Matineh Rahmatbakhsh
| Snapshot Date: 2025-08-11 13:45 -0400 (Mon, 11 Aug 2025) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: b0c624c |
| git_last_commit_date: 2025-04-15 12:38:30 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-08-12 12:07 -0400 (Tue, 12 Aug 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4818 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.5.1 (2025-06-13 ucrt) -- "Great Square Root" | 4553 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4595 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4537 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4535 |
| 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 987/2317 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.15.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| 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: 1.15.0 |
| Command: F:\biocbuild\bbs-3.22-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.22-bioc\R\library --no-vignettes --timings HPiP_1.15.0.tar.gz |
| StartedAt: 2025-08-12 03:14:24 -0400 (Tue, 12 Aug 2025) |
| EndedAt: 2025-08-12 03:20:45 -0400 (Tue, 12 Aug 2025) |
| EllapsedTime: 380.6 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.22-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.22-bioc\R\library --no-vignettes --timings HPiP_1.15.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck'
* using R version 4.5.1 (2025-06-13 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.15.0'
* 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 whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
FSmethod 35.50 2.18 37.71
var_imp 35.67 1.31 36.98
corr_plot 34.85 1.79 36.66
pred_ensembel 14.42 0.31 13.17
enrichfindP 0.64 0.10 12.89
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
'F:/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.22-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.22-bioc/R/library' * installing *source* package 'HPiP' ... ** this is package 'HPiP' version '1.15.0' ** 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 4.5.1 (2025-06-13 ucrt) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 94.715978
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 104.208159
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 94.780771
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 95.907695
final value 93.582418
converged
Fitting Repeat 5
# weights: 103
initial value 94.992185
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 103.942583
final value 93.582418
converged
Fitting Repeat 2
# weights: 305
initial value 97.296845
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 102.775498
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 101.783075
final value 93.582418
converged
Fitting Repeat 5
# weights: 305
initial value 98.513354
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 107.688843
final value 93.582418
converged
Fitting Repeat 2
# weights: 507
initial value 95.247359
final value 93.582418
converged
Fitting Repeat 3
# weights: 507
initial value 100.532439
iter 10 value 91.418208
iter 20 value 86.452646
iter 30 value 84.050725
iter 40 value 83.195698
iter 50 value 82.440014
final value 82.420887
converged
Fitting Repeat 4
# weights: 507
initial value 101.682477
iter 10 value 85.017021
iter 20 value 84.752741
iter 30 value 84.747755
iter 40 value 84.745410
final value 84.745344
converged
Fitting Repeat 5
# weights: 507
initial value 107.999785
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 98.893664
iter 10 value 94.270817
iter 20 value 94.062230
iter 30 value 94.015577
iter 40 value 87.922633
iter 50 value 87.206928
iter 60 value 84.291503
iter 70 value 82.882225
iter 80 value 81.953012
iter 90 value 81.806085
iter 100 value 81.790556
final value 81.790556
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 103.109956
iter 10 value 93.753532
iter 20 value 92.109500
iter 30 value 86.843537
iter 40 value 82.269967
iter 50 value 82.073299
iter 60 value 82.046116
iter 70 value 82.034316
iter 80 value 81.898948
iter 90 value 81.760100
iter 100 value 81.724830
final value 81.724830
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 103.197861
iter 10 value 93.999078
iter 20 value 93.378022
iter 30 value 93.331644
iter 40 value 89.336056
iter 50 value 87.391944
iter 60 value 86.789160
iter 70 value 86.645249
iter 80 value 86.578464
iter 90 value 85.047070
iter 100 value 84.782471
final value 84.782471
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.995150
iter 10 value 92.743567
iter 20 value 87.372103
iter 30 value 85.310411
iter 40 value 85.019067
iter 50 value 84.948034
iter 60 value 84.770370
final value 84.770104
converged
Fitting Repeat 5
# weights: 103
initial value 113.557428
iter 10 value 93.903946
iter 20 value 87.110598
iter 30 value 85.294997
iter 40 value 84.807809
iter 50 value 84.770424
final value 84.770104
converged
Fitting Repeat 1
# weights: 305
initial value 105.871816
iter 10 value 94.055338
iter 20 value 90.363213
iter 30 value 85.642105
iter 40 value 84.310831
iter 50 value 84.204345
iter 60 value 83.989263
iter 70 value 83.842562
iter 80 value 82.652777
iter 90 value 81.533641
iter 100 value 80.769958
final value 80.769958
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 110.637375
iter 10 value 93.765772
iter 20 value 90.371437
iter 30 value 86.655476
iter 40 value 84.795817
iter 50 value 83.239381
iter 60 value 82.553011
iter 70 value 82.109545
iter 80 value 82.017118
iter 90 value 81.619832
iter 100 value 81.244715
final value 81.244715
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.081660
iter 10 value 94.059365
iter 20 value 93.980450
iter 30 value 92.793359
iter 40 value 83.982362
iter 50 value 83.096192
iter 60 value 82.362664
iter 70 value 81.445895
iter 80 value 81.276884
iter 90 value 80.908408
iter 100 value 80.204016
final value 80.204016
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.773084
iter 10 value 92.414808
iter 20 value 88.666336
iter 30 value 84.696140
iter 40 value 82.065998
iter 50 value 81.234009
iter 60 value 80.902817
iter 70 value 80.642172
iter 80 value 80.573408
iter 90 value 80.510076
iter 100 value 80.474843
final value 80.474843
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.528695
iter 10 value 93.849068
iter 20 value 90.499244
iter 30 value 85.822044
iter 40 value 84.708270
iter 50 value 83.468578
iter 60 value 82.859027
iter 70 value 82.000568
iter 80 value 80.682128
iter 90 value 80.197497
iter 100 value 80.053240
final value 80.053240
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.553250
iter 10 value 93.735619
iter 20 value 93.633938
iter 30 value 86.938362
iter 40 value 85.034702
iter 50 value 81.867164
iter 60 value 81.089693
iter 70 value 80.339269
iter 80 value 79.992949
iter 90 value 79.830027
iter 100 value 79.782194
final value 79.782194
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.825131
iter 10 value 94.464270
iter 20 value 93.703652
iter 30 value 93.390294
iter 40 value 86.093494
iter 50 value 84.795457
iter 60 value 84.665650
iter 70 value 84.418557
iter 80 value 82.425118
iter 90 value 81.237644
iter 100 value 81.002818
final value 81.002818
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.161847
iter 10 value 93.455792
iter 20 value 92.339775
iter 30 value 91.958900
iter 40 value 86.335223
iter 50 value 85.628382
iter 60 value 85.029686
iter 70 value 84.651180
iter 80 value 83.937818
iter 90 value 83.225487
iter 100 value 81.799857
final value 81.799857
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 123.117384
iter 10 value 95.659501
iter 20 value 89.081698
iter 30 value 85.560351
iter 40 value 84.836751
iter 50 value 84.586027
iter 60 value 84.298646
iter 70 value 82.910698
iter 80 value 82.544108
iter 90 value 82.253891
iter 100 value 81.779475
final value 81.779475
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.427481
iter 10 value 93.879279
iter 20 value 89.131484
iter 30 value 86.890037
iter 40 value 85.727595
iter 50 value 83.804019
iter 60 value 82.721051
iter 70 value 82.161549
iter 80 value 81.951910
iter 90 value 81.769216
iter 100 value 81.619075
final value 81.619075
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.277207
final value 94.054322
converged
Fitting Repeat 2
# weights: 103
initial value 104.223032
final value 94.054697
converged
Fitting Repeat 3
# weights: 103
initial value 97.635219
iter 10 value 85.615587
iter 20 value 84.888958
iter 30 value 84.877248
iter 40 value 84.876823
final value 84.875958
converged
Fitting Repeat 4
# weights: 103
initial value 99.327706
final value 94.056247
converged
Fitting Repeat 5
# weights: 103
initial value 96.036402
iter 10 value 93.765297
iter 20 value 93.584540
iter 30 value 93.583518
final value 93.582774
converged
Fitting Repeat 1
# weights: 305
initial value 102.040034
iter 10 value 94.057979
iter 20 value 94.053040
iter 30 value 91.738915
iter 40 value 87.400798
iter 50 value 87.095753
iter 60 value 87.056084
iter 70 value 87.055019
iter 80 value 85.295867
iter 90 value 85.287374
iter 100 value 85.097125
final value 85.097125
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 93.444800
iter 10 value 92.548241
iter 20 value 85.532683
iter 30 value 84.954244
iter 40 value 84.272929
iter 50 value 84.234903
iter 60 value 84.231472
final value 84.230911
converged
Fitting Repeat 3
# weights: 305
initial value 115.132164
iter 10 value 94.057693
iter 20 value 94.044425
iter 30 value 89.110232
iter 40 value 84.092206
iter 50 value 82.817990
iter 60 value 82.651503
iter 70 value 80.504753
iter 80 value 79.781357
iter 90 value 79.477539
iter 100 value 79.288890
final value 79.288890
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.905681
iter 10 value 94.057534
iter 20 value 93.988382
iter 30 value 84.550869
iter 40 value 84.073598
iter 50 value 83.737868
iter 60 value 83.481194
iter 70 value 83.480351
iter 80 value 83.471027
iter 90 value 83.298382
iter 100 value 82.916281
final value 82.916281
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.861935
iter 10 value 93.587765
iter 20 value 93.583548
iter 30 value 92.642593
iter 40 value 85.236493
iter 50 value 84.941157
iter 60 value 84.940172
iter 70 value 84.939297
iter 80 value 84.929760
iter 90 value 84.926702
iter 100 value 84.592851
final value 84.592851
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.585884
iter 10 value 91.400745
iter 20 value 90.822148
iter 30 value 90.673234
iter 40 value 90.670289
iter 50 value 90.571594
iter 60 value 90.571092
iter 70 value 90.546511
iter 80 value 90.482314
iter 90 value 90.458517
iter 100 value 90.445258
final value 90.445258
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.793703
iter 10 value 93.997016
iter 20 value 93.880187
final value 93.583241
converged
Fitting Repeat 3
# weights: 507
initial value 126.093108
iter 10 value 93.590682
iter 20 value 93.582326
iter 30 value 87.452659
iter 40 value 85.282089
iter 50 value 85.026581
iter 60 value 82.449709
iter 70 value 81.994643
iter 80 value 81.028968
iter 90 value 80.453406
iter 100 value 79.688215
final value 79.688215
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 136.946137
iter 10 value 93.819561
iter 20 value 93.808556
iter 30 value 93.510386
iter 40 value 87.232683
iter 50 value 83.396882
iter 60 value 80.625514
iter 70 value 79.854638
iter 80 value 79.475300
iter 90 value 79.339726
iter 100 value 79.321974
final value 79.321974
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 96.958305
iter 10 value 93.590556
iter 20 value 93.353719
iter 30 value 86.854625
iter 40 value 86.834582
iter 50 value 86.813333
iter 60 value 86.669081
final value 86.668905
converged
Fitting Repeat 1
# weights: 103
initial value 103.327162
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.843518
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 98.467830
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.929032
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 99.348145
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 105.620090
final value 94.038251
converged
Fitting Repeat 2
# weights: 305
initial value 96.315854
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 108.282671
final value 94.038251
converged
Fitting Repeat 4
# weights: 305
initial value 102.051679
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 102.332342
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 99.623606
final value 94.038251
converged
Fitting Repeat 2
# weights: 507
initial value 110.028613
iter 10 value 94.133469
iter 20 value 94.052923
final value 94.052911
converged
Fitting Repeat 3
# weights: 507
initial value 121.037753
final value 94.038251
converged
Fitting Repeat 4
# weights: 507
initial value 99.769041
final value 94.052911
converged
Fitting Repeat 5
# weights: 507
initial value 96.544412
iter 10 value 92.312669
iter 20 value 83.323120
iter 30 value 82.982264
iter 40 value 82.979157
iter 40 value 82.979157
iter 40 value 82.979157
final value 82.979157
converged
Fitting Repeat 1
# weights: 103
initial value 109.051208
iter 10 value 94.144568
iter 20 value 94.052734
iter 30 value 93.965458
iter 40 value 93.522977
iter 50 value 85.424374
iter 60 value 84.210942
iter 70 value 83.988412
iter 80 value 83.314589
iter 90 value 82.494422
iter 100 value 82.270643
final value 82.270643
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 106.269675
iter 10 value 93.981950
iter 20 value 91.931913
iter 30 value 86.647924
iter 40 value 85.233636
iter 50 value 84.221773
iter 60 value 83.801716
iter 70 value 83.543853
iter 80 value 83.341673
iter 90 value 81.886281
iter 100 value 81.203550
final value 81.203550
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 102.118531
iter 10 value 94.032029
iter 20 value 86.793463
iter 30 value 85.552008
iter 40 value 85.045992
iter 50 value 84.580964
iter 60 value 84.334178
iter 70 value 83.208406
iter 80 value 82.399868
iter 90 value 82.370338
final value 82.370301
converged
Fitting Repeat 4
# weights: 103
initial value 96.397102
iter 10 value 89.680152
iter 20 value 85.756420
iter 30 value 85.018714
iter 40 value 83.713171
iter 50 value 83.259901
iter 60 value 82.754331
iter 70 value 82.721166
final value 82.721163
converged
Fitting Repeat 5
# weights: 103
initial value 98.026939
iter 10 value 92.246678
iter 20 value 86.526814
iter 30 value 85.123646
iter 40 value 84.587028
iter 50 value 83.494639
iter 60 value 82.845624
iter 70 value 82.370390
final value 82.370301
converged
Fitting Repeat 1
# weights: 305
initial value 106.231529
iter 10 value 94.067084
iter 20 value 93.119587
iter 30 value 85.180768
iter 40 value 84.144431
iter 50 value 81.659128
iter 60 value 81.249903
iter 70 value 80.388819
iter 80 value 79.945105
iter 90 value 79.914073
iter 100 value 79.907486
final value 79.907486
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 107.852310
iter 10 value 95.557924
iter 20 value 94.090124
iter 30 value 91.329762
iter 40 value 85.245562
iter 50 value 83.755445
iter 60 value 81.072605
iter 70 value 80.867898
iter 80 value 80.003031
iter 90 value 79.580531
iter 100 value 79.363226
final value 79.363226
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.562346
iter 10 value 94.331135
iter 20 value 94.055157
iter 30 value 89.161678
iter 40 value 88.556043
iter 50 value 88.116414
iter 60 value 86.836748
iter 70 value 83.876680
iter 80 value 83.504342
iter 90 value 82.949606
iter 100 value 81.192279
final value 81.192279
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.572510
iter 10 value 94.045777
iter 20 value 85.708103
iter 30 value 84.258296
iter 40 value 83.790626
iter 50 value 83.647452
iter 60 value 82.936457
iter 70 value 80.778291
iter 80 value 79.748521
iter 90 value 79.692237
iter 100 value 79.645244
final value 79.645244
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.916654
iter 10 value 95.554830
iter 20 value 86.636573
iter 30 value 84.961033
iter 40 value 82.636437
iter 50 value 81.851825
iter 60 value 81.615858
iter 70 value 81.282805
iter 80 value 81.169417
iter 90 value 81.166832
iter 100 value 81.144181
final value 81.144181
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.866093
iter 10 value 93.823760
iter 20 value 87.533763
iter 30 value 85.563236
iter 40 value 82.784755
iter 50 value 81.229511
iter 60 value 80.478689
iter 70 value 79.832106
iter 80 value 79.588493
iter 90 value 79.294463
iter 100 value 79.074806
final value 79.074806
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.331134
iter 10 value 89.755239
iter 20 value 85.766796
iter 30 value 85.108966
iter 40 value 84.483411
iter 50 value 83.394347
iter 60 value 82.957676
iter 70 value 82.605054
iter 80 value 81.772097
iter 90 value 80.976155
iter 100 value 80.405276
final value 80.405276
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.532594
iter 10 value 94.357524
iter 20 value 91.372171
iter 30 value 84.899207
iter 40 value 83.352601
iter 50 value 83.194262
iter 60 value 81.637847
iter 70 value 80.690792
iter 80 value 79.986431
iter 90 value 79.646258
iter 100 value 79.273971
final value 79.273971
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 102.659448
iter 10 value 94.181089
iter 20 value 86.819024
iter 30 value 84.437380
iter 40 value 83.317984
iter 50 value 82.200538
iter 60 value 81.459213
iter 70 value 80.930842
iter 80 value 80.811424
iter 90 value 80.297805
iter 100 value 79.920474
final value 79.920474
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 111.123992
iter 10 value 93.402146
iter 20 value 91.361565
iter 30 value 85.603140
iter 40 value 84.272918
iter 50 value 83.891065
iter 60 value 83.350902
iter 70 value 82.858067
iter 80 value 81.578902
iter 90 value 80.361279
iter 100 value 79.820792
final value 79.820792
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.723724
final value 94.054510
converged
Fitting Repeat 2
# weights: 103
initial value 97.064131
final value 94.054368
converged
Fitting Repeat 3
# weights: 103
initial value 100.312969
iter 10 value 94.054548
iter 20 value 94.052695
iter 30 value 93.625098
iter 40 value 91.054194
iter 50 value 91.011148
final value 91.010656
converged
Fitting Repeat 4
# weights: 103
initial value 101.488711
final value 94.054357
converged
Fitting Repeat 5
# weights: 103
initial value 99.925099
iter 10 value 93.429036
iter 20 value 93.373502
iter 30 value 85.565081
iter 40 value 85.379970
iter 50 value 85.378203
final value 85.378163
converged
Fitting Repeat 1
# weights: 305
initial value 113.478846
iter 10 value 94.042197
iter 20 value 90.054909
iter 30 value 86.900272
iter 30 value 86.900272
iter 30 value 86.900272
final value 86.900272
converged
Fitting Repeat 2
# weights: 305
initial value 99.509389
iter 10 value 94.057426
iter 20 value 93.957653
iter 30 value 86.331446
iter 40 value 85.335471
iter 50 value 84.957563
final value 84.951297
converged
Fitting Repeat 3
# weights: 305
initial value 95.796205
iter 10 value 94.057728
final value 94.053073
converged
Fitting Repeat 4
# weights: 305
initial value 99.896888
iter 10 value 94.043468
iter 20 value 93.835522
iter 30 value 89.421663
iter 40 value 88.654915
iter 50 value 88.544667
iter 60 value 88.439606
iter 70 value 88.278763
iter 80 value 88.277287
iter 90 value 88.231021
iter 100 value 83.667234
final value 83.667234
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.509466
iter 10 value 94.057180
iter 20 value 93.616035
final value 93.372543
converged
Fitting Repeat 1
# weights: 507
initial value 117.700609
iter 10 value 94.062304
iter 20 value 94.051608
iter 30 value 85.883511
iter 40 value 83.881879
iter 50 value 83.868664
iter 60 value 83.593590
iter 70 value 83.292078
final value 83.290406
converged
Fitting Repeat 2
# weights: 507
initial value 95.079137
iter 10 value 94.047058
iter 20 value 94.045825
iter 30 value 94.034895
iter 40 value 90.557129
iter 50 value 90.448350
iter 60 value 84.383687
iter 70 value 82.355820
iter 80 value 82.007778
iter 90 value 81.970940
final value 81.970629
converged
Fitting Repeat 3
# weights: 507
initial value 100.554269
iter 10 value 93.714582
iter 20 value 92.836580
iter 30 value 87.844211
iter 40 value 87.829554
iter 50 value 86.108966
iter 60 value 85.882232
iter 70 value 85.342850
iter 80 value 83.891833
iter 90 value 81.180053
iter 100 value 81.067935
final value 81.067935
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 97.047041
iter 10 value 92.212498
iter 20 value 91.482809
iter 30 value 91.439271
iter 40 value 91.396276
final value 91.396069
converged
Fitting Repeat 5
# weights: 507
initial value 105.749311
iter 10 value 94.059989
iter 20 value 88.959179
iter 30 value 86.900566
final value 86.900555
converged
Fitting Repeat 1
# weights: 103
initial value 96.591186
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.647089
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.403405
iter 10 value 94.442543
final value 94.442073
converged
Fitting Repeat 4
# weights: 103
initial value 119.759732
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.741934
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 99.200881
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 101.047996
iter 10 value 94.482480
final value 94.482478
converged
Fitting Repeat 3
# weights: 305
initial value 101.025562
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 104.771609
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 108.889167
iter 10 value 94.291299
iter 10 value 94.291299
iter 10 value 94.291299
final value 94.291299
converged
Fitting Repeat 1
# weights: 507
initial value 124.414148
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 96.908432
final value 94.467391
converged
Fitting Repeat 3
# weights: 507
initial value 105.721491
final value 94.482149
converged
Fitting Repeat 4
# weights: 507
initial value 97.351445
iter 10 value 94.467392
iter 10 value 94.467391
iter 10 value 94.467391
final value 94.467391
converged
Fitting Repeat 5
# weights: 507
initial value 99.303998
iter 10 value 94.468210
final value 94.467391
converged
Fitting Repeat 1
# weights: 103
initial value 97.916254
iter 10 value 94.480378
iter 20 value 91.726997
iter 30 value 86.399114
iter 40 value 83.609980
iter 50 value 83.032119
iter 60 value 82.490063
iter 70 value 82.280016
iter 80 value 81.590099
iter 90 value 81.533821
iter 90 value 81.533821
final value 81.533821
converged
Fitting Repeat 2
# weights: 103
initial value 104.589241
iter 10 value 94.492913
iter 20 value 94.265304
iter 30 value 93.250213
iter 40 value 91.766029
iter 50 value 86.705684
iter 60 value 83.959804
iter 70 value 83.745948
iter 80 value 83.565080
final value 83.564308
converged
Fitting Repeat 3
# weights: 103
initial value 108.432915
iter 10 value 94.288734
iter 20 value 89.629464
iter 30 value 86.805023
iter 40 value 86.187190
iter 50 value 83.878330
iter 60 value 83.419397
iter 70 value 83.353561
final value 83.353379
converged
Fitting Repeat 4
# weights: 103
initial value 99.076655
iter 10 value 93.333495
iter 20 value 86.376674
iter 30 value 84.604750
iter 40 value 84.434941
iter 50 value 84.395437
iter 60 value 83.734647
iter 70 value 83.617537
final value 83.610812
converged
Fitting Repeat 5
# weights: 103
initial value 96.833957
iter 10 value 94.523362
iter 20 value 93.889356
iter 30 value 92.779197
iter 40 value 87.671786
iter 50 value 87.513232
iter 60 value 87.455451
iter 70 value 86.817118
iter 80 value 84.669584
iter 90 value 83.468059
iter 100 value 83.414373
final value 83.414373
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.930690
iter 10 value 94.797154
iter 20 value 93.191823
iter 30 value 89.585378
iter 40 value 87.589578
iter 50 value 87.267744
iter 60 value 84.889350
iter 70 value 83.269203
iter 80 value 82.234920
iter 90 value 81.436648
iter 100 value 80.716970
final value 80.716970
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 115.529185
iter 10 value 95.333678
iter 20 value 85.853573
iter 30 value 84.228939
iter 40 value 84.044020
iter 50 value 82.081676
iter 60 value 81.737236
iter 70 value 81.211125
iter 80 value 80.229245
iter 90 value 79.755272
iter 100 value 79.700957
final value 79.700957
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.396171
iter 10 value 93.027125
iter 20 value 86.536793
iter 30 value 85.918141
iter 40 value 85.242058
iter 50 value 83.465355
iter 60 value 82.913613
iter 70 value 82.106707
iter 80 value 81.824013
iter 90 value 81.740727
iter 100 value 81.685333
final value 81.685333
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.911360
iter 10 value 94.594987
iter 20 value 90.805340
iter 30 value 86.548625
iter 40 value 84.651204
iter 50 value 83.490808
iter 60 value 83.296225
iter 70 value 83.277659
iter 80 value 82.978090
iter 90 value 82.191934
iter 100 value 81.751933
final value 81.751933
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.210429
iter 10 value 94.435907
iter 20 value 86.067156
iter 30 value 84.674823
iter 40 value 84.137291
iter 50 value 83.898118
iter 60 value 83.307646
iter 70 value 82.109409
iter 80 value 82.000331
iter 90 value 81.934221
iter 100 value 81.892918
final value 81.892918
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 119.920355
iter 10 value 95.297999
iter 20 value 89.050864
iter 30 value 86.450923
iter 40 value 85.471081
iter 50 value 84.142876
iter 60 value 83.538311
iter 70 value 81.303388
iter 80 value 80.510712
iter 90 value 80.189212
iter 100 value 79.817830
final value 79.817830
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 112.077248
iter 10 value 98.200133
iter 20 value 86.954908
iter 30 value 84.536188
iter 40 value 80.817096
iter 50 value 80.225166
iter 60 value 80.107878
iter 70 value 79.555706
iter 80 value 79.177369
iter 90 value 79.068679
iter 100 value 79.050331
final value 79.050331
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 140.320851
iter 10 value 94.920941
iter 20 value 92.260663
iter 30 value 87.276237
iter 40 value 86.137412
iter 50 value 85.639470
iter 60 value 85.387792
iter 70 value 83.742760
iter 80 value 82.637166
iter 90 value 82.471601
iter 100 value 82.379799
final value 82.379799
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.412531
iter 10 value 94.745934
iter 20 value 94.447304
iter 30 value 85.614417
iter 40 value 83.939801
iter 50 value 83.354955
iter 60 value 81.157789
iter 70 value 80.304716
iter 80 value 79.970284
iter 90 value 79.798255
iter 100 value 79.606602
final value 79.606602
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 116.365989
iter 10 value 88.466028
iter 20 value 86.334377
iter 30 value 84.367445
iter 40 value 82.281920
iter 50 value 80.268066
iter 60 value 80.061699
iter 70 value 79.989352
iter 80 value 79.887838
iter 90 value 79.834512
iter 100 value 79.661681
final value 79.661681
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 104.875448
final value 94.486005
converged
Fitting Repeat 2
# weights: 103
initial value 96.185426
iter 10 value 94.485922
final value 94.484492
converged
Fitting Repeat 3
# weights: 103
initial value 106.197218
final value 94.485870
converged
Fitting Repeat 4
# weights: 103
initial value 95.625899
final value 94.485867
converged
Fitting Repeat 5
# weights: 103
initial value 100.924749
final value 94.485766
converged
Fitting Repeat 1
# weights: 305
initial value 110.020885
iter 10 value 94.488970
iter 20 value 94.484462
iter 30 value 94.383627
iter 40 value 92.211154
iter 50 value 92.185791
iter 60 value 90.096158
iter 70 value 89.890245
iter 80 value 89.885427
final value 89.883189
converged
Fitting Repeat 2
# weights: 305
initial value 110.015935
iter 10 value 94.434063
iter 20 value 93.574143
iter 30 value 85.526071
iter 40 value 85.522567
iter 50 value 85.476818
iter 60 value 84.739389
iter 70 value 84.622927
final value 84.622895
converged
Fitting Repeat 3
# weights: 305
initial value 102.542499
iter 10 value 94.472323
iter 20 value 94.467583
iter 30 value 86.817421
final value 86.509760
converged
Fitting Repeat 4
# weights: 305
initial value 107.014867
iter 10 value 94.489579
iter 20 value 94.484643
iter 30 value 87.264563
iter 40 value 85.039894
iter 50 value 84.919555
iter 60 value 84.919465
final value 84.918549
converged
Fitting Repeat 5
# weights: 305
initial value 100.051387
iter 10 value 94.489195
iter 20 value 94.484169
iter 30 value 84.168960
iter 40 value 82.317007
iter 50 value 82.315938
final value 82.315931
converged
Fitting Repeat 1
# weights: 507
initial value 126.090895
iter 10 value 94.477048
iter 20 value 94.472080
iter 30 value 94.262859
iter 40 value 93.378939
iter 50 value 85.457587
iter 60 value 85.139064
iter 70 value 85.135322
iter 80 value 85.134957
iter 90 value 84.359112
iter 100 value 82.728500
final value 82.728500
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 95.049472
iter 10 value 94.449860
iter 20 value 94.397892
iter 30 value 86.943294
iter 40 value 86.728697
iter 50 value 86.658026
iter 60 value 84.989387
iter 70 value 84.850800
iter 80 value 84.403380
iter 90 value 80.687150
iter 100 value 79.553083
final value 79.553083
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 101.514030
iter 10 value 94.491787
iter 20 value 94.086439
iter 30 value 88.593011
iter 40 value 84.000522
iter 50 value 83.747051
iter 60 value 83.499740
final value 83.498072
converged
Fitting Repeat 4
# weights: 507
initial value 94.773710
iter 10 value 94.096919
iter 20 value 94.089349
final value 94.089277
converged
Fitting Repeat 5
# weights: 507
initial value 109.367581
iter 10 value 94.476335
iter 20 value 94.470918
iter 30 value 94.469384
iter 40 value 94.221229
iter 50 value 83.627042
iter 60 value 81.024530
iter 70 value 79.194898
iter 80 value 77.971127
iter 90 value 77.711757
iter 100 value 77.691790
final value 77.691790
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 106.248960
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.785787
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.150457
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 101.867826
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 100.166576
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.351223
final value 93.772973
converged
Fitting Repeat 2
# weights: 305
initial value 100.570683
iter 10 value 93.772973
iter 10 value 93.772973
iter 10 value 93.772973
final value 93.772973
converged
Fitting Repeat 3
# weights: 305
initial value 106.141434
iter 10 value 93.772976
final value 93.772973
converged
Fitting Repeat 4
# weights: 305
initial value 96.549681
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 101.895334
iter 10 value 94.313012
iter 20 value 93.438628
final value 93.291715
converged
Fitting Repeat 1
# weights: 507
initial value 93.772209
iter 10 value 83.398502
final value 83.377495
converged
Fitting Repeat 2
# weights: 507
initial value 96.314286
iter 10 value 93.690645
final value 93.690592
converged
Fitting Repeat 3
# weights: 507
initial value 104.066791
final value 94.052435
converged
Fitting Repeat 4
# weights: 507
initial value 105.769993
final value 94.484206
converged
Fitting Repeat 5
# weights: 507
initial value 116.563475
iter 10 value 93.773155
final value 93.772973
converged
Fitting Repeat 1
# weights: 103
initial value 108.304927
iter 10 value 94.494185
iter 20 value 93.987011
iter 30 value 85.342652
iter 40 value 84.442959
iter 50 value 84.255274
iter 60 value 83.959071
iter 70 value 83.917573
final value 83.917300
converged
Fitting Repeat 2
# weights: 103
initial value 100.878439
iter 10 value 94.406691
iter 20 value 84.268623
iter 30 value 83.809159
iter 40 value 83.706909
iter 50 value 83.704160
iter 50 value 83.704159
iter 50 value 83.704159
final value 83.704159
converged
Fitting Repeat 3
# weights: 103
initial value 96.626584
iter 10 value 90.461698
iter 20 value 85.153139
iter 30 value 83.578376
iter 40 value 83.120989
iter 50 value 83.012611
iter 60 value 82.954287
final value 82.954182
converged
Fitting Repeat 4
# weights: 103
initial value 106.727258
iter 10 value 94.284506
iter 20 value 84.948822
iter 30 value 84.227095
iter 40 value 83.944321
iter 50 value 83.917995
final value 83.917300
converged
Fitting Repeat 5
# weights: 103
initial value 98.948659
iter 10 value 94.487752
iter 20 value 93.184412
iter 30 value 93.135361
iter 40 value 93.091068
iter 50 value 92.061779
iter 60 value 88.284256
iter 70 value 87.987686
iter 80 value 86.349179
iter 90 value 83.397032
iter 100 value 82.237828
final value 82.237828
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 111.779483
iter 10 value 94.491830
iter 20 value 92.117253
iter 30 value 87.134644
iter 40 value 86.281443
iter 50 value 82.830908
iter 60 value 80.279036
iter 70 value 79.971917
iter 80 value 79.596637
iter 90 value 79.551078
iter 100 value 79.413619
final value 79.413619
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.361188
iter 10 value 96.305002
iter 20 value 91.419414
iter 30 value 87.461031
iter 40 value 84.115125
iter 50 value 82.029927
iter 60 value 81.854566
iter 70 value 81.256912
iter 80 value 81.084507
iter 90 value 80.977954
iter 100 value 80.956919
final value 80.956919
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.886921
iter 10 value 94.354839
iter 20 value 93.620359
iter 30 value 88.945047
iter 40 value 84.881931
iter 50 value 83.501461
iter 60 value 82.959955
iter 70 value 82.664244
iter 80 value 82.566730
iter 90 value 82.473211
iter 100 value 82.390249
final value 82.390249
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.787236
iter 10 value 95.139357
iter 20 value 90.276803
iter 30 value 86.773785
iter 40 value 85.840699
iter 50 value 85.612021
iter 60 value 85.100085
iter 70 value 82.376054
iter 80 value 80.816786
iter 90 value 80.127260
iter 100 value 79.670388
final value 79.670388
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 118.960872
iter 10 value 94.497155
iter 20 value 93.484840
iter 30 value 86.892695
iter 40 value 86.337312
iter 50 value 83.095585
iter 60 value 80.596075
iter 70 value 79.886415
iter 80 value 79.735585
iter 90 value 79.600851
iter 100 value 79.511681
final value 79.511681
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.913353
iter 10 value 93.871062
iter 20 value 91.070686
iter 30 value 89.720040
iter 40 value 89.072171
iter 50 value 84.489747
iter 60 value 81.553156
iter 70 value 80.284228
iter 80 value 80.046475
iter 90 value 79.976838
iter 100 value 79.693992
final value 79.693992
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 119.547230
iter 10 value 93.899820
iter 20 value 86.411217
iter 30 value 84.964727
iter 40 value 83.840086
iter 50 value 81.476292
iter 60 value 81.215789
iter 70 value 80.887604
iter 80 value 80.545857
iter 90 value 80.102378
iter 100 value 79.932537
final value 79.932537
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 119.905468
iter 10 value 95.472714
iter 20 value 94.368149
iter 30 value 84.811287
iter 40 value 83.890895
iter 50 value 81.758054
iter 60 value 80.755660
iter 70 value 80.600583
iter 80 value 80.508480
iter 90 value 80.013707
iter 100 value 79.618630
final value 79.618630
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 116.266576
iter 10 value 93.408241
iter 20 value 84.874489
iter 30 value 82.852391
iter 40 value 82.418996
iter 50 value 82.218364
iter 60 value 81.945161
iter 70 value 81.382524
iter 80 value 80.799700
iter 90 value 79.771752
iter 100 value 79.619912
final value 79.619912
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.019508
iter 10 value 94.549599
iter 20 value 92.547053
iter 30 value 91.951332
iter 40 value 90.128573
iter 50 value 83.383339
iter 60 value 82.899275
iter 70 value 81.092545
iter 80 value 80.366999
iter 90 value 80.133821
iter 100 value 80.019776
final value 80.019776
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 105.191351
iter 10 value 92.999693
iter 20 value 92.999065
iter 20 value 92.999065
final value 92.999065
converged
Fitting Repeat 2
# weights: 103
initial value 94.653998
final value 94.485856
converged
Fitting Repeat 3
# weights: 103
initial value 101.487336
final value 94.485931
converged
Fitting Repeat 4
# weights: 103
initial value 98.203232
iter 10 value 94.485979
final value 94.484223
converged
Fitting Repeat 5
# weights: 103
initial value 96.848997
final value 94.486148
converged
Fitting Repeat 1
# weights: 305
initial value 100.246960
iter 10 value 94.489086
iter 20 value 94.484235
iter 30 value 93.417706
final value 93.417705
converged
Fitting Repeat 2
# weights: 305
initial value 112.791335
iter 10 value 94.057391
iter 20 value 92.620954
iter 30 value 84.289240
iter 40 value 82.776496
iter 50 value 82.070421
iter 60 value 81.866607
iter 70 value 81.831792
iter 80 value 81.831257
final value 81.830636
converged
Fitting Repeat 3
# weights: 305
initial value 106.384020
iter 10 value 94.489115
iter 20 value 94.410904
iter 30 value 92.997659
iter 30 value 92.997658
iter 30 value 92.997658
final value 92.997658
converged
Fitting Repeat 4
# weights: 305
initial value 96.495786
iter 10 value 93.778454
iter 20 value 93.294793
iter 30 value 92.997691
iter 40 value 92.872932
final value 92.870208
converged
Fitting Repeat 5
# weights: 305
initial value 95.676407
iter 10 value 93.778084
iter 20 value 93.761527
iter 30 value 92.946236
iter 40 value 82.275062
iter 50 value 80.517048
iter 60 value 80.108127
iter 70 value 79.802528
iter 80 value 79.756638
iter 90 value 79.750619
final value 79.750614
converged
Fitting Repeat 1
# weights: 507
initial value 97.328753
iter 10 value 93.782066
iter 20 value 93.778642
iter 30 value 93.774310
iter 30 value 93.774310
iter 30 value 93.774310
final value 93.774310
converged
Fitting Repeat 2
# weights: 507
initial value 112.243458
iter 10 value 94.492366
iter 20 value 94.446425
iter 30 value 93.005690
iter 40 value 92.914548
iter 50 value 92.864261
iter 60 value 92.862105
iter 70 value 92.806792
iter 80 value 92.787266
iter 90 value 92.786708
iter 100 value 92.786015
final value 92.786015
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.043090
iter 10 value 94.492071
iter 20 value 90.250250
iter 30 value 86.945865
iter 40 value 86.643767
iter 50 value 84.646129
iter 60 value 81.135671
iter 70 value 80.137491
iter 80 value 79.683415
iter 90 value 79.585862
iter 100 value 79.585436
final value 79.585436
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.834214
iter 10 value 94.492269
iter 20 value 94.420800
final value 93.417606
converged
Fitting Repeat 5
# weights: 507
initial value 131.538479
iter 10 value 93.508544
iter 20 value 92.236383
iter 30 value 92.196701
iter 40 value 92.123955
final value 92.123140
converged
Fitting Repeat 1
# weights: 103
initial value 95.259884
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 98.422929
final value 94.214007
converged
Fitting Repeat 3
# weights: 103
initial value 96.551105
final value 94.354396
converged
Fitting Repeat 4
# weights: 103
initial value 102.492454
iter 10 value 94.002999
iter 10 value 94.002999
iter 10 value 94.002999
final value 94.002999
converged
Fitting Repeat 5
# weights: 103
initial value 95.031142
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 105.374043
iter 10 value 94.145902
final value 94.144481
converged
Fitting Repeat 2
# weights: 305
initial value 97.303736
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 102.335170
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 106.311912
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 108.701408
final value 94.354395
converged
Fitting Repeat 1
# weights: 507
initial value 109.895050
iter 10 value 94.323805
final value 94.270000
converged
Fitting Repeat 2
# weights: 507
initial value 116.719958
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 101.658283
iter 10 value 91.469344
final value 91.467949
converged
Fitting Repeat 4
# weights: 507
initial value 98.505190
final value 94.354396
converged
Fitting Repeat 5
# weights: 507
initial value 105.927732
iter 10 value 93.464299
final value 93.464287
converged
Fitting Repeat 1
# weights: 103
initial value 98.030304
iter 10 value 93.328007
iter 20 value 93.149060
iter 30 value 88.783088
iter 40 value 84.454657
iter 50 value 83.387757
iter 60 value 83.002811
iter 70 value 82.898767
iter 80 value 82.836595
final value 82.831752
converged
Fitting Repeat 2
# weights: 103
initial value 111.799496
iter 10 value 92.902092
iter 20 value 86.521641
iter 30 value 86.403882
iter 40 value 86.298290
iter 50 value 86.061340
iter 60 value 86.029899
final value 86.025235
converged
Fitting Repeat 3
# weights: 103
initial value 100.093083
iter 10 value 94.412944
iter 20 value 91.689705
iter 30 value 88.893736
iter 40 value 87.196401
iter 50 value 86.157787
iter 60 value 83.542309
iter 70 value 82.794879
iter 80 value 82.766429
final value 82.752775
converged
Fitting Repeat 4
# weights: 103
initial value 98.103884
iter 10 value 94.488548
iter 20 value 91.492355
iter 30 value 90.023575
iter 40 value 88.402287
iter 50 value 86.355104
iter 60 value 86.271778
iter 70 value 86.038173
iter 80 value 86.025240
final value 86.025235
converged
Fitting Repeat 5
# weights: 103
initial value 108.571796
iter 10 value 94.427090
iter 20 value 88.238308
iter 30 value 86.499658
iter 40 value 86.095111
iter 50 value 86.038588
iter 60 value 86.025235
iter 60 value 86.025235
iter 60 value 86.025235
final value 86.025235
converged
Fitting Repeat 1
# weights: 305
initial value 106.069422
iter 10 value 94.545424
iter 20 value 94.370567
iter 30 value 91.112669
iter 40 value 85.420587
iter 50 value 82.690868
iter 60 value 82.350211
iter 70 value 81.987698
iter 80 value 81.671212
iter 90 value 81.635088
iter 100 value 81.576367
final value 81.576367
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.196662
iter 10 value 94.699792
iter 20 value 94.148480
iter 30 value 94.006838
iter 40 value 90.209129
iter 50 value 87.328127
iter 60 value 86.128360
iter 70 value 86.066192
iter 80 value 84.904984
iter 90 value 84.744654
iter 100 value 84.639711
final value 84.639711
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 111.299554
iter 10 value 94.104349
iter 20 value 88.118786
iter 30 value 87.018481
iter 40 value 86.442681
iter 50 value 85.772491
iter 60 value 85.644262
iter 70 value 85.589350
iter 80 value 85.111700
iter 90 value 84.524894
iter 100 value 81.923585
final value 81.923585
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.342912
iter 10 value 94.502199
iter 20 value 91.570900
iter 30 value 90.247070
iter 40 value 88.754762
iter 50 value 87.189520
iter 60 value 86.064421
iter 70 value 83.864725
iter 80 value 82.587036
iter 90 value 82.387527
iter 100 value 82.002988
final value 82.002988
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.042035
iter 10 value 94.521740
iter 20 value 93.201977
iter 30 value 90.630565
iter 40 value 85.929804
iter 50 value 83.776215
iter 60 value 83.201743
iter 70 value 83.082426
iter 80 value 83.000198
iter 90 value 82.987534
iter 100 value 82.889561
final value 82.889561
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.860441
iter 10 value 94.760197
iter 20 value 87.634366
iter 30 value 87.086565
iter 40 value 84.858682
iter 50 value 82.641382
iter 60 value 82.433176
iter 70 value 82.080959
iter 80 value 81.630667
iter 90 value 81.492783
iter 100 value 81.478222
final value 81.478222
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 124.967652
iter 10 value 97.533148
iter 20 value 88.171854
iter 30 value 84.897742
iter 40 value 84.064014
iter 50 value 83.351127
iter 60 value 82.444007
iter 70 value 81.874081
iter 80 value 81.489747
iter 90 value 81.387665
iter 100 value 81.292268
final value 81.292268
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.243938
iter 10 value 94.924136
iter 20 value 85.460804
iter 30 value 84.949173
iter 40 value 84.233814
iter 50 value 83.095116
iter 60 value 82.829412
iter 70 value 82.077165
iter 80 value 81.968945
iter 90 value 81.935722
iter 100 value 81.914164
final value 81.914164
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 135.099481
iter 10 value 96.406194
iter 20 value 94.418768
iter 30 value 88.682877
iter 40 value 87.263800
iter 50 value 83.317650
iter 60 value 82.117457
iter 70 value 81.922249
iter 80 value 81.797495
iter 90 value 81.507022
iter 100 value 81.258779
final value 81.258779
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 108.215144
iter 10 value 90.230701
iter 20 value 87.523807
iter 30 value 85.081513
iter 40 value 83.705799
iter 50 value 83.248017
iter 60 value 82.532017
iter 70 value 82.149279
iter 80 value 81.970818
iter 90 value 81.799660
iter 100 value 81.753475
final value 81.753475
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.279583
final value 94.485822
converged
Fitting Repeat 2
# weights: 103
initial value 103.540766
final value 94.485901
converged
Fitting Repeat 3
# weights: 103
initial value 95.913263
final value 94.485940
converged
Fitting Repeat 4
# weights: 103
initial value 111.241678
iter 10 value 94.356191
iter 20 value 94.221460
iter 30 value 93.188815
final value 92.614379
converged
Fitting Repeat 5
# weights: 103
initial value 96.168282
final value 94.485891
converged
Fitting Repeat 1
# weights: 305
initial value 96.711160
iter 10 value 94.489215
iter 20 value 94.484235
iter 30 value 93.806970
iter 40 value 86.800741
iter 50 value 86.782234
iter 60 value 86.768926
iter 70 value 85.729454
iter 80 value 85.126704
iter 90 value 84.970848
iter 100 value 84.823860
final value 84.823860
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 95.168428
iter 10 value 94.489083
iter 20 value 94.232120
iter 30 value 87.215010
iter 40 value 85.723948
iter 50 value 84.154671
iter 60 value 84.152130
iter 70 value 84.119920
iter 80 value 84.117397
iter 90 value 82.962899
iter 100 value 82.460710
final value 82.460710
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.898803
iter 10 value 94.351948
iter 20 value 94.324742
iter 30 value 94.319045
iter 40 value 88.379519
iter 50 value 87.373578
iter 60 value 87.288516
iter 70 value 83.373791
iter 80 value 82.395407
iter 90 value 82.394733
iter 100 value 82.369994
final value 82.369994
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 110.766302
iter 10 value 94.488645
iter 20 value 91.690357
iter 30 value 87.843249
final value 87.796053
converged
Fitting Repeat 5
# weights: 305
initial value 104.632052
iter 10 value 94.488687
iter 20 value 94.339586
final value 93.568324
converged
Fitting Repeat 1
# weights: 507
initial value 106.572882
iter 10 value 93.123579
iter 20 value 92.800351
iter 30 value 92.732505
iter 40 value 92.698321
iter 50 value 92.615857
iter 60 value 92.357912
iter 70 value 92.088646
iter 80 value 86.918322
iter 90 value 85.658841
iter 100 value 85.017138
final value 85.017138
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 96.261330
iter 10 value 94.359427
iter 20 value 94.174265
iter 30 value 93.969221
iter 40 value 91.231944
iter 50 value 90.853375
iter 60 value 90.793725
iter 70 value 90.589772
iter 80 value 90.581201
iter 90 value 90.517915
iter 100 value 86.987762
final value 86.987762
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.828039
iter 10 value 94.491957
iter 20 value 94.251328
iter 30 value 88.874113
iter 40 value 88.768975
iter 50 value 87.812704
iter 60 value 87.791233
iter 70 value 84.888324
iter 80 value 84.887125
iter 90 value 84.883619
iter 100 value 84.498936
final value 84.498936
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 100.555095
iter 10 value 94.362060
iter 20 value 92.538885
iter 30 value 85.222868
iter 40 value 85.167920
final value 85.167763
converged
Fitting Repeat 5
# weights: 507
initial value 99.431161
iter 10 value 94.492348
iter 20 value 93.265974
iter 30 value 91.464582
iter 30 value 91.464581
iter 30 value 91.464581
final value 91.464581
converged
Fitting Repeat 1
# weights: 305
initial value 123.907565
iter 10 value 117.894969
final value 117.890430
converged
Fitting Repeat 2
# weights: 305
initial value 121.289210
iter 10 value 117.748129
iter 20 value 108.028245
iter 30 value 106.365120
iter 40 value 106.260029
iter 50 value 105.918939
iter 60 value 105.918440
final value 105.913600
converged
Fitting Repeat 3
# weights: 305
initial value 124.028598
iter 10 value 117.857291
iter 20 value 117.176693
iter 30 value 116.966635
iter 40 value 107.712858
iter 50 value 107.672942
iter 60 value 107.332017
iter 70 value 104.304555
iter 80 value 104.295189
iter 90 value 104.264777
iter 100 value 104.261042
final value 104.261042
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 120.953704
iter 10 value 110.759344
iter 20 value 108.421920
iter 30 value 106.844939
iter 40 value 106.833632
iter 50 value 106.830732
final value 106.828924
converged
Fitting Repeat 5
# weights: 305
initial value 119.128017
iter 10 value 117.764213
iter 20 value 117.760542
iter 30 value 117.719323
iter 40 value 116.174723
iter 50 value 105.728041
iter 60 value 105.408114
iter 70 value 104.674121
iter 80 value 104.670639
final value 104.670267
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 -- Tue Aug 12 03:20:34 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
44.78 1.53 117.34
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 35.50 | 2.18 | 37.71 | |
| FreqInteractors | 0.22 | 0.01 | 0.25 | |
| calculateAAC | 0.06 | 0.00 | 0.06 | |
| calculateAutocor | 0.47 | 0.11 | 0.58 | |
| calculateCTDC | 0.08 | 0.00 | 0.08 | |
| calculateCTDD | 0.74 | 0.05 | 0.78 | |
| calculateCTDT | 0.38 | 0.01 | 0.40 | |
| calculateCTriad | 0.43 | 0.02 | 0.45 | |
| calculateDC | 0.13 | 0.00 | 0.12 | |
| calculateF | 0.36 | 0.03 | 0.39 | |
| calculateKSAAP | 0.14 | 0.00 | 0.14 | |
| calculateQD_Sm | 2.05 | 0.19 | 2.24 | |
| calculateTC | 1.73 | 0.09 | 1.83 | |
| calculateTC_Sm | 0.37 | 0.02 | 0.40 | |
| corr_plot | 34.85 | 1.79 | 36.66 | |
| enrichfindP | 0.64 | 0.10 | 12.89 | |
| enrichfind_hp | 0.06 | 0.03 | 1.05 | |
| enrichplot | 0.44 | 0.00 | 0.43 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.02 | 0.03 | 2.08 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.08 | 0.00 | 0.08 | |
| pred_ensembel | 14.42 | 0.31 | 13.17 | |
| var_imp | 35.67 | 1.31 | 36.98 | |