Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-01-21 11:43 -0500 (Tue, 21 Jan 2025).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences" | 4777 |
palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences" | 4502 |
lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" | 4467 |
kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" | 4422 |
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | R Under development (unstable) (2024-11-24 r87369) -- "Unsuffered Consequences" | 4406 |
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 977/2286 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.13.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | |||||||||
palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | |||||||||
kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | OK | OK | |||||||||
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: HPiP |
Version: 1.13.0 |
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_1.13.0.tar.gz |
StartedAt: 2025-01-20 21:20:01 -0500 (Mon, 20 Jan 2025) |
EndedAt: 2025-01-20 21:25:56 -0500 (Mon, 20 Jan 2025) |
EllapsedTime: 354.7 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_1.13.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’ * using R Under development (unstable) (2024-11-20 r87352) * using platform: x86_64-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 Monterey 12.7.6 * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘HPiP/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘HPiP’ version ‘1.13.0’ * 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 ... INFO Package unavailable to check Rd xrefs: ‘ftrCOOL’ * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking contents of ‘data’ directory ... OK * checking data for non-ASCII characters ... OK * checking data for ASCII and uncompressed saves ... OK * checking R/sysdata.rda ... OK * checking files in ‘vignettes’ ... OK * checking examples ... OK Examples with CPU (user + system) or elapsed time > 5s user system elapsed var_imp 35.320 1.684 37.404 corr_plot 33.951 1.577 35.772 FSmethod 33.858 1.576 35.764 pred_ensembel 14.111 0.442 12.646 enrichfindP 0.462 0.058 8.568 * 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: 2 NOTEs See ‘/Users/biocbuild/bbs-3.21-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/4.5-x86_64/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 Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-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 98.491231 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 101.300721 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 102.296347 final value 94.466823 converged Fitting Repeat 4 # weights: 103 initial value 94.713976 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 109.020814 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 96.933208 final value 94.164201 converged Fitting Repeat 2 # weights: 305 initial value 96.829343 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 96.886147 final value 94.354396 converged Fitting Repeat 4 # weights: 305 initial value 110.664524 iter 10 value 94.397515 iter 20 value 94.312581 final value 94.312039 converged Fitting Repeat 5 # weights: 305 initial value 110.101137 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 119.876622 iter 10 value 94.164207 final value 94.164201 converged Fitting Repeat 2 # weights: 507 initial value 95.500458 final value 94.354396 converged Fitting Repeat 3 # weights: 507 initial value 103.678040 final value 94.354396 converged Fitting Repeat 4 # weights: 507 initial value 102.259283 final value 94.164201 converged Fitting Repeat 5 # weights: 507 initial value 98.581493 iter 10 value 94.115458 final value 94.112570 converged Fitting Repeat 1 # weights: 103 initial value 100.194202 iter 10 value 94.638102 iter 20 value 93.352249 iter 30 value 86.209139 iter 40 value 85.895465 iter 50 value 85.875973 iter 60 value 83.827528 iter 70 value 81.234356 iter 80 value 80.391968 iter 90 value 80.325856 iter 100 value 80.273674 final value 80.273674 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 96.393526 iter 10 value 93.368084 iter 20 value 82.735196 iter 30 value 82.395073 iter 40 value 80.656344 iter 50 value 80.259016 iter 60 value 79.898104 iter 70 value 79.768393 iter 80 value 79.690000 final value 79.689893 converged Fitting Repeat 3 # weights: 103 initial value 110.379296 iter 10 value 94.342797 iter 20 value 90.345494 iter 30 value 86.030252 iter 40 value 85.878483 iter 50 value 83.594662 iter 60 value 82.976569 iter 70 value 82.967509 final value 82.966208 converged Fitting Repeat 4 # weights: 103 initial value 96.164003 iter 10 value 94.472838 iter 20 value 94.197072 iter 30 value 91.731992 iter 40 value 86.549016 iter 50 value 83.234731 iter 60 value 83.102129 iter 70 value 83.001516 iter 80 value 82.966222 final value 82.966208 converged Fitting Repeat 5 # weights: 103 initial value 96.552481 iter 10 value 94.520457 iter 20 value 94.107598 iter 30 value 89.723845 iter 40 value 85.781934 iter 50 value 83.005470 iter 60 value 82.409342 iter 70 value 82.379140 iter 80 value 82.367565 final value 82.367558 converged Fitting Repeat 1 # weights: 305 initial value 135.609453 iter 10 value 94.442458 iter 20 value 92.397619 iter 30 value 87.526907 iter 40 value 86.561297 iter 50 value 84.763959 iter 60 value 81.463698 iter 70 value 79.241338 iter 80 value 78.309863 iter 90 value 77.935129 iter 100 value 77.907915 final value 77.907915 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 110.750957 iter 10 value 94.760582 iter 20 value 93.507835 iter 30 value 91.048591 iter 40 value 89.797828 iter 50 value 84.937370 iter 60 value 80.329356 iter 70 value 79.746344 iter 80 value 78.980912 iter 90 value 78.269348 iter 100 value 78.126372 final value 78.126372 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 102.657202 iter 10 value 94.101867 iter 20 value 87.731228 iter 30 value 84.536830 iter 40 value 84.123847 iter 50 value 83.817208 iter 60 value 81.546422 iter 70 value 79.921565 iter 80 value 79.603411 iter 90 value 78.265525 iter 100 value 77.924292 final value 77.924292 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 105.503993 iter 10 value 86.600158 iter 20 value 85.921112 iter 30 value 84.419461 iter 40 value 82.869728 iter 50 value 81.479163 iter 60 value 81.258208 iter 70 value 80.681741 iter 80 value 80.429795 iter 90 value 80.283255 iter 100 value 80.092763 final value 80.092763 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 105.238211 iter 10 value 93.946743 iter 20 value 82.569112 iter 30 value 82.077396 iter 40 value 81.888753 iter 50 value 79.534247 iter 60 value 79.284887 iter 70 value 78.404143 iter 80 value 78.042081 iter 90 value 77.889136 iter 100 value 77.740930 final value 77.740930 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 110.306604 iter 10 value 91.057582 iter 20 value 85.295441 iter 30 value 83.146680 iter 40 value 82.791442 iter 50 value 81.877415 iter 60 value 80.251780 iter 70 value 79.336249 iter 80 value 78.618526 iter 90 value 78.542516 iter 100 value 78.379298 final value 78.379298 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 111.596543 iter 10 value 94.734567 iter 20 value 94.579877 iter 30 value 94.139787 iter 40 value 83.317562 iter 50 value 82.075313 iter 60 value 81.509707 iter 70 value 80.039130 iter 80 value 79.866074 iter 90 value 79.789647 iter 100 value 79.346638 final value 79.346638 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 105.371094 iter 10 value 95.683507 iter 20 value 94.150813 iter 30 value 88.667471 iter 40 value 86.148386 iter 50 value 84.454331 iter 60 value 83.600356 iter 70 value 81.022573 iter 80 value 79.908936 iter 90 value 79.249091 iter 100 value 78.526961 final value 78.526961 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.348896 iter 10 value 95.055704 iter 20 value 85.589500 iter 30 value 85.366998 iter 40 value 83.084911 iter 50 value 81.197099 iter 60 value 80.818801 iter 70 value 79.201674 iter 80 value 78.943771 iter 90 value 78.482286 iter 100 value 77.942594 final value 77.942594 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 111.603723 iter 10 value 96.023337 iter 20 value 94.549888 iter 30 value 93.397734 iter 40 value 85.406531 iter 50 value 84.474380 iter 60 value 84.098273 iter 70 value 83.602092 iter 80 value 81.890080 iter 90 value 80.357426 iter 100 value 80.126717 final value 80.126717 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.196696 final value 94.485855 converged Fitting Repeat 2 # weights: 103 initial value 99.776131 final value 94.485847 converged Fitting Repeat 3 # weights: 103 initial value 97.886764 final value 94.485601 converged Fitting Repeat 4 # weights: 103 initial value 99.088189 final value 94.485952 converged Fitting Repeat 5 # weights: 103 initial value 102.913582 final value 94.485706 converged Fitting Repeat 1 # weights: 305 initial value 105.014388 iter 10 value 94.313220 iter 20 value 86.140683 iter 30 value 83.725644 iter 40 value 83.621791 iter 50 value 83.612360 iter 60 value 83.610914 iter 70 value 83.607521 final value 83.607009 converged Fitting Repeat 2 # weights: 305 initial value 95.599377 iter 10 value 94.359287 iter 20 value 93.635836 iter 30 value 92.857010 iter 40 value 92.856013 iter 50 value 92.855924 final value 92.855911 converged Fitting Repeat 3 # weights: 305 initial value 104.257572 iter 10 value 94.359761 iter 20 value 94.354678 final value 94.354619 converged Fitting Repeat 4 # weights: 305 initial value 96.176259 iter 10 value 94.359322 iter 20 value 94.056895 iter 30 value 87.737034 iter 40 value 87.712626 iter 50 value 84.380187 iter 60 value 83.648446 iter 70 value 83.633416 iter 80 value 83.632719 iter 90 value 83.619828 iter 100 value 83.613772 final value 83.613772 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 106.801315 iter 10 value 94.359027 iter 20 value 92.996026 iter 30 value 85.364149 iter 40 value 85.360912 iter 50 value 85.360755 iter 60 value 85.360262 iter 70 value 85.359879 iter 80 value 85.070181 iter 90 value 84.887390 iter 100 value 84.886391 final value 84.886391 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 121.165500 iter 10 value 94.320342 iter 20 value 94.289126 final value 94.113833 converged Fitting Repeat 2 # weights: 507 initial value 102.712562 iter 10 value 94.492262 iter 20 value 86.253830 iter 30 value 84.040866 iter 40 value 84.017905 iter 50 value 84.015950 iter 60 value 83.987691 iter 70 value 83.172944 iter 80 value 83.167750 iter 90 value 82.896734 iter 100 value 82.080281 final value 82.080281 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 114.832654 iter 10 value 94.362600 iter 20 value 94.110931 iter 30 value 83.278257 iter 40 value 80.475672 iter 50 value 77.898904 iter 60 value 75.648519 iter 70 value 75.421567 final value 75.408335 converged Fitting Repeat 4 # weights: 507 initial value 100.604551 iter 10 value 94.492387 iter 20 value 94.344748 iter 30 value 94.032667 iter 40 value 84.554934 iter 50 value 83.737575 iter 60 value 83.736662 iter 70 value 83.734018 iter 80 value 83.733083 iter 90 value 82.286799 iter 100 value 80.396150 final value 80.396150 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 117.060512 iter 10 value 94.171361 iter 20 value 94.117350 iter 30 value 94.110850 iter 40 value 92.402274 iter 50 value 86.964299 iter 60 value 86.961314 iter 70 value 84.579555 iter 80 value 84.558329 iter 90 value 84.557732 iter 90 value 84.557732 final value 84.557732 converged Fitting Repeat 1 # weights: 103 initial value 106.173027 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 97.833561 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 105.595724 iter 10 value 94.026550 final value 94.026542 converged Fitting Repeat 4 # weights: 103 initial value 97.712433 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 105.252095 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 94.955657 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 99.273023 iter 10 value 86.843485 iter 20 value 83.712496 iter 30 value 82.894056 iter 40 value 82.496644 iter 50 value 82.495295 final value 82.495275 converged Fitting Repeat 3 # weights: 305 initial value 120.264134 final value 94.020991 converged Fitting Repeat 4 # weights: 305 initial value 97.697219 iter 10 value 94.484214 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 102.894183 iter 10 value 93.320244 final value 93.320225 converged Fitting Repeat 1 # weights: 507 initial value 107.373364 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 101.577914 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 105.460062 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 114.238634 final value 94.026542 converged Fitting Repeat 5 # weights: 507 initial value 98.455218 iter 10 value 93.550186 final value 93.264982 converged Fitting Repeat 1 # weights: 103 initial value 105.135752 iter 10 value 94.240929 iter 20 value 93.299884 iter 30 value 89.935766 iter 40 value 84.745002 iter 50 value 83.878014 iter 60 value 83.403634 iter 70 value 83.102608 iter 80 value 82.894176 iter 80 value 82.894175 iter 80 value 82.894175 final value 82.894175 converged Fitting Repeat 2 # weights: 103 initial value 97.292720 iter 10 value 94.480835 iter 20 value 85.347638 iter 30 value 84.793224 iter 40 value 84.052142 iter 50 value 83.857861 iter 60 value 83.705762 iter 70 value 83.657528 iter 80 value 83.619415 iter 90 value 83.614022 final value 83.613974 converged Fitting Repeat 3 # weights: 103 initial value 95.271977 iter 10 value 86.700980 iter 20 value 83.814052 iter 30 value 83.670392 iter 40 value 83.620741 iter 50 value 83.614027 final value 83.613977 converged Fitting Repeat 4 # weights: 103 initial value 117.861739 iter 10 value 94.427166 iter 20 value 91.788880 iter 30 value 87.141136 iter 40 value 86.732952 iter 50 value 86.088306 iter 60 value 85.308800 iter 70 value 83.313457 iter 80 value 82.904857 iter 90 value 82.897072 iter 100 value 82.894336 final value 82.894336 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 112.192927 iter 10 value 94.394857 iter 20 value 90.170200 iter 30 value 84.648730 iter 40 value 83.057665 iter 50 value 82.892350 iter 60 value 82.761870 iter 70 value 81.937190 iter 80 value 81.154934 iter 90 value 81.089015 iter 100 value 81.073505 final value 81.073505 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 135.564661 iter 10 value 94.573902 iter 20 value 93.514890 iter 30 value 92.549338 iter 40 value 88.537364 iter 50 value 85.830649 iter 60 value 83.137327 iter 70 value 82.247355 iter 80 value 81.837181 iter 90 value 81.651740 iter 100 value 81.258436 final value 81.258436 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 111.297012 iter 10 value 94.054251 iter 20 value 91.319988 iter 30 value 88.763219 iter 40 value 87.956524 iter 50 value 85.923993 iter 60 value 83.890704 iter 70 value 82.705795 iter 80 value 81.399750 iter 90 value 80.736460 iter 100 value 80.422459 final value 80.422459 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 101.449288 iter 10 value 94.635268 iter 20 value 94.460120 iter 30 value 92.967961 iter 40 value 91.446533 iter 50 value 84.395537 iter 60 value 83.279833 iter 70 value 82.626797 iter 80 value 81.728265 iter 90 value 80.622930 iter 100 value 79.886651 final value 79.886651 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 105.885336 iter 10 value 94.409512 iter 20 value 92.472705 iter 30 value 85.457992 iter 40 value 83.475661 iter 50 value 83.389608 iter 60 value 83.205019 iter 70 value 82.439668 iter 80 value 80.340340 iter 90 value 79.880340 iter 100 value 79.739282 final value 79.739282 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 101.565802 iter 10 value 94.481281 iter 20 value 90.929161 iter 30 value 87.527158 iter 40 value 83.864811 iter 50 value 83.547726 iter 60 value 82.345318 iter 70 value 81.810913 iter 80 value 81.373305 iter 90 value 81.181591 iter 100 value 81.170623 final value 81.170623 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 108.458807 iter 10 value 95.138211 iter 20 value 93.960152 iter 30 value 91.608226 iter 40 value 85.057917 iter 50 value 83.654478 iter 60 value 82.437766 iter 70 value 81.614910 iter 80 value 80.607724 iter 90 value 80.347267 iter 100 value 80.022229 final value 80.022229 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 120.018677 iter 10 value 95.679557 iter 20 value 93.093735 iter 30 value 87.118309 iter 40 value 85.853200 iter 50 value 85.466402 iter 60 value 85.141106 iter 70 value 83.825670 iter 80 value 81.534426 iter 90 value 80.741253 iter 100 value 80.412215 final value 80.412215 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 106.615945 iter 10 value 95.113794 iter 20 value 94.206844 iter 30 value 93.570017 iter 40 value 87.175283 iter 50 value 84.688927 iter 60 value 82.272805 iter 70 value 81.218340 iter 80 value 80.375361 iter 90 value 80.130082 iter 100 value 79.865829 final value 79.865829 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.330769 iter 10 value 94.852381 iter 20 value 94.553615 iter 30 value 94.501079 iter 40 value 89.743016 iter 50 value 84.112480 iter 60 value 83.582594 iter 70 value 83.434512 iter 80 value 83.220238 iter 90 value 83.036203 iter 100 value 81.561121 final value 81.561121 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 107.044970 iter 10 value 95.241424 iter 20 value 87.111129 iter 30 value 85.828135 iter 40 value 85.496603 iter 50 value 82.651871 iter 60 value 81.957250 iter 70 value 81.200565 iter 80 value 79.942410 iter 90 value 79.818277 iter 100 value 79.790378 final value 79.790378 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.066503 final value 94.486086 converged Fitting Repeat 2 # weights: 103 initial value 109.868681 final value 94.486082 converged Fitting Repeat 3 # weights: 103 initial value 98.833229 iter 10 value 94.485829 iter 20 value 94.484217 iter 30 value 84.199370 iter 40 value 83.999312 final value 83.950406 converged Fitting Repeat 4 # weights: 103 initial value 94.277550 iter 10 value 92.591871 iter 20 value 92.552548 iter 30 value 91.617655 iter 40 value 91.470132 iter 50 value 91.466327 iter 60 value 91.465956 final value 91.465791 converged Fitting Repeat 5 # weights: 103 initial value 103.202996 final value 93.789647 converged Fitting Repeat 1 # weights: 305 initial value 95.342076 iter 10 value 94.488969 iter 20 value 92.987971 iter 30 value 85.645502 iter 40 value 85.644002 final value 85.643268 converged Fitting Repeat 2 # weights: 305 initial value 106.723748 iter 10 value 94.509470 iter 20 value 94.489347 iter 30 value 93.331019 iter 40 value 93.322227 iter 50 value 93.289314 iter 60 value 84.311676 iter 70 value 81.306063 iter 80 value 80.207747 iter 90 value 79.948607 iter 100 value 79.781794 final value 79.781794 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 128.235478 iter 10 value 94.488628 iter 20 value 94.474737 final value 94.027248 converged Fitting Repeat 4 # weights: 305 initial value 104.763422 iter 10 value 94.489691 iter 20 value 94.484632 final value 94.484433 converged Fitting Repeat 5 # weights: 305 initial value 103.247178 iter 10 value 94.489341 iter 20 value 94.484234 iter 30 value 93.788262 final value 93.788238 converged Fitting Repeat 1 # weights: 507 initial value 98.628529 iter 10 value 93.742964 iter 20 value 93.718782 iter 30 value 93.281785 iter 40 value 93.280178 iter 50 value 89.404138 iter 60 value 82.437931 iter 70 value 81.766565 iter 80 value 79.315144 iter 90 value 79.005272 iter 100 value 78.995107 final value 78.995107 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 111.107455 iter 10 value 94.410276 iter 20 value 93.349072 iter 30 value 93.327701 iter 40 value 93.326627 final value 93.321379 converged Fitting Repeat 3 # weights: 507 initial value 99.853449 iter 10 value 88.107895 iter 20 value 88.030814 iter 30 value 87.677025 iter 40 value 87.547736 iter 50 value 87.545061 iter 60 value 85.605496 iter 70 value 80.941512 iter 80 value 79.468962 iter 90 value 79.193043 iter 100 value 79.046613 final value 79.046613 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 100.904384 iter 10 value 94.490940 iter 20 value 94.482725 iter 30 value 85.440098 iter 40 value 85.418461 iter 50 value 84.751725 iter 60 value 81.884244 iter 70 value 80.065526 iter 80 value 79.788413 iter 90 value 79.088963 iter 100 value 78.189869 final value 78.189869 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 123.536988 iter 10 value 92.434963 iter 20 value 92.400882 iter 30 value 92.390293 iter 40 value 83.423985 iter 50 value 83.339419 iter 60 value 83.338535 iter 70 value 83.276612 iter 80 value 82.646728 final value 82.639933 converged Fitting Repeat 1 # weights: 103 initial value 94.320073 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 97.096668 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 99.686613 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 96.000578 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 96.738984 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 101.459995 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 99.578518 iter 10 value 88.187873 final value 87.609764 converged Fitting Repeat 3 # weights: 305 initial value 95.274585 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 111.484568 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 99.644649 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 101.656684 final value 94.052910 converged Fitting Repeat 2 # weights: 507 initial value 107.504522 iter 10 value 94.017176 final value 94.017114 converged Fitting Repeat 3 # weights: 507 initial value 104.027199 iter 10 value 94.052910 iter 10 value 94.052910 iter 10 value 94.052910 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 107.203795 final value 93.810010 converged Fitting Repeat 5 # weights: 507 initial value 112.381070 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 102.788490 iter 10 value 94.064700 iter 20 value 94.007727 iter 30 value 92.876697 iter 40 value 89.519466 iter 50 value 88.814658 iter 60 value 85.494145 iter 70 value 84.930900 iter 80 value 84.755365 iter 90 value 84.729705 iter 90 value 84.729705 final value 84.729705 converged Fitting Repeat 2 # weights: 103 initial value 97.670507 iter 10 value 93.903585 iter 20 value 92.764066 iter 30 value 92.388857 iter 40 value 90.681708 iter 50 value 86.474602 iter 60 value 85.152688 iter 70 value 85.115357 iter 80 value 85.019749 iter 90 value 84.526056 iter 100 value 84.394135 final value 84.394135 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 100.389262 iter 10 value 94.077955 iter 20 value 93.024183 iter 30 value 88.158698 iter 40 value 87.395239 iter 50 value 87.118637 iter 60 value 85.533438 iter 70 value 84.877437 iter 80 value 84.227369 final value 84.225265 converged Fitting Repeat 4 # weights: 103 initial value 129.291347 iter 10 value 93.965616 iter 20 value 93.426222 iter 30 value 90.497099 iter 40 value 86.030223 iter 50 value 85.320454 iter 60 value 84.636870 iter 70 value 84.428018 final value 84.425386 converged Fitting Repeat 5 # weights: 103 initial value 105.509522 iter 10 value 94.058243 iter 20 value 89.172336 iter 30 value 87.268893 iter 40 value 86.472271 iter 50 value 86.020078 iter 60 value 85.538130 iter 70 value 85.154209 iter 80 value 84.983441 final value 84.981528 converged Fitting Repeat 1 # weights: 305 initial value 104.459363 iter 10 value 94.244604 iter 20 value 93.809234 iter 30 value 93.035308 iter 40 value 88.691583 iter 50 value 86.329998 iter 60 value 86.155926 iter 70 value 84.840732 iter 80 value 83.926158 iter 90 value 82.861522 iter 100 value 82.426752 final value 82.426752 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 101.444869 iter 10 value 93.997811 iter 20 value 86.934439 iter 30 value 86.679640 iter 40 value 86.320307 iter 50 value 85.018925 iter 60 value 82.913977 iter 70 value 82.199497 iter 80 value 82.020340 iter 90 value 81.690780 iter 100 value 81.654950 final value 81.654950 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 128.698835 iter 10 value 94.059119 iter 20 value 87.049516 iter 30 value 86.323128 iter 40 value 85.678324 iter 50 value 84.748099 iter 60 value 84.583799 iter 70 value 84.514033 iter 80 value 84.207193 iter 90 value 83.321883 iter 100 value 82.296719 final value 82.296719 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 104.648991 iter 10 value 95.114756 iter 20 value 92.437425 iter 30 value 88.502993 iter 40 value 86.134882 iter 50 value 85.327202 iter 60 value 82.654215 iter 70 value 82.182853 iter 80 value 82.051582 iter 90 value 81.944173 iter 100 value 81.812419 final value 81.812419 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 124.397094 iter 10 value 94.041048 iter 20 value 87.840956 iter 30 value 86.733196 iter 40 value 86.191034 iter 50 value 85.076125 iter 60 value 84.477007 iter 70 value 84.352019 iter 80 value 84.180288 iter 90 value 83.898795 iter 100 value 82.427194 final value 82.427194 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 105.838392 iter 10 value 95.031953 iter 20 value 94.177888 iter 30 value 86.380142 iter 40 value 84.311772 iter 50 value 82.515477 iter 60 value 81.914756 iter 70 value 81.745431 iter 80 value 81.608629 iter 90 value 81.549784 iter 100 value 81.492161 final value 81.492161 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 111.105005 iter 10 value 93.893216 iter 20 value 86.885750 iter 30 value 85.087409 iter 40 value 84.961895 iter 50 value 84.508900 iter 60 value 83.601850 iter 70 value 83.304005 iter 80 value 83.242158 iter 90 value 82.487265 iter 100 value 81.811660 final value 81.811660 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 107.100480 iter 10 value 93.047395 iter 20 value 88.111599 iter 30 value 87.391624 iter 40 value 84.958308 iter 50 value 82.425549 iter 60 value 81.511210 iter 70 value 81.385813 iter 80 value 81.338563 iter 90 value 81.228720 iter 100 value 80.976935 final value 80.976935 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 112.590721 iter 10 value 94.010514 iter 20 value 92.207031 iter 30 value 91.173782 iter 40 value 88.023200 iter 50 value 85.764707 iter 60 value 83.636088 iter 70 value 82.047251 iter 80 value 81.634601 iter 90 value 81.428115 iter 100 value 81.276400 final value 81.276400 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 116.100955 iter 10 value 93.902443 iter 20 value 93.147973 iter 30 value 91.393834 iter 40 value 90.867246 iter 50 value 86.490968 iter 60 value 85.193392 iter 70 value 83.563772 iter 80 value 82.235925 iter 90 value 81.940167 iter 100 value 81.618283 final value 81.618283 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 94.105221 iter 10 value 94.054788 final value 94.052931 converged Fitting Repeat 2 # weights: 103 initial value 102.090414 final value 94.054588 converged Fitting Repeat 3 # weights: 103 initial value 97.961623 final value 94.043859 converged Fitting Repeat 4 # weights: 103 initial value 101.861422 iter 10 value 93.840076 iter 20 value 93.837680 iter 30 value 93.786436 final value 93.786221 converged Fitting Repeat 5 # weights: 103 initial value 97.202533 final value 94.054513 converged Fitting Repeat 1 # weights: 305 initial value 96.195905 iter 10 value 94.057484 iter 20 value 93.869388 iter 30 value 88.462112 iter 40 value 88.069167 iter 50 value 88.053241 iter 60 value 87.877338 iter 70 value 87.056305 iter 80 value 86.446370 iter 90 value 85.545420 iter 100 value 85.393372 final value 85.393372 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 97.186244 iter 10 value 94.057475 iter 20 value 94.018925 final value 93.836363 converged Fitting Repeat 3 # weights: 305 initial value 94.888695 iter 10 value 94.057714 iter 20 value 94.053002 final value 94.052918 converged Fitting Repeat 4 # weights: 305 initial value 97.912239 iter 10 value 93.921049 iter 20 value 93.483208 iter 30 value 93.448072 iter 40 value 93.440621 iter 50 value 87.879870 iter 60 value 85.579431 iter 70 value 85.287393 iter 80 value 85.284473 final value 85.284453 converged Fitting Repeat 5 # weights: 305 initial value 98.016375 iter 10 value 94.058572 iter 20 value 93.869847 iter 30 value 87.133068 iter 40 value 86.415167 iter 50 value 86.403258 iter 60 value 86.396045 iter 70 value 84.997870 iter 80 value 83.291530 iter 90 value 83.191404 iter 100 value 83.190502 final value 83.190502 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 101.861046 iter 10 value 94.060546 iter 20 value 93.987059 iter 30 value 87.959431 iter 40 value 86.835840 iter 50 value 86.829934 final value 86.829806 converged Fitting Repeat 2 # weights: 507 initial value 125.293033 iter 10 value 89.290208 iter 20 value 85.217734 iter 30 value 84.393237 iter 40 value 83.983626 iter 50 value 83.977447 iter 60 value 83.971827 final value 83.971779 converged Fitting Repeat 3 # weights: 507 initial value 101.102542 iter 10 value 94.061712 iter 20 value 92.634343 iter 30 value 86.258222 iter 40 value 86.247736 iter 50 value 86.247644 iter 60 value 86.208489 iter 70 value 85.419570 iter 80 value 84.587571 iter 90 value 84.488325 iter 100 value 84.164975 final value 84.164975 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 109.127607 iter 10 value 88.131914 iter 20 value 87.260610 iter 30 value 86.745408 iter 40 value 85.578774 final value 85.500189 converged Fitting Repeat 5 # weights: 507 initial value 121.944774 iter 10 value 94.060790 iter 20 value 94.052965 iter 30 value 85.757675 iter 40 value 85.538852 iter 40 value 85.538852 final value 85.538852 converged Fitting Repeat 1 # weights: 103 initial value 110.279264 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 95.865184 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 101.611218 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 101.884710 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 94.663133 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 97.420406 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 102.478859 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 112.659744 final value 93.991525 converged Fitting Repeat 4 # weights: 305 initial value 107.314581 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 105.815986 iter 10 value 89.483489 iter 20 value 85.665756 iter 30 value 85.491483 iter 40 value 84.686715 iter 50 value 84.357864 final value 84.350220 converged Fitting Repeat 1 # weights: 507 initial value 103.286129 final value 93.967787 converged Fitting Repeat 2 # weights: 507 initial value 110.157209 final value 94.052910 converged Fitting Repeat 3 # weights: 507 initial value 111.789173 iter 10 value 84.249599 iter 20 value 84.150174 final value 84.150007 converged Fitting Repeat 4 # weights: 507 initial value 101.668131 iter 10 value 93.177687 iter 20 value 87.487056 iter 30 value 84.131782 iter 40 value 83.951985 iter 50 value 83.950932 final value 83.950858 converged Fitting Repeat 5 # weights: 507 initial value 100.443460 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 96.320493 iter 10 value 94.035575 iter 20 value 93.797296 iter 30 value 89.837052 iter 40 value 87.440778 iter 50 value 87.260463 iter 60 value 86.855250 iter 70 value 85.915521 iter 80 value 85.490192 final value 85.488696 converged Fitting Repeat 2 # weights: 103 initial value 98.609307 iter 10 value 94.057027 iter 20 value 87.312008 iter 30 value 86.766394 iter 40 value 84.896619 iter 50 value 83.135413 iter 60 value 82.624621 iter 70 value 82.363066 iter 80 value 82.317351 iter 90 value 82.249719 iter 100 value 82.200080 final value 82.200080 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 98.371045 iter 10 value 90.417863 iter 20 value 86.706073 iter 30 value 86.563966 iter 40 value 86.337244 iter 50 value 85.718244 iter 60 value 84.846173 iter 70 value 84.788694 iter 80 value 84.703470 iter 90 value 84.542433 iter 100 value 84.517675 final value 84.517675 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 104.254037 iter 10 value 94.118997 iter 20 value 93.977129 iter 30 value 93.577757 iter 40 value 87.154051 iter 50 value 85.481607 iter 60 value 85.185898 iter 70 value 84.976402 iter 80 value 84.912708 iter 90 value 84.865899 final value 84.864880 converged Fitting Repeat 5 # weights: 103 initial value 101.900783 iter 10 value 94.056681 iter 20 value 93.860389 iter 30 value 93.825099 iter 40 value 93.821610 iter 50 value 93.793794 iter 60 value 87.191208 iter 70 value 86.715512 iter 80 value 85.186435 iter 90 value 84.996533 iter 100 value 84.902486 final value 84.902486 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 101.157366 iter 10 value 94.039919 iter 20 value 93.620190 iter 30 value 86.420532 iter 40 value 83.302463 iter 50 value 82.259658 iter 60 value 81.481119 iter 70 value 81.392729 iter 80 value 81.366832 iter 90 value 81.339786 iter 100 value 81.296302 final value 81.296302 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 111.015088 iter 10 value 94.054851 iter 20 value 93.840054 iter 30 value 90.603702 iter 40 value 88.099695 iter 50 value 86.065073 iter 60 value 85.588914 iter 70 value 85.396772 iter 80 value 85.284879 iter 90 value 84.883805 iter 100 value 83.367158 final value 83.367158 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.118499 iter 10 value 94.518216 iter 20 value 93.844046 iter 30 value 92.389115 iter 40 value 85.511243 iter 50 value 83.987064 iter 60 value 82.834570 iter 70 value 82.000463 iter 80 value 81.564325 iter 90 value 81.296506 iter 100 value 81.180105 final value 81.180105 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 103.753898 iter 10 value 94.271436 iter 20 value 90.615922 iter 30 value 84.900339 iter 40 value 83.402645 iter 50 value 82.555061 iter 60 value 82.144697 iter 70 value 82.142238 iter 80 value 82.110330 iter 90 value 81.646805 iter 100 value 81.384796 final value 81.384796 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 102.851597 iter 10 value 93.976302 iter 20 value 90.125146 iter 30 value 87.257143 iter 40 value 85.054680 iter 50 value 82.682352 iter 60 value 82.008301 iter 70 value 81.723284 iter 80 value 81.486189 iter 90 value 81.439599 iter 100 value 81.382547 final value 81.382547 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 120.005774 iter 10 value 94.094912 iter 20 value 93.075767 iter 30 value 85.579575 iter 40 value 84.319948 iter 50 value 83.634997 iter 60 value 82.248601 iter 70 value 81.826033 iter 80 value 81.754975 iter 90 value 81.688010 iter 100 value 81.612659 final value 81.612659 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 105.274855 iter 10 value 93.883588 iter 20 value 88.153194 iter 30 value 85.569834 iter 40 value 84.659661 iter 50 value 83.278821 iter 60 value 82.280505 iter 70 value 82.062730 iter 80 value 81.951030 iter 90 value 81.762266 iter 100 value 81.482279 final value 81.482279 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.514988 iter 10 value 95.235317 iter 20 value 91.618432 iter 30 value 88.303810 iter 40 value 88.017334 iter 50 value 85.591731 iter 60 value 81.292558 iter 70 value 81.013301 iter 80 value 80.955803 iter 90 value 80.825982 iter 100 value 80.755780 final value 80.755780 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 137.060741 iter 10 value 94.485879 iter 20 value 88.576069 iter 30 value 86.458319 iter 40 value 85.967177 iter 50 value 85.097996 iter 60 value 84.863231 iter 70 value 84.732344 iter 80 value 83.567908 iter 90 value 82.002429 iter 100 value 81.354621 final value 81.354621 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 106.506824 iter 10 value 94.693441 iter 20 value 94.087678 iter 30 value 93.967776 iter 40 value 88.605369 iter 50 value 86.855233 iter 60 value 83.954322 iter 70 value 83.179058 iter 80 value 82.964935 iter 90 value 82.854060 iter 100 value 82.595633 final value 82.595633 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 94.066303 final value 94.054340 converged Fitting Repeat 2 # weights: 103 initial value 104.361110 final value 93.970777 converged Fitting Repeat 3 # weights: 103 initial value 114.008663 final value 94.054517 converged Fitting Repeat 4 # weights: 103 initial value 96.026702 final value 94.054598 converged Fitting Repeat 5 # weights: 103 initial value 99.440690 final value 94.054558 converged Fitting Repeat 1 # weights: 305 initial value 108.742412 iter 10 value 94.038008 iter 20 value 93.880514 iter 30 value 90.083572 iter 40 value 90.081114 iter 40 value 90.081114 final value 90.081102 converged Fitting Repeat 2 # weights: 305 initial value 109.434503 iter 10 value 94.057502 iter 20 value 94.053089 iter 30 value 88.509306 iter 40 value 86.013401 iter 50 value 85.553062 iter 60 value 82.745034 iter 70 value 82.217512 iter 80 value 82.201859 iter 90 value 81.961523 final value 81.879571 converged Fitting Repeat 3 # weights: 305 initial value 96.527564 iter 10 value 94.057664 iter 20 value 94.008481 iter 30 value 87.484024 iter 40 value 87.371860 final value 87.365001 converged Fitting Repeat 4 # weights: 305 initial value 110.160168 iter 10 value 94.038487 iter 20 value 93.575293 iter 30 value 88.164775 iter 40 value 88.155081 iter 50 value 88.154134 final value 88.154061 converged Fitting Repeat 5 # weights: 305 initial value 108.597857 iter 10 value 94.057728 iter 20 value 94.052963 iter 30 value 94.032444 iter 40 value 92.942029 iter 50 value 92.744425 iter 60 value 88.729988 iter 70 value 88.153865 iter 80 value 88.098069 iter 90 value 88.066057 iter 100 value 88.057317 final value 88.057317 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 106.900340 iter 10 value 94.061346 iter 20 value 93.971810 iter 30 value 85.792928 iter 40 value 85.429884 iter 50 value 85.428191 final value 85.427477 converged Fitting Repeat 2 # weights: 507 initial value 94.822152 iter 10 value 94.061108 iter 20 value 93.986923 iter 30 value 93.792624 iter 40 value 93.695754 iter 50 value 92.903218 iter 60 value 88.782669 iter 70 value 86.837521 iter 80 value 81.740878 iter 90 value 81.028620 iter 100 value 80.546666 final value 80.546666 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 122.000094 iter 10 value 94.041451 iter 20 value 94.037402 iter 30 value 94.037095 final value 94.037069 converged Fitting Repeat 4 # weights: 507 initial value 99.737059 iter 10 value 94.041331 iter 20 value 93.973583 iter 30 value 89.016645 iter 40 value 85.825022 iter 50 value 85.822614 iter 60 value 85.660550 iter 70 value 85.659846 iter 80 value 85.657529 iter 90 value 85.578566 final value 85.578466 converged Fitting Repeat 5 # weights: 507 initial value 98.531732 iter 10 value 93.975951 iter 20 value 93.969538 iter 30 value 93.790691 iter 40 value 93.789709 final value 93.789606 converged Fitting Repeat 1 # weights: 103 initial value 96.106006 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 110.691537 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 98.058860 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 104.769012 iter 10 value 93.268391 iter 20 value 92.897403 iter 30 value 92.896665 final value 92.896662 converged Fitting Repeat 5 # weights: 103 initial value 101.438284 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 95.940751 iter 10 value 92.340453 iter 20 value 92.300909 final value 92.300753 converged Fitting Repeat 2 # weights: 305 initial value 107.442091 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 112.833938 final value 94.473118 converged Fitting Repeat 4 # weights: 305 initial value 110.162399 final value 94.473118 converged Fitting Repeat 5 # weights: 305 initial value 106.020734 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 101.736567 iter 10 value 93.787953 final value 93.783550 converged Fitting Repeat 2 # weights: 507 initial value 109.397713 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 94.745171 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 122.351912 final value 94.473118 converged Fitting Repeat 5 # weights: 507 initial value 117.082032 final value 94.473118 converged Fitting Repeat 1 # weights: 103 initial value 98.688402 iter 10 value 94.413317 iter 20 value 90.862857 iter 30 value 89.202420 iter 40 value 87.332441 iter 50 value 84.682907 iter 60 value 83.918068 iter 70 value 82.554657 iter 80 value 82.265298 iter 90 value 81.805087 iter 100 value 81.396972 final value 81.396972 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 103.520146 iter 10 value 93.082157 iter 20 value 84.859280 iter 30 value 83.683703 iter 40 value 83.441025 iter 50 value 83.418286 final value 83.418269 converged Fitting Repeat 3 # weights: 103 initial value 107.431140 iter 10 value 94.487854 iter 20 value 94.486973 iter 30 value 94.221355 iter 40 value 93.573623 iter 50 value 92.041620 iter 60 value 90.822297 iter 70 value 90.731307 iter 80 value 90.668354 final value 90.668036 converged Fitting Repeat 4 # weights: 103 initial value 96.544190 iter 10 value 94.486600 iter 20 value 93.474531 iter 30 value 86.334181 iter 40 value 84.727852 iter 50 value 84.246172 iter 60 value 84.152379 iter 70 value 83.962157 iter 80 value 83.858021 final value 83.856356 converged Fitting Repeat 5 # weights: 103 initial value 97.227752 iter 10 value 94.245059 iter 20 value 86.504505 iter 30 value 85.965122 iter 40 value 85.741840 iter 50 value 85.068699 iter 60 value 82.682380 iter 70 value 81.373895 iter 80 value 81.309517 final value 81.309449 converged Fitting Repeat 1 # weights: 305 initial value 104.899064 iter 10 value 94.634261 iter 20 value 94.499335 iter 30 value 93.310498 iter 40 value 91.847827 iter 50 value 85.938504 iter 60 value 85.285185 iter 70 value 82.707238 iter 80 value 81.172230 iter 90 value 80.768939 iter 100 value 80.577018 final value 80.577018 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 105.275547 iter 10 value 94.492140 iter 20 value 92.912236 iter 30 value 86.761833 iter 40 value 84.808174 iter 50 value 83.816882 iter 60 value 83.593353 iter 70 value 82.692331 iter 80 value 81.066663 iter 90 value 80.892747 iter 100 value 80.642593 final value 80.642593 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 102.800369 iter 10 value 94.153199 iter 20 value 89.310346 iter 30 value 86.402150 iter 40 value 85.545321 iter 50 value 83.655607 iter 60 value 81.666408 iter 70 value 81.406197 iter 80 value 81.152469 iter 90 value 81.119407 iter 100 value 81.106389 final value 81.106389 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 114.556878 iter 10 value 99.910014 iter 20 value 89.987563 iter 30 value 85.041476 iter 40 value 84.908005 iter 50 value 82.910275 iter 60 value 81.926565 iter 70 value 81.018623 iter 80 value 80.476801 iter 90 value 80.306281 iter 100 value 80.186821 final value 80.186821 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.038391 iter 10 value 95.082498 iter 20 value 89.631260 iter 30 value 86.417463 iter 40 value 84.222119 iter 50 value 83.381966 iter 60 value 82.585393 iter 70 value 82.319368 iter 80 value 82.030056 iter 90 value 80.848435 iter 100 value 79.932589 final value 79.932589 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 103.412453 iter 10 value 91.777514 iter 20 value 87.719790 iter 30 value 85.805721 iter 40 value 84.238472 iter 50 value 82.385023 iter 60 value 81.720717 iter 70 value 80.970325 iter 80 value 80.387290 iter 90 value 79.795496 iter 100 value 79.537393 final value 79.537393 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 111.003581 iter 10 value 94.914522 iter 20 value 94.315922 iter 30 value 89.110791 iter 40 value 85.117556 iter 50 value 84.299185 iter 60 value 83.689055 iter 70 value 83.000626 iter 80 value 82.364450 iter 90 value 80.971119 iter 100 value 80.615607 final value 80.615607 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 116.199268 iter 10 value 96.050247 iter 20 value 93.602311 iter 30 value 86.534330 iter 40 value 86.211932 iter 50 value 85.234160 iter 60 value 83.344614 iter 70 value 82.264595 iter 80 value 81.526285 iter 90 value 80.948076 iter 100 value 80.393935 final value 80.393935 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 117.697569 iter 10 value 94.948866 iter 20 value 94.724093 iter 30 value 87.635442 iter 40 value 84.865674 iter 50 value 84.606913 iter 60 value 83.899957 iter 70 value 82.388124 iter 80 value 81.735700 iter 90 value 81.267815 iter 100 value 81.024110 final value 81.024110 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 113.782887 iter 10 value 94.723310 iter 20 value 94.217572 iter 30 value 93.645487 iter 40 value 85.782216 iter 50 value 84.704914 iter 60 value 84.378367 iter 70 value 83.442313 iter 80 value 82.329351 iter 90 value 82.002008 iter 100 value 81.919803 final value 81.919803 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.811483 final value 94.485664 converged Fitting Repeat 2 # weights: 103 initial value 96.527310 final value 94.485833 converged Fitting Repeat 3 # weights: 103 initial value 102.385368 final value 94.485961 converged Fitting Repeat 4 # weights: 103 initial value 101.941247 iter 10 value 94.474567 iter 10 value 94.474566 iter 10 value 94.474566 final value 94.474566 converged Fitting Repeat 5 # weights: 103 initial value 95.713536 iter 10 value 94.485752 iter 20 value 94.484222 iter 30 value 91.676156 iter 40 value 85.880340 iter 50 value 85.877161 iter 60 value 85.876805 iter 60 value 85.876805 iter 70 value 85.631477 iter 80 value 85.630133 final value 85.630131 converged Fitting Repeat 1 # weights: 305 initial value 112.095728 iter 10 value 94.478432 iter 20 value 93.879569 iter 30 value 93.787638 iter 40 value 93.767998 iter 50 value 93.683011 iter 60 value 92.680619 iter 70 value 90.675735 iter 80 value 89.736642 iter 90 value 88.300729 iter 100 value 83.360214 final value 83.360214 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 112.698674 iter 10 value 94.478308 iter 20 value 94.474342 iter 30 value 89.490005 iter 40 value 87.268308 iter 50 value 87.266805 iter 60 value 87.137783 iter 70 value 87.119137 iter 80 value 87.117525 iter 90 value 87.117399 final value 87.117372 converged Fitting Repeat 3 # weights: 305 initial value 99.331531 iter 10 value 94.477771 iter 20 value 94.171114 iter 30 value 93.900552 final value 93.819110 converged Fitting Repeat 4 # weights: 305 initial value 113.599100 iter 10 value 94.489222 iter 20 value 92.917942 iter 30 value 84.761063 iter 40 value 84.304732 iter 50 value 84.081704 iter 60 value 83.881306 iter 70 value 83.877351 iter 80 value 83.678651 iter 90 value 83.404508 iter 100 value 83.235341 final value 83.235341 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 113.964437 iter 10 value 94.489078 iter 20 value 94.245746 iter 30 value 89.810450 iter 40 value 89.541997 iter 50 value 89.057555 iter 60 value 89.051614 iter 70 value 89.051340 final value 89.050711 converged Fitting Repeat 1 # weights: 507 initial value 97.189120 iter 10 value 89.025513 iter 20 value 87.340543 iter 30 value 87.329236 iter 40 value 84.288255 iter 50 value 83.905490 iter 60 value 83.619241 iter 70 value 83.283438 iter 80 value 83.187509 iter 90 value 83.185607 iter 100 value 82.342840 final value 82.342840 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 98.557686 iter 10 value 94.492478 iter 20 value 94.476388 final value 94.473376 converged Fitting Repeat 3 # weights: 507 initial value 103.982434 iter 10 value 94.274568 iter 20 value 93.942162 iter 30 value 91.388582 iter 40 value 84.232991 iter 50 value 84.230018 iter 60 value 84.226840 iter 70 value 84.208269 iter 80 value 83.975220 iter 90 value 83.661935 iter 100 value 80.807675 final value 80.807675 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 104.889176 iter 10 value 88.381649 iter 20 value 87.275105 iter 30 value 87.269783 iter 40 value 87.268982 iter 50 value 87.268452 iter 60 value 87.265714 final value 87.265672 converged Fitting Repeat 5 # weights: 507 initial value 102.560542 iter 10 value 94.478026 iter 20 value 94.064590 iter 30 value 94.053890 iter 40 value 93.873014 iter 50 value 93.859237 iter 60 value 93.266724 iter 70 value 93.260466 iter 80 value 93.256697 iter 90 value 91.758375 iter 100 value 84.277467 final value 84.277467 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 158.356706 iter 10 value 117.767380 iter 20 value 117.642156 iter 30 value 107.660073 iter 40 value 107.119594 iter 50 value 107.087874 iter 60 value 107.085213 iter 70 value 107.084202 final value 107.084096 converged Fitting Repeat 2 # weights: 507 initial value 141.307850 iter 10 value 117.898158 iter 20 value 116.950923 iter 30 value 105.989956 iter 40 value 104.908330 iter 50 value 104.907328 iter 50 value 104.907328 iter 50 value 104.907328 final value 104.907328 converged Fitting Repeat 3 # weights: 507 initial value 121.530001 iter 10 value 117.899597 iter 20 value 117.751958 iter 30 value 116.858213 iter 40 value 107.123926 iter 50 value 107.006532 iter 60 value 105.113900 iter 70 value 105.048813 iter 80 value 105.014064 iter 90 value 104.153534 iter 100 value 103.430513 final value 103.430513 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 127.773822 iter 10 value 117.865468 iter 20 value 117.858768 final value 117.858748 converged Fitting Repeat 5 # weights: 507 initial value 122.604554 iter 10 value 117.898345 iter 20 value 117.718797 iter 30 value 108.082533 iter 40 value 106.445254 iter 50 value 101.868476 iter 60 value 100.852262 iter 70 value 100.678631 iter 80 value 100.668375 iter 90 value 100.594218 iter 100 value 99.937851 final value 99.937851 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 Jan 20 21:25:45 2025 *********************************************** Number of test functions: 7 Number of errors: 0 Number of failures: 0 1 Test Suite : HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures Number of test functions: 7 Number of errors: 0 Number of failures: 0 Warning messages: 1: `repeats` has no meaning for this resampling method. 2: executing %dopar% sequentially: no parallel backend registered > > > > > proc.time() user system elapsed 41.243 1.644 105.991
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 33.858 | 1.576 | 35.764 | |
FreqInteractors | 0.245 | 0.013 | 0.260 | |
calculateAAC | 0.043 | 0.007 | 0.051 | |
calculateAutocor | 0.388 | 0.063 | 0.455 | |
calculateCTDC | 0.080 | 0.004 | 0.084 | |
calculateCTDD | 0.585 | 0.020 | 0.610 | |
calculateCTDT | 0.242 | 0.010 | 0.255 | |
calculateCTriad | 0.388 | 0.030 | 0.422 | |
calculateDC | 0.106 | 0.012 | 0.157 | |
calculateF | 0.345 | 0.009 | 0.355 | |
calculateKSAAP | 0.104 | 0.012 | 0.116 | |
calculateQD_Sm | 1.781 | 0.112 | 1.905 | |
calculateTC | 1.646 | 0.141 | 1.796 | |
calculateTC_Sm | 0.269 | 0.021 | 0.291 | |
corr_plot | 33.951 | 1.577 | 35.772 | |
enrichfindP | 0.462 | 0.058 | 8.568 | |
enrichfind_hp | 0.076 | 0.024 | 1.039 | |
enrichplot | 0.401 | 0.008 | 0.412 | |
filter_missing_values | 0.001 | 0.000 | 0.001 | |
getFASTA | 0.068 | 0.011 | 3.557 | |
getHPI | 0.001 | 0.000 | 0.001 | |
get_negativePPI | 0.002 | 0.000 | 0.003 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0.002 | 0.001 | 0.002 | |
plotPPI | 0.085 | 0.003 | 0.089 | |
pred_ensembel | 14.111 | 0.442 | 12.646 | |
var_imp | 35.320 | 1.684 | 37.404 | |