Back to Multiple platform build/check report for BioC 3.18: simplified long |
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This page was generated on 2024-04-17 11:36:02 -0400 (Wed, 17 Apr 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4676 |
palomino4 | Windows Server 2022 Datacenter | x64 | 4.3.3 (2024-02-29 ucrt) -- "Angel Food Cake" | 4414 |
merida1 | macOS 12.7.1 Monterey | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4437 |
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 974/2266 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.8.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | |||||||||
palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
merida1 | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | |||||||||
kjohnson1 | macOS 13.6.1 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: 1.8.0 |
Command: /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings HPiP_1.8.0.tar.gz |
StartedAt: 2024-04-15 23:50:41 -0400 (Mon, 15 Apr 2024) |
EndedAt: 2024-04-16 00:13:15 -0400 (Tue, 16 Apr 2024) |
EllapsedTime: 1354.8 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings HPiP_1.8.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck’ * using R version 4.3.3 (2024-02-29) * using platform: x86_64-pc-linux-gnu (64-bit) * 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 ‘1.8.0’ * 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 ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking R 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 ... OK * 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 35.452 0.972 36.425 FSmethod 34.518 0.776 35.296 corr_plot 34.397 0.488 34.885 pred_ensembel 13.456 0.560 10.701 enrichfindP 0.469 0.048 9.622 * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘runTests.R’ OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes in ‘inst/doc’ ... OK * checking running R code from vignettes ... ‘HPiP_tutorial.Rmd’ using ‘UTF-8’... OK OK * checking re-building of vignette outputs ... OK * checking PDF version of manual ... OK * DONE Status: 1 NOTE See ‘/home/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck/00check.log’ for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.18-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 4.3.3 (2024-02-29) -- "Angel Food Cake" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) 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 94.750978 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 94.571468 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 109.811643 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 97.194553 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 105.869559 iter 10 value 94.275362 iter 10 value 94.275362 iter 10 value 94.275362 final value 94.275362 converged Fitting Repeat 1 # weights: 305 initial value 101.637063 iter 10 value 93.893341 final value 93.831039 converged Fitting Repeat 2 # weights: 305 initial value 109.894267 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 101.397370 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 95.875994 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 99.502235 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 115.663018 iter 10 value 94.305896 final value 94.305882 converged Fitting Repeat 2 # weights: 507 initial value 104.295666 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 103.982660 final value 94.275362 converged Fitting Repeat 4 # weights: 507 initial value 100.704547 final value 94.448052 converged Fitting Repeat 5 # weights: 507 initial value 100.892852 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 97.954327 iter 10 value 94.488560 iter 20 value 94.345266 iter 30 value 86.092464 iter 40 value 84.106750 iter 50 value 83.715153 iter 60 value 83.473569 iter 70 value 81.917909 iter 80 value 81.882583 final value 81.882582 converged Fitting Repeat 2 # weights: 103 initial value 98.054408 iter 10 value 94.489904 iter 20 value 94.482368 iter 30 value 94.360332 iter 40 value 94.352643 iter 50 value 94.346553 iter 60 value 94.336115 iter 70 value 94.155556 iter 80 value 92.839728 iter 90 value 86.604517 iter 100 value 84.288128 final value 84.288128 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 96.170908 iter 10 value 94.459238 iter 20 value 86.199875 iter 30 value 84.884070 iter 40 value 84.372083 iter 50 value 83.036558 iter 60 value 82.095049 iter 70 value 81.882586 final value 81.882582 converged Fitting Repeat 4 # weights: 103 initial value 104.436199 iter 10 value 94.476891 iter 20 value 87.069253 iter 30 value 84.784946 iter 40 value 84.473950 iter 50 value 83.493388 iter 60 value 82.720309 iter 70 value 82.290132 iter 80 value 81.594729 iter 90 value 81.547469 final value 81.547435 converged Fitting Repeat 5 # weights: 103 initial value 98.970151 iter 10 value 94.488533 iter 20 value 94.314645 iter 30 value 86.194157 iter 40 value 85.504215 iter 50 value 85.124367 iter 60 value 84.529050 iter 70 value 83.315879 iter 80 value 83.165303 iter 90 value 83.143753 iter 100 value 82.766719 final value 82.766719 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 103.838401 iter 10 value 94.295377 iter 20 value 85.340731 iter 30 value 83.904193 iter 40 value 83.759902 iter 50 value 83.257562 iter 60 value 83.032866 iter 70 value 82.495367 iter 80 value 81.073836 iter 90 value 80.710015 iter 100 value 80.674780 final value 80.674780 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 104.936861 iter 10 value 94.497395 iter 20 value 86.371563 iter 30 value 84.578146 iter 40 value 82.674579 iter 50 value 81.576086 iter 60 value 81.140281 iter 70 value 80.999429 iter 80 value 80.761597 iter 90 value 80.520265 iter 100 value 80.482811 final value 80.482811 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 102.756115 iter 10 value 94.417146 iter 20 value 86.051468 iter 30 value 84.701484 iter 40 value 83.206065 iter 50 value 82.928193 iter 60 value 82.792036 iter 70 value 82.668237 iter 80 value 81.666678 iter 90 value 80.468794 iter 100 value 80.378192 final value 80.378192 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 104.390532 iter 10 value 94.484748 iter 20 value 93.835547 iter 30 value 92.571609 iter 40 value 89.196967 iter 50 value 86.861319 iter 60 value 85.670990 iter 70 value 85.340163 iter 80 value 84.254361 iter 90 value 82.395794 iter 100 value 81.147243 final value 81.147243 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 101.565298 iter 10 value 94.585444 iter 20 value 93.659063 iter 30 value 88.008582 iter 40 value 86.011885 iter 50 value 83.254814 iter 60 value 82.486174 iter 70 value 81.812895 iter 80 value 81.718928 iter 90 value 81.243052 iter 100 value 80.966001 final value 80.966001 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 130.633032 iter 10 value 93.917389 iter 20 value 84.702326 iter 30 value 83.756960 iter 40 value 82.881162 iter 50 value 81.888806 iter 60 value 81.637968 iter 70 value 80.955867 iter 80 value 80.838787 iter 90 value 80.644161 iter 100 value 80.490362 final value 80.490362 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 124.893000 iter 10 value 94.547255 iter 20 value 93.984274 iter 30 value 87.848977 iter 40 value 84.930089 iter 50 value 83.235757 iter 60 value 82.164039 iter 70 value 80.779960 iter 80 value 80.699341 iter 90 value 80.396320 iter 100 value 80.216033 final value 80.216033 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 119.591239 iter 10 value 100.618764 iter 20 value 94.236447 iter 30 value 90.510799 iter 40 value 86.848704 iter 50 value 84.379170 iter 60 value 83.311219 iter 70 value 81.867820 iter 80 value 80.663086 iter 90 value 80.160169 iter 100 value 79.950344 final value 79.950344 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 106.369352 iter 10 value 90.855763 iter 20 value 86.067997 iter 30 value 83.976483 iter 40 value 83.187115 iter 50 value 81.777684 iter 60 value 81.431040 iter 70 value 80.914813 iter 80 value 80.631590 iter 90 value 80.474925 iter 100 value 80.386203 final value 80.386203 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 109.992534 iter 10 value 94.483784 iter 20 value 85.293731 iter 30 value 84.323578 iter 40 value 83.732696 iter 50 value 81.946173 iter 60 value 81.077602 iter 70 value 80.630585 iter 80 value 80.272158 iter 90 value 80.114004 iter 100 value 79.962085 final value 79.962085 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 110.940291 final value 94.485763 converged Fitting Repeat 2 # weights: 103 initial value 96.633088 iter 10 value 94.486101 iter 20 value 93.395892 iter 30 value 84.195473 iter 30 value 84.195472 iter 40 value 84.054066 iter 50 value 84.051590 iter 60 value 83.960649 iter 60 value 83.960649 iter 60 value 83.960649 final value 83.960649 converged Fitting Repeat 3 # weights: 103 initial value 96.954048 final value 94.485806 converged Fitting Repeat 4 # weights: 103 initial value 105.377107 final value 94.486407 converged Fitting Repeat 5 # weights: 103 initial value 98.552816 final value 94.277087 converged Fitting Repeat 1 # weights: 305 initial value 102.454206 iter 10 value 94.489087 iter 20 value 93.723687 iter 30 value 92.625284 iter 40 value 89.813018 iter 50 value 89.809782 iter 60 value 84.221563 final value 84.193713 converged Fitting Repeat 2 # weights: 305 initial value 97.673838 iter 10 value 94.489074 iter 20 value 94.473528 iter 30 value 94.128825 iter 40 value 90.827820 final value 90.818890 converged Fitting Repeat 3 # weights: 305 initial value 96.422296 iter 10 value 92.492807 iter 20 value 87.933307 iter 30 value 87.136797 iter 40 value 87.125358 iter 50 value 86.410056 iter 60 value 86.405018 iter 70 value 86.398285 iter 80 value 86.394889 iter 90 value 86.394623 final value 86.394126 converged Fitting Repeat 4 # weights: 305 initial value 123.127689 iter 10 value 94.489088 iter 20 value 94.376633 iter 30 value 89.197310 iter 40 value 88.430655 iter 50 value 88.425224 iter 60 value 88.314798 iter 70 value 86.178455 iter 80 value 85.330480 iter 90 value 84.389545 iter 100 value 84.387390 final value 84.387390 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 99.492204 iter 10 value 94.488883 iter 20 value 94.473194 iter 30 value 94.341189 iter 40 value 90.082863 iter 50 value 87.956097 iter 60 value 86.273941 iter 70 value 85.109366 iter 80 value 82.413859 iter 90 value 80.670478 iter 100 value 80.486189 final value 80.486189 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 105.600419 iter 10 value 94.494229 iter 20 value 94.489080 iter 30 value 92.018299 iter 40 value 91.566421 iter 50 value 91.465914 final value 91.465780 converged Fitting Repeat 2 # weights: 507 initial value 110.170356 iter 10 value 94.321798 iter 20 value 92.360102 iter 30 value 87.952800 final value 87.952762 converged Fitting Repeat 3 # weights: 507 initial value 124.120462 iter 10 value 94.494081 iter 20 value 94.119441 iter 30 value 91.749900 iter 40 value 86.132735 iter 50 value 86.041487 iter 60 value 85.775048 iter 70 value 85.755042 iter 80 value 85.398861 iter 90 value 84.510328 iter 100 value 84.491097 final value 84.491097 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 130.231369 iter 10 value 94.314165 iter 20 value 94.278857 iter 30 value 94.198188 iter 40 value 90.059190 iter 50 value 84.836783 iter 60 value 84.227440 iter 70 value 84.210261 iter 80 value 84.209621 final value 84.209243 converged Fitting Repeat 5 # weights: 507 initial value 95.077309 iter 10 value 90.798572 iter 20 value 87.218360 iter 30 value 86.743603 iter 40 value 85.459043 iter 50 value 85.368289 final value 85.367200 converged Fitting Repeat 1 # weights: 103 initial value 94.374125 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 95.589252 iter 10 value 86.392952 iter 20 value 85.478130 final value 85.101326 converged Fitting Repeat 3 # weights: 103 initial value 94.512357 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 96.162946 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 94.772770 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 106.392494 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 96.776733 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 94.403633 iter 10 value 92.891056 iter 20 value 89.866315 iter 30 value 89.584012 iter 40 value 89.581403 final value 89.581291 converged Fitting Repeat 4 # weights: 305 initial value 109.453463 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 97.332836 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 97.862155 iter 10 value 93.747273 iter 20 value 93.691390 final value 93.691359 converged Fitting Repeat 2 # weights: 507 initial value 104.975739 final value 94.038251 converged Fitting Repeat 3 # weights: 507 initial value 106.941349 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 95.519214 iter 10 value 93.692087 final value 93.679487 converged Fitting Repeat 5 # weights: 507 initial value 105.135031 final value 94.052909 converged Fitting Repeat 1 # weights: 103 initial value 103.652848 iter 10 value 94.002671 iter 20 value 87.410703 iter 30 value 87.217226 iter 40 value 86.595209 iter 50 value 85.771289 iter 60 value 85.228633 iter 70 value 85.124313 iter 80 value 85.045135 final value 85.044589 converged Fitting Repeat 2 # weights: 103 initial value 99.874652 iter 10 value 94.030715 iter 20 value 89.888063 iter 30 value 88.574820 iter 40 value 86.993531 iter 50 value 85.132422 iter 60 value 84.257205 iter 70 value 84.120177 iter 80 value 84.101630 iter 90 value 83.715832 iter 100 value 83.419800 final value 83.419800 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 101.050195 iter 10 value 94.032196 iter 20 value 92.018866 iter 30 value 86.709163 iter 40 value 85.563059 iter 50 value 84.934884 iter 60 value 84.748175 final value 84.737736 converged Fitting Repeat 4 # weights: 103 initial value 104.909134 iter 10 value 94.059533 iter 20 value 89.097677 iter 30 value 86.714386 iter 40 value 86.234202 iter 50 value 86.120835 iter 60 value 85.901158 iter 70 value 85.806541 iter 80 value 85.790802 iter 80 value 85.790801 iter 80 value 85.790801 final value 85.790801 converged Fitting Repeat 5 # weights: 103 initial value 99.382485 iter 10 value 94.057927 iter 20 value 93.948645 iter 30 value 93.823814 iter 40 value 93.722380 iter 50 value 88.621955 iter 60 value 86.506562 iter 70 value 85.278823 iter 80 value 84.826527 iter 90 value 84.564777 iter 100 value 83.570038 final value 83.570038 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 105.770297 iter 10 value 94.028872 iter 20 value 88.572906 iter 30 value 86.647756 iter 40 value 86.455593 iter 50 value 85.410272 iter 60 value 84.747054 iter 70 value 83.307083 iter 80 value 82.093993 iter 90 value 81.709604 iter 100 value 81.161061 final value 81.161061 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 103.071756 iter 10 value 94.217161 iter 20 value 93.043552 iter 30 value 87.494770 iter 40 value 84.073460 iter 50 value 82.293565 iter 60 value 81.913312 iter 70 value 81.755515 iter 80 value 81.620482 iter 90 value 81.573398 iter 100 value 81.560694 final value 81.560694 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 108.414560 iter 10 value 94.084683 iter 20 value 92.987030 iter 30 value 88.094152 iter 40 value 87.175692 iter 50 value 86.244029 iter 60 value 86.033267 iter 70 value 84.903210 iter 80 value 84.209693 iter 90 value 83.070624 iter 100 value 82.237247 final value 82.237247 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.773563 iter 10 value 94.035151 iter 20 value 92.386399 iter 30 value 87.225001 iter 40 value 86.823864 iter 50 value 85.780836 iter 60 value 82.871866 iter 70 value 82.481202 iter 80 value 82.241574 iter 90 value 81.794771 iter 100 value 81.256484 final value 81.256484 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 103.456599 iter 10 value 93.994564 iter 20 value 88.008275 iter 30 value 87.177603 iter 40 value 86.448327 iter 50 value 86.176209 iter 60 value 85.825300 iter 70 value 85.626021 iter 80 value 85.285363 iter 90 value 84.324778 iter 100 value 82.767466 final value 82.767466 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 102.912770 iter 10 value 94.003879 iter 20 value 92.504186 iter 30 value 89.004730 iter 40 value 86.312410 iter 50 value 85.361847 iter 60 value 84.631213 iter 70 value 83.397192 iter 80 value 82.861087 iter 90 value 82.729343 iter 100 value 82.128432 final value 82.128432 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 112.904050 iter 10 value 94.068190 iter 20 value 91.700073 iter 30 value 85.094933 iter 40 value 83.653229 iter 50 value 82.995458 iter 60 value 82.183193 iter 70 value 82.035108 iter 80 value 81.948518 iter 90 value 81.706640 iter 100 value 81.597994 final value 81.597994 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 121.334799 iter 10 value 94.009321 iter 20 value 91.513677 iter 30 value 90.072464 iter 40 value 86.806289 iter 50 value 86.738116 iter 60 value 86.047296 iter 70 value 85.635537 iter 80 value 84.597940 iter 90 value 83.878020 iter 100 value 83.498410 final value 83.498410 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 105.797457 iter 10 value 94.247333 iter 20 value 89.782725 iter 30 value 87.673741 iter 40 value 86.854094 iter 50 value 85.230046 iter 60 value 84.050834 iter 70 value 82.828933 iter 80 value 81.734456 iter 90 value 81.434343 iter 100 value 81.131925 final value 81.131925 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 105.800863 iter 10 value 94.074373 iter 20 value 89.827068 iter 30 value 87.590394 iter 40 value 86.743272 iter 50 value 85.754682 iter 60 value 84.660438 iter 70 value 83.603236 iter 80 value 82.920065 iter 90 value 82.535332 iter 100 value 81.565913 final value 81.565913 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.329285 iter 10 value 94.054562 iter 20 value 94.052966 iter 30 value 92.518121 iter 40 value 88.998306 iter 50 value 88.910880 iter 60 value 88.908390 iter 70 value 88.904873 iter 80 value 85.070958 iter 90 value 84.936570 iter 100 value 84.930208 final value 84.930208 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 95.800545 final value 94.054395 converged Fitting Repeat 3 # weights: 103 initial value 95.693690 final value 94.039988 converged Fitting Repeat 4 # weights: 103 initial value 97.401742 final value 94.054488 converged Fitting Repeat 5 # weights: 103 initial value 95.294972 iter 10 value 94.054664 iter 20 value 94.048905 iter 30 value 88.549920 iter 40 value 88.517637 iter 50 value 88.485411 final value 88.485249 converged Fitting Repeat 1 # weights: 305 initial value 94.937560 iter 10 value 94.043499 iter 20 value 94.038402 iter 30 value 93.824816 iter 40 value 88.540655 iter 50 value 88.422719 iter 60 value 88.374420 iter 70 value 87.594825 final value 87.594779 converged Fitting Repeat 2 # weights: 305 initial value 94.271028 iter 10 value 93.702599 iter 20 value 92.563624 iter 30 value 92.526822 iter 40 value 92.116417 iter 50 value 92.100207 iter 60 value 91.881114 iter 70 value 91.860692 final value 91.854974 converged Fitting Repeat 3 # weights: 305 initial value 101.890765 iter 10 value 93.966799 iter 20 value 93.916308 iter 30 value 93.911935 final value 93.911919 converged Fitting Repeat 4 # weights: 305 initial value 99.281386 iter 10 value 94.057811 iter 20 value 91.552720 iter 30 value 86.379634 iter 40 value 85.664348 iter 50 value 84.892851 iter 60 value 83.301635 iter 70 value 81.003202 iter 80 value 80.605722 iter 90 value 80.427155 iter 100 value 80.260878 final value 80.260878 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 124.618256 iter 10 value 94.058596 iter 20 value 94.052724 iter 30 value 93.635324 iter 40 value 87.288996 iter 50 value 86.490585 iter 60 value 86.042658 iter 70 value 85.999881 iter 80 value 85.998413 iter 90 value 85.998174 iter 100 value 85.998109 final value 85.998109 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 103.397483 iter 10 value 94.046529 iter 20 value 94.039242 iter 30 value 89.766378 iter 40 value 86.288762 iter 50 value 85.371975 iter 60 value 85.363400 iter 70 value 84.949348 iter 80 value 84.946490 final value 84.939857 converged Fitting Repeat 2 # weights: 507 initial value 96.763384 iter 10 value 94.046121 iter 20 value 94.038615 iter 30 value 93.377321 iter 40 value 91.285211 iter 50 value 91.206840 iter 60 value 91.205183 iter 70 value 90.476441 iter 80 value 90.458222 iter 90 value 90.072984 final value 90.062397 converged Fitting Repeat 3 # weights: 507 initial value 93.117936 iter 10 value 88.606342 iter 20 value 87.988805 iter 30 value 87.837502 iter 40 value 87.836347 iter 50 value 87.803433 iter 60 value 87.798007 iter 60 value 87.798007 final value 87.798007 converged Fitting Repeat 4 # weights: 507 initial value 103.124797 iter 10 value 94.060468 iter 20 value 94.052070 iter 30 value 87.397718 iter 40 value 83.999036 iter 50 value 82.353409 iter 60 value 80.047385 iter 70 value 80.037837 final value 80.037704 converged Fitting Repeat 5 # weights: 507 initial value 104.073983 iter 10 value 94.046642 iter 20 value 94.027817 iter 30 value 93.810427 final value 93.810424 converged Fitting Repeat 1 # weights: 103 initial value 124.760464 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 102.713036 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 100.845041 final value 92.211113 converged Fitting Repeat 4 # weights: 103 initial value 100.311464 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 113.793450 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 96.095392 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 115.908939 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 94.519263 final value 93.915746 converged Fitting Repeat 4 # weights: 305 initial value 97.027370 final value 93.915746 converged Fitting Repeat 5 # weights: 305 initial value 113.869459 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 108.505195 final value 93.915746 converged Fitting Repeat 2 # weights: 507 initial value 117.418487 iter 10 value 92.191089 final value 92.116925 converged Fitting Repeat 3 # weights: 507 initial value 95.471588 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 122.102468 iter 10 value 93.288889 iter 10 value 93.288889 iter 10 value 93.288889 final value 93.288889 converged Fitting Repeat 5 # weights: 507 initial value 96.423219 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 107.051902 iter 10 value 94.055138 iter 20 value 93.809998 iter 30 value 93.456360 iter 40 value 93.448658 iter 50 value 93.445785 iter 60 value 92.585801 iter 70 value 87.506931 iter 80 value 86.803527 iter 90 value 82.613117 iter 100 value 80.435025 final value 80.435025 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 95.909694 iter 10 value 94.055905 iter 20 value 93.848929 iter 30 value 93.471562 iter 40 value 93.441798 iter 50 value 86.592429 iter 60 value 86.199541 iter 70 value 84.759699 iter 80 value 83.138803 iter 90 value 83.122367 final value 83.122310 converged Fitting Repeat 3 # weights: 103 initial value 102.887790 iter 10 value 94.121429 iter 20 value 94.046368 iter 30 value 93.605523 iter 40 value 88.794592 iter 50 value 81.577643 iter 60 value 81.398146 iter 70 value 81.368395 iter 80 value 79.705974 iter 90 value 79.211675 iter 100 value 79.090929 final value 79.090929 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 105.359802 iter 10 value 93.806722 iter 20 value 86.388294 iter 30 value 81.251961 iter 40 value 80.209723 iter 50 value 79.520087 iter 60 value 79.373062 iter 70 value 79.175914 iter 80 value 79.097115 final value 79.096282 converged Fitting Repeat 5 # weights: 103 initial value 97.456410 iter 10 value 93.276785 iter 20 value 85.020120 iter 30 value 84.140942 iter 40 value 83.316697 iter 50 value 83.159059 iter 60 value 83.128559 final value 83.128265 converged Fitting Repeat 1 # weights: 305 initial value 101.272110 iter 10 value 93.758596 iter 20 value 86.923477 iter 30 value 85.694090 iter 40 value 84.042983 iter 50 value 81.995188 iter 60 value 80.666618 iter 70 value 79.718017 iter 80 value 79.440269 iter 90 value 79.367654 iter 100 value 79.351139 final value 79.351139 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.817375 iter 10 value 91.431994 iter 20 value 86.967895 iter 30 value 86.078262 iter 40 value 85.878676 iter 50 value 85.278079 iter 60 value 84.690820 iter 70 value 83.723433 iter 80 value 81.479336 iter 90 value 80.671762 iter 100 value 80.612673 final value 80.612673 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 107.522314 iter 10 value 94.040303 iter 20 value 93.802919 iter 30 value 93.505133 iter 40 value 92.573055 iter 50 value 85.919465 iter 60 value 80.782937 iter 70 value 79.545717 iter 80 value 78.909154 iter 90 value 78.580836 iter 100 value 78.521667 final value 78.521667 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 113.260068 iter 10 value 93.913354 iter 20 value 89.907459 iter 30 value 87.573515 iter 40 value 85.915389 iter 50 value 84.289092 iter 60 value 82.928195 iter 70 value 81.597865 iter 80 value 80.463766 iter 90 value 78.350577 iter 100 value 77.864182 final value 77.864182 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 118.129225 iter 10 value 94.178896 iter 20 value 91.959161 iter 30 value 84.210497 iter 40 value 83.424573 iter 50 value 82.893850 iter 60 value 82.584007 iter 70 value 82.488701 iter 80 value 82.375717 iter 90 value 82.358747 iter 100 value 82.347657 final value 82.347657 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 106.143283 iter 10 value 94.074816 iter 20 value 90.813715 iter 30 value 85.005204 iter 40 value 82.376748 iter 50 value 80.238135 iter 60 value 78.407344 iter 70 value 77.741223 iter 80 value 77.495898 iter 90 value 77.356611 iter 100 value 77.149245 final value 77.149245 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 102.187143 iter 10 value 86.850028 iter 20 value 84.574043 iter 30 value 83.584498 iter 40 value 81.379633 iter 50 value 79.243860 iter 60 value 78.352932 iter 70 value 77.898390 iter 80 value 77.788704 iter 90 value 77.524304 iter 100 value 77.365045 final value 77.365045 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.851459 iter 10 value 94.204454 iter 20 value 87.673704 iter 30 value 84.837650 iter 40 value 82.826901 iter 50 value 81.783908 iter 60 value 80.697044 iter 70 value 79.916411 iter 80 value 79.831849 iter 90 value 79.650564 iter 100 value 79.434171 final value 79.434171 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 105.619070 iter 10 value 94.923319 iter 20 value 91.337436 iter 30 value 85.841735 iter 40 value 82.111319 iter 50 value 79.682435 iter 60 value 78.750319 iter 70 value 78.427403 iter 80 value 77.657733 iter 90 value 77.499550 iter 100 value 77.449434 final value 77.449434 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 118.545026 iter 10 value 93.586334 iter 20 value 83.318980 iter 30 value 81.113504 iter 40 value 79.943676 iter 50 value 78.660413 iter 60 value 78.445901 iter 70 value 78.292435 iter 80 value 78.181520 iter 90 value 78.048591 iter 100 value 77.963828 final value 77.963828 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 110.411439 iter 10 value 93.917759 iter 20 value 93.916056 iter 30 value 84.257641 iter 40 value 82.783510 iter 50 value 82.740344 iter 60 value 82.677922 iter 70 value 82.676874 iter 80 value 82.389712 final value 82.382518 converged Fitting Repeat 2 # weights: 103 initial value 100.858670 final value 94.054320 converged Fitting Repeat 3 # weights: 103 initial value 101.669643 final value 94.054557 converged Fitting Repeat 4 # weights: 103 initial value 96.524974 final value 93.456737 converged Fitting Repeat 5 # weights: 103 initial value 99.194173 final value 94.054598 converged Fitting Repeat 1 # weights: 305 initial value 109.889218 iter 10 value 94.057833 iter 20 value 94.040655 iter 30 value 93.455137 iter 40 value 93.439734 final value 93.438810 converged Fitting Repeat 2 # weights: 305 initial value 94.287163 iter 10 value 93.833539 iter 20 value 83.318773 iter 30 value 81.954465 iter 40 value 81.684524 iter 50 value 81.464448 iter 60 value 81.437742 iter 70 value 81.094029 iter 80 value 80.213212 iter 90 value 80.156872 iter 100 value 80.150992 final value 80.150992 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 96.724163 iter 10 value 93.920431 iter 20 value 93.800840 iter 30 value 88.374510 iter 40 value 84.143303 iter 50 value 84.124272 final value 84.124148 converged Fitting Repeat 4 # weights: 305 initial value 97.590638 iter 10 value 94.057618 iter 20 value 93.845038 iter 30 value 93.439288 iter 40 value 93.373962 iter 50 value 93.373767 iter 50 value 93.373766 iter 50 value 93.373766 final value 93.373766 converged Fitting Repeat 5 # weights: 305 initial value 101.084958 iter 10 value 81.425569 iter 20 value 80.708469 iter 30 value 80.705785 iter 40 value 80.616966 iter 50 value 80.614929 iter 60 value 80.421281 iter 70 value 80.419565 iter 80 value 80.418713 iter 90 value 80.413380 iter 100 value 80.383722 final value 80.383722 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 106.590050 iter 10 value 93.923394 iter 20 value 93.918097 iter 30 value 93.916833 iter 40 value 89.069968 iter 50 value 84.357921 iter 60 value 84.245527 iter 70 value 84.229380 iter 80 value 84.226870 final value 84.226847 converged Fitting Repeat 2 # weights: 507 initial value 108.345920 iter 10 value 93.894237 iter 20 value 93.873996 iter 30 value 93.420044 iter 40 value 88.289624 iter 50 value 84.129283 iter 60 value 84.126040 iter 70 value 84.125235 iter 80 value 83.943618 iter 90 value 83.460612 iter 100 value 83.449279 final value 83.449279 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 108.234456 iter 10 value 93.297205 iter 20 value 93.296256 iter 30 value 90.582209 iter 40 value 82.462641 iter 50 value 82.279914 iter 60 value 82.254087 iter 70 value 82.253986 final value 82.253433 converged Fitting Repeat 4 # weights: 507 initial value 96.630661 iter 10 value 93.469170 iter 20 value 93.399260 iter 30 value 93.396811 iter 40 value 90.727926 iter 50 value 85.388090 iter 60 value 85.387893 iter 70 value 85.277421 iter 80 value 85.276835 iter 90 value 85.274550 iter 100 value 85.119941 final value 85.119941 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 129.561255 iter 10 value 94.061205 iter 20 value 94.054285 iter 30 value 92.259749 iter 40 value 92.011844 iter 50 value 90.956659 final value 90.955249 converged Fitting Repeat 1 # weights: 103 initial value 98.401187 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 102.353880 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 103.157994 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 100.725251 iter 10 value 94.461207 iter 10 value 94.461207 iter 10 value 94.461207 final value 94.461207 converged Fitting Repeat 5 # weights: 103 initial value 100.119397 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 97.742304 final value 93.772973 converged Fitting Repeat 2 # weights: 305 initial value 96.959279 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 105.979490 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 96.353445 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 97.073215 iter 10 value 94.484794 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 102.363582 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 103.623486 iter 10 value 93.564151 final value 93.540410 converged Fitting Repeat 3 # weights: 507 initial value 92.636686 iter 10 value 86.909008 iter 20 value 86.766317 iter 30 value 86.765971 iter 40 value 86.765835 iter 40 value 86.765835 iter 40 value 86.765835 final value 86.765835 converged Fitting Repeat 4 # weights: 507 initial value 100.752755 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 107.735823 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 105.133608 iter 10 value 94.339222 iter 20 value 87.014810 iter 30 value 84.839796 iter 40 value 84.527044 iter 50 value 84.170007 iter 60 value 83.851022 iter 70 value 83.822356 final value 83.822251 converged Fitting Repeat 2 # weights: 103 initial value 97.302282 iter 10 value 94.537741 iter 20 value 94.487875 iter 30 value 94.383674 iter 40 value 93.960313 iter 50 value 93.901291 iter 60 value 93.815691 iter 70 value 88.736383 iter 80 value 82.715915 iter 90 value 82.010898 iter 100 value 81.699175 final value 81.699175 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 96.634761 iter 10 value 94.489995 iter 20 value 94.356771 iter 30 value 93.858801 iter 40 value 93.840625 iter 50 value 93.729198 iter 60 value 90.409276 iter 70 value 87.457901 iter 80 value 83.447256 iter 90 value 82.354185 iter 100 value 80.944360 final value 80.944360 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 98.080689 iter 10 value 94.500372 iter 20 value 92.665162 iter 30 value 84.609066 iter 40 value 83.956571 iter 50 value 83.870758 iter 60 value 82.965040 iter 70 value 82.608107 iter 80 value 82.261978 iter 90 value 81.600286 iter 100 value 81.147153 final value 81.147153 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 103.059900 iter 10 value 94.472954 iter 20 value 92.667416 iter 30 value 87.913633 iter 40 value 83.275165 iter 50 value 82.823037 iter 60 value 82.604366 iter 70 value 81.771137 iter 80 value 81.764290 final value 81.764288 converged Fitting Repeat 1 # weights: 305 initial value 102.156075 iter 10 value 93.701426 iter 20 value 86.069510 iter 30 value 84.312628 iter 40 value 81.452257 iter 50 value 80.599822 iter 60 value 79.878990 iter 70 value 79.715466 iter 80 value 79.648728 iter 90 value 79.639298 iter 100 value 79.633609 final value 79.633609 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 104.428329 iter 10 value 94.236398 iter 20 value 93.675761 iter 30 value 88.686020 iter 40 value 84.920035 iter 50 value 83.859820 iter 60 value 83.547614 iter 70 value 83.390015 iter 80 value 83.057639 iter 90 value 81.556758 iter 100 value 79.986560 final value 79.986560 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 104.850214 iter 10 value 94.392944 iter 20 value 89.428603 iter 30 value 84.382604 iter 40 value 83.451595 iter 50 value 83.220966 iter 60 value 82.583241 iter 70 value 81.997692 iter 80 value 81.721784 iter 90 value 80.062440 iter 100 value 79.716360 final value 79.716360 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 107.283669 iter 10 value 94.361155 iter 20 value 93.775035 iter 30 value 90.124072 iter 40 value 84.663567 iter 50 value 83.978539 iter 60 value 81.159935 iter 70 value 79.738898 iter 80 value 79.222868 iter 90 value 79.119448 iter 100 value 79.054601 final value 79.054601 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 104.383114 iter 10 value 95.718121 iter 20 value 93.287400 iter 30 value 86.248450 iter 40 value 83.809990 iter 50 value 82.977856 iter 60 value 82.120121 iter 70 value 81.229124 iter 80 value 80.611974 iter 90 value 80.203402 iter 100 value 79.979709 final value 79.979709 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 120.375140 iter 10 value 94.765717 iter 20 value 84.963422 iter 30 value 83.981076 iter 40 value 82.278999 iter 50 value 81.614775 iter 60 value 81.514563 iter 70 value 81.269226 iter 80 value 80.869121 iter 90 value 79.757682 iter 100 value 79.483187 final value 79.483187 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 114.796286 iter 10 value 87.658863 iter 20 value 85.401673 iter 30 value 84.604551 iter 40 value 81.554776 iter 50 value 80.741177 iter 60 value 79.997328 iter 70 value 79.877511 iter 80 value 79.577355 iter 90 value 79.430239 iter 100 value 79.140918 final value 79.140918 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 104.260200 iter 10 value 96.946835 iter 20 value 94.413147 iter 30 value 92.462854 iter 40 value 91.215593 iter 50 value 83.975062 iter 60 value 83.309086 iter 70 value 82.143690 iter 80 value 80.731207 iter 90 value 80.361634 iter 100 value 80.152153 final value 80.152153 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.725277 iter 10 value 94.036906 iter 20 value 93.942124 iter 30 value 87.377901 iter 40 value 83.732351 iter 50 value 82.708322 iter 60 value 81.238062 iter 70 value 80.841504 iter 80 value 80.284552 iter 90 value 80.267257 iter 100 value 80.189421 final value 80.189421 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 112.108547 iter 10 value 94.586698 iter 20 value 94.079947 iter 30 value 88.656389 iter 40 value 87.004813 iter 50 value 83.735848 iter 60 value 81.638293 iter 70 value 81.048530 iter 80 value 79.782936 iter 90 value 79.026733 iter 100 value 78.843752 final value 78.843752 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.167712 iter 10 value 94.485679 iter 20 value 94.484225 iter 20 value 94.484225 iter 20 value 94.484225 final value 94.484225 converged Fitting Repeat 2 # weights: 103 initial value 99.169687 iter 10 value 93.378684 iter 20 value 93.377341 final value 93.376562 converged Fitting Repeat 3 # weights: 103 initial value 104.834328 final value 94.485799 converged Fitting Repeat 4 # weights: 103 initial value 96.971324 final value 94.485782 converged Fitting Repeat 5 # weights: 103 initial value 101.250763 final value 94.485849 converged Fitting Repeat 1 # weights: 305 initial value 105.017391 iter 10 value 93.778244 iter 20 value 93.688040 iter 30 value 92.852302 iter 40 value 86.479715 iter 50 value 81.114236 iter 60 value 79.353548 iter 70 value 78.618911 iter 80 value 78.614483 iter 90 value 78.337442 iter 100 value 78.155847 final value 78.155847 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 106.043896 iter 10 value 93.778451 iter 20 value 93.776845 iter 30 value 93.441964 iter 40 value 84.568527 iter 50 value 81.684519 iter 60 value 81.374631 final value 81.268535 converged Fitting Repeat 3 # weights: 305 initial value 108.735916 iter 10 value 94.493883 iter 20 value 94.488688 final value 94.488600 converged Fitting Repeat 4 # weights: 305 initial value 100.762450 iter 10 value 94.489090 iter 20 value 94.315418 final value 93.773342 converged Fitting Repeat 5 # weights: 305 initial value 117.000040 iter 10 value 89.552579 iter 20 value 86.101338 iter 30 value 86.094537 final value 86.093863 converged Fitting Repeat 1 # weights: 507 initial value 100.125923 iter 10 value 86.312167 iter 20 value 85.902933 iter 30 value 85.428665 iter 40 value 85.426869 iter 50 value 84.999141 iter 60 value 81.054211 iter 70 value 80.320572 iter 80 value 79.885294 iter 90 value 79.882204 final value 79.881721 converged Fitting Repeat 2 # weights: 507 initial value 95.450328 iter 10 value 88.031679 iter 20 value 86.171129 iter 30 value 83.874029 iter 40 value 82.859022 iter 50 value 82.350523 iter 60 value 81.960258 final value 81.959945 converged Fitting Repeat 3 # weights: 507 initial value 111.641876 iter 10 value 94.492521 iter 20 value 94.366306 iter 30 value 85.260363 iter 40 value 81.980565 iter 50 value 81.965186 iter 60 value 81.964398 iter 70 value 81.963622 iter 80 value 81.611818 iter 90 value 80.763458 iter 100 value 79.335149 final value 79.335149 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 103.037601 iter 10 value 94.492783 iter 20 value 94.484111 iter 30 value 87.728291 iter 40 value 83.029965 iter 50 value 80.255594 iter 60 value 79.922943 iter 70 value 79.895700 iter 80 value 79.289805 iter 90 value 78.992722 final value 78.992550 converged Fitting Repeat 5 # weights: 507 initial value 103.124242 iter 10 value 94.365879 iter 20 value 85.774335 iter 30 value 85.718407 iter 40 value 85.642892 iter 50 value 85.572168 final value 85.572087 converged Fitting Repeat 1 # weights: 103 initial value 95.586351 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 107.042586 iter 10 value 92.607050 iter 20 value 92.552247 final value 92.552060 converged Fitting Repeat 3 # weights: 103 initial value 95.677024 final value 94.466823 converged Fitting Repeat 4 # weights: 103 initial value 101.581076 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 107.443663 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 98.486752 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 126.799729 iter 10 value 94.466827 final value 94.466823 converged Fitting Repeat 3 # weights: 305 initial value 96.308352 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 115.333627 final value 94.466823 converged Fitting Repeat 5 # weights: 305 initial value 130.742839 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 96.124173 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 94.873930 iter 10 value 89.211498 iter 20 value 84.546811 iter 30 value 81.722051 iter 40 value 81.495596 iter 50 value 81.472521 final value 81.472496 converged Fitting Repeat 3 # weights: 507 initial value 108.238864 iter 10 value 93.800609 iter 20 value 92.763538 final value 92.763204 converged Fitting Repeat 4 # weights: 507 initial value 107.902294 final value 94.466823 converged Fitting Repeat 5 # weights: 507 initial value 107.229837 iter 10 value 93.997320 iter 20 value 93.946921 final value 93.946831 converged Fitting Repeat 1 # weights: 103 initial value 104.048586 iter 10 value 91.572206 iter 20 value 85.801895 iter 30 value 84.368181 iter 40 value 84.089492 iter 50 value 83.906636 iter 60 value 83.570096 iter 70 value 82.108389 iter 80 value 81.835767 iter 90 value 81.832031 final value 81.832029 converged Fitting Repeat 2 # weights: 103 initial value 100.131279 iter 10 value 95.318897 iter 20 value 94.494952 iter 30 value 93.549906 iter 40 value 85.434368 iter 50 value 85.340432 iter 60 value 84.478414 iter 70 value 84.066648 iter 80 value 83.951355 iter 90 value 83.927742 iter 100 value 83.801196 final value 83.801196 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 97.208042 iter 10 value 94.491155 iter 20 value 91.960376 iter 30 value 91.771460 iter 40 value 91.699808 final value 91.698937 converged Fitting Repeat 4 # weights: 103 initial value 105.809417 iter 10 value 94.397866 iter 20 value 86.312137 iter 30 value 84.443260 iter 40 value 84.221870 iter 50 value 83.887272 iter 60 value 83.792686 final value 83.792570 converged Fitting Repeat 5 # weights: 103 initial value 103.591611 iter 10 value 94.515083 iter 20 value 93.505525 iter 30 value 93.440975 iter 40 value 93.371152 iter 50 value 88.154109 iter 60 value 85.155728 iter 70 value 84.338245 iter 80 value 84.195723 iter 90 value 84.112529 iter 100 value 83.854131 final value 83.854131 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 108.326091 iter 10 value 94.457459 iter 20 value 87.106073 iter 30 value 85.824987 iter 40 value 85.180509 iter 50 value 82.268400 iter 60 value 81.153467 iter 70 value 81.073120 iter 80 value 80.968246 iter 90 value 80.762529 iter 100 value 80.591945 final value 80.591945 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.332797 iter 10 value 94.580496 iter 20 value 94.405756 iter 30 value 87.067948 iter 40 value 86.408210 iter 50 value 85.955236 iter 60 value 85.474489 iter 70 value 82.434125 iter 80 value 81.653902 iter 90 value 81.206799 iter 100 value 81.135300 final value 81.135300 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 130.045034 iter 10 value 93.883207 iter 20 value 86.114503 iter 30 value 85.297367 iter 40 value 84.130523 iter 50 value 82.568532 iter 60 value 82.262995 iter 70 value 82.089982 iter 80 value 81.840175 iter 90 value 81.080730 iter 100 value 80.790015 final value 80.790015 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 126.208534 iter 10 value 94.415015 iter 20 value 90.429792 iter 30 value 82.949002 iter 40 value 82.212538 iter 50 value 81.598431 iter 60 value 81.231571 iter 70 value 81.081433 iter 80 value 81.049876 iter 90 value 80.976720 iter 100 value 80.434042 final value 80.434042 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 106.149855 iter 10 value 94.518021 iter 20 value 94.479941 iter 30 value 88.670038 iter 40 value 87.530025 iter 50 value 85.260268 iter 60 value 84.627938 iter 70 value 83.196120 iter 80 value 82.965783 iter 90 value 82.788877 iter 100 value 82.400669 final value 82.400669 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 104.881216 iter 10 value 89.378909 iter 20 value 86.652089 iter 30 value 85.150297 iter 40 value 84.998641 iter 50 value 84.893233 iter 60 value 84.857358 iter 70 value 84.835075 iter 80 value 84.432262 iter 90 value 83.836908 iter 100 value 83.505390 final value 83.505390 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 115.442978 iter 10 value 95.051846 iter 20 value 94.534399 iter 30 value 92.897035 iter 40 value 88.614485 iter 50 value 84.999907 iter 60 value 82.331519 iter 70 value 81.622947 iter 80 value 81.222680 iter 90 value 80.909884 iter 100 value 80.435143 final value 80.435143 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.493048 iter 10 value 91.643393 iter 20 value 89.076912 iter 30 value 85.799306 iter 40 value 84.478836 iter 50 value 82.703335 iter 60 value 81.956412 iter 70 value 80.749846 iter 80 value 80.404578 iter 90 value 80.029718 iter 100 value 79.984553 final value 79.984553 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 118.391105 iter 10 value 94.439826 iter 20 value 89.062277 iter 30 value 87.747771 iter 40 value 86.903218 iter 50 value 84.605793 iter 60 value 83.425369 iter 70 value 81.263134 iter 80 value 81.041183 iter 90 value 80.522015 iter 100 value 80.312421 final value 80.312421 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 108.764892 iter 10 value 94.755884 iter 20 value 93.100772 iter 30 value 85.326428 iter 40 value 84.020342 iter 50 value 83.920954 iter 60 value 81.965938 iter 70 value 81.857970 iter 80 value 81.543680 iter 90 value 81.025962 iter 100 value 80.167648 final value 80.167648 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 98.808401 final value 94.485643 converged Fitting Repeat 2 # weights: 103 initial value 110.328201 final value 94.485942 converged Fitting Repeat 3 # weights: 103 initial value 96.902811 final value 94.485959 converged Fitting Repeat 4 # weights: 103 initial value 95.055553 iter 10 value 93.890667 iter 20 value 93.294104 iter 30 value 93.292098 iter 40 value 93.291278 final value 93.290012 converged Fitting Repeat 5 # weights: 103 initial value 100.684015 final value 94.485621 converged Fitting Repeat 1 # weights: 305 initial value 101.001101 iter 10 value 94.489158 iter 20 value 94.376668 iter 30 value 93.487191 iter 40 value 93.413505 iter 50 value 93.211233 iter 60 value 93.209922 final value 93.209877 converged Fitting Repeat 2 # weights: 305 initial value 104.915713 iter 10 value 94.434557 iter 20 value 94.433431 iter 30 value 94.307747 iter 40 value 92.321670 iter 50 value 91.865200 iter 60 value 91.863812 iter 70 value 91.862215 iter 80 value 88.884996 iter 90 value 82.320062 iter 100 value 82.132210 final value 82.132210 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 105.024963 iter 10 value 94.489052 iter 20 value 94.466502 iter 30 value 92.692701 iter 40 value 92.514070 final value 92.514003 converged Fitting Repeat 4 # weights: 305 initial value 104.411910 iter 10 value 94.488673 iter 20 value 94.422889 iter 30 value 86.942250 iter 40 value 85.954931 iter 40 value 85.954930 iter 40 value 85.954930 final value 85.954930 converged Fitting Repeat 5 # weights: 305 initial value 106.152196 iter 10 value 94.471807 iter 20 value 92.627059 iter 30 value 84.667622 iter 40 value 84.232420 final value 84.232419 converged Fitting Repeat 1 # weights: 507 initial value 118.827949 iter 10 value 94.474479 iter 20 value 93.719764 iter 30 value 87.165363 iter 40 value 85.376137 iter 50 value 84.966090 iter 60 value 84.964304 iter 70 value 84.520445 final value 84.520380 converged Fitting Repeat 2 # weights: 507 initial value 119.640621 iter 10 value 94.492584 iter 20 value 94.485007 iter 30 value 92.628026 iter 40 value 88.776948 iter 50 value 88.772292 iter 60 value 88.380087 iter 70 value 85.239366 iter 80 value 81.743694 iter 90 value 81.432893 iter 100 value 81.427860 final value 81.427860 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 113.257916 iter 10 value 94.474875 iter 20 value 94.318480 iter 30 value 86.115374 iter 40 value 84.719851 iter 50 value 82.792062 iter 60 value 82.781484 iter 70 value 82.780914 iter 80 value 82.561772 final value 82.561631 converged Fitting Repeat 4 # weights: 507 initial value 96.291187 iter 10 value 89.019998 iter 20 value 84.895291 iter 30 value 84.801767 iter 40 value 84.721889 iter 50 value 84.692889 iter 60 value 84.178278 iter 70 value 84.146777 iter 80 value 84.146432 iter 90 value 83.404412 iter 100 value 82.955257 final value 82.955257 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 114.849527 iter 10 value 94.562244 iter 20 value 93.460577 iter 30 value 93.370997 iter 40 value 93.330223 iter 50 value 93.309682 iter 60 value 93.303989 iter 70 value 93.295293 iter 80 value 85.248132 iter 90 value 84.975683 iter 100 value 84.912675 final value 84.912675 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 120.276297 iter 10 value 117.508864 iter 20 value 117.506058 iter 30 value 105.882141 iter 40 value 103.456367 iter 50 value 103.393249 iter 60 value 103.280159 iter 70 value 103.238221 iter 80 value 103.237957 iter 90 value 103.237226 final value 103.237216 converged Fitting Repeat 2 # weights: 507 initial value 172.035354 iter 10 value 117.766774 iter 20 value 117.623226 iter 30 value 117.512122 final value 117.511945 converged Fitting Repeat 3 # weights: 507 initial value 129.725083 iter 10 value 117.767042 iter 20 value 117.103679 iter 30 value 110.985989 final value 110.921347 converged Fitting Repeat 4 # weights: 507 initial value 125.350904 iter 10 value 117.897956 iter 20 value 117.808463 iter 30 value 117.060925 iter 40 value 113.720457 iter 50 value 113.717967 iter 60 value 113.558990 iter 70 value 113.398674 final value 113.351984 converged Fitting Repeat 5 # weights: 507 initial value 126.449186 iter 10 value 117.796576 iter 20 value 117.135259 iter 30 value 116.957223 iter 40 value 109.701025 iter 50 value 105.820182 iter 60 value 105.545931 iter 70 value 105.448865 final value 105.447091 converged svmRadial ranger Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases RUNIT TEST PROTOCOL -- Mon Apr 15 23:55:02 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 40.929 1.832 44.141
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 34.518 | 0.776 | 35.296 | |
FreqInteractors | 0.220 | 0.012 | 0.232 | |
calculateAAC | 0.033 | 0.008 | 0.040 | |
calculateAutocor | 0.310 | 0.016 | 0.326 | |
calculateCTDC | 0.072 | 0.000 | 0.072 | |
calculateCTDD | 0.566 | 0.000 | 0.565 | |
calculateCTDT | 0.240 | 0.008 | 0.248 | |
calculateCTriad | 0.337 | 0.024 | 0.361 | |
calculateDC | 0.083 | 0.003 | 0.087 | |
calculateF | 0.290 | 0.004 | 0.294 | |
calculateKSAAP | 0.089 | 0.004 | 0.093 | |
calculateQD_Sm | 1.629 | 0.032 | 1.669 | |
calculateTC | 1.449 | 0.060 | 1.509 | |
calculateTC_Sm | 0.281 | 0.008 | 0.289 | |
corr_plot | 34.397 | 0.488 | 34.885 | |
enrichfindP | 0.469 | 0.048 | 9.622 | |
enrichfind_hp | 0.091 | 0.020 | 1.211 | |
enrichplot | 0.325 | 0.027 | 0.353 | |
filter_missing_values | 0.001 | 0.000 | 0.001 | |
getFASTA | 0.527 | 0.025 | 4.353 | |
getHPI | 0.001 | 0.000 | 0.000 | |
get_negativePPI | 0.001 | 0.000 | 0.001 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0.002 | 0.000 | 0.001 | |
plotPPI | 0.068 | 0.003 | 0.072 | |
pred_ensembel | 13.456 | 0.560 | 10.701 | |
var_imp | 35.452 | 0.972 | 36.425 | |