020311 iter 80 value 82.669993 iter 90 value 82.245631 iter 100 value 82.183959 final value 82.183959 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 100.785206 iter 10 value 94.453544 iter 20 value 93.410165 iter 30 value 92.824391 iter 40 value 90.837667 iter 50 value 84.890419 iter 60 value 84.831425 iter 70 value 83.986737 iter 80 value 83.755012 iter 90 value 83.576506 iter 100 value 83.361912 final value 83.361912 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 125.270006 iter 10 value 93.857260 iter 20 value 89.692574 iter 30 value 88.334524 iter 40 value 87.486566 iter 50 value 84.669848 iter 60 value 83.575399 iter 70 value 83.258133 iter 80 value 82.702225 iter 90 value 82.312330 iter 100 value 82.300922 final value 82.300922 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 114.223001 iter 10 value 94.062408 iter 20 value 90.447107 iter 30 value 86.582132 iter 40 value 86.166382 iter 50 value 84.503875 iter 60 value 82.893730 iter 70 value 82.702360 iter 80 value 82.249287 iter 90 value 82.127009 iter 100 value 81.947928 final value 81.947928 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 120.853658 iter 10 value 94.488116 iter 20 value 90.332852 iter 30 value 87.194999 iter 40 value 84.753406 iter 50 value 83.515834 iter 60 value 83.224986 iter 70 value 83.017308 iter 80 value 82.794082 iter 90 value 82.503079 iter 100 value 82.314357 final value 82.314357 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 108.560880 iter 10 value 94.126951 iter 20 value 91.172842 iter 30 value 87.498428 iter 40 value 86.408625 iter 50 value 86.083590 iter 60 value 85.847054 iter 70 value 84.906992 iter 80 value 83.065608 iter 90 value 82.642944 iter 100 value 82.489141 final value 82.489141 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 105.834247 iter 10 value 94.553383 iter 20 value 93.415806 iter 30 value 86.849224 iter 40 value 86.160241 iter 50 value 84.595474 iter 60 value 82.663507 iter 70 value 82.486936 iter 80 value 82.203819 iter 90 value 82.012124 iter 100 value 81.877990 final value 81.877990 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 107.203600 iter 10 value 94.055188 iter 20 value 91.151714 iter 30 value 87.452651 iter 40 value 84.355467 iter 50 value 83.184737 iter 60 value 82.749522 iter 70 value 82.485463 iter 80 value 82.442504 iter 90 value 82.286222 iter 100 value 82.011515 final value 82.011515 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 103.250376 iter 10 value 91.398650 iter 20 value 86.214646 iter 30 value 85.456222 iter 40 value 85.060554 iter 50 value 83.792160 iter 60 value 82.821012 iter 70 value 82.758428 iter 80 value 82.613585 iter 90 value 82.074899 iter 100 value 81.903133 final value 81.903133 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 105.352282 iter 10 value 92.285792 iter 20 value 87.916799 iter 30 value 86.209606 iter 40 value 85.557736 iter 50 value 84.531541 iter 60 value 83.175746 iter 70 value 82.758056 iter 80 value 82.111388 iter 90 value 81.897780 iter 100 value 81.808988 final value 81.808988 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 103.877689 iter 10 value 94.054679 iter 20 value 93.944369 iter 30 value 87.310618 iter 40 value 85.945159 iter 50 value 85.643573 iter 60 value 85.633607 final value 85.633593 converged Fitting Repeat 2 # weights: 103 initial value 94.961700 final value 94.054824 converged Fitting Repeat 3 # weights: 103 initial value 97.347523 final value 94.054743 converged Fitting Repeat 4 # weights: 103 initial value 115.424176 final value 94.054446 converged Fitting Repeat 5 # weights: 103 initial value 102.078266 final value 94.054387 converged Fitting Repeat 1 # weights: 305 initial value 100.062346 iter 10 value 93.992098 iter 20 value 93.989286 iter 30 value 93.931651 iter 40 value 89.262197 iter 50 value 86.873685 iter 60 value 85.133888 iter 70 value 83.820288 iter 80 value 82.676425 iter 90 value 82.270240 iter 100 value 81.900451 final value 81.900451 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 106.442081 iter 10 value 94.057278 iter 20 value 93.889592 iter 30 value 89.051618 iter 40 value 87.536562 iter 50 value 87.523313 iter 60 value 86.827991 iter 70 value 86.778524 iter 80 value 86.765164 iter 90 value 86.756061 iter 100 value 86.619059 final value 86.619059 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 101.956160 iter 10 value 94.058475 iter 20 value 93.558111 iter 30 value 86.472077 iter 40 value 83.914547 iter 50 value 83.799334 iter 60 value 83.702039 final value 83.702020 converged Fitting Repeat 4 # weights: 305 initial value 116.147843 iter 10 value 94.037564 iter 20 value 94.033336 iter 30 value 93.975790 iter 40 value 91.915217 iter 50 value 85.449395 iter 60 value 84.216575 iter 70 value 82.647819 iter 80 value 82.492301 iter 90 value 82.443426 iter 100 value 82.441415 final value 82.441415 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 96.672515 iter 10 value 94.057704 iter 20 value 88.648889 iter 30 value 88.130582 iter 40 value 87.729873 iter 50 value 87.094611 iter 60 value 87.088855 iter 70 value 87.064209 iter 80 value 86.942674 iter 90 value 85.371566 iter 100 value 85.021988 final value 85.021988 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 97.461521 iter 10 value 92.846557 iter 20 value 92.674382 iter 30 value 92.260476 iter 40 value 90.975266 iter 50 value 88.605894 iter 60 value 85.717984 iter 70 value 85.571447 final value 85.571440 converged Fitting Repeat 2 # weights: 507 initial value 113.127098 iter 10 value 93.992713 iter 20 value 92.758172 iter 30 value 92.661766 iter 40 value 91.884023 iter 50 value 91.616170 iter 60 value 91.574077 iter 70 value 91.501049 iter 80 value 91.497779 iter 90 value 91.491024 final value 91.490721 converged Fitting Repeat 3 # weights: 507 initial value 101.222368 iter 10 value 93.918187 iter 20 value 93.891056 iter 30 value 93.378905 iter 40 value 87.386573 iter 50 value 87.382810 iter 60 value 87.366022 iter 70 value 85.364726 iter 80 value 85.189157 iter 90 value 84.999533 iter 100 value 84.964428 final value 84.964428 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 97.427944 iter 10 value 94.060055 iter 20 value 87.875841 iter 30 value 86.497455 iter 40 value 86.440973 iter 50 value 85.641468 iter 60 value 84.532041 iter 70 value 82.763160 iter 80 value 81.298479 iter 90 value 81.195510 iter 100 value 81.092598 final value 81.092598 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 116.479518 iter 10 value 86.755588 iter 20 value 85.373663 iter 30 value 85.369948 iter 40 value 85.362293 iter 50 value 85.296853 iter 60 value 85.296725 iter 70 value 85.295268 final value 85.295222 converged Fitting Repeat 1 # weights: 103 initial value 98.564806 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 103.462631 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 105.059685 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 99.215765 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 95.655487 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 94.785718 final value 94.052911 converged Fitting Repeat 2 # weights: 305 initial value 104.029551 final value 93.567162 converged Fitting Repeat 3 # weights: 305 initial value 100.184895 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 96.121829 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 95.796653 final value 93.582418 converged Fitting Repeat 1 # weights: 507 initial value 94.658295 iter 10 value 93.545637 iter 20 value 93.544731 final value 93.544713 converged Fitting Repeat 2 # weights: 507 initial value 102.137283 iter 10 value 93.753868 final value 93.582418 converged Fitting Repeat 3 # weights: 507 initial value 121.722410 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 103.241934 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 107.839540 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 102.719109 iter 10 value 93.387321 iter 20 value 87.371740 iter 30 value 86.971722 iter 40 value 86.415459 iter 50 value 85.126918 iter 60 value 84.614591 iter 70 value 84.106020 iter 80 value 84.101548 iter 90 value 84.099126 final value 84.094316 converged Fitting Repeat 2 # weights: 103 initial value 122.706507 iter 10 value 94.065280 iter 20 value 93.787289 iter 30 value 87.147263 iter 40 value 86.577111 iter 50 value 86.450259 iter 60 value 86.048482 iter 70 value 85.395987 iter 80 value 84.960354 iter 90 value 84.657967 final value 84.650443 converged Fitting Repeat 3 # weights: 103 initial value 99.766355 iter 10 value 93.024972 iter 20 value 87.130004 iter 30 value 86.519363 iter 40 value 86.168430 iter 50 value 85.796828 iter 60 value 85.335239 iter 70 value 85.151691 final value 85.151684 converged Fitting Repeat 4 # weights: 103 initial value 97.165679 iter 10 value 94.055311 iter 20 value 94.054680 iter 30 value 92.254504 iter 40 value 89.595106 iter 50 value 89.473960 iter 60 value 87.857561 iter 70 value 86.850792 iter 80 value 86.424021 iter 90 value 86.210357 final value 86.210354 converged Fitting Repeat 5 # weights: 103 initial value 96.886700 iter 10 value 93.923072 iter 20 value 86.814020 iter 30 value 85.969618 iter 40 value 85.871834 iter 50 value 85.750383 iter 60 value 85.711195 final value 85.711179 converged Fitting Repeat 1 # weights: 305 initial value 103.850759 iter 10 value 93.993193 iter 20 value 93.220451 iter 30 value 88.738205 iter 40 value 87.048970 iter 50 value 86.424407 iter 60 value 85.451803 iter 70 value 85.204651 iter 80 value 84.992667 iter 90 value 84.058220 iter 100 value 83.120725 final value 83.120725 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 106.735711 iter 10 value 94.013784 iter 20 value 93.637831 iter 30 value 87.432234 iter 40 value 86.758418 iter 50 value 86.576659 iter 60 value 85.459708 iter 70 value 84.703120 iter 80 value 84.152039 iter 90 value 83.549780 iter 100 value 83.293685 final value 83.293685 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 116.039176 iter 10 value 94.129321 iter 20 value 94.005928 iter 30 value 93.645036 iter 40 value 89.560509 iter 50 value 88.043837 iter 60 value 87.571436 iter 70 value 86.416637 iter 80 value 85.293742 iter 90 value 84.611140 iter 100 value 83.195631 final value 83.195631 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.415589 iter 10 value 94.060341 iter 20 value 93.948548 iter 30 value 88.825990 iter 40 value 88.283955 iter 50 value 85.750875 iter 60 value 84.530819 iter 70 value 84.160538 iter 80 value 83.664742 iter 90 value 83.404369 iter 100 value 83.277486 final value 83.277486 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 123.305193 iter 10 value 94.051836 iter 20 value 91.505686 iter 30 value 88.283805 iter 40 value 87.182853 iter 50 value 85.711456 iter 60 value 83.611025 iter 70 value 83.298638 iter 80 value 83.048468 iter 90 value 82.795905 iter 100 value 82.652063 final value 82.652063 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 118.537699 iter 10 value 94.869053 iter 20 value 91.081160 iter 30 value 87.992469 iter 40 value 86.958015 iter 50 value 84.762120 iter 60 value 83.450207 iter 70 value 83.168126 iter 80 value 82.821854 iter 90 value 82.575508 iter 100 value 82.450820 final value 82.450820 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 122.553033 iter 10 value 94.110951 iter 20 value 89.703081 iter 30 value 87.332068 iter 40 value 86.463978 iter 50 value 85.323199 iter 60 value 83.634519 iter 70 value 83.258344 iter 80 value 82.948083 iter 90 value 82.553222 iter 100 value 82.433493 final value 82.433493 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 115.989386 iter 10 value 93.744060 iter 20 value 92.220411 iter 30 value 88.139429 iter 40 value 86.537134 iter 50 value 85.115553 iter 60 value 84.698955 iter 70 value 83.879340 iter 80 value 83.104486 iter 90 value 82.893343 iter 100 value 82.770658 final value 82.770658 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 110.935441 iter 10 value 93.479136 iter 20 value 89.883442 iter 30 value 87.669894 iter 40 value 86.766506 iter 50 value 85.618212 iter 60 value 84.951201 iter 70 value 84.839487 iter 80 value 84.412956 iter 90 value 84.042764 iter 100 value 83.784773 final value 83.784773 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 123.475532 iter 10 value 94.145165 iter 20 value 93.033696 iter 30 value 88.498876 iter 40 value 87.352303 iter 50 value 85.261930 iter 60 value 84.112882 iter 70 value 83.494034 iter 80 value 83.149109 iter 90 value 82.972193 iter 100 value 82.626355 final value 82.626355 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.365022 final value 94.054715 converged Fitting Repeat 2 # weights: 103 initial value 95.351756 final value 94.054284 converged Fitting Repeat 3 # weights: 103 initial value 100.216385 iter 10 value 94.054773 iter 20 value 94.052534 iter 30 value 93.585330 iter 40 value 93.582936 final value 93.582919 converged Fitting Repeat 4 # weights: 103 initial value 94.996563 final value 93.584205 converged Fitting Repeat 5 # weights: 103 initial value 99.046292 final value 94.054625 converged Fitting Repeat 1 # weights: 305 initial value 102.449981 iter 10 value 94.040075 iter 20 value 90.092035 iter 30 value 89.389655 iter 40 value 87.991599 iter 50 value 87.613347 iter 50 value 87.613347 final value 87.613347 converged Fitting Repeat 2 # weights: 305 initial value 150.878133 iter 10 value 94.057646 iter 20 value 94.053172 iter 30 value 92.462910 iter 40 value 87.341965 iter 50 value 87.335876 iter 60 value 87.180972 iter 70 value 85.024689 iter 80 value 84.923002 iter 90 value 84.921971 iter 100 value 84.921131 final value 84.921131 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 116.299802 iter 10 value 94.058279 iter 20 value 93.998001 iter 30 value 85.971561 iter 40 value 84.989968 iter 50 value 84.719536 iter 60 value 84.378781 iter 70 value 84.197953 iter 70 value 84.197953 iter 70 value 84.197953 final value 84.197953 converged Fitting Repeat 4 # weights: 305 initial value 103.482644 iter 10 value 94.057742 iter 20 value 93.857774 iter 30 value 87.758625 iter 40 value 87.157637 iter 40 value 87.157636 iter 40 value 87.157636 final value 87.157636 converged Fitting Repeat 5 # weights: 305 initial value 94.265094 iter 10 value 94.057448 iter 20 value 93.867605 iter 30 value 93.550265 iter 40 value 93.509482 iter 50 value 93.089082 iter 60 value 87.660835 iter 70 value 85.671530 iter 80 value 85.499452 final value 85.497288 converged Fitting Repeat 1 # weights: 507 initial value 98.722956 iter 10 value 93.679205 iter 20 value 93.672187 final value 93.672116 converged Fitting Repeat 2 # weights: 507 initial value 96.058389 iter 10 value 93.095289 iter 20 value 93.093183 iter 30 value 87.160103 iter 40 value 86.402728 final value 86.402680 converged Fitting Repeat 3 # weights: 507 initial value 99.977267 iter 10 value 93.590854 iter 20 value 93.582804 iter 30 value 93.532747 iter 40 value 93.528541 final value 93.528538 converged Fitting Repeat 4 # weights: 507 initial value 103.899491 final value 94.060954 converged Fitting Repeat 5 # weights: 507 initial value 95.402709 iter 10 value 93.849777 iter 20 value 93.694979 iter 30 value 93.617132 iter 40 value 93.613868 iter 50 value 93.099040 iter 60 value 93.084543 iter 70 value 93.045462 iter 80 value 93.029396 final value 93.029364 converged Fitting Repeat 1 # weights: 103 initial value 102.767293 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 98.099637 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 97.637672 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 110.331405 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 96.694709 iter 10 value 88.909265 iter 20 value 87.820112 final value 87.820055 converged Fitting Repeat 1 # weights: 305 initial value 101.443205 iter 10 value 86.777932 iter 20 value 85.072614 iter 30 value 84.990005 iter 40 value 84.974507 final value 84.974481 converged Fitting Repeat 2 # weights: 305 initial value 102.008264 iter 10 value 94.484137 iter 10 value 94.484137 iter 10 value 94.484137 final value 94.484137 converged Fitting Repeat 3 # weights: 305 initial value 103.005288 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 97.981163 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 113.896616 final value 94.466823 converged Fitting Repeat 1 # weights: 507 initial value 116.563745 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 100.233543 iter 10 value 92.841776 iter 20 value 92.822940 final value 92.822885 converged Fitting Repeat 3 # weights: 507 initial value 99.553583 iter 10 value 93.423058 iter 20 value 93.413331 final value 93.413318 converged Fitting Repeat 4 # weights: 507 initial value 114.298561 final value 94.466823 converged Fitting Repeat 5 # weights: 507 initial value 97.697657 iter 10 value 92.440828 iter 20 value 92.363440 final value 92.363316 converged Fitting Repeat 1 # weights: 103 initial value 100.216681 iter 10 value 94.362045 iter 20 value 90.254237 iter 30 value 87.598944 iter 40 value 85.733409 iter 50 value 85.586124 iter 60 value 85.372415 iter 70 value 85.140436 final value 85.128753 converged Fitting Repeat 2 # weights: 103 initial value 107.465632 iter 10 value 94.874151 iter 20 value 93.926034 iter 30 value 87.202802 iter 40 value 87.026433 iter 50 value 86.815372 iter 60 value 86.424680 iter 70 value 85.625266 iter 80 value 85.350030 iter 90 value 84.677870 iter 100 value 84.180213 final value 84.180213 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 105.357506 iter 10 value 94.486435 iter 20 value 94.171311 iter 30 value 92.463909 iter 40 value 88.563515 iter 50 value 84.944731 iter 60 value 83.386413 iter 70 value 82.724122 iter 80 value 82.495010 iter 90 value 82.449308 iter 100 value 82.402955 final value 82.402955 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 103.276622 iter 10 value 94.494020 iter 20 value 90.601722 iter 30 value 90.260172 iter 40 value 87.214878 iter 50 value 86.697909 iter 60 value 84.693962 iter 70 value 84.314336 iter 80 value 84.282157 iter 90 value 84.273148 iter 100 value 84.168268 final value 84.168268 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 97.005684 iter 10 value 94.490579 iter 20 value 92.415773 iter 30 value 87.812346 iter 40 value 86.145582 iter 50 value 84.922796 iter 60 value 83.603367 iter 70 value 82.839334 iter 80 value 82.666805 iter 90 value 82.485111 iter 100 value 82.401732 final value 82.401732 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 113.036489 iter 10 value 94.517846 iter 20 value 88.559627 iter 30 value 83.705297 iter 40 value 82.568561 iter 50 value 82.227188 iter 60 value 82.008615 iter 70 value 81.527311 iter 80 value 81.354983 iter 90 value 81.271702 iter 100 value 81.130726 final value 81.130726 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.626993 iter 10 value 97.475005 iter 20 value 93.304598 iter 30 value 88.290203 iter 40 value 87.967649 iter 50 value 86.845546 iter 60 value 85.541215 iter 70 value 84.947510 iter 80 value 84.844629 iter 90 value 84.827659 iter 100 value 84.805029 final value 84.805029 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 101.914904 iter 10 value 94.407580 iter 20 value 93.989183 iter 30 value 89.456772 iter 40 value 86.078390 iter 50 value 84.038058 iter 60 value 83.438088 iter 70 value 82.914411 iter 80 value 81.995971 iter 90 value 81.666208 iter 100 value 81.409257 final value 81.409257 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 105.634084 iter 10 value 94.419855 iter 20 value 90.320014 iter 30 value 87.909020 iter 40 value 86.418235 iter 50 value 84.646422 iter 60 value 82.806492 iter 70 value 81.917733 iter 80 value 81.651235 iter 90 value 81.488045 iter 100 value 81.473197 final value 81.473197 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 108.877126 iter 10 value 94.326898 iter 20 value 88.409325 iter 30 value 87.599465 iter 40 value 87.515920 iter 50 value 85.300090 iter 60 value 84.880569 iter 70 value 84.772395 iter 80 value 84.736342 iter 90 value 84.696652 iter 100 value 84.044743 final value 84.044743 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 105.777062 iter 10 value 94.493076 iter 20 value 89.050693 iter 30 value 87.501278 iter 40 value 84.424534 iter 50 value 83.071849 iter 60 value 82.625225 iter 70 value 82.485776 iter 80 value 82.220186 iter 90 value 82.076574 iter 100 value 81.337959 final value 81.337959 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 108.755343 iter 10 value 94.923773 iter 20 value 86.430208 iter 30 value 85.850253 iter 40 value 85.126129 iter 50 value 83.674638 iter 60 value 83.206039 iter 70 value 82.188750 iter 80 value 81.392152 iter 90 value 81.214840 iter 100 value 80.878974 final value 80.878974 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 109.300226 iter 10 value 94.532663 iter 20 value 89.766329 iter 30 value 88.020387 iter 40 value 86.877729 iter 50 value 85.872382 iter 60 value 85.569521 iter 70 value 83.102304 iter 80 value 82.439143 iter 90 value 81.706556 iter 100 value 81.411196 final value 81.411196 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 113.428255 iter 10 value 95.166685 iter 20 value 94.835486 iter 30 value 91.673306 iter 40 value 87.703074 iter 50 value 87.222112 iter 60 value 87.008384 iter 70 value 86.838377 iter 80 value 85.700789 iter 90 value 82.871337 iter 100 value 81.669530 final value 81.669530 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 108.017462 iter 10 value 95.048331 iter 20 value 94.045238 iter 30 value 88.596635 iter 40 value 84.829622 iter 50 value 83.964162 iter 60 value 82.240746 iter 70 value 81.733197 iter 80 value 81.533082 iter 90 value 81.427984 iter 100 value 81.356631 final value 81.356631 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 101.738397 final value 94.485890 converged Fitting Repeat 2 # weights: 103 initial value 97.835867 final value 94.485898 converged Fitting Repeat 3 # weights: 103 initial value 106.262647 final value 94.485714 converged Fitting Repeat 4 # weights: 103 initial value 103.057511 final value 94.485811 converged Fitting Repeat 5 # weights: 103 initial value 97.160889 final value 94.486173 converged Fitting Repeat 1 # weights: 305 initial value 95.936112 iter 10 value 94.488701 iter 20 value 94.404007 iter 30 value 93.723654 iter 40 value 89.823115 iter 50 value 84.914874 iter 60 value 84.780536 iter 70 value 84.778900 iter 80 value 84.403863 iter 90 value 83.967834 iter 100 value 83.174648 final value 83.174648 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 99.728454 iter 10 value 94.488042 iter 20 value 94.375215 iter 30 value 88.149041 iter 40 value 86.948695 iter 50 value 85.648775 iter 60 value 85.642961 iter 60 value 85.642961 iter 60 value 85.642961 final value 85.642961 converged Fitting Repeat 3 # weights: 305 initial value 100.408828 iter 10 value 94.488657 iter 20 value 94.396570 iter 30 value 85.565828 iter 40 value 85.483413 iter 50 value 85.245537 iter 60 value 85.205932 iter 70 value 85.204047 iter 80 value 85.177680 iter 90 value 85.131429 iter 100 value 85.131362 final value 85.131362 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.397118 iter 10 value 94.471965 iter 20 value 94.467105 final value 94.466893 converged Fitting Repeat 5 # weights: 305 initial value 100.952605 iter 10 value 94.318932 iter 20 value 94.315294 iter 30 value 94.312077 iter 40 value 94.161716 iter 50 value 94.141984 iter 60 value 91.645574 iter 70 value 90.414582 iter 80 value 90.377563 iter 90 value 90.073404 iter 100 value 90.010927 final value 90.010927 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 119.424567 iter 10 value 94.474621 iter 20 value 93.511974 iter 30 value 93.482166 iter 40 value 93.477290 iter 50 value 88.308871 iter 60 value 87.242121 iter 70 value 87.227217 final value 87.225865 converged Fitting Repeat 2 # weights: 507 initial value 95.816217 iter 10 value 94.492382 iter 20 value 94.483108 iter 30 value 88.579799 iter 40 value 88.167823 iter 50 value 84.115851 iter 60 value 82.428638 iter 70 value 82.001933 iter 80 value 81.827280 iter 90 value 81.826477 iter 100 value 81.826035 final value 81.826035 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 96.050840 iter 10 value 94.487804 iter 20 value 94.471222 iter 30 value 94.389476 final value 94.387792 converged Fitting Repeat 4 # weights: 507 initial value 99.369549 iter 10 value 94.474596 iter 20 value 94.048387 iter 30 value 85.795510 iter 40 value 82.427369 iter 50 value 82.137448 iter 60 value 82.046861 iter 70 value 81.709000 iter 80 value 81.264968 iter 90 value 80.565960 iter 100 value 79.651534 final value 79.651534 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 97.931901 iter 10 value 94.174680 iter 20 value 94.081446 iter 30 value 93.940054 iter 40 value 93.920988 iter 50 value 93.902618 iter 60 value 93.900379 final value 93.900069 converged Fitting Repeat 1 # weights: 507 initial value 150.107994 iter 10 value 116.702534 iter 20 value 107.960418 iter 30 value 104.724478 iter 40 value 102.198998 iter 50 value 101.513711 iter 60 value 101.213071 iter 70 value 101.017909 iter 80 value 100.785069 iter 90 value 100.390803 iter 100 value 100.371524 final value 100.371524 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 135.233586 iter 10 value 117.887207 iter 20 value 115.683963 iter 30 value 107.890042 iter 40 value 106.459582 iter 50 value 105.532499 iter 60 value 104.947927 iter 70 value 104.356816 iter 80 value 104.246763 iter 90 value 103.975445 iter 100 value 102.374050 final value 102.374050 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 142.745257 iter 10 value 116.085853 iter 20 value 107.616229 iter 30 value 105.938041 iter 40 value 102.896691 iter 50 value 102.087444 iter 60 value 101.622131 iter 70 value 101.436181 iter 80 value 101.344248 iter 90 value 101.154073 iter 100 value 101.006497 final value 101.006497 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 140.943897 iter 10 value 120.652163 iter 20 value 117.649088 iter 30 value 110.242248 iter 40 value 109.661948 iter 50 value 106.268315 iter 60 value 105.668446 iter 70 value 105.207847 iter 80 value 104.831553 iter 90 value 102.232468 iter 100 value 101.260203 final value 101.260203 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 142.413988 iter 10 value 119.336130 iter 20 value 117.616955 iter 30 value 108.712241 iter 40 value 105.594030 iter 50 value 104.669925 iter 60 value 103.726012 iter 70 value 102.728739 iter 80 value 102.219343 iter 90 value 101.789349 iter 100 value 101.450949 final value 101.450949 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 -- Sat May 4 00:13:27 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 42.400 2.116 46.697
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 34.787 | 0.653 | 35.439 | |
FreqInteractors | 0.230 | 0.015 | 0.246 | |
calculateAAC | 0.032 | 0.012 | 0.044 | |
calculateAutocor | 0.288 | 0.023 | 0.313 | |
calculateCTDC | 0.073 | 0.001 | 0.073 | |
calculateCTDD | 0.542 | 0.000 | 0.542 | |
calculateCTDT | 0.227 | 0.000 | 0.226 | |
calculateCTriad | 0.357 | 0.015 | 0.373 | |
calculateDC | 0.086 | 0.005 | 0.090 | |
calculateF | 0.299 | 0.004 | 0.303 | |
calculateKSAAP | 0.089 | 0.007 | 0.096 | |
calculateQD_Sm | 1.656 | 0.069 | 1.724 | |
calculateTC | 1.498 | 0.148 | 1.646 | |
calculateTC_Sm | 0.282 | 0.004 | 0.286 | |
corr_plot | 34.502 | 0.296 | 34.799 | |
enrichfindP | 0.458 | 0.042 | 12.046 | |
enrichfind_hp | 0.081 | 0.005 | 1.356 | |
enrichplot | 0.348 | 0.028 | 0.376 | |
filter_missing_values | 0.000 | 0.002 | 0.001 | |
getFASTA | 0.418 | 0.005 | 4.708 | |
getHPI | 0.001 | 0.001 | 0.001 | |
get_negativePPI | 0.000 | 0.002 | 0.003 | |
get_positivePPI | 0.000 | 0.000 | 0.001 | |
impute_missing_data | 0.002 | 0.001 | 0.003 | |
plotPPI | 0.070 | 0.010 | 0.082 | |
pred_ensembel | 13.473 | 0.657 | 10.880 | |
var_imp | 36.442 | 0.931 | 37.374 | |