Back to Multiple platform build/check report for BioC 3.20: simplified long |
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This page was generated on 2025-04-02 19:28 -0400 (Wed, 02 Apr 2025).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4764 |
palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.3 (2025-02-28 ucrt) -- "Trophy Case" | 4495 |
merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4522 |
kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4449 |
taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4426 |
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 979/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.12.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | ||||||||
merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | OK | OK | ![]() | ||||||||
taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: HPiP |
Version: 1.12.0 |
Command: /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings HPiP_1.12.0.tar.gz |
StartedAt: 2025-03-31 23:01:32 -0400 (Mon, 31 Mar 2025) |
EndedAt: 2025-03-31 23:16:55 -0400 (Mon, 31 Mar 2025) |
EllapsedTime: 923.0 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings HPiP_1.12.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’ * using R version 4.4.3 (2025-02-28) * using platform: x86_64-pc-linux-gnu * R was compiled by gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 * running under: Ubuntu 24.04.2 LTS * using session charset: UTF-8 * checking for file ‘HPiP/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘HPiP’ version ‘1.12.0’ * 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 34.375 0.578 34.955 corr_plot 33.388 0.299 33.743 FSmethod 33.020 0.365 33.387 pred_ensembel 13.168 0.146 11.954 enrichfindP 0.540 0.030 8.094 * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘runTests.R’ OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking re-building of vignette outputs ... OK * checking PDF version of manual ... OK * DONE Status: 3 NOTEs See ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log’ for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.20-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.4.3 (2025-02-28) -- "Trophy Case" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > BiocGenerics:::testPackage('HPiP') No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE avNNet Loading required package: ggplot2 Loading required package: lattice Fitting Repeat 1 # weights: 103 initial value 95.361750 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 96.449989 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 97.593969 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 97.728448 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 97.055267 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 95.697914 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 98.841025 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 96.622468 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 97.552752 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 98.740004 final value 94.052909 converged Fitting Repeat 1 # weights: 507 initial value 97.410348 final value 94.032967 converged Fitting Repeat 2 # weights: 507 initial value 97.915117 final value 94.032967 converged Fitting Repeat 3 # weights: 507 initial value 97.400740 iter 10 value 93.387472 iter 20 value 91.068002 iter 30 value 91.057682 iter 30 value 91.057682 iter 30 value 91.057682 final value 91.057682 converged Fitting Repeat 4 # weights: 507 initial value 103.398945 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 94.869078 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 99.042469 iter 10 value 93.876170 iter 20 value 88.844378 iter 30 value 86.273118 iter 40 value 85.956208 iter 50 value 85.584768 iter 60 value 85.339433 iter 70 value 85.324309 final value 85.324281 converged Fitting Repeat 2 # weights: 103 initial value 104.492024 iter 10 value 94.053363 iter 20 value 93.521993 iter 30 value 91.924769 iter 40 value 91.888531 iter 50 value 91.867262 iter 60 value 88.587704 iter 70 value 86.035978 iter 80 value 84.374286 iter 90 value 83.414839 iter 100 value 82.970645 final value 82.970645 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 96.044901 iter 10 value 93.774468 iter 20 value 87.024526 iter 30 value 86.678774 iter 40 value 86.073820 iter 50 value 85.336214 iter 60 value 85.286882 final value 85.286879 converged Fitting Repeat 4 # weights: 103 initial value 100.587588 iter 10 value 93.869066 iter 20 value 87.436942 iter 30 value 86.965025 iter 40 value 86.723517 iter 50 value 86.234963 iter 60 value 85.142730 iter 70 value 84.964093 final value 84.958015 converged Fitting Repeat 5 # weights: 103 initial value 101.284252 iter 10 value 94.033056 iter 20 value 93.007841 iter 30 value 88.718151 iter 40 value 86.899970 iter 50 value 84.436317 iter 60 value 83.497932 final value 83.483235 converged Fitting Repeat 1 # weights: 305 initial value 104.598439 iter 10 value 94.099327 iter 20 value 93.778767 iter 30 value 89.947521 iter 40 value 88.979662 iter 50 value 85.832038 iter 60 value 84.739793 iter 70 value 83.224742 iter 80 value 82.797319 iter 90 value 82.294830 iter 100 value 82.053130 final value 82.053130 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 114.631350 iter 10 value 93.074528 iter 20 value 88.853352 iter 30 value 85.607480 iter 40 value 84.313081 iter 50 value 82.416174 iter 60 value 81.742158 iter 70 value 81.346197 iter 80 value 80.990757 iter 90 value 80.898247 iter 100 value 80.836909 final value 80.836909 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 106.948936 iter 10 value 94.052021 iter 20 value 87.399768 iter 30 value 87.001396 iter 40 value 86.608300 iter 50 value 85.892225 iter 60 value 85.500941 iter 70 value 85.358297 iter 80 value 85.114335 iter 90 value 84.985528 iter 100 value 84.335192 final value 84.335192 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 106.388524 iter 10 value 94.037772 iter 20 value 86.201410 iter 30 value 85.707828 iter 40 value 85.048979 iter 50 value 84.397123 iter 60 value 81.949494 iter 70 value 81.644694 iter 80 value 81.522509 iter 90 value 81.431961 iter 100 value 81.273732 final value 81.273732 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.488470 iter 10 value 93.988634 iter 20 value 91.278206 iter 30 value 88.521277 iter 40 value 85.141817 iter 50 value 84.585827 iter 60 value 83.757565 iter 70 value 82.663563 iter 80 value 82.158998 iter 90 value 81.701111 iter 100 value 81.367328 final value 81.367328 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 108.754294 iter 10 value 93.735299 iter 20 value 86.509610 iter 30 value 84.781607 iter 40 value 84.236389 iter 50 value 83.181204 iter 60 value 82.574278 iter 70 value 82.450380 iter 80 value 82.226359 iter 90 value 81.861358 iter 100 value 81.413118 final value 81.413118 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 105.175506 iter 10 value 94.325865 iter 20 value 91.234915 iter 30 value 90.814097 iter 40 value 90.691936 iter 50 value 90.610695 iter 60 value 89.525403 iter 70 value 86.183501 iter 80 value 84.059625 iter 90 value 82.225156 iter 100 value 81.658040 final value 81.658040 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 104.713322 iter 10 value 93.991301 iter 20 value 88.994920 iter 30 value 85.232927 iter 40 value 83.365608 iter 50 value 82.148044 iter 60 value 81.849045 iter 70 value 81.715611 iter 80 value 81.551300 iter 90 value 81.448191 iter 100 value 81.168911 final value 81.168911 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 109.008360 iter 10 value 93.964557 iter 20 value 86.363486 iter 30 value 85.520262 iter 40 value 83.915619 iter 50 value 83.097227 iter 60 value 82.858416 iter 70 value 81.729019 iter 80 value 81.445647 iter 90 value 81.313263 iter 100 value 80.993825 final value 80.993825 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 117.382311 iter 10 value 94.073791 iter 20 value 92.585940 iter 30 value 88.120129 iter 40 value 85.871203 iter 50 value 84.583891 iter 60 value 83.585986 iter 70 value 82.554660 iter 80 value 82.088379 iter 90 value 81.818398 iter 100 value 81.635823 final value 81.635823 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.131566 iter 10 value 93.841078 iter 20 value 93.673139 iter 20 value 93.673138 iter 20 value 93.673138 final value 93.673138 converged Fitting Repeat 2 # weights: 103 initial value 97.408680 iter 10 value 94.054707 iter 20 value 94.052926 iter 30 value 94.004372 iter 40 value 93.810289 iter 40 value 93.810289 iter 40 value 93.810289 final value 93.810289 converged Fitting Repeat 3 # weights: 103 initial value 100.269429 final value 94.054686 converged Fitting Repeat 4 # weights: 103 initial value 94.361581 final value 94.054853 converged Fitting Repeat 5 # weights: 103 initial value 95.348737 final value 94.054523 converged Fitting Repeat 1 # weights: 305 initial value 98.428972 iter 10 value 91.762410 iter 20 value 86.362311 iter 30 value 85.995929 iter 40 value 84.869402 iter 50 value 84.867405 iter 60 value 84.537767 iter 70 value 84.265276 iter 80 value 84.262844 iter 90 value 84.259361 iter 100 value 83.871380 final value 83.871380 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 107.638569 iter 10 value 93.905943 iter 20 value 93.673382 final value 93.672236 converged Fitting Repeat 3 # weights: 305 initial value 102.286677 iter 10 value 94.037849 iter 20 value 94.033473 final value 94.033313 converged Fitting Repeat 4 # weights: 305 initial value 100.163504 iter 10 value 94.057271 iter 20 value 94.043733 iter 30 value 93.202951 iter 40 value 87.147163 iter 50 value 83.898781 iter 60 value 83.344571 iter 70 value 82.577309 iter 80 value 82.403035 iter 90 value 81.540474 iter 100 value 80.354685 final value 80.354685 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 101.611402 iter 10 value 94.057767 iter 20 value 93.483188 final value 92.703136 converged Fitting Repeat 1 # weights: 507 initial value 105.150646 iter 10 value 91.622025 iter 20 value 90.869408 iter 30 value 90.820865 iter 40 value 90.819787 iter 50 value 90.809710 iter 60 value 90.804089 iter 70 value 90.599557 iter 80 value 86.082154 iter 90 value 84.870961 iter 100 value 83.190585 final value 83.190585 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 105.059261 iter 10 value 94.007871 iter 20 value 93.266941 iter 30 value 92.721584 iter 40 value 92.671785 iter 50 value 92.670088 iter 60 value 92.103792 iter 70 value 92.081831 iter 80 value 92.039358 iter 90 value 86.694030 iter 100 value 84.017118 final value 84.017118 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 109.598921 iter 10 value 93.177331 iter 20 value 93.064810 iter 30 value 91.820845 iter 40 value 91.819837 iter 50 value 91.805963 iter 60 value 90.774932 iter 70 value 88.583307 iter 80 value 87.462407 iter 90 value 87.028799 iter 100 value 86.926222 final value 86.926222 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 97.127708 iter 10 value 94.041407 iter 20 value 94.030824 iter 30 value 91.907144 iter 40 value 85.516662 iter 50 value 85.199975 iter 60 value 85.105342 final value 85.105198 converged Fitting Repeat 5 # weights: 507 initial value 101.111208 iter 10 value 93.552118 iter 20 value 93.543292 iter 30 value 93.183891 iter 40 value 90.946466 iter 50 value 85.529656 iter 60 value 85.266322 iter 70 value 84.815171 iter 80 value 84.498636 iter 90 value 83.986690 final value 83.986678 converged Fitting Repeat 1 # weights: 103 initial value 106.684757 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 103.085092 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 99.019878 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 98.255582 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 103.312929 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 98.207110 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 99.363767 iter 10 value 90.690983 iter 20 value 89.925516 final value 89.925513 converged Fitting Repeat 3 # weights: 305 initial value 126.861371 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 101.391956 iter 10 value 94.057231 final value 94.057229 converged Fitting Repeat 5 # weights: 305 initial value 101.224988 final value 94.466823 converged Fitting Repeat 1 # weights: 507 initial value 95.429966 final value 94.466823 converged Fitting Repeat 2 # weights: 507 initial value 114.196562 iter 10 value 93.109891 final value 93.109890 converged Fitting Repeat 3 # weights: 507 initial value 105.888715 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 116.597163 final value 94.025063 converged Fitting Repeat 5 # weights: 507 initial value 96.675821 final value 94.466823 converged Fitting Repeat 1 # weights: 103 initial value 100.540247 iter 10 value 94.488745 iter 20 value 94.118983 iter 30 value 94.065353 iter 40 value 94.033754 iter 50 value 87.716032 iter 60 value 86.556117 iter 70 value 86.439389 iter 80 value 85.561812 iter 90 value 85.044112 final value 85.040692 converged Fitting Repeat 2 # weights: 103 initial value 109.224099 iter 10 value 93.709806 iter 20 value 88.182929 iter 30 value 85.500587 iter 40 value 84.402831 iter 50 value 83.137935 iter 60 value 82.115467 iter 70 value 82.058709 final value 82.057348 converged Fitting Repeat 3 # weights: 103 initial value 98.928758 iter 10 value 94.277490 iter 20 value 91.058569 iter 30 value 90.807323 iter 40 value 83.618052 iter 50 value 82.162745 iter 60 value 82.032364 iter 70 value 81.930650 iter 80 value 81.886340 final value 81.886339 converged Fitting Repeat 4 # weights: 103 initial value 96.689671 iter 10 value 94.477245 iter 20 value 94.099596 iter 30 value 92.140185 iter 40 value 84.673012 iter 50 value 82.734251 iter 60 value 82.479723 iter 70 value 82.290386 iter 80 value 82.227000 iter 90 value 82.154751 final value 82.154750 converged Fitting Repeat 5 # weights: 103 initial value 116.395862 iter 10 value 94.488937 iter 20 value 88.143558 iter 30 value 87.520931 iter 40 value 86.843834 iter 50 value 85.957622 iter 60 value 83.155412 iter 70 value 82.791006 iter 80 value 82.172155 iter 90 value 82.165926 iter 100 value 82.158604 final value 82.158604 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 107.434303 iter 10 value 94.478137 iter 20 value 93.286584 iter 30 value 92.880542 iter 40 value 86.498435 iter 50 value 83.636686 iter 60 value 83.411958 iter 70 value 82.953390 iter 80 value 82.249982 iter 90 value 81.915123 iter 100 value 81.859204 final value 81.859204 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 125.033843 iter 10 value 94.315282 iter 20 value 88.052988 iter 30 value 83.620441 iter 40 value 83.204634 iter 50 value 83.047269 iter 60 value 82.389179 iter 70 value 81.299065 iter 80 value 81.180420 iter 90 value 80.892194 iter 100 value 80.154154 final value 80.154154 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 104.044314 iter 10 value 94.496556 iter 20 value 93.972286 iter 30 value 93.292050 iter 40 value 87.411235 iter 50 value 82.907227 iter 60 value 82.841921 iter 70 value 82.331028 iter 80 value 81.698203 iter 90 value 80.609252 iter 100 value 79.736482 final value 79.736482 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 105.759711 iter 10 value 95.711393 iter 20 value 93.206880 iter 30 value 87.630013 iter 40 value 85.100211 iter 50 value 82.526097 iter 60 value 81.338462 iter 70 value 80.645202 iter 80 value 80.419086 iter 90 value 80.057317 iter 100 value 79.706323 final value 79.706323 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 107.876064 iter 10 value 94.380858 iter 20 value 94.043816 iter 30 value 93.219337 iter 40 value 90.103552 iter 50 value 88.965660 iter 60 value 88.365017 iter 70 value 88.057873 iter 80 value 87.670633 iter 90 value 86.007462 iter 100 value 84.625066 final value 84.625066 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 112.658568 iter 10 value 94.437766 iter 20 value 87.505448 iter 30 value 84.400437 iter 40 value 82.125815 iter 50 value 80.948873 iter 60 value 80.503775 iter 70 value 80.226759 iter 80 value 79.716085 iter 90 value 79.109696 iter 100 value 78.816016 final value 78.816016 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 134.125760 iter 10 value 95.159867 iter 20 value 94.886071 iter 30 value 83.863985 iter 40 value 83.302393 iter 50 value 82.302447 iter 60 value 81.151600 iter 70 value 80.406493 iter 80 value 79.456870 iter 90 value 79.047538 iter 100 value 78.829609 final value 78.829609 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.481474 iter 10 value 95.047460 iter 20 value 94.932035 iter 30 value 90.780935 iter 40 value 86.601437 iter 50 value 86.274002 iter 60 value 86.222994 iter 70 value 83.096515 iter 80 value 83.038435 iter 90 value 82.033467 iter 100 value 80.742536 final value 80.742536 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 117.691483 iter 10 value 94.523250 iter 20 value 89.680506 iter 30 value 87.525791 iter 40 value 86.357698 iter 50 value 85.083786 iter 60 value 84.277206 iter 70 value 83.930997 iter 80 value 82.522803 iter 90 value 80.715100 iter 100 value 80.219440 final value 80.219440 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 115.075134 iter 10 value 94.801943 iter 20 value 87.677662 iter 30 value 85.291820 iter 40 value 84.401008 iter 50 value 81.961906 iter 60 value 80.725806 iter 70 value 79.974532 iter 80 value 79.630831 iter 90 value 79.442136 iter 100 value 79.348167 final value 79.348167 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.952576 final value 94.486065 converged Fitting Repeat 2 # weights: 103 initial value 107.622810 final value 94.486116 converged Fitting Repeat 3 # weights: 103 initial value 97.239977 final value 94.485579 converged Fitting Repeat 4 # weights: 103 initial value 95.874843 iter 10 value 94.445127 iter 20 value 94.439477 iter 30 value 86.227645 iter 40 value 86.038224 iter 50 value 85.977858 iter 60 value 85.819429 iter 70 value 84.107526 iter 80 value 84.063545 final value 84.063172 converged Fitting Repeat 5 # weights: 103 initial value 94.953214 final value 94.485980 converged Fitting Repeat 1 # weights: 305 initial value 97.888028 iter 10 value 92.944995 iter 20 value 91.560824 final value 91.559734 converged Fitting Repeat 2 # weights: 305 initial value 96.315068 iter 10 value 94.475674 iter 20 value 94.470395 iter 30 value 94.367419 iter 40 value 83.765797 iter 50 value 81.337820 iter 60 value 81.170902 iter 70 value 81.159814 iter 80 value 81.158623 iter 90 value 81.157437 final value 81.157347 converged Fitting Repeat 3 # weights: 305 initial value 107.053452 iter 10 value 94.488979 iter 20 value 94.385289 iter 30 value 91.903122 iter 40 value 91.633597 final value 91.632769 converged Fitting Repeat 4 # weights: 305 initial value 99.466945 iter 10 value 93.614694 iter 20 value 90.602274 iter 30 value 85.259710 iter 40 value 83.791067 iter 50 value 83.445709 iter 60 value 83.282747 iter 70 value 82.429241 iter 80 value 82.019937 iter 90 value 82.019141 iter 100 value 81.933014 final value 81.933014 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.216986 iter 10 value 94.489361 iter 20 value 94.288998 final value 94.057495 converged Fitting Repeat 1 # weights: 507 initial value 107.625677 iter 10 value 94.491429 iter 20 value 84.747160 iter 30 value 82.171875 iter 40 value 81.160029 iter 50 value 81.076307 final value 81.074151 converged Fitting Repeat 2 # weights: 507 initial value 97.052453 iter 10 value 94.034801 iter 20 value 94.032646 iter 30 value 94.025748 iter 40 value 93.904658 iter 50 value 84.525842 final value 84.525816 converged Fitting Repeat 3 # weights: 507 initial value 101.044706 iter 10 value 94.491861 iter 20 value 85.287744 iter 30 value 81.563541 iter 40 value 81.465848 final value 81.465505 converged Fitting Repeat 4 # weights: 507 initial value 107.696637 iter 10 value 94.491713 iter 20 value 94.189830 iter 30 value 94.004374 iter 40 value 93.871939 iter 50 value 87.404485 iter 60 value 87.302361 iter 70 value 87.301005 iter 80 value 87.299321 iter 90 value 87.296466 iter 100 value 87.092358 final value 87.092358 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 93.034265 iter 10 value 81.632006 iter 20 value 78.662472 iter 30 value 78.478917 iter 40 value 78.306161 iter 50 value 78.023554 iter 60 value 77.856428 iter 70 value 77.850864 iter 80 value 77.848975 iter 90 value 77.844106 final value 77.844086 converged Fitting Repeat 1 # weights: 103 initial value 96.822888 final value 94.252920 converged Fitting Repeat 2 # weights: 103 initial value 96.912392 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 97.941106 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 99.937202 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 103.645512 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 108.825467 iter 10 value 94.245894 final value 94.229692 converged Fitting Repeat 2 # weights: 305 initial value 98.081845 iter 10 value 85.449640 iter 20 value 85.245528 iter 30 value 85.244710 iter 40 value 85.244579 final value 85.244555 converged Fitting Repeat 3 # weights: 305 initial value 111.428649 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 95.240584 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 107.136852 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 102.588484 final value 94.275362 converged Fitting Repeat 2 # weights: 507 initial value 124.320259 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 96.843787 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 105.185633 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 110.762224 final value 94.275362 converged Fitting Repeat 1 # weights: 103 initial value 98.234852 iter 10 value 94.486889 iter 20 value 94.163222 iter 30 value 91.653771 iter 40 value 90.839654 iter 50 value 85.775422 iter 60 value 84.331723 iter 70 value 84.275955 iter 80 value 83.985117 iter 90 value 83.964859 iter 90 value 83.964859 iter 90 value 83.964859 final value 83.964859 converged Fitting Repeat 2 # weights: 103 initial value 101.452060 iter 10 value 94.463735 iter 20 value 86.765371 iter 30 value 85.940664 iter 40 value 85.636325 iter 50 value 83.814539 iter 60 value 83.548606 iter 70 value 83.526036 final value 83.525857 converged Fitting Repeat 3 # weights: 103 initial value 101.813272 iter 10 value 94.488432 iter 20 value 94.332496 iter 30 value 94.328983 iter 40 value 94.276144 iter 50 value 91.232458 iter 60 value 90.333330 iter 70 value 90.213031 iter 80 value 89.699086 iter 90 value 85.154370 iter 100 value 82.996881 final value 82.996881 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 97.188072 iter 10 value 94.497906 iter 20 value 94.488679 iter 30 value 94.303273 iter 40 value 94.243170 iter 50 value 94.230589 iter 60 value 86.603653 iter 70 value 85.883881 iter 80 value 85.863416 iter 90 value 85.860001 iter 100 value 85.627435 final value 85.627435 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 108.956395 iter 10 value 94.259146 iter 20 value 86.947913 iter 30 value 86.484469 iter 40 value 84.534316 iter 50 value 83.976235 iter 60 value 83.965000 iter 70 value 83.964867 final value 83.964860 converged Fitting Repeat 1 # weights: 305 initial value 102.928421 iter 10 value 94.521228 iter 20 value 90.418918 iter 30 value 89.038645 iter 40 value 86.466144 iter 50 value 84.623202 iter 60 value 82.200011 iter 70 value 81.281305 iter 80 value 80.312429 iter 90 value 80.059081 iter 100 value 79.729940 final value 79.729940 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 123.660595 iter 10 value 94.495739 iter 20 value 92.274151 iter 30 value 84.732341 iter 40 value 84.566571 iter 50 value 83.942402 iter 60 value 82.270780 iter 70 value 82.191698 iter 80 value 81.785102 iter 90 value 81.271657 iter 100 value 80.097431 final value 80.097431 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 101.611084 iter 10 value 94.541691 iter 20 value 94.494281 iter 30 value 94.047350 iter 40 value 90.821012 iter 50 value 87.873469 iter 60 value 86.202392 iter 70 value 82.434993 iter 80 value 81.528807 iter 90 value 80.750247 iter 100 value 80.536630 final value 80.536630 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 106.906046 iter 10 value 94.395232 iter 20 value 87.417415 iter 30 value 86.822216 iter 40 value 84.558069 iter 50 value 82.704500 iter 60 value 81.922701 iter 70 value 81.784328 iter 80 value 81.637552 iter 90 value 81.566948 iter 100 value 81.505209 final value 81.505209 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 106.614864 iter 10 value 94.488682 iter 20 value 93.983108 iter 30 value 91.917940 iter 40 value 85.438174 iter 50 value 85.036814 iter 60 value 83.506420 iter 70 value 82.148778 iter 80 value 81.357476 iter 90 value 80.981433 iter 100 value 80.107324 final value 80.107324 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 124.927415 iter 10 value 93.494114 iter 20 value 90.417588 iter 30 value 89.343182 iter 40 value 84.813865 iter 50 value 84.499743 iter 60 value 84.155961 iter 70 value 83.869737 iter 80 value 83.645585 iter 90 value 83.515903 iter 100 value 82.621504 final value 82.621504 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 135.054722 iter 10 value 100.858535 iter 20 value 98.068395 iter 30 value 92.725641 iter 40 value 87.723289 iter 50 value 84.645657 iter 60 value 83.605450 iter 70 value 83.146770 iter 80 value 82.884800 iter 90 value 82.540811 iter 100 value 80.542594 final value 80.542594 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 107.841415 iter 10 value 95.056315 iter 20 value 92.923566 iter 30 value 84.346428 iter 40 value 84.058291 iter 50 value 83.197080 iter 60 value 82.199285 iter 70 value 81.240391 iter 80 value 80.109876 iter 90 value 79.653288 iter 100 value 79.488468 final value 79.488468 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 123.728823 iter 10 value 94.150767 iter 20 value 88.834218 iter 30 value 87.173538 iter 40 value 87.081802 iter 50 value 84.706861 iter 60 value 83.950602 iter 70 value 82.941752 iter 80 value 81.824325 iter 90 value 81.591797 iter 100 value 81.098369 final value 81.098369 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 106.482850 iter 10 value 94.235764 iter 20 value 92.747335 iter 30 value 90.911764 iter 40 value 83.828850 iter 50 value 82.937739 iter 60 value 82.001091 iter 70 value 81.005268 iter 80 value 79.821990 iter 90 value 79.448473 iter 100 value 79.368248 final value 79.368248 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.888049 final value 94.485838 converged Fitting Repeat 2 # weights: 103 initial value 97.351930 final value 94.485805 converged Fitting Repeat 3 # weights: 103 initial value 94.674192 final value 94.485724 converged Fitting Repeat 4 # weights: 103 initial value 95.280719 iter 10 value 94.485864 iter 20 value 94.484250 final value 94.484216 converged Fitting Repeat 5 # weights: 103 initial value 101.936553 final value 94.486245 converged Fitting Repeat 1 # weights: 305 initial value 96.050648 iter 10 value 94.489146 iter 20 value 94.484382 final value 94.484261 converged Fitting Repeat 2 # weights: 305 initial value 95.769971 iter 10 value 94.462045 iter 20 value 94.033953 iter 30 value 83.403276 iter 40 value 83.145063 iter 50 value 82.347867 iter 60 value 82.251755 final value 82.251720 converged Fitting Repeat 3 # weights: 305 initial value 101.112501 iter 10 value 94.484483 iter 20 value 94.276403 iter 30 value 94.275847 iter 40 value 94.256761 iter 50 value 94.185556 iter 60 value 85.040880 iter 70 value 84.523939 iter 80 value 84.434147 iter 90 value 84.433966 iter 90 value 84.433965 iter 90 value 84.433965 final value 84.433965 converged Fitting Repeat 4 # weights: 305 initial value 103.626638 iter 10 value 94.488946 iter 20 value 93.833013 final value 93.702085 converged Fitting Repeat 5 # weights: 305 initial value 98.682350 iter 10 value 94.489016 iter 20 value 94.484361 iter 30 value 94.040739 iter 40 value 83.812332 iter 50 value 83.749314 iter 60 value 83.745009 iter 70 value 83.738397 iter 80 value 83.736999 iter 90 value 83.734581 iter 100 value 82.754565 final value 82.754565 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 99.359955 iter 10 value 94.283321 iter 20 value 94.228595 iter 30 value 91.516156 iter 40 value 90.293121 iter 50 value 89.609067 iter 60 value 83.226085 iter 70 value 81.685875 iter 80 value 81.549650 iter 90 value 81.321329 iter 100 value 81.302389 final value 81.302389 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 107.150674 iter 10 value 93.511955 iter 20 value 93.507132 iter 30 value 87.291119 iter 40 value 85.250682 iter 50 value 85.247665 iter 60 value 84.446858 final value 84.362215 converged Fitting Repeat 3 # weights: 507 initial value 99.822308 iter 10 value 86.408791 iter 20 value 85.656485 iter 30 value 85.251073 iter 40 value 85.249775 iter 50 value 85.248449 iter 60 value 85.248010 final value 85.247941 converged Fitting Repeat 4 # weights: 507 initial value 117.407335 iter 10 value 94.493014 iter 20 value 94.481895 iter 30 value 88.719966 iter 40 value 88.411813 iter 40 value 88.411813 iter 40 value 88.411813 final value 88.411813 converged Fitting Repeat 5 # weights: 507 initial value 102.656022 iter 10 value 90.031825 iter 20 value 86.516513 iter 30 value 86.514869 iter 40 value 86.506663 iter 50 value 86.491159 iter 60 value 84.236831 iter 70 value 83.033337 iter 80 value 83.028906 iter 90 value 82.889452 iter 100 value 82.390248 final value 82.390248 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.698691 iter 10 value 93.773018 final value 93.772973 converged Fitting Repeat 2 # weights: 103 initial value 95.556094 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 101.217429 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 102.698755 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 105.719804 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 103.188605 final value 94.046703 converged Fitting Repeat 2 # weights: 305 initial value 96.567206 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 108.130829 iter 10 value 94.486975 iter 20 value 94.484213 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 97.579678 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 96.228444 final value 93.772974 converged Fitting Repeat 1 # weights: 507 initial value 95.798415 final value 94.484137 converged Fitting Repeat 2 # weights: 507 initial value 97.055336 iter 10 value 93.773994 final value 93.772973 converged Fitting Repeat 3 # weights: 507 initial value 102.402948 iter 10 value 93.778551 iter 20 value 93.724301 iter 30 value 93.722226 final value 93.722223 converged Fitting Repeat 4 # weights: 507 initial value 108.234652 iter 10 value 93.797481 iter 20 value 93.194713 iter 30 value 93.108075 iter 40 value 93.086119 final value 93.070833 converged Fitting Repeat 5 # weights: 507 initial value 107.495993 iter 10 value 93.772973 iter 10 value 93.772973 iter 10 value 93.772973 final value 93.772973 converged Fitting Repeat 1 # weights: 103 initial value 98.334893 iter 10 value 94.556903 iter 20 value 94.464794 iter 30 value 92.785039 iter 40 value 90.973082 iter 50 value 89.134402 iter 60 value 85.341435 iter 70 value 84.759076 iter 80 value 84.317768 iter 90 value 84.216229 final value 84.210353 converged Fitting Repeat 2 # weights: 103 initial value 97.601693 iter 10 value 94.490049 iter 20 value 91.083450 iter 30 value 90.884897 iter 40 value 87.146358 iter 50 value 82.399257 iter 60 value 81.433256 iter 70 value 81.221688 iter 80 value 81.026433 iter 90 value 80.974049 iter 100 value 80.958129 final value 80.958129 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 115.085194 iter 10 value 94.449155 iter 20 value 88.936802 iter 30 value 87.250843 iter 40 value 84.772186 iter 50 value 84.608984 iter 60 value 84.606907 iter 60 value 84.606906 iter 60 value 84.606906 final value 84.606906 converged Fitting Repeat 4 # weights: 103 initial value 97.794635 iter 10 value 93.989179 iter 20 value 93.968713 iter 30 value 93.575015 iter 40 value 87.004255 iter 50 value 84.679744 iter 60 value 83.513126 iter 70 value 82.835455 iter 80 value 82.045770 iter 90 value 81.771049 iter 100 value 80.900679 final value 80.900679 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 96.980458 iter 10 value 94.476432 iter 20 value 91.041222 iter 30 value 84.915417 iter 40 value 83.177618 iter 50 value 82.170544 iter 60 value 81.495728 iter 70 value 80.964818 final value 80.957415 converged Fitting Repeat 1 # weights: 305 initial value 101.391160 iter 10 value 94.574124 iter 20 value 89.609988 iter 30 value 85.654162 iter 40 value 84.904810 iter 50 value 83.826816 iter 60 value 83.083774 iter 70 value 82.428884 iter 80 value 82.001023 iter 90 value 80.701823 iter 100 value 80.255153 final value 80.255153 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 108.746824 iter 10 value 94.032493 iter 20 value 93.315840 iter 30 value 86.983190 iter 40 value 83.455233 iter 50 value 81.954546 iter 60 value 81.251975 iter 70 value 80.562144 iter 80 value 79.475594 iter 90 value 79.225862 iter 100 value 79.191718 final value 79.191718 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 105.125646 iter 10 value 88.678920 iter 20 value 87.683287 iter 30 value 87.151679 iter 40 value 86.613330 iter 50 value 83.568480 iter 60 value 81.371735 iter 70 value 79.876597 iter 80 value 79.795967 iter 90 value 79.415496 iter 100 value 79.274696 final value 79.274696 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 124.873313 iter 10 value 94.507134 iter 20 value 92.414481 iter 30 value 89.591965 iter 40 value 85.441753 iter 50 value 85.028101 iter 60 value 84.923088 iter 70 value 84.394525 iter 80 value 82.668683 iter 90 value 80.654475 iter 100 value 79.956041 final value 79.956041 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 133.733087 iter 10 value 93.528490 iter 20 value 90.058028 iter 30 value 89.632845 iter 40 value 88.085581 iter 50 value 83.647406 iter 60 value 82.015078 iter 70 value 81.531852 iter 80 value 81.349614 iter 90 value 80.895888 iter 100 value 80.669720 final value 80.669720 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 122.371842 iter 10 value 92.490055 iter 20 value 89.327222 iter 30 value 86.065121 iter 40 value 85.562310 iter 50 value 84.950509 iter 60 value 82.621723 iter 70 value 82.170412 iter 80 value 81.695691 iter 90 value 81.288800 iter 100 value 81.131120 final value 81.131120 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 103.371043 iter 10 value 95.603842 iter 20 value 88.860678 iter 30 value 86.134484 iter 40 value 85.652335 iter 50 value 84.677610 iter 60 value 84.003541 iter 70 value 81.773051 iter 80 value 80.218188 iter 90 value 79.877103 iter 100 value 79.647591 final value 79.647591 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 103.871976 iter 10 value 94.068258 iter 20 value 91.548986 iter 30 value 88.199583 iter 40 value 87.382393 iter 50 value 84.824818 iter 60 value 81.782231 iter 70 value 80.563114 iter 80 value 80.168612 iter 90 value 80.058494 iter 100 value 79.821963 final value 79.821963 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 105.728144 iter 10 value 94.409875 iter 20 value 88.687315 iter 30 value 84.811114 iter 40 value 82.140843 iter 50 value 80.913647 iter 60 value 80.558451 iter 70 value 80.216510 iter 80 value 80.127356 iter 90 value 80.064203 iter 100 value 79.925504 final value 79.925504 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 105.353245 iter 10 value 94.771628 iter 20 value 90.141114 iter 30 value 88.711885 iter 40 value 87.509374 iter 50 value 86.059954 iter 60 value 83.535957 iter 70 value 82.542388 iter 80 value 82.414376 iter 90 value 81.654269 iter 100 value 81.518482 final value 81.518482 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.454367 iter 10 value 94.389158 iter 20 value 93.731457 iter 30 value 93.727386 final value 93.727359 converged Fitting Repeat 2 # weights: 103 initial value 97.858468 final value 94.485719 converged Fitting Repeat 3 # weights: 103 initial value 95.641446 final value 94.485595 converged Fitting Repeat 4 # weights: 103 initial value 96.029859 final value 94.485901 converged Fitting Repeat 5 # weights: 103 initial value 101.663165 iter 10 value 93.469160 iter 20 value 93.458330 iter 30 value 92.925526 iter 40 value 92.114126 final value 92.114118 converged Fitting Repeat 1 # weights: 305 initial value 104.245418 iter 10 value 94.488463 iter 20 value 93.966514 final value 93.773326 converged Fitting Repeat 2 # weights: 305 initial value 96.589730 iter 10 value 92.843383 iter 20 value 89.497432 final value 89.362492 converged Fitting Repeat 3 # weights: 305 initial value 137.482258 iter 10 value 94.059599 iter 20 value 94.054828 iter 30 value 92.067916 iter 40 value 87.123933 iter 50 value 81.575016 iter 60 value 80.610645 iter 70 value 79.325215 iter 80 value 78.887750 iter 90 value 78.702382 iter 100 value 78.668504 final value 78.668504 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 103.759250 iter 10 value 94.489044 iter 20 value 94.476852 iter 30 value 92.618324 final value 92.617570 converged Fitting Repeat 5 # weights: 305 initial value 97.666092 iter 10 value 93.573826 iter 20 value 92.868929 iter 30 value 92.859486 iter 40 value 92.858503 iter 50 value 92.857247 iter 60 value 92.772883 iter 70 value 92.770756 iter 80 value 92.770705 iter 90 value 92.770604 final value 92.770574 converged Fitting Repeat 1 # weights: 507 initial value 102.600836 iter 10 value 94.132459 iter 20 value 93.624275 iter 30 value 93.210011 iter 40 value 92.096147 iter 50 value 91.870050 iter 60 value 91.181763 iter 70 value 91.151296 iter 80 value 91.149755 iter 90 value 91.147462 iter 100 value 90.587336 final value 90.587336 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 103.346415 iter 10 value 93.781830 iter 20 value 93.770116 iter 30 value 93.723802 iter 40 value 93.723517 iter 50 value 88.684789 iter 60 value 80.279687 iter 70 value 79.781325 iter 80 value 79.755901 iter 90 value 79.734610 iter 100 value 79.166897 final value 79.166897 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 101.988556 iter 10 value 94.491377 iter 20 value 94.452331 iter 30 value 90.766971 iter 40 value 90.646816 iter 50 value 90.547596 iter 60 value 90.329303 iter 70 value 90.324993 iter 80 value 90.322160 iter 90 value 90.123922 final value 90.123832 converged Fitting Repeat 4 # weights: 507 initial value 106.037489 iter 10 value 92.974561 iter 20 value 85.825603 iter 30 value 85.792989 iter 40 value 84.747953 iter 50 value 83.423512 iter 60 value 83.367662 iter 70 value 83.296934 iter 80 value 83.295589 iter 90 value 83.293099 iter 100 value 83.222894 final value 83.222894 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 122.384482 iter 10 value 94.492076 iter 20 value 93.081060 iter 30 value 87.353218 iter 40 value 85.000007 iter 50 value 80.204034 iter 60 value 79.389720 iter 70 value 79.366779 iter 80 value 79.332914 iter 90 value 79.240968 iter 100 value 79.236899 final value 79.236899 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.464811 iter 10 value 94.044615 final value 94.044529 converged Fitting Repeat 2 # weights: 103 initial value 97.998056 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 96.615156 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 107.151721 iter 10 value 93.768924 iter 20 value 93.714334 final value 93.714286 converged Fitting Repeat 5 # weights: 103 initial value 99.200346 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 97.481329 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 102.883432 final value 94.032967 converged Fitting Repeat 3 # weights: 305 initial value 94.150395 iter 10 value 91.026871 iter 20 value 90.770754 iter 30 value 90.764004 final value 90.763994 converged Fitting Repeat 4 # weights: 305 initial value 96.522027 iter 10 value 93.746082 iter 20 value 83.876215 iter 30 value 82.848939 final value 82.848894 converged Fitting Repeat 5 # weights: 305 initial value 103.935166 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 97.463471 final value 94.052906 converged Fitting Repeat 2 # weights: 507 initial value 101.408871 iter 10 value 93.818049 iter 20 value 93.712398 iter 30 value 93.682529 iter 40 value 93.651924 iter 50 value 93.649811 iter 60 value 93.625641 iter 70 value 93.611857 final value 93.611849 converged Fitting Repeat 3 # weights: 507 initial value 109.456537 final value 93.697143 converged Fitting Repeat 4 # weights: 507 initial value 105.935585 iter 10 value 88.797806 final value 86.618182 converged Fitting Repeat 5 # weights: 507 initial value 126.502930 final value 93.697143 converged Fitting Repeat 1 # weights: 103 initial value 97.689117 iter 10 value 94.057396 iter 20 value 93.958292 iter 30 value 93.266382 iter 40 value 87.431511 iter 50 value 86.287668 iter 60 value 86.115528 iter 70 value 86.005585 iter 80 value 85.948784 iter 90 value 85.630070 iter 100 value 81.400398 final value 81.400398 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 99.208441 iter 10 value 94.106792 iter 20 value 94.055278 iter 30 value 93.296334 iter 40 value 93.261549 iter 50 value 93.257227 iter 60 value 93.246540 iter 70 value 91.266765 iter 80 value 84.955082 iter 90 value 83.467544 iter 100 value 82.903475 final value 82.903475 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 100.568710 iter 10 value 93.730253 iter 20 value 84.894112 iter 30 value 84.008849 iter 40 value 83.292275 iter 50 value 82.889094 final value 82.876460 converged Fitting Repeat 4 # weights: 103 initial value 98.911833 iter 10 value 94.056699 iter 20 value 86.653628 iter 30 value 84.011537 iter 40 value 83.106852 iter 50 value 82.876572 final value 82.876460 converged Fitting Repeat 5 # weights: 103 initial value 101.417963 iter 10 value 94.055306 iter 20 value 93.363905 iter 30 value 93.264337 iter 40 value 93.259850 iter 50 value 93.257498 iter 60 value 93.257293 iter 70 value 90.998997 iter 80 value 85.147951 iter 90 value 83.691418 iter 100 value 82.984030 final value 82.984030 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 115.821218 iter 10 value 94.081661 iter 20 value 92.886991 iter 30 value 87.425463 iter 40 value 84.399506 iter 50 value 83.117363 iter 60 value 82.630196 iter 70 value 82.544513 iter 80 value 82.470191 iter 90 value 82.294291 iter 100 value 81.243242 final value 81.243242 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 100.249158 iter 10 value 84.922475 iter 20 value 83.692472 iter 30 value 82.718477 iter 40 value 81.385268 iter 50 value 80.600583 iter 60 value 80.456163 iter 70 value 80.334594 iter 80 value 80.183387 iter 90 value 79.874367 iter 100 value 79.751936 final value 79.751936 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.381114 iter 10 value 94.030027 iter 20 value 93.401003 iter 30 value 93.184205 iter 40 value 92.230415 iter 50 value 84.616348 iter 60 value 83.091443 iter 70 value 82.638903 iter 80 value 81.312712 iter 90 value 80.623695 iter 100 value 80.430997 final value 80.430997 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 106.111992 iter 10 value 94.095837 iter 20 value 92.293466 iter 30 value 87.956191 iter 40 value 85.511339 iter 50 value 84.480292 iter 60 value 82.288542 iter 70 value 81.315798 iter 80 value 80.529721 iter 90 value 80.329751 iter 100 value 80.236652 final value 80.236652 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 115.042371 iter 10 value 94.150372 iter 20 value 93.986808 iter 30 value 84.352373 iter 40 value 83.627770 iter 50 value 81.744835 iter 60 value 81.346345 iter 70 value 81.283701 iter 80 value 81.243808 iter 90 value 81.057208 iter 100 value 80.926371 final value 80.926371 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 107.686677 iter 10 value 94.048468 iter 20 value 87.781384 iter 30 value 84.049974 iter 40 value 83.122547 iter 50 value 82.475976 iter 60 value 81.901209 iter 70 value 81.498030 iter 80 value 81.198568 iter 90 value 80.838778 iter 100 value 80.375011 final value 80.375011 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 129.208091 iter 10 value 93.945665 iter 20 value 91.090858 iter 30 value 82.901339 iter 40 value 81.245898 iter 50 value 80.729881 iter 60 value 80.328963 iter 70 value 80.124027 iter 80 value 79.844060 iter 90 value 79.444753 iter 100 value 79.378687 final value 79.378687 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 108.883503 iter 10 value 94.180988 iter 20 value 86.926938 iter 30 value 84.668052 iter 40 value 83.800112 iter 50 value 83.464264 iter 60 value 82.939770 iter 70 value 81.791266 iter 80 value 80.309952 iter 90 value 79.956475 iter 100 value 79.791640 final value 79.791640 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 129.542951 iter 10 value 95.466591 iter 20 value 84.823382 iter 30 value 83.131714 iter 40 value 82.035149 iter 50 value 80.955946 iter 60 value 80.332825 iter 70 value 80.131888 iter 80 value 79.941549 iter 90 value 79.719075 iter 100 value 79.550310 final value 79.550310 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 106.161243 iter 10 value 91.346171 iter 20 value 84.029965 iter 30 value 82.054377 iter 40 value 80.990305 iter 50 value 80.765909 iter 60 value 80.667377 iter 70 value 80.522748 iter 80 value 80.289421 iter 90 value 80.054828 iter 100 value 79.779094 final value 79.779094 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.515122 final value 94.034426 converged Fitting Repeat 2 # weights: 103 initial value 101.740726 final value 94.054421 converged Fitting Repeat 3 # weights: 103 initial value 98.670997 final value 94.054486 converged Fitting Repeat 4 # weights: 103 initial value 96.257541 final value 94.054350 converged Fitting Repeat 5 # weights: 103 initial value 94.907011 final value 94.054550 converged Fitting Repeat 1 # weights: 305 initial value 94.491473 iter 10 value 94.055104 iter 20 value 92.983716 iter 30 value 85.746376 iter 40 value 85.592189 iter 50 value 85.378921 iter 60 value 83.468879 iter 70 value 80.576440 iter 80 value 80.157539 iter 90 value 79.554469 iter 100 value 79.339880 final value 79.339880 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 94.531410 iter 10 value 93.702151 iter 20 value 93.171324 iter 30 value 93.053878 iter 40 value 84.115434 iter 50 value 83.911742 iter 60 value 83.905390 iter 70 value 83.872358 final value 83.871927 converged Fitting Repeat 3 # weights: 305 initial value 98.411498 iter 10 value 94.057857 iter 20 value 93.973119 iter 30 value 86.598968 iter 40 value 84.414062 iter 50 value 81.230062 iter 60 value 81.225724 final value 81.225037 converged Fitting Repeat 4 # weights: 305 initial value 99.492962 iter 10 value 93.672103 iter 20 value 93.669914 iter 30 value 91.092673 iter 40 value 83.471794 iter 50 value 83.432469 iter 60 value 83.430825 iter 70 value 82.560051 iter 80 value 81.259129 iter 90 value 81.090199 iter 100 value 81.079324 final value 81.079324 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 109.147266 iter 10 value 94.058126 iter 20 value 94.052935 iter 30 value 93.193089 iter 40 value 86.100723 iter 50 value 86.034628 iter 60 value 84.916811 iter 60 value 84.916810 iter 60 value 84.916810 final value 84.916810 converged Fitting Repeat 1 # weights: 507 initial value 99.241458 iter 10 value 93.686687 iter 20 value 93.674477 iter 30 value 93.215187 iter 40 value 92.890847 iter 50 value 91.963760 iter 60 value 84.164316 iter 70 value 81.806311 iter 80 value 81.213737 iter 90 value 81.095384 iter 100 value 81.044752 final value 81.044752 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 105.821443 iter 10 value 92.032245 iter 20 value 91.799909 iter 30 value 91.797011 iter 40 value 91.793994 final value 91.786807 converged Fitting Repeat 3 # weights: 507 initial value 142.874073 iter 10 value 94.041077 iter 20 value 85.911688 iter 30 value 84.764984 iter 40 value 84.763452 iter 50 value 84.717120 iter 60 value 84.031553 iter 70 value 84.020347 iter 80 value 84.019542 iter 90 value 83.722220 iter 100 value 81.453566 final value 81.453566 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 104.966328 iter 10 value 94.060572 iter 20 value 87.791234 iter 30 value 83.872823 iter 40 value 83.864700 iter 50 value 83.828470 iter 60 value 83.051248 iter 70 value 80.447130 iter 80 value 79.244095 iter 90 value 78.994400 iter 100 value 78.868917 final value 78.868917 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 128.994555 iter 10 value 91.967112 iter 20 value 85.658264 iter 30 value 85.657573 iter 40 value 83.636918 iter 50 value 82.461746 iter 60 value 82.306239 iter 70 value 82.305312 iter 80 value 81.284173 final value 81.280363 converged Fitting Repeat 1 # weights: 305 initial value 120.657455 iter 10 value 117.895501 iter 20 value 117.886826 iter 30 value 113.160967 iter 40 value 105.493539 iter 50 value 105.344839 iter 60 value 105.342538 iter 70 value 105.342205 iter 80 value 104.369492 iter 90 value 103.695140 final value 103.691754 converged Fitting Repeat 2 # weights: 305 initial value 120.474312 iter 10 value 117.763522 iter 20 value 117.746750 iter 30 value 108.568597 iter 40 value 108.524704 iter 50 value 104.872331 iter 60 value 102.811244 final value 102.747210 converged Fitting Repeat 3 # weights: 305 initial value 123.407314 iter 10 value 117.894463 iter 20 value 117.889478 iter 30 value 115.023678 iter 40 value 115.018635 iter 50 value 108.982918 iter 60 value 104.167813 iter 70 value 103.983731 iter 80 value 103.388054 iter 90 value 101.275506 iter 100 value 100.633426 final value 100.633426 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 134.343170 iter 10 value 117.894785 iter 20 value 117.890367 final value 117.890300 converged Fitting Repeat 5 # weights: 305 initial value 142.573598 iter 10 value 117.102887 iter 20 value 116.937084 iter 30 value 113.881456 iter 40 value 113.682456 iter 50 value 113.676115 iter 50 value 113.676114 final value 113.676114 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 Mar 31 23:07:08 2025 *********************************************** Number of test functions: 7 Number of errors: 0 Number of failures: 0 1 Test Suite : HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures Number of test functions: 7 Number of errors: 0 Number of failures: 0 Warning messages: 1: `repeats` has no meaning for this resampling method. 2: executing %dopar% sequentially: no parallel backend registered > > > > > proc.time() user system elapsed 41.670 1.350 128.802
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 33.020 | 0.365 | 33.387 | |
FreqInteractors | 0.199 | 0.016 | 0.216 | |
calculateAAC | 0.033 | 0.003 | 0.036 | |
calculateAutocor | 0.273 | 0.020 | 0.294 | |
calculateCTDC | 0.067 | 0.000 | 0.067 | |
calculateCTDD | 0.475 | 0.000 | 0.475 | |
calculateCTDT | 0.184 | 0.000 | 0.184 | |
calculateCTriad | 0.359 | 0.008 | 0.368 | |
calculateDC | 0.080 | 0.000 | 0.079 | |
calculateF | 0.280 | 0.001 | 0.281 | |
calculateKSAAP | 0.086 | 0.000 | 0.086 | |
calculateQD_Sm | 1.496 | 0.042 | 1.538 | |
calculateTC | 1.412 | 0.031 | 1.443 | |
calculateTC_Sm | 0.314 | 0.001 | 0.315 | |
corr_plot | 33.388 | 0.299 | 33.743 | |
enrichfindP | 0.540 | 0.030 | 8.094 | |
enrichfind_hp | 0.088 | 0.002 | 1.044 | |
enrichplot | 0.338 | 0.000 | 0.338 | |
filter_missing_values | 0.001 | 0.000 | 0.001 | |
getFASTA | 0.439 | 0.005 | 3.959 | |
getHPI | 0.001 | 0.000 | 0.000 | |
get_negativePPI | 0.002 | 0.000 | 0.001 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0.000 | 0.001 | 0.002 | |
plotPPI | 0.067 | 0.003 | 0.071 | |
pred_ensembel | 13.168 | 0.146 | 11.954 | |
var_imp | 34.375 | 0.578 | 34.955 | |