Back to Multiple platform build/check report for BioC 3.19: simplified long |
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This page was generated on 2024-05-09 11:40:57 -0400 (Thu, 09 May 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4748 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" | 4484 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4514 |
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4480 |
Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X |
Package 987/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.10.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | |||||||||
palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | |||||||||
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
kjohnson3 | macOS 13.6.5 Ventura / arm64 | see weekly results here | ||||||||||||
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
Package: HPiP |
Version: 1.10.0 |
Command: /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R-beta-2024-04-15_r86425/site-library --no-vignettes --timings HPiP_1.10.0.tar.gz |
StartedAt: 2024-05-09 08:24:46 -0000 (Thu, 09 May 2024) |
EndedAt: 2024-05-09 08:30:54 -0000 (Thu, 09 May 2024) |
EllapsedTime: 367.7 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R-beta-2024-04-15_r86425/site-library --no-vignettes --timings HPiP_1.10.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’ * using R version 4.4.0 beta (2024-04-15 r86425) * using platform: aarch64-unknown-linux-gnu * R was compiled by gcc (GCC) 10.3.1 GNU Fortran (GCC) 10.3.1 * running under: openEuler 22.03 (LTS-SP1) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘HPiP/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘HPiP’ version ‘1.10.0’ * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘HPiP’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... NOTE License stub is invalid DCF. * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking loading without being on the library search path ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... NOTE checkRd: (-1) getHPI.Rd:29: Lost braces 29 | then the Kronecker product is the code{(pm × qn)} block matrix | ^ * checking Rd metadata ... OK * checking Rd cross-references ... NOTE Package unavailable to check Rd xrefs: ‘ftrCOOL’ * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking contents of ‘data’ directory ... OK * checking data for non-ASCII characters ... OK * checking data for ASCII and uncompressed saves ... OK * checking R/sysdata.rda ... OK * checking files in ‘vignettes’ ... OK * checking examples ... OK Examples with CPU (user + system) or elapsed time > 5s user system elapsed var_imp 40.361 0.766 41.207 FSmethod 38.130 0.615 38.827 corr_plot 38.266 0.412 38.758 pred_ensembel 18.673 0.301 16.620 enrichfindP 0.524 0.028 29.054 getFASTA 0.086 0.008 14.316 * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘runTests.R’ OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking running R code from vignettes ... SKIPPED * checking re-building of vignette outputs ... SKIPPED * checking PDF version of manual ... OK * DONE Status: 3 NOTEs See ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’ for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/R/R-beta-2024-04-15_r86425/site-library’ * installing *source* package ‘HPiP’ ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: aarch64-unknown-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > BiocGenerics:::testPackage('HPiP') No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE avNNet Loading required package: ggplot2 Loading required package: lattice Fitting Repeat 1 # weights: 103 initial value 110.004492 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 93.230158 iter 10 value 85.267561 iter 20 value 84.363772 final value 84.363399 converged Fitting Repeat 3 # weights: 103 initial value 94.652439 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 106.094979 final value 94.291892 converged Fitting Repeat 5 # weights: 103 initial value 95.367261 iter 10 value 94.481316 iter 20 value 93.615420 final value 93.611986 converged Fitting Repeat 1 # weights: 305 initial value 107.144715 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 96.209408 final value 94.291892 converged Fitting Repeat 3 # weights: 305 initial value 110.221583 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 105.010319 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 108.848635 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 100.885163 iter 10 value 94.242106 iter 10 value 94.242106 iter 10 value 94.242106 final value 94.242106 converged Fitting Repeat 2 # weights: 507 initial value 97.803639 final value 94.291892 converged Fitting Repeat 3 # weights: 507 initial value 102.787424 iter 10 value 94.040795 iter 20 value 92.272566 iter 30 value 92.007859 iter 40 value 91.973777 iter 50 value 91.893993 final value 91.893524 converged Fitting Repeat 4 # weights: 507 initial value 95.985574 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 95.565360 iter 10 value 88.502314 iter 20 value 87.976148 final value 87.953872 converged Fitting Repeat 1 # weights: 103 initial value 104.134947 iter 10 value 94.488600 iter 20 value 93.162095 iter 30 value 87.395700 iter 40 value 86.163243 iter 50 value 85.300751 iter 60 value 84.916582 iter 70 value 84.825157 final value 84.820871 converged Fitting Repeat 2 # weights: 103 initial value 107.192908 iter 10 value 94.392319 iter 20 value 91.940246 iter 30 value 87.174402 iter 40 value 86.198715 iter 50 value 85.314028 iter 60 value 84.457302 iter 70 value 83.776839 iter 80 value 83.404098 iter 90 value 83.336738 final value 83.330640 converged Fitting Repeat 3 # weights: 103 initial value 98.104058 iter 10 value 94.500957 iter 20 value 94.479703 iter 30 value 92.985424 iter 40 value 88.101567 iter 50 value 86.595665 iter 60 value 85.851576 iter 70 value 85.514956 iter 80 value 85.504950 final value 85.504943 converged Fitting Repeat 4 # weights: 103 initial value 108.110017 iter 10 value 94.294015 iter 20 value 92.342824 iter 30 value 91.769179 iter 40 value 90.662221 iter 50 value 86.570593 iter 60 value 84.962741 iter 70 value 84.299555 iter 80 value 83.525574 iter 90 value 83.331836 final value 83.330640 converged Fitting Repeat 5 # weights: 103 initial value 105.815374 iter 10 value 94.520903 iter 20 value 94.428218 iter 30 value 90.425952 iter 40 value 87.781357 iter 50 value 86.782903 iter 60 value 86.384987 iter 70 value 86.045191 iter 80 value 85.906243 iter 90 value 85.787966 final value 85.786923 converged Fitting Repeat 1 # weights: 305 initial value 104.454405 iter 10 value 94.251899 iter 20 value 92.728483 iter 30 value 89.286694 iter 40 value 87.016481 iter 50 value 86.347281 iter 60 value 84.562129 iter 70 value 83.113568 iter 80 value 82.811643 iter 90 value 82.717598 iter 100 value 82.676937 final value 82.676937 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 107.316736 iter 10 value 94.488933 iter 20 value 92.626389 iter 30 value 88.116720 iter 40 value 87.288607 iter 50 value 86.016222 iter 60 value 84.698517 iter 70 value 83.799976 iter 80 value 83.671456 iter 90 value 83.485467 iter 100 value 83.100768 final value 83.100768 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 104.066508 iter 10 value 94.382988 iter 20 value 89.966002 iter 30 value 86.728095 iter 40 value 84.097881 iter 50 value 83.333168 iter 60 value 82.760768 iter 70 value 82.494263 iter 80 value 82.319268 iter 90 value 82.243140 iter 100 value 82.207250 final value 82.207250 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 105.671609 iter 10 value 94.499007 iter 20 value 92.583854 iter 30 value 89.915147 iter 40 value 86.352614 iter 50 value 85.336207 iter 60 value 84.965660 iter 70 value 84.796621 iter 80 value 84.372257 iter 90 value 84.247847 iter 100 value 84.198944 final value 84.198944 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 99.754843 iter 10 value 94.529697 iter 20 value 94.242506 iter 30 value 92.601951 iter 40 value 89.684350 iter 50 value 89.109227 iter 60 value 88.846927 iter 70 value 86.609173 iter 80 value 84.427912 iter 90 value 83.974413 iter 100 value 83.547753 final value 83.547753 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 130.694844 iter 10 value 94.383941 iter 20 value 86.955185 iter 30 value 86.026440 iter 40 value 84.240996 iter 50 value 83.775804 iter 60 value 83.206455 iter 70 value 82.761820 iter 80 value 82.701016 iter 90 value 82.497797 iter 100 value 82.307955 final value 82.307955 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 125.347449 iter 10 value 94.586076 iter 20 value 91.859936 iter 30 value 87.879340 iter 40 value 86.664478 iter 50 value 85.437582 iter 60 value 85.151282 iter 70 value 85.078635 iter 80 value 84.937257 iter 90 value 84.930486 iter 100 value 84.834822 final value 84.834822 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 115.195421 iter 10 value 94.444192 iter 20 value 90.497496 iter 30 value 86.391504 iter 40 value 85.575148 iter 50 value 84.525940 iter 60 value 83.927714 iter 70 value 83.142132 iter 80 value 83.088630 iter 90 value 82.942428 iter 100 value 82.552405 final value 82.552405 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 109.937548 iter 10 value 94.529570 iter 20 value 94.334571 iter 30 value 90.008842 iter 40 value 85.860412 iter 50 value 83.403823 iter 60 value 82.920270 iter 70 value 82.509484 iter 80 value 82.166939 iter 90 value 81.952343 iter 100 value 81.858886 final value 81.858886 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 114.965572 iter 10 value 94.724860 iter 20 value 87.837644 iter 30 value 86.849862 iter 40 value 84.155487 iter 50 value 83.565602 iter 60 value 82.564387 iter 70 value 82.278767 iter 80 value 82.192892 iter 90 value 82.129336 iter 100 value 82.079220 final value 82.079220 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.956180 final value 94.485814 converged Fitting Repeat 2 # weights: 103 initial value 96.280582 iter 10 value 88.209405 iter 20 value 87.255006 final value 87.254852 converged Fitting Repeat 3 # weights: 103 initial value 98.661296 iter 10 value 94.485980 iter 20 value 94.483558 iter 30 value 88.680227 iter 40 value 88.448707 iter 50 value 85.939615 iter 60 value 85.745622 iter 70 value 85.627821 iter 80 value 85.622050 iter 90 value 85.360463 iter 90 value 85.360462 final value 85.360457 converged Fitting Repeat 4 # weights: 103 initial value 97.040100 final value 94.485716 converged Fitting Repeat 5 # weights: 103 initial value 106.890811 final value 94.485956 converged Fitting Repeat 1 # weights: 305 initial value 96.306405 iter 10 value 94.488596 iter 20 value 94.477471 final value 94.292044 converged Fitting Repeat 2 # weights: 305 initial value 103.132445 iter 10 value 94.530798 iter 20 value 94.497115 iter 30 value 88.432287 iter 40 value 86.293170 iter 50 value 86.257097 iter 60 value 86.237326 iter 70 value 85.349983 iter 80 value 85.051427 iter 90 value 85.046984 iter 100 value 85.046453 final value 85.046453 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 108.353963 iter 10 value 94.489243 iter 20 value 94.418134 iter 30 value 86.141383 iter 40 value 85.419803 iter 50 value 85.034331 final value 84.999365 converged Fitting Repeat 4 # weights: 305 initial value 103.765210 iter 10 value 94.467032 iter 20 value 87.263470 iter 30 value 87.167332 iter 40 value 87.069443 iter 50 value 86.617213 iter 60 value 86.602011 iter 70 value 86.601956 iter 80 value 86.601719 iter 90 value 86.601542 iter 90 value 86.601542 iter 90 value 86.601542 final value 86.601542 converged Fitting Repeat 5 # weights: 305 initial value 104.041223 iter 10 value 94.491699 iter 20 value 88.966752 iter 30 value 85.806967 iter 40 value 85.703158 iter 50 value 85.696108 iter 60 value 84.669025 iter 70 value 84.409039 iter 80 value 84.383057 iter 90 value 84.381927 iter 100 value 84.377107 final value 84.377107 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 94.174313 iter 10 value 93.932068 iter 20 value 93.873672 iter 30 value 93.872267 iter 40 value 93.728269 iter 50 value 92.178615 iter 60 value 92.000480 iter 70 value 91.322520 iter 80 value 91.260992 final value 91.260771 converged Fitting Repeat 2 # weights: 507 initial value 111.369684 iter 10 value 94.437362 iter 20 value 94.429902 iter 30 value 93.793261 iter 40 value 91.764120 iter 50 value 91.520627 iter 60 value 91.389031 iter 70 value 87.810995 iter 80 value 87.723680 iter 90 value 87.706883 iter 100 value 86.117027 final value 86.117027 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 105.092772 iter 10 value 94.299874 iter 20 value 94.292836 iter 30 value 90.955603 iter 40 value 88.339076 final value 88.335946 converged Fitting Repeat 4 # weights: 507 initial value 110.088521 iter 10 value 94.493745 iter 20 value 94.485495 iter 30 value 93.886166 iter 40 value 92.828594 iter 50 value 92.798962 iter 60 value 92.798637 iter 70 value 92.798384 iter 80 value 92.798016 iter 90 value 92.618882 iter 100 value 92.548441 final value 92.548441 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 112.957617 iter 10 value 94.492325 iter 20 value 94.469622 iter 30 value 88.968816 iter 40 value 87.052842 iter 50 value 87.045575 iter 60 value 87.043384 final value 87.043357 converged Fitting Repeat 1 # weights: 103 initial value 98.970715 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 94.949767 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 114.953761 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 102.530433 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 99.097169 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 95.163418 iter 10 value 88.967868 iter 20 value 86.301393 iter 30 value 86.300497 final value 86.300463 converged Fitting Repeat 2 # weights: 305 initial value 118.580371 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 99.570693 iter 10 value 93.375684 iter 10 value 93.375684 iter 10 value 93.375684 final value 93.375684 converged Fitting Repeat 4 # weights: 305 initial value 130.535135 iter 10 value 94.423530 iter 10 value 94.423529 iter 10 value 94.423529 final value 94.423529 converged Fitting Repeat 5 # weights: 305 initial value 95.223054 iter 10 value 94.484219 final value 94.484212 converged Fitting Repeat 1 # weights: 507 initial value 114.462662 iter 10 value 87.174944 iter 20 value 84.639566 iter 30 value 84.019469 iter 40 value 83.992948 final value 83.992913 converged Fitting Repeat 2 # weights: 507 initial value 111.044084 iter 10 value 90.022914 iter 20 value 89.908125 iter 30 value 89.008173 iter 40 value 89.005861 final value 89.005856 converged Fitting Repeat 3 # weights: 507 initial value 109.873961 iter 10 value 92.331692 iter 20 value 89.116424 iter 30 value 88.894611 iter 40 value 88.893651 final value 88.893647 converged Fitting Repeat 4 # weights: 507 initial value 95.320139 iter 10 value 93.373169 final value 93.372595 converged Fitting Repeat 5 # weights: 507 initial value 94.539356 iter 10 value 89.988282 final value 89.988263 converged Fitting Repeat 1 # weights: 103 initial value 102.442379 iter 10 value 94.453477 iter 20 value 83.644059 iter 30 value 83.175950 iter 40 value 82.890118 iter 50 value 82.675011 iter 60 value 80.587831 iter 70 value 80.307392 iter 80 value 80.279656 final value 80.270362 converged Fitting Repeat 2 # weights: 103 initial value 96.868830 iter 10 value 94.488041 iter 20 value 90.872072 iter 30 value 89.283351 iter 40 value 87.238974 iter 50 value 84.865275 iter 60 value 82.298974 iter 70 value 81.948436 iter 80 value 81.649001 iter 90 value 81.638476 iter 90 value 81.638476 iter 90 value 81.638476 final value 81.638476 converged Fitting Repeat 3 # weights: 103 initial value 101.542372 iter 10 value 94.486642 iter 20 value 87.133566 iter 30 value 85.744209 iter 40 value 84.638973 iter 50 value 82.203519 iter 60 value 80.128899 iter 70 value 78.720883 iter 80 value 78.708040 iter 90 value 78.704822 iter 100 value 78.704755 final value 78.704755 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 108.523862 iter 10 value 94.491331 iter 20 value 90.037004 iter 30 value 85.339216 iter 40 value 85.047096 iter 50 value 82.605109 iter 60 value 81.628554 iter 70 value 81.493237 final value 81.492237 converged Fitting Repeat 5 # weights: 103 initial value 106.854359 iter 10 value 94.209692 iter 20 value 86.210608 iter 30 value 83.287971 iter 40 value 82.835353 iter 50 value 82.206302 iter 60 value 81.727497 iter 70 value 81.638476 iter 70 value 81.638476 iter 70 value 81.638476 final value 81.638476 converged Fitting Repeat 1 # weights: 305 initial value 127.025624 iter 10 value 94.498033 iter 20 value 86.232514 iter 30 value 85.802554 iter 40 value 84.052649 iter 50 value 82.338907 iter 60 value 79.729385 iter 70 value 79.385494 iter 80 value 78.526387 iter 90 value 77.447860 iter 100 value 77.308449 final value 77.308449 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 120.938988 iter 10 value 96.612580 iter 20 value 95.036932 iter 30 value 89.428992 iter 40 value 83.805582 iter 50 value 83.272225 iter 60 value 82.837363 iter 70 value 82.180142 iter 80 value 81.884306 iter 90 value 80.343786 iter 100 value 78.577566 final value 78.577566 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 118.698347 iter 10 value 94.575968 iter 20 value 92.061626 iter 30 value 90.381847 iter 40 value 90.199622 iter 50 value 81.261225 iter 60 value 80.140262 iter 70 value 80.098200 iter 80 value 79.073116 iter 90 value 78.669711 iter 100 value 77.665037 final value 77.665037 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 107.916524 iter 10 value 94.557091 iter 20 value 94.488199 iter 30 value 93.653080 iter 40 value 92.430722 iter 50 value 83.870053 iter 60 value 82.481612 iter 70 value 81.734495 iter 80 value 81.618860 iter 90 value 81.303905 iter 100 value 81.163950 final value 81.163950 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 113.257620 iter 10 value 93.973390 iter 20 value 90.692995 iter 30 value 85.787737 iter 40 value 83.288508 iter 50 value 80.175739 iter 60 value 78.213461 iter 70 value 77.958071 iter 80 value 77.782685 iter 90 value 77.623326 iter 100 value 77.382861 final value 77.382861 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 113.004021 iter 10 value 93.453591 iter 20 value 84.448339 iter 30 value 83.578219 iter 40 value 82.810779 iter 50 value 82.598784 iter 60 value 80.910279 iter 70 value 80.276028 iter 80 value 79.843784 iter 90 value 78.039114 iter 100 value 77.371272 final value 77.371272 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 107.264305 iter 10 value 94.404900 iter 20 value 93.771353 iter 30 value 87.827774 iter 40 value 85.974324 iter 50 value 85.563545 iter 60 value 84.444369 iter 70 value 82.465711 iter 80 value 82.039094 iter 90 value 80.013857 iter 100 value 78.536219 final value 78.536219 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 109.647695 iter 10 value 94.622743 iter 20 value 83.408596 iter 30 value 82.585394 iter 40 value 79.818791 iter 50 value 78.387323 iter 60 value 77.828191 iter 70 value 77.459903 iter 80 value 77.347710 iter 90 value 77.286349 iter 100 value 77.146885 final value 77.146885 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 109.412955 iter 10 value 94.477274 iter 20 value 94.200288 iter 30 value 93.442322 iter 40 value 88.873013 iter 50 value 84.099670 iter 60 value 80.466607 iter 70 value 79.996825 iter 80 value 78.843700 iter 90 value 77.898451 iter 100 value 77.583508 final value 77.583508 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 111.812027 iter 10 value 94.528081 iter 20 value 92.950492 iter 30 value 90.826646 iter 40 value 83.206581 iter 50 value 81.972885 iter 60 value 80.462242 iter 70 value 78.863350 iter 80 value 78.328075 iter 90 value 77.804950 iter 100 value 77.440107 final value 77.440107 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.745741 final value 94.485843 converged Fitting Repeat 2 # weights: 103 initial value 98.419833 final value 94.485503 converged Fitting Repeat 3 # weights: 103 initial value 103.529514 final value 94.485725 converged Fitting Repeat 4 # weights: 103 initial value 101.727478 final value 94.486045 converged Fitting Repeat 5 # weights: 103 initial value 106.922464 iter 10 value 94.485774 iter 20 value 93.947313 iter 30 value 93.406083 iter 40 value 93.365268 iter 50 value 93.365105 final value 93.365103 converged Fitting Repeat 1 # weights: 305 initial value 104.912305 iter 10 value 94.489123 iter 20 value 94.484236 iter 30 value 92.873869 iter 40 value 91.210523 iter 50 value 85.064900 iter 60 value 82.801315 iter 70 value 82.786190 iter 80 value 82.780495 iter 90 value 82.444431 iter 100 value 82.071758 final value 82.071758 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 114.742191 iter 10 value 94.489107 iter 20 value 94.325898 iter 30 value 91.507729 iter 40 value 79.976928 iter 50 value 79.592696 iter 60 value 79.464781 iter 70 value 78.938882 iter 80 value 78.521071 iter 90 value 77.940958 iter 100 value 77.867234 final value 77.867234 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 104.530923 iter 10 value 94.489006 iter 20 value 94.234383 iter 30 value 82.460359 iter 40 value 79.308355 iter 50 value 78.553784 iter 60 value 77.979917 iter 70 value 77.955711 final value 77.955679 converged Fitting Repeat 4 # weights: 305 initial value 100.878776 iter 10 value 94.471969 iter 20 value 94.131978 iter 30 value 83.737527 iter 40 value 81.455028 iter 50 value 81.428380 iter 60 value 81.423650 iter 60 value 81.423649 iter 60 value 81.423649 final value 81.423649 converged Fitting Repeat 5 # weights: 305 initial value 113.887167 iter 10 value 94.488862 iter 20 value 94.310769 iter 30 value 85.122655 final value 85.122653 converged Fitting Repeat 1 # weights: 507 initial value 97.848109 iter 10 value 93.463281 iter 20 value 93.206403 iter 30 value 93.204200 iter 40 value 93.200176 iter 50 value 93.199857 iter 60 value 93.199719 iter 70 value 93.081068 iter 80 value 81.673067 iter 90 value 80.720460 iter 100 value 80.719612 final value 80.719612 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 99.141444 iter 10 value 94.099017 iter 20 value 94.098021 iter 30 value 94.059632 iter 40 value 91.834926 iter 50 value 90.401675 iter 60 value 85.059180 iter 70 value 84.810668 iter 80 value 82.048487 iter 90 value 80.327629 iter 100 value 80.021279 final value 80.021279 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 109.186689 iter 10 value 94.492287 iter 20 value 94.269206 iter 30 value 91.963650 iter 40 value 91.962373 iter 50 value 90.429998 iter 60 value 90.420735 iter 70 value 90.416979 final value 90.415860 converged Fitting Repeat 4 # weights: 507 initial value 101.395429 iter 10 value 86.100519 iter 20 value 86.042801 iter 30 value 84.667970 iter 40 value 84.218422 iter 50 value 84.206806 iter 60 value 83.960574 iter 70 value 83.957758 iter 80 value 83.933116 iter 90 value 83.932443 iter 90 value 83.932442 final value 83.932442 converged Fitting Repeat 5 # weights: 507 initial value 104.574326 iter 10 value 85.754967 iter 20 value 85.658195 iter 30 value 85.655722 final value 85.652069 converged Fitting Repeat 1 # weights: 103 initial value 106.725732 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 96.915200 final value 93.869755 converged Fitting Repeat 3 # weights: 103 initial value 97.023499 final value 92.945355 converged Fitting Repeat 4 # weights: 103 initial value 105.647942 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 94.255329 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 96.895976 iter 10 value 93.531367 final value 93.531283 converged Fitting Repeat 2 # weights: 305 initial value 100.784566 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 98.521277 iter 10 value 92.945396 final value 92.945355 converged Fitting Repeat 4 # weights: 305 initial value 101.951721 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 111.111831 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 101.624669 iter 10 value 94.052954 final value 94.052911 converged Fitting Repeat 2 # weights: 507 initial value 124.942374 iter 10 value 92.945374 final value 92.945355 converged Fitting Repeat 3 # weights: 507 initial value 112.904494 iter 10 value 92.945355 iter 10 value 92.945355 iter 10 value 92.945355 final value 92.945355 converged Fitting Repeat 4 # weights: 507 initial value 103.298487 iter 10 value 94.099366 iter 20 value 93.592241 iter 30 value 91.253677 iter 40 value 91.252791 final value 91.252787 converged Fitting Repeat 5 # weights: 507 initial value 114.126737 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 95.919323 iter 10 value 93.930464 iter 20 value 88.797971 iter 30 value 86.915059 iter 40 value 86.433648 iter 50 value 84.686812 iter 60 value 83.985319 iter 70 value 83.801158 final value 83.801120 converged Fitting Repeat 2 # weights: 103 initial value 96.163115 iter 10 value 94.080807 iter 20 value 93.255918 iter 30 value 93.083313 iter 40 value 92.998152 iter 50 value 90.592739 iter 60 value 88.167597 iter 70 value 84.907880 iter 80 value 82.268105 iter 90 value 81.640310 iter 100 value 81.251025 final value 81.251025 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 99.250080 iter 10 value 93.231818 iter 20 value 91.002991 iter 30 value 85.671943 iter 40 value 84.529345 iter 50 value 84.124174 iter 60 value 83.791651 iter 70 value 83.527662 final value 83.519879 converged Fitting Repeat 4 # weights: 103 initial value 95.645745 iter 10 value 86.483869 iter 20 value 84.731883 iter 30 value 83.636132 iter 40 value 83.284692 final value 83.281501 converged Fitting Repeat 5 # weights: 103 initial value 96.839590 iter 10 value 94.056469 iter 20 value 84.057413 iter 30 value 82.992798 iter 40 value 82.465803 iter 50 value 81.496187 iter 60 value 80.929058 iter 70 value 80.588854 iter 80 value 80.295814 iter 90 value 80.286770 final value 80.275434 converged Fitting Repeat 1 # weights: 305 initial value 103.212462 iter 10 value 93.593621 iter 20 value 92.055829 iter 30 value 87.248424 iter 40 value 85.906882 iter 50 value 84.853737 iter 60 value 82.083704 iter 70 value 80.329658 iter 80 value 79.839523 iter 90 value 78.953793 iter 100 value 78.681670 final value 78.681670 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.628542 iter 10 value 94.446292 iter 20 value 85.838935 iter 30 value 85.361185 iter 40 value 84.922931 iter 50 value 84.858943 iter 60 value 84.809982 iter 70 value 84.157664 iter 80 value 83.277948 iter 90 value 81.339330 iter 100 value 80.416095 final value 80.416095 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 120.706983 iter 10 value 96.677816 iter 20 value 90.910802 iter 30 value 89.722312 iter 40 value 89.261163 iter 50 value 83.357441 iter 60 value 83.046370 iter 70 value 82.831366 iter 80 value 82.474592 iter 90 value 81.164919 iter 100 value 80.076332 final value 80.076332 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 99.867752 iter 10 value 94.138156 iter 20 value 90.426054 iter 30 value 85.637831 iter 40 value 84.990536 iter 50 value 83.141378 iter 60 value 80.733014 iter 70 value 80.343648 iter 80 value 80.226807 iter 90 value 79.602780 iter 100 value 79.375786 final value 79.375786 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 101.649812 iter 10 value 94.046213 iter 20 value 93.128421 iter 30 value 92.450778 iter 40 value 87.404552 iter 50 value 84.699186 iter 60 value 83.151142 iter 70 value 82.142139 iter 80 value 80.521839 iter 90 value 79.890013 iter 100 value 79.635173 final value 79.635173 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 114.317577 iter 10 value 93.539594 iter 20 value 91.258949 iter 30 value 87.132821 iter 40 value 84.501003 iter 50 value 82.072568 iter 60 value 81.550085 iter 70 value 81.280934 iter 80 value 80.740615 iter 90 value 80.512454 iter 100 value 80.404401 final value 80.404401 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 108.345395 iter 10 value 96.984432 iter 20 value 83.558172 iter 30 value 81.939222 iter 40 value 81.481147 iter 50 value 80.579188 iter 60 value 80.215400 iter 70 value 79.984530 iter 80 value 79.889766 iter 90 value 79.826868 iter 100 value 79.120120 final value 79.120120 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.267945 iter 10 value 94.354042 iter 20 value 93.833621 iter 30 value 87.945201 iter 40 value 84.785137 iter 50 value 84.012750 iter 60 value 83.796078 iter 70 value 83.158027 iter 80 value 82.112203 iter 90 value 80.151570 iter 100 value 78.913018 final value 78.913018 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.766811 iter 10 value 94.560716 iter 20 value 93.535903 iter 30 value 87.716472 iter 40 value 83.953709 iter 50 value 80.554298 iter 60 value 79.637870 iter 70 value 79.226529 iter 80 value 78.785727 iter 90 value 78.651505 iter 100 value 78.433978 final value 78.433978 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 109.677175 iter 10 value 94.714412 iter 20 value 85.429845 iter 30 value 84.327656 iter 40 value 83.681456 iter 50 value 83.180266 iter 60 value 82.957383 iter 70 value 82.196228 iter 80 value 80.992950 iter 90 value 80.791884 iter 100 value 80.032003 final value 80.032003 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 98.950078 iter 10 value 92.947643 iter 20 value 92.947284 final value 92.945830 converged Fitting Repeat 2 # weights: 103 initial value 94.952710 final value 93.947883 converged Fitting Repeat 3 # weights: 103 initial value 97.537256 iter 10 value 94.054633 final value 94.052923 converged Fitting Repeat 4 # weights: 103 initial value 98.985921 final value 94.054555 converged Fitting Repeat 5 # weights: 103 initial value 95.506738 final value 94.054655 converged Fitting Repeat 1 # weights: 305 initial value 115.503667 iter 10 value 92.951084 iter 20 value 92.949187 iter 30 value 92.779586 iter 40 value 89.841116 iter 50 value 82.351741 iter 60 value 81.943620 iter 70 value 80.845356 iter 80 value 80.470900 iter 90 value 80.277055 final value 80.276882 converged Fitting Repeat 2 # weights: 305 initial value 96.890361 iter 10 value 94.090534 iter 20 value 94.053978 iter 30 value 94.052930 final value 94.052913 converged Fitting Repeat 3 # weights: 305 initial value 108.781430 iter 10 value 94.063262 iter 20 value 94.058266 iter 30 value 92.960653 iter 40 value 92.843424 iter 50 value 92.596394 iter 60 value 92.584896 iter 70 value 92.573109 iter 80 value 83.049187 iter 90 value 81.478541 iter 100 value 81.227003 final value 81.227003 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 115.621190 iter 10 value 94.057434 iter 20 value 94.052939 iter 30 value 94.008187 iter 40 value 92.930230 iter 50 value 82.212892 iter 60 value 82.056336 iter 70 value 81.648439 iter 80 value 81.397324 final value 81.392364 converged Fitting Repeat 5 # weights: 305 initial value 100.538672 iter 10 value 92.950972 iter 20 value 92.948032 iter 30 value 92.946149 final value 92.946038 converged Fitting Repeat 1 # weights: 507 initial value 105.582286 iter 10 value 93.975772 iter 20 value 93.955022 iter 30 value 93.954789 iter 40 value 92.216746 iter 50 value 87.472224 iter 60 value 87.394094 iter 70 value 84.344018 iter 80 value 84.221160 iter 90 value 82.293008 iter 100 value 80.305670 final value 80.305670 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 101.978487 iter 10 value 92.773673 iter 20 value 92.589734 iter 30 value 92.584481 iter 40 value 87.476439 iter 50 value 86.527446 iter 60 value 86.304661 iter 70 value 86.298462 final value 86.298460 converged Fitting Repeat 3 # weights: 507 initial value 98.832899 iter 10 value 92.959463 iter 20 value 92.841438 iter 30 value 92.830109 iter 40 value 92.825340 iter 50 value 92.824271 iter 60 value 92.761274 iter 70 value 82.014244 iter 80 value 81.174666 final value 81.173740 converged Fitting Repeat 4 # weights: 507 initial value 102.160374 iter 10 value 92.941830 iter 20 value 92.864704 final value 92.823093 converged Fitting Repeat 5 # weights: 507 initial value 109.559433 iter 10 value 94.061547 iter 20 value 94.053628 iter 30 value 93.679589 iter 40 value 92.121104 iter 50 value 85.496624 iter 60 value 85.476820 iter 70 value 83.969397 iter 80 value 83.763724 iter 90 value 83.666798 iter 100 value 83.664440 final value 83.664440 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 100.608051 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 95.900129 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 101.035324 final value 93.288889 converged Fitting Repeat 4 # weights: 103 initial value 99.790552 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 99.654579 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 99.385327 final value 93.836066 converged Fitting Repeat 2 # weights: 305 initial value 105.313162 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 100.871532 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 104.885572 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 98.804215 final value 93.836066 converged Fitting Repeat 1 # weights: 507 initial value 102.433179 final value 94.052910 converged Fitting Repeat 2 # weights: 507 initial value 99.162861 final value 93.836066 converged Fitting Repeat 3 # weights: 507 initial value 117.954509 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 118.554617 iter 10 value 94.052910 iter 10 value 94.052910 iter 10 value 94.052910 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 102.599737 iter 10 value 88.933811 iter 20 value 84.458720 iter 30 value 83.505099 iter 40 value 83.334915 iter 50 value 83.334634 final value 83.334625 converged Fitting Repeat 1 # weights: 103 initial value 108.866998 iter 10 value 94.019349 iter 20 value 93.729400 iter 30 value 89.969779 iter 40 value 89.415629 iter 50 value 87.016035 iter 60 value 86.093189 iter 70 value 85.769819 iter 80 value 83.482744 iter 90 value 82.918590 iter 100 value 82.856273 final value 82.856273 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 102.283845 iter 10 value 92.416857 iter 20 value 87.742824 iter 30 value 85.888570 iter 40 value 85.539601 iter 50 value 85.448984 iter 60 value 85.221402 iter 70 value 85.075164 iter 80 value 85.025748 final value 85.025735 converged Fitting Repeat 3 # weights: 103 initial value 100.534334 iter 10 value 94.056057 iter 20 value 94.034053 iter 30 value 94.002179 iter 40 value 93.784719 iter 50 value 87.468225 iter 60 value 87.072173 iter 70 value 86.962835 iter 80 value 84.012236 iter 90 value 82.723450 iter 100 value 82.604890 final value 82.604890 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 103.534018 iter 10 value 94.057351 iter 20 value 93.549390 iter 30 value 88.404529 iter 40 value 87.203406 iter 50 value 85.891105 iter 60 value 85.415967 iter 70 value 85.246130 iter 80 value 85.201417 iter 90 value 85.051906 final value 85.025735 converged Fitting Repeat 5 # weights: 103 initial value 98.917055 iter 10 value 91.812964 iter 20 value 87.477593 iter 30 value 86.717761 iter 40 value 85.158903 iter 50 value 85.009427 iter 60 value 85.008867 final value 85.008729 converged Fitting Repeat 1 # weights: 305 initial value 112.477816 iter 10 value 93.910613 iter 20 value 89.099912 iter 30 value 87.693522 iter 40 value 85.716127 iter 50 value 84.335906 iter 60 value 83.906395 iter 70 value 83.602217 iter 80 value 83.024235 iter 90 value 82.501714 iter 100 value 81.827997 final value 81.827997 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.992827 iter 10 value 94.045945 iter 20 value 89.131500 iter 30 value 85.844973 iter 40 value 85.264263 iter 50 value 85.216810 iter 60 value 85.175519 iter 70 value 84.809782 iter 80 value 84.252807 iter 90 value 84.062581 iter 100 value 83.277894 final value 83.277894 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 106.351343 iter 10 value 94.220714 iter 20 value 92.729625 iter 30 value 88.208802 iter 40 value 85.846047 iter 50 value 85.613370 iter 60 value 83.909944 iter 70 value 82.650414 iter 80 value 82.255606 iter 90 value 82.162137 iter 100 value 82.055491 final value 82.055491 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 104.726345 iter 10 value 93.877453 iter 20 value 93.240068 iter 30 value 87.331067 iter 40 value 85.472355 iter 50 value 85.326398 iter 60 value 84.438911 iter 70 value 83.340659 iter 80 value 83.141935 iter 90 value 82.727502 iter 100 value 82.229872 final value 82.229872 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 117.223923 iter 10 value 94.025902 iter 20 value 93.751464 iter 30 value 90.359810 iter 40 value 87.612806 iter 50 value 86.510070 iter 60 value 84.673251 iter 70 value 84.196233 iter 80 value 83.548875 iter 90 value 82.210898 iter 100 value 81.413576 final value 81.413576 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 135.599174 iter 10 value 96.785451 iter 20 value 94.273222 iter 30 value 93.379679 iter 40 value 88.129990 iter 50 value 87.703632 iter 60 value 87.271093 iter 70 value 85.863508 iter 80 value 83.677023 iter 90 value 83.156918 iter 100 value 82.636463 final value 82.636463 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 106.262955 iter 10 value 92.645344 iter 20 value 87.714509 iter 30 value 85.948454 iter 40 value 84.257396 iter 50 value 82.727870 iter 60 value 82.139227 iter 70 value 81.903895 iter 80 value 81.740561 iter 90 value 81.624288 iter 100 value 81.578283 final value 81.578283 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.478082 iter 10 value 94.223173 iter 20 value 93.800637 iter 30 value 88.732531 iter 40 value 86.691085 iter 50 value 86.363879 iter 60 value 85.153859 iter 70 value 83.897413 iter 80 value 83.417890 iter 90 value 83.278603 iter 100 value 83.243832 final value 83.243832 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 110.217406 iter 10 value 93.971304 iter 20 value 93.647225 iter 30 value 89.312849 iter 40 value 85.943612 iter 50 value 85.427074 iter 60 value 83.718111 iter 70 value 82.809555 iter 80 value 82.354053 iter 90 value 82.165165 iter 100 value 82.003880 final value 82.003880 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 108.567703 iter 10 value 93.982449 iter 20 value 93.086036 iter 30 value 86.876679 iter 40 value 84.348822 iter 50 value 82.555520 iter 60 value 81.671710 iter 70 value 81.266818 iter 80 value 81.146557 iter 90 value 81.120424 iter 100 value 81.080994 final value 81.080994 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 94.766855 iter 10 value 94.054447 iter 20 value 94.052921 final value 94.052912 converged Fitting Repeat 2 # weights: 103 initial value 99.811909 iter 10 value 94.054700 iter 20 value 94.039940 iter 30 value 93.605418 iter 40 value 93.604919 final value 93.604879 converged Fitting Repeat 3 # weights: 103 initial value 95.734243 final value 94.054957 converged Fitting Repeat 4 # weights: 103 initial value 97.845874 final value 94.054369 converged Fitting Repeat 5 # weights: 103 initial value 95.856020 final value 94.054538 converged Fitting Repeat 1 # weights: 305 initial value 95.732631 iter 10 value 93.294054 iter 20 value 93.292826 iter 30 value 88.293421 iter 40 value 86.424107 iter 50 value 86.409748 iter 60 value 86.399004 iter 70 value 86.398367 iter 80 value 86.397186 iter 80 value 86.397186 iter 80 value 86.397185 final value 86.397185 converged Fitting Repeat 2 # weights: 305 initial value 97.280089 iter 10 value 93.811904 iter 20 value 93.807830 iter 30 value 93.606271 final value 93.605756 converged Fitting Repeat 3 # weights: 305 initial value 98.464514 iter 10 value 93.809801 iter 20 value 93.805280 iter 30 value 86.818541 iter 40 value 86.176898 iter 50 value 85.990114 final value 85.990032 converged Fitting Repeat 4 # weights: 305 initial value 103.375371 iter 10 value 93.352251 iter 20 value 93.109234 iter 30 value 93.095959 iter 40 value 91.672391 iter 50 value 91.659736 iter 60 value 91.659051 iter 70 value 91.643066 iter 80 value 87.452124 iter 90 value 84.186399 iter 100 value 83.590026 final value 83.590026 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 102.032423 iter 10 value 94.057531 iter 20 value 94.050088 iter 30 value 91.950046 iter 40 value 86.641708 iter 50 value 86.597109 iter 60 value 86.482298 iter 70 value 85.735649 iter 80 value 85.735322 final value 85.735307 converged Fitting Repeat 1 # weights: 507 initial value 110.712456 iter 10 value 94.060501 iter 20 value 94.054145 iter 30 value 93.985852 iter 40 value 93.193583 iter 50 value 85.243856 iter 60 value 84.601621 final value 84.601533 converged Fitting Repeat 2 # weights: 507 initial value 99.149551 iter 10 value 94.061096 iter 20 value 93.986038 final value 93.836688 converged Fitting Repeat 3 # weights: 507 initial value 111.770880 iter 10 value 94.061066 iter 20 value 93.870367 iter 30 value 91.901538 iter 40 value 89.203903 iter 50 value 89.165315 iter 60 value 88.820238 iter 70 value 88.781328 iter 80 value 88.757111 iter 90 value 88.666969 iter 100 value 88.652871 final value 88.652871 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.642150 iter 10 value 93.844312 iter 20 value 93.836204 iter 30 value 87.170425 iter 40 value 86.009801 iter 50 value 85.868280 iter 60 value 85.865113 final value 85.865085 converged Fitting Repeat 5 # weights: 507 initial value 95.754059 iter 10 value 94.059667 iter 20 value 92.587009 iter 30 value 88.944493 iter 40 value 88.943310 final value 88.942504 converged Fitting Repeat 1 # weights: 103 initial value 102.309869 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 103.003139 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 115.137004 final value 94.354396 converged Fitting Repeat 4 # weights: 103 initial value 96.266734 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 95.316292 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 108.964749 iter 10 value 93.928539 iter 20 value 93.701839 final value 93.701658 converged Fitting Repeat 2 # weights: 305 initial value 95.273572 iter 10 value 93.942751 iter 20 value 93.942287 iter 20 value 93.942286 iter 20 value 93.942286 final value 93.942286 converged Fitting Repeat 3 # weights: 305 initial value 108.683220 final value 94.354396 converged Fitting Repeat 4 # weights: 305 initial value 96.144565 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 97.426087 iter 10 value 94.354396 iter 10 value 94.354396 iter 10 value 94.354396 final value 94.354396 converged Fitting Repeat 1 # weights: 507 initial value 96.599670 final value 94.484208 converged Fitting Repeat 2 # weights: 507 initial value 100.521203 iter 10 value 87.013000 iter 20 value 84.435619 iter 30 value 84.252095 iter 40 value 84.107129 final value 84.107012 converged Fitting Repeat 3 # weights: 507 initial value 105.789449 iter 10 value 94.334955 iter 20 value 93.352385 iter 30 value 93.315871 final value 93.315658 converged Fitting Repeat 4 # weights: 507 initial value 97.833606 iter 10 value 94.275432 final value 94.275362 converged Fitting Repeat 5 # weights: 507 initial value 103.364587 final value 93.701658 converged Fitting Repeat 1 # weights: 103 initial value 102.033403 iter 10 value 94.373644 iter 20 value 88.915173 iter 30 value 84.862054 iter 40 value 84.549170 iter 50 value 84.018772 iter 60 value 83.822379 iter 70 value 83.765549 final value 83.762623 converged Fitting Repeat 2 # weights: 103 initial value 102.517752 iter 10 value 94.427260 iter 20 value 87.763217 iter 30 value 86.426390 iter 40 value 84.749459 iter 50 value 84.211278 iter 60 value 84.073021 iter 70 value 84.026976 final value 84.026859 converged Fitting Repeat 3 # weights: 103 initial value 97.815412 iter 10 value 94.420721 iter 20 value 91.767786 iter 30 value 87.635060 iter 40 value 86.032867 iter 50 value 85.686930 iter 60 value 84.151904 iter 70 value 84.026936 final value 84.026859 converged Fitting Repeat 4 # weights: 103 initial value 96.011333 iter 10 value 94.239102 iter 20 value 86.700556 iter 30 value 84.982863 iter 40 value 84.803941 iter 50 value 84.028169 iter 60 value 83.971560 final value 83.971403 converged Fitting Repeat 5 # weights: 103 initial value 97.881887 iter 10 value 94.486700 iter 20 value 94.041127 iter 30 value 93.981068 iter 40 value 86.667603 iter 50 value 85.574870 iter 60 value 84.871602 iter 70 value 84.285222 iter 80 value 84.088450 iter 90 value 84.027122 final value 84.026859 converged Fitting Repeat 1 # weights: 305 initial value 105.167430 iter 10 value 94.457812 iter 20 value 91.845621 iter 30 value 88.030944 iter 40 value 87.718312 iter 50 value 87.142319 iter 60 value 86.377090 iter 70 value 84.680092 iter 80 value 83.869348 iter 90 value 82.848651 iter 100 value 80.960534 final value 80.960534 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.534846 iter 10 value 94.596384 iter 20 value 92.446693 iter 30 value 86.023651 iter 40 value 84.773957 iter 50 value 84.649166 iter 60 value 84.445108 iter 70 value 82.875665 iter 80 value 80.966530 iter 90 value 80.776424 iter 100 value 80.647293 final value 80.647293 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 102.862483 iter 10 value 93.992318 iter 20 value 86.372094 iter 30 value 83.265858 iter 40 value 82.365270 iter 50 value 82.209180 iter 60 value 81.289155 iter 70 value 80.558814 iter 80 value 80.403176 iter 90 value 80.398111 iter 100 value 80.396013 final value 80.396013 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 110.129348 iter 10 value 94.132542 iter 20 value 90.119215 iter 30 value 84.461541 iter 40 value 82.041849 iter 50 value 81.895321 iter 60 value 81.584594 iter 70 value 81.168077 iter 80 value 80.979479 iter 90 value 80.948154 iter 100 value 80.916962 final value 80.916962 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 104.669892 iter 10 value 94.527397 iter 20 value 94.488739 iter 30 value 94.428046 iter 40 value 93.513415 iter 50 value 88.608693 iter 60 value 85.699480 iter 70 value 85.294852 iter 80 value 85.065336 iter 90 value 83.250585 iter 100 value 82.335584 final value 82.335584 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 106.462072 iter 10 value 95.179234 iter 20 value 92.950767 iter 30 value 89.730149 iter 40 value 87.981693 iter 50 value 87.162592 iter 60 value 83.884893 iter 70 value 81.643074 iter 80 value 80.799623 iter 90 value 80.717196 iter 100 value 80.677904 final value 80.677904 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 104.657772 iter 10 value 94.380617 iter 20 value 85.746484 iter 30 value 85.147202 iter 40 value 84.270654 iter 50 value 83.991913 iter 60 value 82.233688 iter 70 value 81.127302 iter 80 value 80.839878 iter 90 value 80.704480 iter 100 value 80.525677 final value 80.525677 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.608371 iter 10 value 96.056689 iter 20 value 94.584565 iter 30 value 89.560861 iter 40 value 86.998262 iter 50 value 85.401723 iter 60 value 82.888837 iter 70 value 82.501221 iter 80 value 82.205185 iter 90 value 81.058901 iter 100 value 80.684547 final value 80.684547 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 109.348701 iter 10 value 94.612805 iter 20 value 93.972112 iter 30 value 88.268812 iter 40 value 87.915293 iter 50 value 87.569817 iter 60 value 86.821155 iter 70 value 83.730497 iter 80 value 82.409556 iter 90 value 81.837713 iter 100 value 80.943590 final value 80.943590 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 107.927294 iter 10 value 94.201365 iter 20 value 85.424157 iter 30 value 84.357696 iter 40 value 83.817433 iter 50 value 83.685815 iter 60 value 82.092654 iter 70 value 81.499446 iter 80 value 81.064832 iter 90 value 80.941015 iter 100 value 80.905614 final value 80.905614 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 94.770592 final value 94.485752 converged Fitting Repeat 2 # weights: 103 initial value 98.387056 final value 94.485753 converged Fitting Repeat 3 # weights: 103 initial value 95.993619 iter 10 value 94.485665 iter 20 value 94.385862 iter 30 value 85.653259 iter 40 value 85.650183 iter 50 value 84.766330 iter 60 value 84.765452 iter 70 value 84.764131 iter 80 value 84.764028 final value 84.763988 converged Fitting Repeat 4 # weights: 103 initial value 97.499859 final value 94.485786 converged Fitting Repeat 5 # weights: 103 initial value 104.233661 final value 94.485844 converged Fitting Repeat 1 # weights: 305 initial value 112.718890 iter 10 value 94.170475 iter 20 value 94.165837 iter 30 value 86.846704 iter 40 value 83.570820 iter 50 value 83.555736 iter 60 value 83.178534 iter 70 value 82.789091 iter 80 value 82.572025 iter 90 value 82.571926 final value 82.571914 converged Fitting Repeat 2 # weights: 305 initial value 101.109664 iter 10 value 94.488838 iter 20 value 94.061242 iter 30 value 85.019317 iter 40 value 84.876527 iter 50 value 84.762423 final value 84.483804 converged Fitting Repeat 3 # weights: 305 initial value 103.615422 iter 10 value 94.487127 final value 94.484228 converged Fitting Repeat 4 # weights: 305 initial value 98.622834 iter 10 value 94.317116 iter 20 value 93.840498 iter 30 value 87.199302 iter 40 value 86.522652 final value 86.522463 converged Fitting Repeat 5 # weights: 305 initial value 96.177336 iter 10 value 94.488390 iter 20 value 94.477174 iter 30 value 93.702373 final value 93.702372 converged Fitting Repeat 1 # weights: 507 initial value 101.723586 iter 10 value 94.173085 iter 20 value 93.960269 iter 30 value 87.817220 iter 40 value 87.263060 iter 50 value 87.258919 iter 60 value 85.910567 final value 85.899643 converged Fitting Repeat 2 # weights: 507 initial value 97.750267 iter 10 value 92.198021 iter 20 value 84.332560 iter 30 value 83.016912 iter 40 value 81.720491 iter 50 value 81.710960 iter 60 value 81.552774 iter 70 value 81.118836 iter 80 value 80.892456 iter 90 value 80.469554 iter 100 value 80.446991 final value 80.446991 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 98.092034 iter 10 value 94.362673 iter 20 value 93.966710 iter 30 value 93.933013 iter 40 value 93.932601 final value 93.932566 converged Fitting Repeat 4 # weights: 507 initial value 108.642475 iter 10 value 93.608719 iter 20 value 93.601675 iter 30 value 85.644008 iter 40 value 84.418604 iter 50 value 84.400987 iter 60 value 84.380196 iter 70 value 84.379801 iter 80 value 84.377255 iter 90 value 84.376904 iter 100 value 84.376494 final value 84.376494 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 99.575451 iter 10 value 94.491825 iter 20 value 93.956220 iter 30 value 89.788913 iter 40 value 89.774012 iter 50 value 89.735190 iter 60 value 84.004561 iter 70 value 83.216507 iter 80 value 82.610930 iter 90 value 82.333976 iter 100 value 82.262891 final value 82.262891 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 132.677321 iter 10 value 117.875795 iter 20 value 114.676234 iter 30 value 107.718955 iter 40 value 106.692748 iter 50 value 105.985042 iter 60 value 105.402592 iter 70 value 105.160153 iter 80 value 104.929391 iter 90 value 104.894820 iter 100 value 104.676891 final value 104.676891 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 125.829967 iter 10 value 117.255513 iter 20 value 107.761298 iter 30 value 106.728854 iter 40 value 106.109281 iter 50 value 103.409841 iter 60 value 102.982953 iter 70 value 102.450476 iter 80 value 102.087771 final value 102.065847 converged Fitting Repeat 3 # weights: 305 initial value 124.041053 iter 10 value 118.023193 iter 20 value 117.715963 iter 30 value 112.310562 iter 40 value 106.679761 iter 50 value 105.713337 iter 60 value 105.666590 iter 70 value 104.015303 iter 80 value 102.408974 iter 90 value 101.532952 iter 100 value 101.286806 final value 101.286806 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 123.902911 iter 10 value 117.746842 iter 20 value 112.954985 iter 30 value 110.306998 iter 40 value 109.751369 iter 50 value 109.645648 iter 60 value 107.978992 iter 70 value 104.876741 iter 80 value 102.921625 iter 90 value 102.154467 iter 100 value 102.095201 final value 102.095201 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 131.979456 iter 10 value 118.052676 iter 20 value 117.856275 iter 30 value 110.872009 iter 40 value 107.529867 iter 50 value 106.439816 iter 60 value 106.089912 iter 70 value 104.891490 iter 80 value 103.310151 iter 90 value 102.057725 iter 100 value 100.963289 final value 100.963289 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 -- Thu May 9 08:30:50 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 54.870 2.200 72.581
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 38.130 | 0.615 | 38.827 | |
FreqInteractors | 0.283 | 0.016 | 0.300 | |
calculateAAC | 0.043 | 0.004 | 0.047 | |
calculateAutocor | 0.716 | 0.020 | 0.739 | |
calculateCTDC | 0.095 | 0.000 | 0.095 | |
calculateCTDD | 0.769 | 0.000 | 0.770 | |
calculateCTDT | 0.278 | 0.000 | 0.278 | |
calculateCTriad | 0.459 | 0.020 | 0.483 | |
calculateDC | 0.133 | 0.000 | 0.132 | |
calculateF | 0.468 | 0.012 | 0.481 | |
calculateKSAAP | 0.135 | 0.012 | 0.148 | |
calculateQD_Sm | 2.492 | 0.031 | 2.530 | |
calculateTC | 2.502 | 0.012 | 2.520 | |
calculateTC_Sm | 0.399 | 0.000 | 0.400 | |
corr_plot | 38.266 | 0.412 | 38.758 | |
enrichfindP | 0.524 | 0.028 | 29.054 | |
enrichfind_hp | 0.085 | 0.000 | 1.456 | |
enrichplot | 0.470 | 0.000 | 0.471 | |
filter_missing_values | 0.001 | 0.000 | 0.001 | |
getFASTA | 0.086 | 0.008 | 14.316 | |
getHPI | 0.001 | 0.000 | 0.001 | |
get_negativePPI | 0.002 | 0.000 | 0.002 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0.001 | 0.000 | 0.002 | |
plotPPI | 0.083 | 0.000 | 0.084 | |
pred_ensembel | 18.673 | 0.301 | 16.620 | |
var_imp | 40.361 | 0.766 | 41.207 | |