Matineh Rahmatbakhsh
| Snapshot Date: 2025-03-31 13:00 -0400 (Mon, 31 Mar 2025) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_20 |
| git_last_commit: ce9e305 |
| git_last_commit_date: 2024-10-29 11:04:11 -0400 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-04-02 19:30 -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: F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.12.0.tar.gz |
| StartedAt: 2025-04-01 02:30:55 -0400 (Tue, 01 Apr 2025) |
| EndedAt: 2025-04-01 02:37:06 -0400 (Tue, 01 Apr 2025) |
| EllapsedTime: 370.7 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck'
* using R version 4.4.3 (2025-02-28 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 13.3.0
GNU Fortran (GCC) 13.3.0
* 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 '1.12.0'
* 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 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 ... 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
FSmethod 33.52 2.04 35.70
corr_plot 33.34 1.98 35.39
var_imp 33.70 1.34 35.05
pred_ensembel 14.21 0.27 13.04
enrichfindP 0.55 0.14 12.59
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 3 NOTEs
See
'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.20-bioc/R/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 ucrt) -- "Trophy Case"
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 94.237285
final value 93.915746
converged
Fitting Repeat 2
# weights: 103
initial value 97.357218
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 104.107051
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 97.602423
final value 93.915746
converged
Fitting Repeat 5
# weights: 103
initial value 94.634152
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 94.443699
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 103.060901
final value 93.915746
converged
Fitting Repeat 3
# weights: 305
initial value 110.140692
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 101.040855
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 98.520295
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 99.210354
final value 93.915746
converged
Fitting Repeat 2
# weights: 507
initial value 119.716460
final value 93.915746
converged
Fitting Repeat 3
# weights: 507
initial value 100.912572
final value 93.915746
converged
Fitting Repeat 4
# weights: 507
initial value 98.649995
iter 10 value 94.052910
iter 10 value 94.052910
iter 10 value 94.052910
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 133.214857
iter 10 value 94.052910
iter 10 value 94.052910
iter 10 value 94.052910
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 113.255710
iter 10 value 94.039985
iter 20 value 88.143782
iter 30 value 85.833384
iter 40 value 85.078122
final value 85.039628
converged
Fitting Repeat 2
# weights: 103
initial value 99.744399
iter 10 value 94.089506
iter 20 value 94.056676
iter 30 value 94.032492
iter 40 value 93.944454
iter 50 value 93.931943
iter 60 value 93.915921
iter 70 value 93.865516
iter 80 value 84.811969
iter 90 value 82.981168
iter 100 value 82.214120
final value 82.214120
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 98.102845
iter 10 value 94.139029
iter 20 value 92.474551
iter 30 value 86.382101
iter 40 value 83.453318
iter 50 value 81.696521
iter 60 value 81.208656
iter 70 value 80.967896
iter 80 value 80.965316
final value 80.954465
converged
Fitting Repeat 4
# weights: 103
initial value 99.359287
iter 10 value 94.085366
iter 20 value 94.016896
iter 30 value 86.268970
iter 40 value 85.842390
iter 50 value 85.609395
iter 60 value 84.279591
iter 70 value 83.998961
iter 80 value 83.883402
final value 83.862844
converged
Fitting Repeat 5
# weights: 103
initial value 96.204379
iter 10 value 94.045701
iter 20 value 87.935057
iter 30 value 84.574876
iter 40 value 82.349576
iter 50 value 82.289904
iter 60 value 82.189509
iter 70 value 81.509413
iter 80 value 81.009103
iter 90 value 80.965146
final value 80.965102
converged
Fitting Repeat 1
# weights: 305
initial value 115.137443
iter 10 value 94.279347
iter 20 value 90.053447
iter 30 value 88.496562
iter 40 value 84.699229
iter 50 value 82.128407
iter 60 value 81.442856
iter 70 value 81.015324
iter 80 value 80.645949
iter 90 value 79.933711
iter 100 value 79.774884
final value 79.774884
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.289705
iter 10 value 94.067213
iter 20 value 85.298796
iter 30 value 83.053888
iter 40 value 80.231507
iter 50 value 78.580148
iter 60 value 78.121863
iter 70 value 77.844024
iter 80 value 77.716946
iter 90 value 77.683866
iter 100 value 77.647291
final value 77.647291
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 111.590429
iter 10 value 93.930630
iter 20 value 91.390772
iter 30 value 90.695040
iter 40 value 82.168501
iter 50 value 79.792128
iter 60 value 79.169062
iter 70 value 78.181174
iter 80 value 77.883172
iter 90 value 77.815009
iter 100 value 77.769849
final value 77.769849
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 98.997529
iter 10 value 94.029532
iter 20 value 86.611295
iter 30 value 85.011133
iter 40 value 80.475133
iter 50 value 78.797594
iter 60 value 78.297528
iter 70 value 78.094390
iter 80 value 77.975331
iter 90 value 77.903700
iter 100 value 77.687352
final value 77.687352
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 111.266847
iter 10 value 89.830846
iter 20 value 82.080548
iter 30 value 81.716873
iter 40 value 81.071157
iter 50 value 80.861461
iter 60 value 80.363920
iter 70 value 80.327469
iter 80 value 80.256745
iter 90 value 78.973618
iter 100 value 78.606081
final value 78.606081
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 116.416309
iter 10 value 94.288232
iter 20 value 88.248614
iter 30 value 83.469099
iter 40 value 82.311792
iter 50 value 79.217321
iter 60 value 77.891475
iter 70 value 77.709390
iter 80 value 77.238899
iter 90 value 77.017962
iter 100 value 76.944743
final value 76.944743
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 122.866372
iter 10 value 93.897550
iter 20 value 88.527798
iter 30 value 84.190661
iter 40 value 81.812095
iter 50 value 80.796895
iter 60 value 80.251287
iter 70 value 80.048068
iter 80 value 79.757603
iter 90 value 79.409482
iter 100 value 79.307435
final value 79.307435
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.790346
iter 10 value 94.058926
iter 20 value 92.589913
iter 30 value 89.484676
iter 40 value 86.619404
iter 50 value 80.398681
iter 60 value 78.225445
iter 70 value 77.468239
iter 80 value 77.285509
iter 90 value 77.146201
iter 100 value 76.878080
final value 76.878080
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.487254
iter 10 value 93.589522
iter 20 value 90.199017
iter 30 value 89.799902
iter 40 value 86.851969
iter 50 value 84.170713
iter 60 value 81.597304
iter 70 value 80.758278
iter 80 value 80.412885
iter 90 value 79.957345
iter 100 value 79.885168
final value 79.885168
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.114155
iter 10 value 94.725289
iter 20 value 88.125515
iter 30 value 85.317885
iter 40 value 81.813270
iter 50 value 79.683684
iter 60 value 79.125917
iter 70 value 77.817023
iter 80 value 77.324711
iter 90 value 77.258845
iter 100 value 77.163774
final value 77.163774
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.556065
final value 94.054653
converged
Fitting Repeat 2
# weights: 103
initial value 98.023999
iter 10 value 93.917676
iter 20 value 93.878366
iter 30 value 93.867396
iter 40 value 93.863621
final value 93.863619
converged
Fitting Repeat 3
# weights: 103
initial value 94.342553
iter 10 value 92.092084
iter 20 value 91.946941
iter 30 value 91.946056
iter 40 value 91.939582
iter 50 value 91.934101
final value 91.934095
converged
Fitting Repeat 4
# weights: 103
initial value 96.237488
final value 94.054577
converged
Fitting Repeat 5
# weights: 103
initial value 95.460379
final value 94.054827
converged
Fitting Repeat 1
# weights: 305
initial value 98.350621
iter 10 value 94.013741
iter 20 value 94.010166
iter 30 value 94.009658
iter 40 value 93.952244
iter 50 value 93.949916
iter 60 value 93.799293
iter 70 value 93.798341
iter 80 value 91.528751
iter 90 value 91.265324
iter 100 value 91.226976
final value 91.226976
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.074406
iter 10 value 93.920078
iter 20 value 93.916307
final value 93.915971
converged
Fitting Repeat 3
# weights: 305
initial value 120.488571
iter 10 value 94.057391
iter 20 value 94.052927
iter 30 value 93.997589
iter 40 value 93.301554
iter 50 value 93.300797
final value 93.300758
converged
Fitting Repeat 4
# weights: 305
initial value 104.706637
iter 10 value 88.146342
iter 20 value 88.020511
iter 30 value 88.020102
iter 40 value 85.672234
iter 50 value 85.118661
iter 60 value 85.116823
iter 70 value 85.114567
iter 80 value 83.458325
iter 90 value 83.213936
iter 100 value 83.209848
final value 83.209848
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 95.250593
iter 10 value 93.920650
iter 20 value 92.089362
iter 30 value 86.667853
iter 40 value 86.296406
iter 50 value 86.176072
iter 60 value 81.853428
iter 70 value 80.013141
iter 80 value 78.903162
iter 90 value 78.859601
iter 100 value 78.856664
final value 78.856664
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.807356
iter 10 value 93.996752
iter 20 value 93.801052
iter 30 value 90.025834
iter 40 value 89.433030
iter 50 value 88.924376
final value 88.921993
converged
Fitting Repeat 2
# weights: 507
initial value 115.033956
iter 10 value 93.923777
iter 20 value 93.918216
iter 30 value 93.914236
iter 30 value 93.914236
iter 30 value 93.914236
final value 93.914236
converged
Fitting Repeat 3
# weights: 507
initial value 98.842215
iter 10 value 93.878246
iter 20 value 93.868627
final value 93.866573
converged
Fitting Repeat 4
# weights: 507
initial value 117.470796
iter 10 value 93.875041
iter 20 value 93.866633
iter 30 value 93.831485
iter 40 value 86.392701
iter 50 value 82.868929
iter 60 value 82.220750
iter 70 value 82.013979
iter 80 value 81.986886
iter 90 value 81.981977
iter 100 value 79.572506
final value 79.572506
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.278775
iter 10 value 93.296828
iter 20 value 93.294805
iter 30 value 93.071404
iter 40 value 86.303990
iter 50 value 84.035567
iter 60 value 79.146258
iter 70 value 77.481552
iter 80 value 76.093944
iter 90 value 75.967960
iter 100 value 75.967492
final value 75.967492
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.966374
iter 10 value 89.166401
iter 20 value 88.512157
final value 88.506719
converged
Fitting Repeat 2
# weights: 103
initial value 102.340249
iter 10 value 93.613090
iter 20 value 93.578663
final value 93.577423
converged
Fitting Repeat 3
# weights: 103
initial value 97.508472
final value 94.312038
converged
Fitting Repeat 4
# weights: 103
initial value 94.527798
final value 94.484213
converged
Fitting Repeat 5
# weights: 103
initial value 99.380368
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 105.602265
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 96.206112
iter 10 value 93.935001
iter 20 value 93.901430
final value 93.901356
converged
Fitting Repeat 3
# weights: 305
initial value 104.714503
iter 10 value 93.753333
final value 93.753294
converged
Fitting Repeat 4
# weights: 305
initial value 94.738293
iter 10 value 85.582745
iter 20 value 85.229704
iter 30 value 85.229653
final value 85.229651
converged
Fitting Repeat 5
# weights: 305
initial value 100.985250
iter 10 value 94.004445
iter 20 value 93.922224
iter 20 value 93.922224
iter 20 value 93.922224
final value 93.922224
converged
Fitting Repeat 1
# weights: 507
initial value 104.562878
iter 10 value 88.460830
iter 20 value 87.857719
iter 30 value 87.855212
iter 40 value 87.853900
iter 50 value 87.853876
iter 50 value 87.853875
iter 50 value 87.853875
final value 87.853875
converged
Fitting Repeat 2
# weights: 507
initial value 98.962355
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 114.510204
iter 10 value 93.753425
iter 20 value 93.617619
iter 30 value 93.507140
iter 30 value 93.507140
iter 30 value 93.507140
final value 93.507140
converged
Fitting Repeat 4
# weights: 507
initial value 113.091115
iter 10 value 94.466846
final value 94.466662
converged
Fitting Repeat 5
# weights: 507
initial value 129.804753
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 102.559715
iter 10 value 94.489265
iter 20 value 93.824997
iter 30 value 86.803759
iter 40 value 83.901122
iter 50 value 83.381295
iter 60 value 82.859680
iter 70 value 82.434949
iter 80 value 81.709502
iter 90 value 80.548066
iter 100 value 80.008978
final value 80.008978
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 99.726896
iter 10 value 94.403908
iter 20 value 93.884776
iter 30 value 93.805321
iter 40 value 93.746368
iter 50 value 90.341842
iter 60 value 84.576426
iter 70 value 84.228914
iter 80 value 83.636068
iter 90 value 83.414355
iter 100 value 83.050942
final value 83.050942
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 106.791488
iter 10 value 91.710422
iter 20 value 86.746041
iter 30 value 86.535797
iter 40 value 84.906250
iter 50 value 84.104518
iter 60 value 83.505476
iter 70 value 83.357772
iter 80 value 83.037429
final value 82.989675
converged
Fitting Repeat 4
# weights: 103
initial value 96.381708
iter 10 value 94.497887
iter 20 value 94.468310
iter 30 value 94.284703
iter 40 value 93.835923
iter 50 value 93.754591
iter 60 value 90.829943
iter 70 value 84.860663
iter 80 value 82.572592
iter 90 value 82.094779
iter 100 value 81.004828
final value 81.004828
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 102.410060
iter 10 value 94.483486
iter 20 value 84.116480
iter 30 value 83.498700
iter 40 value 82.706377
final value 82.678197
converged
Fitting Repeat 1
# weights: 305
initial value 103.833663
iter 10 value 89.917566
iter 20 value 86.084746
iter 30 value 82.911472
iter 40 value 80.987475
iter 50 value 80.661519
iter 60 value 80.011223
iter 70 value 79.868569
iter 80 value 79.626327
iter 90 value 78.772036
iter 100 value 78.668362
final value 78.668362
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.953631
iter 10 value 94.088023
iter 20 value 87.579615
iter 30 value 84.231000
iter 40 value 81.362788
iter 50 value 79.278083
iter 60 value 78.756985
iter 70 value 78.561463
iter 80 value 78.333181
iter 90 value 78.204138
iter 100 value 78.095297
final value 78.095297
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 119.067200
iter 10 value 94.418215
iter 20 value 90.203562
iter 30 value 86.082979
iter 40 value 84.418793
iter 50 value 82.869785
iter 60 value 82.169472
iter 70 value 81.924974
iter 80 value 81.678010
iter 90 value 81.034085
iter 100 value 79.317591
final value 79.317591
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.377525
iter 10 value 94.434764
iter 20 value 94.313099
iter 30 value 93.958684
iter 40 value 86.977624
iter 50 value 84.779597
iter 60 value 84.598319
iter 70 value 84.418589
iter 80 value 83.636122
iter 90 value 82.958579
iter 100 value 80.800680
final value 80.800680
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.544609
iter 10 value 94.425964
iter 20 value 89.532321
iter 30 value 86.777631
iter 40 value 84.480874
iter 50 value 82.768718
iter 60 value 81.846818
iter 70 value 79.944660
iter 80 value 79.122814
iter 90 value 78.895462
iter 100 value 78.686328
final value 78.686328
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 136.325314
iter 10 value 93.832499
iter 20 value 83.519457
iter 30 value 81.619371
iter 40 value 80.428058
iter 50 value 79.521591
iter 60 value 78.840437
iter 70 value 78.404646
iter 80 value 78.339551
iter 90 value 78.145668
iter 100 value 78.027397
final value 78.027397
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.204831
iter 10 value 94.509288
iter 20 value 89.487398
iter 30 value 86.619216
iter 40 value 86.096162
iter 50 value 81.712037
iter 60 value 80.024837
iter 70 value 79.309459
iter 80 value 78.488185
iter 90 value 78.183998
iter 100 value 78.012778
final value 78.012778
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 122.939018
iter 10 value 94.833352
iter 20 value 92.423721
iter 30 value 90.987859
iter 40 value 87.961752
iter 50 value 84.800371
iter 60 value 82.417148
iter 70 value 81.012257
iter 80 value 80.559051
iter 90 value 79.834238
iter 100 value 79.520182
final value 79.520182
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 121.627429
iter 10 value 94.436127
iter 20 value 93.886082
iter 30 value 90.836712
iter 40 value 84.797428
iter 50 value 83.943989
iter 60 value 81.829067
iter 70 value 81.733926
iter 80 value 80.818374
iter 90 value 80.436327
iter 100 value 79.214341
final value 79.214341
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.553249
iter 10 value 92.223542
iter 20 value 88.414780
iter 30 value 83.778024
iter 40 value 83.580888
iter 50 value 81.901900
iter 60 value 80.794585
iter 70 value 80.048730
iter 80 value 79.171343
iter 90 value 78.978548
iter 100 value 78.588500
final value 78.588500
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.954395
iter 10 value 94.485859
iter 20 value 94.484223
iter 30 value 87.979722
iter 40 value 87.040581
iter 50 value 86.536795
iter 60 value 86.535200
iter 70 value 86.534789
iter 80 value 84.868110
iter 90 value 84.032068
iter 100 value 84.031374
final value 84.031374
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.477726
final value 94.485767
converged
Fitting Repeat 3
# weights: 103
initial value 104.429407
iter 10 value 94.057334
iter 20 value 93.762772
final value 93.754855
converged
Fitting Repeat 4
# weights: 103
initial value 96.771618
iter 10 value 94.485900
iter 20 value 90.698211
iter 30 value 82.988049
iter 40 value 82.914192
final value 82.913854
converged
Fitting Repeat 5
# weights: 103
initial value 114.459911
iter 10 value 94.485907
iter 20 value 90.210893
final value 86.945897
converged
Fitting Repeat 1
# weights: 305
initial value 104.253109
iter 10 value 94.489174
final value 94.484560
converged
Fitting Repeat 2
# weights: 305
initial value 130.050173
iter 10 value 94.447825
iter 20 value 94.267495
iter 30 value 88.399686
iter 40 value 88.393543
iter 50 value 83.648520
iter 60 value 82.906819
final value 82.906787
converged
Fitting Repeat 3
# weights: 305
initial value 97.303026
iter 10 value 94.486807
iter 20 value 91.095567
iter 30 value 80.387085
iter 40 value 80.076384
iter 50 value 79.826030
iter 60 value 79.057353
final value 79.026304
converged
Fitting Repeat 4
# weights: 305
initial value 105.660470
iter 10 value 94.489586
iter 20 value 94.438875
iter 30 value 88.631979
iter 40 value 83.536370
iter 50 value 83.532453
iter 60 value 83.531446
iter 70 value 82.252712
iter 80 value 82.045906
iter 90 value 82.039034
iter 100 value 82.033246
final value 82.033246
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.420227
iter 10 value 94.489018
iter 20 value 94.477190
iter 30 value 85.458495
iter 40 value 84.298815
iter 50 value 82.410967
iter 60 value 82.397231
iter 70 value 82.253828
iter 80 value 82.138432
iter 90 value 82.138206
iter 100 value 82.137661
final value 82.137661
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 116.160775
iter 10 value 94.320246
iter 20 value 94.312571
iter 30 value 93.946004
iter 40 value 88.803827
iter 50 value 85.741867
iter 60 value 85.701547
iter 70 value 85.700261
iter 80 value 84.531110
final value 84.346672
converged
Fitting Repeat 2
# weights: 507
initial value 121.796276
iter 10 value 94.493346
iter 20 value 94.485448
iter 30 value 94.471226
iter 40 value 91.600526
iter 50 value 91.193962
iter 60 value 89.445625
iter 70 value 85.658620
iter 80 value 85.650089
iter 90 value 85.581030
iter 100 value 85.490343
final value 85.490343
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 99.168356
iter 10 value 93.730624
iter 20 value 93.725838
iter 30 value 93.624732
iter 40 value 89.956785
iter 50 value 83.115440
iter 60 value 82.069899
iter 70 value 81.895138
iter 80 value 80.960138
final value 80.959548
converged
Fitting Repeat 4
# weights: 507
initial value 95.024297
iter 10 value 82.751967
iter 20 value 81.265221
iter 30 value 80.811934
iter 40 value 80.565042
iter 50 value 80.532898
iter 60 value 80.528221
iter 70 value 80.526854
iter 80 value 80.525482
final value 80.525107
converged
Fitting Repeat 5
# weights: 507
initial value 102.297409
iter 10 value 94.451765
iter 20 value 93.912609
iter 30 value 85.190128
iter 40 value 84.088831
iter 50 value 84.040823
iter 60 value 84.040341
iter 70 value 83.995290
final value 83.989561
converged
Fitting Repeat 1
# weights: 103
initial value 95.276320
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.803429
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.340093
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.514350
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 102.586278
iter 10 value 94.026542
iter 10 value 94.026542
iter 10 value 94.026542
final value 94.026542
converged
Fitting Repeat 1
# weights: 305
initial value 108.071509
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 109.454961
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 95.848860
iter 10 value 93.750776
iter 20 value 93.201466
iter 30 value 93.201309
iter 30 value 93.201308
final value 93.201305
converged
Fitting Repeat 4
# weights: 305
initial value 109.402537
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 100.839051
final value 94.026542
converged
Fitting Repeat 1
# weights: 507
initial value 100.628915
iter 10 value 93.320268
final value 93.320225
converged
Fitting Repeat 2
# weights: 507
initial value 102.117963
iter 10 value 94.231389
iter 20 value 93.772975
final value 93.772973
converged
Fitting Repeat 3
# weights: 507
initial value 102.646360
iter 10 value 93.598541
iter 20 value 93.597903
iter 20 value 93.597903
iter 20 value 93.597903
final value 93.597903
converged
Fitting Repeat 4
# weights: 507
initial value 105.696195
iter 10 value 94.310510
iter 10 value 94.310510
iter 10 value 94.310510
final value 94.310510
converged
Fitting Repeat 5
# weights: 507
initial value 114.450279
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 98.120199
iter 10 value 94.488652
iter 20 value 94.164149
iter 30 value 91.406808
iter 40 value 86.533699
iter 50 value 85.774110
iter 60 value 85.569369
iter 70 value 85.418323
iter 80 value 84.297463
iter 90 value 83.408238
iter 100 value 83.244742
final value 83.244742
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 109.586474
iter 10 value 94.486575
iter 20 value 94.344883
iter 30 value 94.126474
iter 40 value 93.497204
iter 50 value 93.495314
iter 60 value 91.979592
iter 70 value 87.451221
iter 80 value 86.876633
iter 90 value 86.704789
iter 100 value 86.437613
final value 86.437613
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.180945
iter 10 value 94.519638
iter 20 value 94.488532
iter 30 value 87.194478
iter 40 value 86.524402
iter 50 value 86.324968
iter 60 value 84.892414
iter 70 value 83.692004
iter 80 value 83.478462
iter 90 value 83.079523
iter 100 value 83.061014
final value 83.061014
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.953108
iter 10 value 93.795230
iter 20 value 92.053230
iter 30 value 91.896654
iter 40 value 91.416945
iter 50 value 91.217370
final value 91.216929
converged
Fitting Repeat 5
# weights: 103
initial value 98.328763
iter 10 value 94.488159
iter 20 value 88.073573
iter 30 value 86.407665
iter 40 value 86.192588
iter 50 value 85.683070
iter 60 value 84.729744
iter 70 value 84.534451
iter 80 value 83.212139
iter 90 value 83.147028
final value 83.145413
converged
Fitting Repeat 1
# weights: 305
initial value 108.991008
iter 10 value 95.291413
iter 20 value 87.509374
iter 30 value 86.327741
iter 40 value 85.563157
iter 50 value 83.382704
iter 60 value 82.780838
iter 70 value 82.401341
iter 80 value 82.256319
iter 90 value 82.099764
iter 100 value 82.055615
final value 82.055615
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.787526
iter 10 value 91.001345
iter 20 value 86.028550
iter 30 value 84.632401
iter 40 value 84.315946
iter 50 value 84.178023
iter 60 value 83.898107
iter 70 value 83.363854
iter 80 value 82.670945
iter 90 value 82.548445
iter 100 value 82.331478
final value 82.331478
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 117.267419
iter 10 value 94.036105
iter 20 value 88.690172
iter 30 value 85.809556
iter 40 value 83.897026
iter 50 value 83.275322
iter 60 value 82.732302
iter 70 value 82.501104
iter 80 value 82.358781
iter 90 value 81.989011
iter 100 value 81.891820
final value 81.891820
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.275449
iter 10 value 94.619238
iter 20 value 92.112935
iter 30 value 87.144921
iter 40 value 86.849625
iter 50 value 85.693595
iter 60 value 84.732613
iter 70 value 82.461239
iter 80 value 82.080391
iter 90 value 81.831720
iter 100 value 81.759748
final value 81.759748
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.280988
iter 10 value 94.518089
iter 20 value 93.743842
iter 30 value 91.187881
iter 40 value 89.530824
iter 50 value 88.645472
iter 60 value 86.274347
iter 70 value 84.405599
iter 80 value 83.471227
iter 90 value 83.280274
iter 100 value 82.778844
final value 82.778844
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.048626
iter 10 value 95.105164
iter 20 value 87.395339
iter 30 value 83.936791
iter 40 value 82.702996
iter 50 value 82.613567
iter 60 value 82.440083
iter 70 value 81.999112
iter 80 value 81.706594
iter 90 value 81.590141
iter 100 value 81.515616
final value 81.515616
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.530853
iter 10 value 94.267471
iter 20 value 92.939754
iter 30 value 90.910938
iter 40 value 86.398658
iter 50 value 84.120144
iter 60 value 83.053223
iter 70 value 82.636245
iter 80 value 82.325079
iter 90 value 82.087078
iter 100 value 82.020905
final value 82.020905
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 135.566712
iter 10 value 94.737203
iter 20 value 87.095360
iter 30 value 84.786625
iter 40 value 83.492054
iter 50 value 82.666603
iter 60 value 82.546620
iter 70 value 82.442045
iter 80 value 82.361881
iter 90 value 82.222114
iter 100 value 82.082632
final value 82.082632
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.974463
iter 10 value 94.474159
iter 20 value 88.656191
iter 30 value 87.951778
iter 40 value 85.784932
iter 50 value 83.702753
iter 60 value 83.091079
iter 70 value 82.817302
iter 80 value 82.610887
iter 90 value 82.585424
iter 100 value 82.546019
final value 82.546019
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.454031
iter 10 value 94.067590
iter 20 value 93.533792
iter 30 value 89.577120
iter 40 value 87.161087
iter 50 value 86.018777
iter 60 value 84.892823
iter 70 value 83.166432
iter 80 value 82.536056
iter 90 value 82.057836
iter 100 value 81.825466
final value 81.825466
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.969430
final value 94.485704
converged
Fitting Repeat 2
# weights: 103
initial value 95.034429
iter 10 value 94.028352
final value 94.027881
converged
Fitting Repeat 3
# weights: 103
initial value 94.883687
final value 94.486100
converged
Fitting Repeat 4
# weights: 103
initial value 97.648464
final value 94.485576
converged
Fitting Repeat 5
# weights: 103
initial value 100.017329
iter 10 value 94.485916
iter 20 value 94.484232
final value 94.484216
converged
Fitting Repeat 1
# weights: 305
initial value 98.731697
iter 10 value 94.487544
iter 20 value 93.083312
iter 30 value 86.697989
final value 86.697617
converged
Fitting Repeat 2
# weights: 305
initial value 114.985242
iter 10 value 94.489191
iter 20 value 94.484430
iter 30 value 93.320748
iter 30 value 93.320748
iter 30 value 93.320748
final value 93.320748
converged
Fitting Repeat 3
# weights: 305
initial value 99.359612
iter 10 value 94.031644
iter 20 value 94.030055
iter 30 value 93.324898
iter 40 value 93.322311
final value 93.322050
converged
Fitting Repeat 4
# weights: 305
initial value 105.875897
iter 10 value 91.954140
iter 20 value 86.653487
iter 30 value 86.505116
iter 40 value 85.343306
iter 50 value 85.216631
iter 60 value 85.216218
iter 70 value 85.183642
iter 80 value 84.659487
final value 84.574543
converged
Fitting Repeat 5
# weights: 305
initial value 105.582064
iter 10 value 94.489602
iter 20 value 94.484253
iter 30 value 94.312715
iter 40 value 90.567151
final value 87.812704
converged
Fitting Repeat 1
# weights: 507
initial value 104.315833
iter 10 value 94.457740
iter 20 value 93.722566
iter 30 value 93.489852
iter 40 value 93.487371
iter 50 value 93.485295
iter 60 value 91.704248
iter 70 value 91.664055
final value 91.664007
converged
Fitting Repeat 2
# weights: 507
initial value 95.723197
iter 10 value 94.490637
iter 20 value 92.226922
iter 30 value 87.816000
iter 40 value 87.788406
iter 50 value 86.783160
iter 60 value 84.403820
iter 70 value 83.445651
iter 80 value 83.422735
iter 90 value 83.422024
iter 90 value 83.422024
iter 90 value 83.422024
final value 83.422024
converged
Fitting Repeat 3
# weights: 507
initial value 109.078616
iter 10 value 92.924563
iter 20 value 88.718638
iter 30 value 88.690552
iter 40 value 88.680549
iter 50 value 85.902682
iter 60 value 84.607306
iter 70 value 83.292934
iter 80 value 82.522203
iter 90 value 81.795896
iter 100 value 80.862565
final value 80.862565
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.830230
iter 10 value 94.063323
iter 20 value 94.053027
iter 30 value 87.367398
iter 40 value 83.927349
iter 50 value 83.080405
iter 60 value 82.815954
iter 70 value 82.787407
iter 80 value 82.787122
final value 82.787075
converged
Fitting Repeat 5
# weights: 507
initial value 96.169967
iter 10 value 92.456169
iter 20 value 91.961022
iter 30 value 91.747170
iter 40 value 91.671331
iter 50 value 91.662429
iter 60 value 91.555689
iter 70 value 91.552837
iter 80 value 86.683691
iter 90 value 84.889190
iter 100 value 84.572114
final value 84.572114
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.812773
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.069134
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.176622
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 108.101256
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.569858
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 99.077190
iter 10 value 87.381695
iter 20 value 86.702442
iter 30 value 86.682981
iter 40 value 86.682133
final value 86.682091
converged
Fitting Repeat 2
# weights: 305
initial value 96.583545
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 109.914641
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 101.889153
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 93.967785
iter 10 value 86.404957
iter 20 value 86.400019
final value 86.400011
converged
Fitting Repeat 1
# weights: 507
initial value 96.966070
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 114.166485
iter 10 value 94.340808
final value 94.275345
converged
Fitting Repeat 3
# weights: 507
initial value 99.481450
final value 94.483810
converged
Fitting Repeat 4
# weights: 507
initial value 103.936575
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 112.865537
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 108.614482
iter 10 value 94.346572
iter 20 value 91.331975
iter 30 value 89.347880
iter 40 value 89.124831
iter 50 value 89.046626
iter 60 value 87.679963
iter 70 value 86.560864
iter 80 value 85.307049
iter 90 value 84.796186
final value 84.792033
converged
Fitting Repeat 2
# weights: 103
initial value 103.518132
iter 10 value 88.635613
iter 20 value 87.150955
iter 30 value 86.280954
iter 40 value 84.703724
iter 50 value 84.417714
iter 60 value 84.375228
final value 84.366335
converged
Fitting Repeat 3
# weights: 103
initial value 102.698696
iter 10 value 94.311232
iter 20 value 87.909409
iter 30 value 86.407084
iter 40 value 85.836208
iter 50 value 85.736638
final value 85.736612
converged
Fitting Repeat 4
# weights: 103
initial value 103.628751
iter 10 value 94.435270
iter 20 value 91.296690
iter 30 value 88.473480
iter 40 value 88.293958
iter 50 value 87.670043
iter 60 value 87.248013
iter 70 value 84.811574
iter 80 value 84.165273
iter 90 value 84.138905
iter 100 value 84.107802
final value 84.107802
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.608532
iter 10 value 94.486542
iter 20 value 94.159833
iter 30 value 90.330060
iter 40 value 87.494496
iter 50 value 86.863957
iter 60 value 86.493852
final value 86.493736
converged
Fitting Repeat 1
# weights: 305
initial value 103.438032
iter 10 value 94.565681
iter 20 value 88.167959
iter 30 value 87.337703
iter 40 value 86.976277
iter 50 value 86.557303
iter 60 value 85.051107
iter 70 value 84.028724
iter 80 value 83.792981
iter 90 value 83.254262
iter 100 value 82.703582
final value 82.703582
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 109.996527
iter 10 value 95.964047
iter 20 value 94.324525
iter 30 value 87.377945
iter 40 value 86.290858
iter 50 value 86.018976
iter 60 value 85.736748
iter 70 value 85.671122
iter 80 value 85.135185
iter 90 value 85.016742
iter 100 value 84.373442
final value 84.373442
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.655528
iter 10 value 94.355564
iter 20 value 91.468751
iter 30 value 87.860636
iter 40 value 87.450088
iter 50 value 86.535354
iter 60 value 85.356555
iter 70 value 84.615146
iter 80 value 83.816949
iter 90 value 83.240142
iter 100 value 82.903766
final value 82.903766
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 114.747774
iter 10 value 94.359831
iter 20 value 93.470912
iter 30 value 91.156160
iter 40 value 87.961729
iter 50 value 87.313230
iter 60 value 87.037297
iter 70 value 84.853790
iter 80 value 83.644031
iter 90 value 83.444633
iter 100 value 83.211711
final value 83.211711
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.111686
iter 10 value 95.525538
iter 20 value 94.399965
iter 30 value 94.367873
iter 40 value 91.846760
iter 50 value 87.340614
iter 60 value 85.124480
iter 70 value 84.340401
iter 80 value 84.061877
iter 90 value 83.152437
iter 100 value 82.989733
final value 82.989733
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 114.795447
iter 10 value 94.483620
iter 20 value 89.281614
iter 30 value 87.679917
iter 40 value 86.414295
iter 50 value 86.164468
iter 60 value 85.398398
iter 70 value 83.962185
iter 80 value 83.050605
iter 90 value 82.748188
iter 100 value 82.574937
final value 82.574937
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 118.400964
iter 10 value 94.499633
iter 20 value 94.173664
iter 30 value 89.223224
iter 40 value 87.784204
iter 50 value 85.979217
iter 60 value 84.176229
iter 70 value 83.501522
iter 80 value 83.018238
iter 90 value 82.798215
iter 100 value 82.653134
final value 82.653134
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 120.662356
iter 10 value 97.390586
iter 20 value 93.860154
iter 30 value 87.781086
iter 40 value 85.830757
iter 50 value 84.333759
iter 60 value 83.603861
iter 70 value 83.257425
iter 80 value 83.143956
iter 90 value 83.029473
iter 100 value 82.991783
final value 82.991783
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.175867
iter 10 value 94.419941
iter 20 value 90.012818
iter 30 value 86.694769
iter 40 value 86.140269
iter 50 value 85.846699
iter 60 value 85.613875
iter 70 value 84.933371
iter 80 value 83.325712
iter 90 value 83.086205
iter 100 value 82.989364
final value 82.989364
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.213673
iter 10 value 94.927630
iter 20 value 89.534401
iter 30 value 87.413563
iter 40 value 87.066446
iter 50 value 86.079259
iter 60 value 83.851010
iter 70 value 83.223378
iter 80 value 83.080977
iter 90 value 82.984050
iter 100 value 82.763874
final value 82.763874
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 105.180951
final value 94.485852
converged
Fitting Repeat 2
# weights: 103
initial value 96.059403
iter 10 value 94.485887
iter 20 value 94.482554
iter 30 value 88.099841
iter 40 value 85.900954
iter 50 value 85.758423
iter 60 value 85.694161
iter 70 value 85.693671
final value 85.693669
converged
Fitting Repeat 3
# weights: 103
initial value 95.018635
final value 94.485911
converged
Fitting Repeat 4
# weights: 103
initial value 100.722637
iter 10 value 94.277622
iter 20 value 94.276606
final value 94.275563
converged
Fitting Repeat 5
# weights: 103
initial value 103.101759
final value 94.485798
converged
Fitting Repeat 1
# weights: 305
initial value 102.276794
iter 10 value 94.280390
iter 20 value 94.276164
final value 94.275785
converged
Fitting Repeat 2
# weights: 305
initial value 102.023404
iter 10 value 94.489266
iter 20 value 94.420168
iter 30 value 87.456647
iter 40 value 87.375444
iter 50 value 87.334911
iter 60 value 87.246936
iter 70 value 87.233559
final value 87.219783
converged
Fitting Repeat 3
# weights: 305
initial value 98.949351
iter 10 value 94.489477
iter 20 value 93.717444
iter 30 value 87.984130
iter 40 value 87.982885
iter 40 value 87.982885
final value 87.982885
converged
Fitting Repeat 4
# weights: 305
initial value 106.578081
iter 10 value 94.446793
iter 20 value 91.529816
iter 30 value 88.802400
iter 40 value 87.717013
iter 50 value 87.705970
iter 60 value 86.742426
iter 70 value 86.738521
iter 80 value 86.737182
iter 90 value 86.735584
final value 86.735469
converged
Fitting Repeat 5
# weights: 305
initial value 96.741866
iter 10 value 94.484463
iter 20 value 94.421001
iter 30 value 92.663512
iter 40 value 92.628297
iter 50 value 92.574268
iter 50 value 92.574268
final value 92.574268
converged
Fitting Repeat 1
# weights: 507
initial value 103.120306
iter 10 value 94.491911
iter 20 value 94.484233
iter 30 value 92.748559
iter 40 value 87.567870
iter 50 value 86.945199
iter 60 value 86.944299
iter 70 value 86.596254
iter 80 value 86.520710
iter 90 value 85.648353
iter 100 value 85.475994
final value 85.475994
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 94.940536
iter 10 value 94.491571
iter 20 value 94.435539
iter 30 value 92.731437
iter 40 value 92.707162
iter 50 value 87.142998
iter 60 value 86.847921
iter 70 value 86.757906
iter 80 value 86.702729
iter 90 value 86.700509
iter 100 value 86.662154
final value 86.662154
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.100727
iter 10 value 94.492254
iter 20 value 94.484405
iter 30 value 87.610845
iter 40 value 86.088851
iter 50 value 86.076317
iter 60 value 86.075695
iter 70 value 86.074053
iter 80 value 86.073549
iter 90 value 85.958481
iter 100 value 85.825825
final value 85.825825
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.563037
iter 10 value 94.489726
iter 20 value 92.173579
iter 30 value 86.929011
final value 86.797053
converged
Fitting Repeat 5
# weights: 507
initial value 95.865081
iter 10 value 94.283510
iter 20 value 94.276054
iter 30 value 90.463303
iter 40 value 86.069672
iter 50 value 83.477884
iter 60 value 83.406943
iter 70 value 83.406100
iter 80 value 83.294180
iter 90 value 82.968936
iter 100 value 82.176547
final value 82.176547
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.157576
final value 94.038251
converged
Fitting Repeat 2
# weights: 103
initial value 95.049517
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 96.763272
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 96.538939
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 96.470391
iter 10 value 94.038258
final value 94.038251
converged
Fitting Repeat 1
# weights: 305
initial value 101.976205
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 103.437054
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 95.485858
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 102.704079
final value 94.052908
converged
Fitting Repeat 5
# weights: 305
initial value 106.698165
final value 94.038251
converged
Fitting Repeat 1
# weights: 507
initial value 102.562076
iter 10 value 94.038251
iter 10 value 94.038251
iter 10 value 94.038251
final value 94.038251
converged
Fitting Repeat 2
# weights: 507
initial value 105.945354
final value 94.038251
converged
Fitting Repeat 3
# weights: 507
initial value 103.799521
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 114.847045
final value 94.038251
converged
Fitting Repeat 5
# weights: 507
initial value 98.535938
iter 10 value 93.864032
iter 20 value 93.860383
iter 30 value 85.916130
iter 40 value 85.182170
final value 85.181512
converged
Fitting Repeat 1
# weights: 103
initial value 101.230817
iter 10 value 94.056911
iter 20 value 93.839849
iter 30 value 87.890730
iter 40 value 84.802445
iter 50 value 84.556206
iter 60 value 84.529066
final value 84.526853
converged
Fitting Repeat 2
# weights: 103
initial value 104.094770
iter 10 value 94.014658
iter 20 value 88.348424
iter 30 value 87.135262
iter 40 value 86.817986
iter 50 value 85.140011
iter 60 value 84.753775
iter 70 value 84.533798
iter 80 value 84.526856
final value 84.526853
converged
Fitting Repeat 3
# weights: 103
initial value 103.283763
iter 10 value 94.320227
iter 20 value 94.056371
iter 30 value 93.980852
iter 40 value 92.066823
iter 50 value 91.500419
iter 60 value 91.301400
iter 70 value 88.848748
iter 80 value 83.485954
iter 90 value 82.574005
iter 100 value 82.018999
final value 82.018999
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.395551
iter 10 value 94.002886
iter 20 value 86.948190
iter 30 value 85.702760
iter 40 value 85.008652
iter 50 value 84.825635
iter 60 value 84.651575
iter 70 value 84.527154
final value 84.526853
converged
Fitting Repeat 5
# weights: 103
initial value 96.455122
iter 10 value 94.033150
iter 20 value 90.657401
iter 30 value 84.769909
iter 40 value 84.247659
iter 50 value 84.016654
iter 60 value 83.575455
iter 70 value 82.006402
iter 80 value 81.633570
iter 90 value 81.445221
iter 100 value 81.199257
final value 81.199257
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 112.777802
iter 10 value 89.682499
iter 20 value 85.197163
iter 30 value 84.928387
iter 40 value 84.520630
iter 50 value 83.678342
iter 60 value 83.264125
iter 70 value 83.037558
iter 80 value 82.700427
iter 90 value 82.386052
iter 100 value 81.878738
final value 81.878738
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.511033
iter 10 value 93.887443
iter 20 value 85.735783
iter 30 value 83.790011
iter 40 value 83.048617
iter 50 value 82.996552
iter 60 value 82.865049
iter 70 value 81.491918
iter 80 value 80.606718
iter 90 value 80.438505
iter 100 value 80.204263
final value 80.204263
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 137.844540
iter 10 value 94.119993
iter 20 value 90.445202
iter 30 value 85.444778
iter 40 value 85.120312
iter 50 value 84.496216
iter 60 value 83.061136
iter 70 value 82.125909
iter 80 value 81.819050
iter 90 value 81.433423
iter 100 value 81.030265
final value 81.030265
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.493931
iter 10 value 93.845058
iter 20 value 87.423746
iter 30 value 83.536112
iter 40 value 82.224869
iter 50 value 81.425628
iter 60 value 81.079919
iter 70 value 80.780435
iter 80 value 80.523889
iter 90 value 80.428554
iter 100 value 80.223685
final value 80.223685
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.446719
iter 10 value 93.860206
iter 20 value 85.518219
iter 30 value 83.174387
iter 40 value 82.927613
iter 50 value 82.366109
iter 60 value 81.319155
iter 70 value 80.448770
iter 80 value 80.192525
iter 90 value 80.156034
iter 100 value 80.124754
final value 80.124754
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 126.073395
iter 10 value 94.080129
iter 20 value 93.986345
iter 30 value 86.195036
iter 40 value 85.473472
iter 50 value 81.944020
iter 60 value 81.439698
iter 70 value 80.399757
iter 80 value 80.097464
iter 90 value 79.702860
iter 100 value 79.328356
final value 79.328356
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.529444
iter 10 value 94.100095
iter 20 value 85.980076
iter 30 value 84.723449
iter 40 value 84.510817
iter 50 value 84.029417
iter 60 value 83.887580
iter 70 value 83.843633
iter 80 value 83.233374
iter 90 value 82.611030
iter 100 value 82.431157
final value 82.431157
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.619467
iter 10 value 93.915394
iter 20 value 85.179417
iter 30 value 82.603789
iter 40 value 82.005979
iter 50 value 80.600517
iter 60 value 80.307616
iter 70 value 79.993942
iter 80 value 79.640457
iter 90 value 79.431612
iter 100 value 79.394116
final value 79.394116
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.787632
iter 10 value 93.976922
iter 20 value 86.760626
iter 30 value 85.847209
iter 40 value 84.457531
iter 50 value 84.108612
iter 60 value 83.943655
iter 70 value 82.119325
iter 80 value 81.516336
iter 90 value 80.744660
iter 100 value 80.218719
final value 80.218719
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.447903
iter 10 value 94.098541
iter 20 value 89.265634
iter 30 value 86.704635
iter 40 value 86.063368
iter 50 value 84.105137
iter 60 value 83.802109
iter 70 value 83.089359
iter 80 value 82.267275
iter 90 value 81.520609
iter 100 value 81.132406
final value 81.132406
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.595504
final value 94.054861
converged
Fitting Repeat 2
# weights: 103
initial value 96.684306
final value 94.054700
converged
Fitting Repeat 3
# weights: 103
initial value 97.468509
final value 94.054699
converged
Fitting Repeat 4
# weights: 103
initial value 97.085487
final value 94.054323
converged
Fitting Repeat 5
# weights: 103
initial value 101.633558
final value 94.054779
converged
Fitting Repeat 1
# weights: 305
initial value 98.531526
iter 10 value 94.057665
iter 20 value 94.048180
iter 30 value 92.817035
iter 40 value 90.049728
iter 50 value 89.936223
iter 60 value 89.898051
final value 89.897458
converged
Fitting Repeat 2
# weights: 305
initial value 101.266334
iter 10 value 94.058214
iter 20 value 94.052833
iter 30 value 85.681037
iter 40 value 84.210684
iter 50 value 80.810070
iter 60 value 80.310578
iter 70 value 80.227119
iter 80 value 80.209813
iter 90 value 80.207990
iter 100 value 80.205412
final value 80.205412
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.759706
iter 10 value 94.057816
iter 20 value 94.022932
iter 30 value 85.898301
iter 40 value 85.431679
iter 50 value 82.487158
iter 60 value 80.141917
iter 70 value 79.132912
iter 80 value 78.816415
iter 90 value 78.586704
iter 100 value 78.310020
final value 78.310020
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 95.617320
iter 10 value 85.151612
iter 20 value 84.135128
iter 30 value 84.129650
iter 40 value 83.872994
iter 50 value 83.815380
iter 60 value 83.811654
iter 70 value 83.809245
iter 80 value 83.809084
final value 83.809036
converged
Fitting Repeat 5
# weights: 305
initial value 126.799658
iter 10 value 94.057451
iter 20 value 94.051972
iter 30 value 87.256916
iter 40 value 85.804768
iter 50 value 84.009184
iter 60 value 80.726000
iter 70 value 79.468195
iter 80 value 78.747257
iter 90 value 77.888051
iter 100 value 77.816275
final value 77.816275
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 96.128967
iter 10 value 93.738257
iter 20 value 92.949170
iter 30 value 92.777458
iter 40 value 92.708783
iter 50 value 92.627493
iter 60 value 84.726013
iter 70 value 84.244090
iter 80 value 84.013822
iter 90 value 82.799057
iter 100 value 82.705511
final value 82.705511
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 122.943114
iter 10 value 94.061942
iter 20 value 94.053556
iter 30 value 93.465666
iter 40 value 93.465295
final value 93.465252
converged
Fitting Repeat 3
# weights: 507
initial value 131.957865
iter 10 value 94.059222
iter 20 value 93.981323
iter 30 value 89.151168
iter 40 value 84.926698
iter 50 value 84.922736
iter 60 value 84.915113
iter 70 value 84.912934
iter 80 value 84.632487
iter 90 value 84.631986
iter 100 value 84.631413
final value 84.631413
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 92.504549
iter 10 value 85.386456
iter 20 value 85.330467
iter 30 value 85.319607
iter 40 value 84.832991
iter 50 value 84.785408
final value 84.785044
converged
Fitting Repeat 5
# weights: 507
initial value 110.226503
iter 10 value 94.056172
iter 20 value 93.362349
iter 30 value 93.333700
final value 93.333699
converged
Fitting Repeat 1
# weights: 305
initial value 139.563624
iter 10 value 117.895946
iter 20 value 117.891080
iter 30 value 117.684962
iter 40 value 112.117550
iter 50 value 112.057009
iter 60 value 112.056783
iter 70 value 111.746179
iter 80 value 111.733969
final value 111.733741
converged
Fitting Repeat 2
# weights: 305
initial value 131.968517
iter 10 value 117.763857
iter 20 value 116.766372
iter 30 value 105.103988
iter 40 value 103.981045
iter 50 value 103.977467
iter 60 value 103.975449
iter 70 value 103.794628
iter 80 value 102.762059
iter 90 value 101.115395
iter 100 value 99.696810
final value 99.696810
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 138.198007
iter 10 value 117.894555
iter 20 value 114.813699
iter 30 value 107.615651
iter 40 value 107.551225
iter 50 value 106.914396
iter 60 value 103.970055
iter 70 value 103.922972
iter 80 value 103.746373
iter 90 value 103.649935
iter 100 value 103.647896
final value 103.647896
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 125.566662
iter 10 value 117.895202
iter 20 value 117.890534
iter 30 value 115.539827
iter 40 value 106.824660
final value 106.778003
converged
Fitting Repeat 5
# weights: 305
initial value 122.384354
iter 10 value 117.894447
iter 20 value 117.761924
iter 30 value 108.535344
final value 108.528318
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 Apr 1 02:36:54 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
40.92 1.43 117.37
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.52 | 2.04 | 35.70 | |
| FreqInteractors | 0.29 | 0.05 | 0.38 | |
| calculateAAC | 0.05 | 0.02 | 0.06 | |
| calculateAutocor | 0.76 | 0.09 | 0.86 | |
| calculateCTDC | 0.1 | 0.0 | 0.1 | |
| calculateCTDD | 0.81 | 0.00 | 0.81 | |
| calculateCTDT | 0.28 | 0.00 | 0.28 | |
| calculateCTriad | 0.45 | 0.00 | 0.43 | |
| calculateDC | 0.14 | 0.00 | 0.14 | |
| calculateF | 0.39 | 0.02 | 0.41 | |
| calculateKSAAP | 0.08 | 0.01 | 0.09 | |
| calculateQD_Sm | 2.07 | 0.17 | 2.25 | |
| calculateTC | 1.79 | 0.14 | 1.94 | |
| calculateTC_Sm | 0.30 | 0.02 | 0.31 | |
| corr_plot | 33.34 | 1.98 | 35.39 | |
| enrichfindP | 0.55 | 0.14 | 12.59 | |
| enrichfind_hp | 0.08 | 0.02 | 1.06 | |
| enrichplot | 0.48 | 0.03 | 0.52 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.01 | 0.00 | 2.05 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.11 | 0.00 | 0.11 | |
| pred_ensembel | 14.21 | 0.27 | 13.04 | |
| var_imp | 33.70 | 1.34 | 35.05 | |