Matineh Rahmatbakhsh
| Snapshot Date: 2025-03-20 13:00 -0400 (Thu, 20 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 2025-03-24 12:08 -0400 (Mon, 24 Mar 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" | 4763 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.3 (2025-02-28 ucrt) -- "Trophy Case" | 4494 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4521 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4448 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4414 |
| 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: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.12.0.tar.gz |
| StartedAt: 2025-03-21 04:21:11 -0400 (Fri, 21 Mar 2025) |
| EndedAt: 2025-03-21 04:29:58 -0400 (Fri, 21 Mar 2025) |
| EllapsedTime: 526.4 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.3 (2025-02-28)
* using platform: x86_64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.6
* 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 for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
var_imp 50.689 1.721 57.319
FSmethod 50.522 1.751 54.687
corr_plot 50.432 1.737 55.343
pred_ensembel 25.270 0.474 24.488
calculateTC 4.725 0.451 5.421
enrichfindP 0.908 0.086 13.554
* 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
‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’ * installing *source* package ‘HPiP’ ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.4.3 (2025-02-28) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
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 102.686740
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.070142
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.627767
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 101.156461
iter 10 value 88.959164
iter 20 value 86.868860
final value 86.866841
converged
Fitting Repeat 5
# weights: 103
initial value 103.998422
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 95.765459
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 118.476911
iter 10 value 89.676191
iter 20 value 86.935374
iter 30 value 86.317320
final value 86.315313
converged
Fitting Repeat 3
# weights: 305
initial value 101.993679
final value 94.466823
converged
Fitting Repeat 4
# weights: 305
initial value 94.543522
final value 92.608648
converged
Fitting Repeat 5
# weights: 305
initial value 98.884159
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 105.580628
final value 93.568966
converged
Fitting Repeat 2
# weights: 507
initial value 96.254623
iter 10 value 94.484215
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 101.631478
iter 10 value 93.568979
iter 10 value 93.568979
final value 93.568970
converged
Fitting Repeat 4
# weights: 507
initial value 112.429492
final value 94.466823
converged
Fitting Repeat 5
# weights: 507
initial value 97.325303
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 102.879697
iter 10 value 94.459025
iter 20 value 91.496121
iter 30 value 89.230511
iter 40 value 83.463153
iter 50 value 82.645872
iter 60 value 81.967399
iter 70 value 81.889326
iter 80 value 81.884739
final value 81.884734
converged
Fitting Repeat 2
# weights: 103
initial value 98.803550
iter 10 value 94.484407
iter 20 value 85.867766
iter 30 value 84.177305
iter 40 value 84.019083
iter 50 value 82.472398
iter 60 value 82.181398
iter 70 value 81.948311
iter 80 value 81.935462
iter 80 value 81.935462
iter 80 value 81.935462
final value 81.935462
converged
Fitting Repeat 3
# weights: 103
initial value 108.949518
iter 10 value 94.507846
iter 20 value 94.391493
iter 30 value 94.304773
iter 40 value 92.524335
iter 50 value 85.981674
iter 60 value 85.429540
iter 70 value 81.724983
iter 80 value 81.617976
iter 90 value 81.535703
iter 100 value 81.483937
final value 81.483937
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 103.578558
iter 10 value 94.431695
iter 20 value 94.191466
iter 30 value 94.176666
iter 40 value 92.597745
iter 50 value 85.604948
iter 60 value 85.134732
iter 70 value 84.963858
iter 80 value 84.610411
iter 90 value 83.675391
iter 100 value 83.153092
final value 83.153092
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 107.986708
iter 10 value 94.489340
iter 20 value 94.296866
iter 30 value 94.265851
iter 40 value 85.474157
iter 50 value 85.123150
iter 60 value 84.512720
iter 70 value 81.788658
iter 80 value 81.143063
iter 90 value 80.348755
iter 100 value 80.230949
final value 80.230949
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 108.538449
iter 10 value 94.584117
iter 20 value 88.788208
iter 30 value 86.712662
iter 40 value 85.360207
iter 50 value 83.701676
iter 60 value 80.804888
iter 70 value 80.219534
iter 80 value 79.643635
iter 90 value 79.133467
iter 100 value 79.006824
final value 79.006824
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.516504
iter 10 value 94.682446
iter 20 value 82.470067
iter 30 value 81.660812
iter 40 value 81.579769
iter 50 value 81.501705
iter 60 value 81.476787
iter 70 value 81.153181
iter 80 value 80.444148
iter 90 value 80.252705
iter 100 value 80.202667
final value 80.202667
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.699483
iter 10 value 94.433970
iter 20 value 86.991728
iter 30 value 83.514996
iter 40 value 81.818546
iter 50 value 81.538192
iter 60 value 81.402951
iter 70 value 81.348997
iter 80 value 80.997659
iter 90 value 79.876083
iter 100 value 79.661596
final value 79.661596
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.349209
iter 10 value 96.221818
iter 20 value 86.680263
iter 30 value 84.904838
iter 40 value 82.215588
iter 50 value 81.822655
iter 60 value 81.670707
iter 70 value 81.370344
iter 80 value 79.360411
iter 90 value 79.122407
iter 100 value 78.980886
final value 78.980886
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 112.304524
iter 10 value 94.390350
iter 20 value 87.950005
iter 30 value 85.474407
iter 40 value 85.448782
iter 50 value 85.348833
iter 60 value 83.278252
iter 70 value 81.866021
iter 80 value 80.547143
iter 90 value 79.476677
iter 100 value 79.196311
final value 79.196311
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.528872
iter 10 value 94.794570
iter 20 value 94.366061
iter 30 value 92.210634
iter 40 value 86.732399
iter 50 value 85.921149
iter 60 value 84.913001
iter 70 value 84.473025
iter 80 value 83.058693
iter 90 value 81.892117
iter 100 value 80.150395
final value 80.150395
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 137.005525
iter 10 value 94.849654
iter 20 value 92.439915
iter 30 value 82.198708
iter 40 value 81.862460
iter 50 value 81.590303
iter 60 value 80.275822
iter 70 value 79.252598
iter 80 value 78.868254
iter 90 value 78.657036
iter 100 value 78.461013
final value 78.461013
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.188786
iter 10 value 96.357308
iter 20 value 94.094021
iter 30 value 91.026304
iter 40 value 85.001577
iter 50 value 81.934896
iter 60 value 81.685837
iter 70 value 81.402882
iter 80 value 81.279193
iter 90 value 81.260822
iter 100 value 81.132869
final value 81.132869
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.199507
iter 10 value 94.654025
iter 20 value 94.461585
iter 30 value 88.132477
iter 40 value 85.965142
iter 50 value 85.273351
iter 60 value 82.633465
iter 70 value 81.614554
iter 80 value 81.438872
iter 90 value 81.190550
iter 100 value 80.775126
final value 80.775126
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 123.492657
iter 10 value 94.678775
iter 20 value 86.074579
iter 30 value 84.121695
iter 40 value 82.944085
iter 50 value 81.307394
iter 60 value 80.181961
iter 70 value 79.636035
iter 80 value 79.382202
iter 90 value 79.093040
iter 100 value 79.063041
final value 79.063041
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.379471
final value 94.485925
converged
Fitting Repeat 2
# weights: 103
initial value 97.052631
final value 94.486027
converged
Fitting Repeat 3
# weights: 103
initial value 95.302341
iter 10 value 94.485850
iter 20 value 94.484225
iter 30 value 94.470459
iter 40 value 91.929370
iter 50 value 91.493138
iter 60 value 86.249923
iter 70 value 84.484616
iter 80 value 84.479639
iter 90 value 84.470918
final value 84.470917
converged
Fitting Repeat 4
# weights: 103
initial value 95.288213
final value 94.485892
converged
Fitting Repeat 5
# weights: 103
initial value 95.939016
final value 94.485637
converged
Fitting Repeat 1
# weights: 305
initial value 93.895214
iter 10 value 80.716346
iter 20 value 80.693036
iter 30 value 80.440823
iter 40 value 80.410474
iter 50 value 80.399365
iter 60 value 80.394847
iter 70 value 80.355309
iter 80 value 80.354955
final value 80.353973
converged
Fitting Repeat 2
# weights: 305
initial value 101.201630
iter 10 value 94.488831
iter 20 value 94.074289
iter 30 value 84.488681
final value 84.484174
converged
Fitting Repeat 3
# weights: 305
initial value 108.776675
iter 10 value 94.488967
iter 20 value 94.405745
iter 30 value 92.786263
final value 92.786182
converged
Fitting Repeat 4
# weights: 305
initial value 108.319286
iter 10 value 94.489061
iter 20 value 94.402961
iter 30 value 91.459388
iter 40 value 91.156967
iter 50 value 91.154295
final value 91.154219
converged
Fitting Repeat 5
# weights: 305
initial value 96.815519
iter 10 value 91.949555
iter 20 value 91.416475
iter 30 value 91.415253
iter 40 value 91.415013
iter 50 value 91.327585
final value 91.327336
converged
Fitting Repeat 1
# weights: 507
initial value 128.338720
iter 10 value 94.416945
iter 20 value 94.411082
final value 94.408674
converged
Fitting Repeat 2
# weights: 507
initial value 110.680144
iter 10 value 94.474900
iter 20 value 91.721663
iter 30 value 84.482762
final value 84.482759
converged
Fitting Repeat 3
# weights: 507
initial value 104.436819
iter 10 value 94.492114
iter 20 value 94.436759
iter 30 value 94.355378
iter 40 value 81.770228
iter 50 value 81.491708
iter 60 value 80.794027
iter 70 value 80.728416
iter 80 value 80.636937
iter 90 value 79.499170
iter 100 value 78.875780
final value 78.875780
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.709157
iter 10 value 94.474593
iter 20 value 94.473159
iter 30 value 94.470597
iter 40 value 94.466752
iter 50 value 94.427727
iter 60 value 84.522858
iter 70 value 84.470349
iter 80 value 84.468637
iter 90 value 80.700494
iter 100 value 80.691850
final value 80.691850
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 101.070792
iter 10 value 93.512347
iter 20 value 86.943923
iter 30 value 86.553116
iter 40 value 86.542060
iter 50 value 85.522946
iter 60 value 85.060288
iter 70 value 84.596734
iter 80 value 84.501640
iter 90 value 84.492412
iter 100 value 83.467619
final value 83.467619
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.909180
iter 10 value 94.275362
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 2
# weights: 103
initial value 103.195114
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 99.757383
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.872714
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.355506
final value 94.275362
converged
Fitting Repeat 1
# weights: 305
initial value 108.859720
final value 94.275362
converged
Fitting Repeat 2
# weights: 305
initial value 113.855172
iter 10 value 94.275362
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 3
# weights: 305
initial value 100.775116
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 98.126101
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 104.521895
iter 10 value 94.484288
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 107.939838
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 104.037973
iter 10 value 90.330248
iter 20 value 86.114846
iter 30 value 85.873475
iter 40 value 85.843752
final value 85.843638
converged
Fitting Repeat 3
# weights: 507
initial value 97.532720
iter 10 value 94.275362
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 4
# weights: 507
initial value 98.973558
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 99.755167
iter 10 value 90.006312
iter 20 value 88.652803
iter 30 value 88.541571
iter 40 value 88.541405
iter 40 value 88.541405
iter 40 value 88.541405
final value 88.541405
converged
Fitting Repeat 1
# weights: 103
initial value 102.796351
iter 10 value 94.487178
iter 20 value 92.578989
iter 30 value 91.296707
iter 40 value 90.130748
iter 50 value 89.889671
iter 60 value 81.994112
iter 70 value 80.910898
iter 80 value 80.495257
final value 80.495026
converged
Fitting Repeat 2
# weights: 103
initial value 97.827380
iter 10 value 94.437725
iter 20 value 90.347657
iter 30 value 87.458286
iter 40 value 86.002227
iter 50 value 84.428762
iter 60 value 83.594985
iter 70 value 83.543263
iter 80 value 83.512439
final value 83.512432
converged
Fitting Repeat 3
# weights: 103
initial value 105.402851
iter 10 value 94.091078
iter 20 value 86.622599
iter 30 value 86.070758
iter 40 value 84.007059
iter 50 value 83.044439
iter 60 value 82.491112
iter 70 value 80.914192
iter 80 value 80.503743
iter 90 value 80.498454
iter 100 value 80.495756
final value 80.495756
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.537422
iter 10 value 94.493298
iter 20 value 88.804290
iter 30 value 85.512018
iter 40 value 84.296181
iter 50 value 83.643391
iter 60 value 81.207457
iter 70 value 80.591366
iter 80 value 80.293469
final value 80.292846
converged
Fitting Repeat 5
# weights: 103
initial value 96.170908
iter 10 value 94.474423
iter 20 value 90.861535
iter 30 value 88.663559
iter 40 value 84.704494
iter 50 value 82.863451
iter 60 value 81.831990
iter 70 value 80.873071
iter 80 value 80.486794
iter 90 value 80.343410
final value 80.292846
converged
Fitting Repeat 1
# weights: 305
initial value 110.320279
iter 10 value 94.479625
iter 20 value 93.877150
iter 30 value 93.776292
iter 40 value 89.706891
iter 50 value 85.217885
iter 60 value 83.808241
iter 70 value 83.196302
iter 80 value 82.613085
iter 90 value 80.473540
iter 100 value 79.640873
final value 79.640873
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.945528
iter 10 value 94.750685
iter 20 value 93.883056
iter 30 value 93.654534
iter 40 value 89.038877
iter 50 value 83.347115
iter 60 value 82.377793
iter 70 value 81.462052
iter 80 value 80.795278
iter 90 value 79.471820
iter 100 value 79.307663
final value 79.307663
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.551468
iter 10 value 94.670779
iter 20 value 92.511136
iter 30 value 91.833759
iter 40 value 86.320564
iter 50 value 85.714835
iter 60 value 84.511332
iter 70 value 84.229007
iter 80 value 82.046511
iter 90 value 81.623902
iter 100 value 80.845646
final value 80.845646
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.441164
iter 10 value 94.967128
iter 20 value 91.681397
iter 30 value 86.908383
iter 40 value 85.484444
iter 50 value 83.602975
iter 60 value 82.000988
iter 70 value 79.794562
iter 80 value 79.245375
iter 90 value 79.006614
iter 100 value 78.653878
final value 78.653878
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.311824
iter 10 value 94.448848
iter 20 value 89.219893
iter 30 value 88.324235
iter 40 value 86.967923
iter 50 value 83.287861
iter 60 value 82.387724
iter 70 value 81.871810
iter 80 value 81.323986
iter 90 value 80.097703
iter 100 value 78.757081
final value 78.757081
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 118.739938
iter 10 value 94.563982
iter 20 value 86.852042
iter 30 value 85.136362
iter 40 value 84.566249
iter 50 value 83.604513
iter 60 value 81.870469
iter 70 value 81.017556
iter 80 value 80.089744
iter 90 value 79.846433
iter 100 value 79.625466
final value 79.625466
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.747564
iter 10 value 100.915851
iter 20 value 94.361617
iter 30 value 92.947587
iter 40 value 92.312341
iter 50 value 91.967892
iter 60 value 91.653711
iter 70 value 91.065069
iter 80 value 90.926734
iter 90 value 90.614126
iter 100 value 84.256204
final value 84.256204
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 124.959209
iter 10 value 93.621983
iter 20 value 91.468472
iter 30 value 85.238181
iter 40 value 83.532916
iter 50 value 81.317558
iter 60 value 81.170664
iter 70 value 80.429829
iter 80 value 79.437894
iter 90 value 79.179889
iter 100 value 79.132799
final value 79.132799
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 142.845162
iter 10 value 95.725936
iter 20 value 94.440360
iter 30 value 87.145188
iter 40 value 85.806112
iter 50 value 84.482471
iter 60 value 83.255990
iter 70 value 79.968094
iter 80 value 78.994672
iter 90 value 78.593601
iter 100 value 78.476652
final value 78.476652
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 108.163755
iter 10 value 94.096572
iter 20 value 84.965631
iter 30 value 84.598758
iter 40 value 81.380785
iter 50 value 80.110719
iter 60 value 79.683019
iter 70 value 79.136255
iter 80 value 79.045938
iter 90 value 78.917454
iter 100 value 78.842454
final value 78.842454
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.460134
final value 94.485869
converged
Fitting Repeat 2
# weights: 103
initial value 106.623878
iter 10 value 94.012134
iter 20 value 93.924738
iter 30 value 93.923994
final value 93.922815
converged
Fitting Repeat 3
# weights: 103
initial value 94.976095
final value 94.485851
converged
Fitting Repeat 4
# weights: 103
initial value 96.705378
final value 94.276940
converged
Fitting Repeat 5
# weights: 103
initial value 95.774732
iter 10 value 94.485964
iter 20 value 94.484232
iter 30 value 94.275499
iter 30 value 94.275499
iter 30 value 94.275499
final value 94.275499
converged
Fitting Repeat 1
# weights: 305
initial value 98.665339
iter 10 value 94.488386
iter 20 value 94.166785
iter 30 value 93.788503
iter 40 value 93.776873
iter 50 value 93.708049
iter 60 value 93.707565
final value 93.707536
converged
Fitting Repeat 2
# weights: 305
initial value 103.218097
iter 10 value 94.280863
iter 20 value 94.277596
iter 30 value 94.274772
iter 40 value 88.164107
iter 50 value 86.968710
iter 60 value 86.962230
iter 70 value 85.922410
iter 80 value 85.704751
iter 90 value 85.702890
iter 100 value 85.701919
final value 85.701919
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.811265
iter 10 value 94.489459
iter 20 value 94.279183
iter 30 value 87.852477
iter 40 value 85.280084
iter 50 value 85.033201
final value 85.032975
converged
Fitting Repeat 4
# weights: 305
initial value 100.991840
iter 10 value 94.488921
iter 20 value 94.321395
final value 93.788643
converged
Fitting Repeat 5
# weights: 305
initial value 96.221152
iter 10 value 94.489109
iter 20 value 94.462006
iter 30 value 94.323250
iter 40 value 92.554613
iter 50 value 88.251106
iter 60 value 87.194199
iter 60 value 87.194198
iter 60 value 87.194198
final value 87.194198
converged
Fitting Repeat 1
# weights: 507
initial value 94.461594
iter 10 value 85.517629
iter 20 value 84.081143
iter 30 value 84.077416
iter 40 value 84.076746
iter 50 value 84.075490
iter 60 value 84.075002
final value 84.074846
converged
Fitting Repeat 2
# weights: 507
initial value 107.592406
iter 10 value 94.341261
iter 20 value 94.101129
iter 30 value 88.804605
iter 40 value 82.345649
iter 50 value 82.323135
iter 60 value 82.298070
iter 70 value 81.694469
iter 80 value 81.595728
iter 90 value 80.199653
iter 100 value 79.075677
final value 79.075677
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.641939
iter 10 value 94.492826
iter 20 value 94.484692
iter 30 value 94.279983
iter 40 value 94.276036
iter 50 value 94.269383
iter 60 value 93.790878
iter 70 value 93.788905
iter 80 value 93.788764
iter 90 value 93.762996
iter 100 value 93.675047
final value 93.675047
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 96.750324
iter 10 value 94.283537
iter 20 value 93.740782
iter 30 value 84.947702
iter 40 value 82.986658
iter 50 value 82.743042
iter 60 value 82.733261
final value 82.733245
converged
Fitting Repeat 5
# weights: 507
initial value 104.755959
iter 10 value 94.320517
iter 20 value 91.799770
iter 30 value 87.992395
iter 40 value 87.296354
iter 50 value 86.766473
iter 60 value 85.073765
iter 70 value 82.041168
iter 80 value 81.577795
iter 90 value 80.868395
iter 100 value 79.526987
final value 79.526987
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.946394
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 99.983331
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 97.360687
final value 93.836066
converged
Fitting Repeat 4
# weights: 103
initial value 99.636107
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 106.068676
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 94.555443
final value 93.836066
converged
Fitting Repeat 2
# weights: 305
initial value 99.645437
final value 93.836066
converged
Fitting Repeat 3
# weights: 305
initial value 113.011182
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 95.109522
iter 10 value 94.054253
iter 20 value 94.052911
iter 20 value 94.052911
iter 20 value 94.052911
final value 94.052911
converged
Fitting Repeat 5
# weights: 305
initial value 96.525642
final value 93.836066
converged
Fitting Repeat 1
# weights: 507
initial value 109.462278
iter 10 value 94.095683
iter 20 value 84.857601
iter 30 value 84.674353
iter 40 value 84.578285
final value 84.578275
converged
Fitting Repeat 2
# weights: 507
initial value 107.152064
final value 93.836066
converged
Fitting Repeat 3
# weights: 507
initial value 110.400044
final value 93.836066
converged
Fitting Repeat 4
# weights: 507
initial value 103.440761
final value 93.836066
converged
Fitting Repeat 5
# weights: 507
initial value 104.481337
iter 10 value 94.055756
iter 20 value 94.052777
iter 30 value 93.852953
final value 93.836066
converged
Fitting Repeat 1
# weights: 103
initial value 97.806594
iter 10 value 94.005084
iter 20 value 89.283984
iter 30 value 86.528136
iter 40 value 84.354229
iter 50 value 83.679361
iter 60 value 82.640555
iter 70 value 82.225109
iter 80 value 82.043068
iter 90 value 82.042004
final value 82.041938
converged
Fitting Repeat 2
# weights: 103
initial value 106.129291
iter 10 value 93.938120
iter 20 value 86.438573
iter 30 value 82.555933
iter 40 value 80.574397
iter 50 value 79.883728
iter 60 value 79.697479
iter 70 value 79.634017
iter 80 value 79.596235
final value 79.596234
converged
Fitting Repeat 3
# weights: 103
initial value 105.491652
iter 10 value 93.963475
iter 20 value 89.148341
iter 30 value 88.015335
iter 40 value 84.958840
iter 50 value 84.242889
iter 60 value 83.026084
iter 70 value 82.654223
iter 80 value 82.381974
iter 90 value 82.347915
iter 100 value 80.126196
final value 80.126196
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 113.717014
iter 10 value 93.889032
iter 20 value 91.088584
iter 30 value 85.863528
iter 40 value 85.543848
iter 50 value 85.499387
iter 60 value 85.404780
iter 70 value 83.108319
iter 80 value 83.010872
iter 90 value 83.006265
iter 100 value 83.005426
final value 83.005426
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 97.083275
iter 10 value 94.063588
iter 20 value 94.036570
iter 30 value 92.026701
iter 40 value 91.558436
iter 50 value 91.495355
iter 60 value 83.992149
iter 70 value 83.534468
iter 80 value 83.250704
iter 90 value 83.029393
iter 100 value 83.010388
final value 83.010388
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 104.383510
iter 10 value 94.024341
iter 20 value 90.582345
iter 30 value 86.984487
iter 40 value 83.404807
iter 50 value 83.121772
iter 60 value 83.053326
iter 70 value 83.016129
iter 80 value 82.904330
iter 90 value 82.394993
iter 100 value 79.831248
final value 79.831248
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.213902
iter 10 value 93.467823
iter 20 value 87.124502
iter 30 value 83.792243
iter 40 value 83.187985
iter 50 value 82.872249
iter 60 value 82.399493
iter 70 value 79.452872
iter 80 value 78.359123
iter 90 value 78.182927
iter 100 value 78.000629
final value 78.000629
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 129.134396
iter 10 value 95.598630
iter 20 value 91.938417
iter 30 value 88.837599
iter 40 value 88.717847
iter 50 value 87.599985
iter 60 value 82.095410
iter 70 value 81.387091
iter 80 value 80.988115
iter 90 value 80.690138
iter 100 value 80.426070
final value 80.426070
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.777994
iter 10 value 94.079175
iter 20 value 93.908018
iter 30 value 85.276542
iter 40 value 84.721700
iter 50 value 84.024269
iter 60 value 83.430499
iter 70 value 83.147508
iter 80 value 82.854302
iter 90 value 82.748140
iter 100 value 82.546828
final value 82.546828
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.031017
iter 10 value 94.151140
iter 20 value 86.300222
iter 30 value 85.408668
iter 40 value 84.845112
iter 50 value 83.723921
iter 60 value 82.802115
iter 70 value 82.675371
iter 80 value 82.613927
iter 90 value 82.608462
iter 100 value 82.426107
final value 82.426107
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 121.134327
iter 10 value 94.443697
iter 20 value 94.058666
iter 30 value 93.397880
iter 40 value 89.245072
iter 50 value 84.614379
iter 60 value 82.616953
iter 70 value 81.571815
iter 80 value 81.048131
iter 90 value 78.741257
iter 100 value 77.735241
final value 77.735241
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.497512
iter 10 value 93.071987
iter 20 value 89.704340
iter 30 value 86.327937
iter 40 value 83.559180
iter 50 value 81.112396
iter 60 value 79.961317
iter 70 value 79.586700
iter 80 value 79.387090
iter 90 value 79.330477
iter 100 value 79.274872
final value 79.274872
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 107.380334
iter 10 value 94.199323
iter 20 value 94.057432
iter 30 value 90.855395
iter 40 value 83.608928
iter 50 value 82.010932
iter 60 value 80.782824
iter 70 value 78.972156
iter 80 value 78.715217
iter 90 value 78.463519
iter 100 value 78.209180
final value 78.209180
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.826919
iter 10 value 94.184939
iter 20 value 86.762718
iter 30 value 84.128460
iter 40 value 82.040023
iter 50 value 79.493343
iter 60 value 79.031128
iter 70 value 78.625893
iter 80 value 78.375900
iter 90 value 78.213399
iter 100 value 78.177484
final value 78.177484
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.336398
iter 10 value 92.477555
iter 20 value 84.140969
iter 30 value 82.962921
iter 40 value 82.759737
iter 50 value 82.375553
iter 60 value 82.093577
iter 70 value 81.670389
iter 80 value 81.235770
iter 90 value 81.068220
iter 100 value 80.907739
final value 80.907739
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.881003
iter 10 value 91.508804
iter 20 value 83.668812
iter 30 value 83.636498
iter 40 value 83.635817
final value 83.635072
converged
Fitting Repeat 2
# weights: 103
initial value 96.542551
final value 94.054344
converged
Fitting Repeat 3
# weights: 103
initial value 94.721594
iter 10 value 94.054645
iter 20 value 94.052950
final value 93.836280
converged
Fitting Repeat 4
# weights: 103
initial value 94.365023
iter 10 value 93.811961
iter 20 value 93.807882
final value 93.807262
converged
Fitting Repeat 5
# weights: 103
initial value 103.416892
final value 94.054542
converged
Fitting Repeat 1
# weights: 305
initial value 95.490918
iter 10 value 94.057597
iter 20 value 93.707537
iter 30 value 84.722831
iter 40 value 84.651999
iter 50 value 83.652037
iter 60 value 83.257861
iter 70 value 83.255137
iter 80 value 83.182583
iter 90 value 78.683238
iter 100 value 78.656738
final value 78.656738
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.295638
iter 10 value 84.138820
iter 20 value 83.636562
iter 30 value 83.634674
iter 40 value 83.619131
iter 50 value 83.485940
iter 60 value 83.452954
final value 83.452410
converged
Fitting Repeat 3
# weights: 305
initial value 106.088686
iter 10 value 94.057661
iter 20 value 92.458361
iter 30 value 83.978436
iter 40 value 80.584391
iter 50 value 78.845437
iter 60 value 78.781847
final value 78.781725
converged
Fitting Repeat 4
# weights: 305
initial value 105.775010
iter 10 value 93.840988
iter 20 value 92.791331
iter 30 value 85.435166
iter 40 value 80.720622
iter 50 value 79.788166
iter 60 value 79.594916
iter 70 value 79.583932
iter 80 value 79.582140
iter 90 value 79.578441
iter 100 value 79.559375
final value 79.559375
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 112.871090
iter 10 value 93.840958
iter 20 value 93.836443
iter 30 value 93.810464
iter 40 value 92.645748
iter 50 value 86.918197
iter 60 value 79.752836
iter 70 value 78.500659
iter 80 value 78.426484
iter 90 value 78.426144
iter 100 value 78.422275
final value 78.422275
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 100.690687
iter 10 value 93.844690
iter 20 value 93.837043
iter 30 value 92.089317
iter 40 value 81.428841
iter 50 value 80.995784
iter 50 value 80.995784
final value 80.995784
converged
Fitting Repeat 2
# weights: 507
initial value 101.886699
iter 10 value 93.806136
iter 20 value 93.781758
iter 30 value 93.779033
iter 40 value 93.772154
final value 93.771377
converged
Fitting Repeat 3
# weights: 507
initial value 114.084740
iter 10 value 92.951953
iter 20 value 92.579378
iter 30 value 90.820525
iter 40 value 90.795751
iter 50 value 90.777419
iter 60 value 90.746790
iter 70 value 89.195236
iter 80 value 88.605378
iter 90 value 88.597908
iter 100 value 88.553954
final value 88.553954
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 113.362551
iter 10 value 94.061287
iter 20 value 93.945460
iter 30 value 83.449183
iter 40 value 79.172377
iter 50 value 76.702245
iter 60 value 76.389453
iter 70 value 76.071436
iter 80 value 75.873779
iter 90 value 75.853380
iter 100 value 75.852837
final value 75.852837
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 133.969884
iter 10 value 94.061112
iter 20 value 94.052095
iter 30 value 85.923902
iter 40 value 83.197861
iter 50 value 80.268435
iter 60 value 78.754305
iter 70 value 78.517552
iter 80 value 78.372792
iter 90 value 77.768859
iter 100 value 76.642219
final value 76.642219
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.651581
iter 10 value 94.192095
iter 20 value 89.898921
iter 30 value 89.878316
final value 89.878271
converged
Fitting Repeat 2
# weights: 103
initial value 95.915213
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.749020
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.467251
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.326428
iter 10 value 93.939237
final value 93.939206
converged
Fitting Repeat 1
# weights: 305
initial value 110.416792
iter 10 value 93.975471
iter 20 value 92.343237
iter 30 value 92.121637
iter 30 value 92.121637
iter 30 value 92.121637
final value 92.121637
converged
Fitting Repeat 2
# weights: 305
initial value 100.531612
final value 94.467391
converged
Fitting Repeat 3
# weights: 305
initial value 110.235031
final value 94.484209
converged
Fitting Repeat 4
# weights: 305
initial value 103.353300
iter 10 value 94.472273
iter 10 value 94.472273
iter 10 value 94.472273
final value 94.472273
converged
Fitting Repeat 5
# weights: 305
initial value 101.886621
final value 94.467391
converged
Fitting Repeat 1
# weights: 507
initial value 113.989062
final value 94.467391
converged
Fitting Repeat 2
# weights: 507
initial value 110.503683
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 95.944858
iter 10 value 94.484591
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 99.128851
final value 94.467391
converged
Fitting Repeat 5
# weights: 507
initial value 107.151503
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 106.451530
iter 10 value 94.411368
iter 20 value 89.374328
iter 30 value 86.161685
iter 40 value 84.209585
iter 50 value 84.010049
iter 60 value 83.883642
iter 70 value 83.206516
iter 80 value 82.638276
iter 90 value 82.603874
final value 82.603870
converged
Fitting Repeat 2
# weights: 103
initial value 103.332428
iter 10 value 94.488545
iter 20 value 94.452624
iter 30 value 89.995034
iter 40 value 88.870691
iter 50 value 88.479972
iter 60 value 85.444412
iter 70 value 85.093310
iter 80 value 84.694828
iter 90 value 84.663737
final value 84.663315
converged
Fitting Repeat 3
# weights: 103
initial value 106.438512
iter 10 value 94.191787
iter 20 value 86.720628
iter 30 value 85.762157
iter 40 value 85.210906
iter 50 value 85.032549
iter 60 value 84.994536
final value 84.994447
converged
Fitting Repeat 4
# weights: 103
initial value 98.165311
iter 10 value 93.260555
iter 20 value 90.574700
iter 30 value 88.310825
iter 40 value 87.418811
iter 50 value 86.349741
iter 60 value 85.237793
iter 70 value 82.852228
iter 80 value 82.622328
iter 90 value 82.608095
final value 82.603869
converged
Fitting Repeat 5
# weights: 103
initial value 113.623842
iter 10 value 93.597234
iter 20 value 86.498100
iter 30 value 85.665562
iter 40 value 85.513228
iter 50 value 85.466720
final value 85.465101
converged
Fitting Repeat 1
# weights: 305
initial value 102.590714
iter 10 value 94.501353
iter 20 value 94.425873
iter 30 value 93.655712
iter 40 value 89.907704
iter 50 value 87.282291
iter 60 value 85.722177
iter 70 value 83.012218
iter 80 value 82.507553
iter 90 value 82.023541
iter 100 value 81.645235
final value 81.645235
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 111.440233
iter 10 value 94.616340
iter 20 value 91.389901
iter 30 value 89.953685
iter 40 value 88.891716
iter 50 value 86.253746
iter 60 value 85.562144
iter 70 value 85.465161
iter 80 value 84.729145
iter 90 value 84.387599
iter 100 value 84.382583
final value 84.382583
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.680988
iter 10 value 94.493912
iter 20 value 93.845953
iter 30 value 90.071829
iter 40 value 87.552682
iter 50 value 86.378145
iter 60 value 84.891765
iter 70 value 84.254390
iter 80 value 83.098914
iter 90 value 82.266545
iter 100 value 81.875045
final value 81.875045
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.488667
iter 10 value 94.547605
iter 20 value 90.876669
iter 30 value 86.329281
iter 40 value 85.345450
iter 50 value 84.967217
iter 60 value 84.591884
iter 70 value 83.628741
iter 80 value 83.083846
iter 90 value 82.671648
iter 100 value 82.244284
final value 82.244284
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.770447
iter 10 value 95.032494
iter 20 value 94.484820
iter 30 value 92.738190
iter 40 value 92.328182
iter 50 value 92.085341
iter 60 value 91.673010
iter 70 value 86.942794
iter 80 value 85.506214
iter 90 value 83.870204
iter 100 value 83.280121
final value 83.280121
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.914919
iter 10 value 94.875828
iter 20 value 87.027736
iter 30 value 83.527925
iter 40 value 82.876367
iter 50 value 81.738387
iter 60 value 81.606202
iter 70 value 81.478146
iter 80 value 81.292743
iter 90 value 81.192457
iter 100 value 81.012467
final value 81.012467
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 112.023129
iter 10 value 95.730299
iter 20 value 94.501860
iter 30 value 89.147610
iter 40 value 85.521386
iter 50 value 83.272802
iter 60 value 82.714394
iter 70 value 82.248094
iter 80 value 81.847284
iter 90 value 81.616492
iter 100 value 81.233375
final value 81.233375
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 125.742164
iter 10 value 94.707939
iter 20 value 93.856399
iter 30 value 93.220000
iter 40 value 92.074350
iter 50 value 91.612227
iter 60 value 91.262667
iter 70 value 86.966654
iter 80 value 85.000928
iter 90 value 84.155196
iter 100 value 82.861153
final value 82.861153
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 125.084674
iter 10 value 95.692591
iter 20 value 94.763033
iter 30 value 92.347558
iter 40 value 89.808412
iter 50 value 89.133798
iter 60 value 83.592610
iter 70 value 82.351197
iter 80 value 81.941631
iter 90 value 81.753324
iter 100 value 81.644843
final value 81.644843
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 125.460455
iter 10 value 94.286223
iter 20 value 92.290515
iter 30 value 92.182944
iter 40 value 92.120288
iter 50 value 92.059975
iter 60 value 86.166926
iter 70 value 84.514675
iter 80 value 83.319439
iter 90 value 82.178897
iter 100 value 82.076581
final value 82.076581
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 105.639399
final value 94.485811
converged
Fitting Repeat 2
# weights: 103
initial value 100.934726
final value 94.469274
converged
Fitting Repeat 3
# weights: 103
initial value 100.271932
final value 94.486097
converged
Fitting Repeat 4
# weights: 103
initial value 96.475951
final value 94.485937
converged
Fitting Repeat 5
# weights: 103
initial value 100.321287
final value 94.468995
converged
Fitting Repeat 1
# weights: 305
initial value 100.262893
iter 10 value 94.487324
iter 20 value 94.413738
iter 30 value 88.187766
iter 40 value 87.227104
iter 50 value 86.572760
iter 60 value 86.545339
iter 70 value 86.542956
iter 80 value 86.528072
iter 90 value 86.154241
iter 100 value 85.137163
final value 85.137163
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.083836
iter 10 value 94.483961
iter 20 value 94.467673
final value 94.467539
converged
Fitting Repeat 3
# weights: 305
initial value 112.305039
iter 10 value 93.937706
iter 20 value 93.905582
iter 30 value 93.902588
iter 40 value 93.853273
iter 50 value 93.843828
iter 60 value 92.478463
iter 70 value 92.235380
iter 80 value 92.222403
final value 92.222362
converged
Fitting Repeat 4
# weights: 305
initial value 95.826934
iter 10 value 94.088834
iter 20 value 93.564399
iter 30 value 88.562354
iter 40 value 88.558177
iter 50 value 87.556063
final value 86.952581
converged
Fitting Repeat 5
# weights: 305
initial value 97.719278
iter 10 value 94.489058
iter 20 value 94.478383
iter 30 value 93.281907
iter 40 value 93.136482
iter 50 value 93.136434
iter 60 value 93.129265
final value 93.129263
converged
Fitting Repeat 1
# weights: 507
initial value 98.795353
iter 10 value 94.492233
iter 20 value 91.349851
iter 30 value 87.315012
iter 40 value 82.476176
iter 50 value 81.319654
iter 60 value 80.979790
iter 70 value 80.717417
iter 80 value 80.681043
iter 90 value 80.659170
iter 100 value 80.482560
final value 80.482560
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 98.633144
iter 10 value 94.492423
iter 20 value 94.475845
iter 30 value 91.003813
iter 40 value 89.562782
iter 50 value 88.456322
iter 60 value 86.628413
final value 86.621264
converged
Fitting Repeat 3
# weights: 507
initial value 107.206820
iter 10 value 94.491885
iter 20 value 94.126422
iter 30 value 87.919881
iter 40 value 87.030987
iter 50 value 85.879856
iter 60 value 85.539781
iter 70 value 82.898780
iter 80 value 82.747235
iter 90 value 82.740197
iter 100 value 82.694652
final value 82.694652
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 101.345114
iter 10 value 94.492707
iter 20 value 94.439307
iter 30 value 93.438541
iter 40 value 89.607832
iter 50 value 86.031091
iter 60 value 85.930000
iter 70 value 83.806944
iter 80 value 83.475802
iter 90 value 83.365218
iter 100 value 82.468279
final value 82.468279
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 119.074516
iter 10 value 94.475576
iter 20 value 94.463845
iter 30 value 92.401787
iter 40 value 92.136163
iter 50 value 92.135707
final value 92.135694
converged
Fitting Repeat 1
# weights: 103
initial value 94.835944
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 100.241592
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 102.151979
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 97.749871
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 105.068078
final value 93.582418
converged
Fitting Repeat 1
# weights: 305
initial value 93.990645
final value 92.142857
converged
Fitting Repeat 2
# weights: 305
initial value 105.217251
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 95.720757
final value 93.582418
converged
Fitting Repeat 4
# weights: 305
initial value 101.534341
final value 93.582418
converged
Fitting Repeat 5
# weights: 305
initial value 115.716154
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 99.513565
final value 93.582418
converged
Fitting Repeat 2
# weights: 507
initial value 100.441700
iter 10 value 93.486191
iter 20 value 92.676015
iter 30 value 92.669560
final value 92.669553
converged
Fitting Repeat 3
# weights: 507
initial value 103.697632
final value 93.582418
converged
Fitting Repeat 4
# weights: 507
initial value 107.415237
iter 10 value 93.582418
iter 10 value 93.582418
iter 10 value 93.582418
final value 93.582418
converged
Fitting Repeat 5
# weights: 507
initial value 101.420492
final value 92.861582
converged
Fitting Repeat 1
# weights: 103
initial value 99.407864
iter 10 value 94.046964
iter 20 value 93.337122
iter 30 value 93.238950
iter 40 value 92.709806
iter 50 value 89.147727
iter 60 value 87.603146
iter 70 value 87.051694
iter 80 value 86.566709
iter 90 value 85.447749
iter 100 value 84.615655
final value 84.615655
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.258388
iter 10 value 93.992411
iter 20 value 90.637524
iter 30 value 89.581859
iter 40 value 88.797446
iter 50 value 88.138833
iter 60 value 88.048300
iter 70 value 85.758374
iter 80 value 84.727918
iter 90 value 84.528117
final value 84.527940
converged
Fitting Repeat 3
# weights: 103
initial value 103.990665
iter 10 value 94.055002
iter 20 value 90.648413
iter 30 value 88.317003
iter 40 value 87.180511
iter 50 value 86.702117
iter 60 value 85.261605
iter 70 value 84.607430
iter 80 value 84.562903
iter 90 value 84.545980
iter 100 value 84.527944
final value 84.527944
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 103.088755
iter 10 value 94.033443
iter 20 value 92.441674
iter 30 value 88.255312
iter 40 value 87.063783
iter 50 value 86.585714
iter 60 value 86.288506
iter 70 value 85.436647
iter 80 value 84.598602
iter 90 value 84.539303
iter 100 value 84.535469
final value 84.535469
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 109.423605
iter 10 value 93.954173
iter 20 value 92.135761
iter 30 value 88.063529
iter 40 value 87.634501
iter 50 value 86.997362
iter 60 value 86.939172
iter 70 value 86.509140
iter 80 value 86.294096
iter 90 value 85.157440
iter 100 value 84.538205
final value 84.538205
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.218277
iter 10 value 93.996385
iter 20 value 93.783730
iter 30 value 90.025847
iter 40 value 89.227565
iter 50 value 88.879399
iter 60 value 88.490426
iter 70 value 86.990032
iter 80 value 86.577474
iter 90 value 86.158660
iter 100 value 85.956882
final value 85.956882
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 112.854075
iter 10 value 93.979682
iter 20 value 92.859955
iter 30 value 88.423209
iter 40 value 86.457777
iter 50 value 85.090401
iter 60 value 84.302060
iter 70 value 84.065441
iter 80 value 83.924640
iter 90 value 83.801633
iter 100 value 83.624289
final value 83.624289
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.644483
iter 10 value 94.707983
iter 20 value 90.457023
iter 30 value 87.395525
iter 40 value 85.681266
iter 50 value 84.490512
iter 60 value 83.735676
iter 70 value 83.616479
iter 80 value 83.520373
iter 90 value 83.453384
iter 100 value 83.433920
final value 83.433920
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.917536
iter 10 value 94.284315
iter 20 value 93.074265
iter 30 value 91.098595
iter 40 value 87.719902
iter 50 value 86.412627
iter 60 value 84.695189
iter 70 value 84.155644
iter 80 value 83.970048
iter 90 value 83.754446
iter 100 value 83.694919
final value 83.694919
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 110.671596
iter 10 value 94.559375
iter 20 value 94.065426
iter 30 value 89.240590
iter 40 value 87.553155
iter 50 value 85.893584
iter 60 value 84.455047
iter 70 value 84.371387
iter 80 value 84.341236
iter 90 value 84.184755
iter 100 value 83.737330
final value 83.737330
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 113.859511
iter 10 value 93.781709
iter 20 value 89.431951
iter 30 value 88.151455
iter 40 value 85.512443
iter 50 value 84.935344
iter 60 value 84.836285
iter 70 value 84.230988
iter 80 value 83.838843
iter 90 value 83.608158
iter 100 value 83.521646
final value 83.521646
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 119.729498
iter 10 value 94.807811
iter 20 value 90.963234
iter 30 value 88.149676
iter 40 value 85.675417
iter 50 value 83.917986
iter 60 value 83.570365
iter 70 value 83.526830
iter 80 value 83.520846
iter 90 value 83.497941
iter 100 value 83.463748
final value 83.463748
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.101859
iter 10 value 94.053114
iter 20 value 88.432640
iter 30 value 87.630878
iter 40 value 85.910155
iter 50 value 84.678478
iter 60 value 84.076539
iter 70 value 83.968148
iter 80 value 83.771614
iter 90 value 83.593711
iter 100 value 83.487272
final value 83.487272
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.403387
iter 10 value 94.023105
iter 20 value 92.954373
iter 30 value 89.908084
iter 40 value 87.877880
iter 50 value 87.286425
iter 60 value 86.940431
iter 70 value 86.844278
iter 80 value 86.473207
iter 90 value 85.402900
iter 100 value 85.010460
final value 85.010460
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 121.991239
iter 10 value 94.078489
iter 20 value 93.429739
iter 30 value 92.301625
iter 40 value 91.619739
iter 50 value 90.257056
iter 60 value 87.168774
iter 70 value 86.067276
iter 80 value 85.752770
iter 90 value 84.588384
iter 100 value 83.986052
final value 83.986052
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.278441
final value 94.054402
converged
Fitting Repeat 2
# weights: 103
initial value 98.841599
iter 10 value 94.054332
iter 20 value 94.052918
iter 30 value 87.488946
iter 40 value 87.241113
iter 50 value 87.025616
iter 60 value 86.270655
iter 70 value 86.120503
iter 80 value 86.074898
iter 80 value 86.074897
final value 86.074897
converged
Fitting Repeat 3
# weights: 103
initial value 96.868425
final value 94.054479
converged
Fitting Repeat 4
# weights: 103
initial value 95.279845
final value 94.054689
converged
Fitting Repeat 5
# weights: 103
initial value 99.287604
iter 10 value 93.584015
iter 20 value 93.582886
iter 30 value 93.582567
iter 40 value 92.705605
iter 50 value 87.735526
iter 60 value 85.718477
iter 70 value 83.804196
iter 80 value 83.575755
iter 90 value 83.519893
iter 100 value 83.006061
final value 83.006061
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 114.599258
iter 10 value 93.587455
iter 20 value 93.584094
iter 30 value 93.582282
iter 40 value 90.072073
iter 50 value 88.166029
iter 60 value 88.117524
iter 70 value 88.114926
iter 80 value 88.006900
iter 90 value 87.986242
final value 87.986189
converged
Fitting Repeat 2
# weights: 305
initial value 96.389521
iter 10 value 94.057534
iter 20 value 94.052907
iter 30 value 92.854412
iter 40 value 92.810660
iter 50 value 92.810090
iter 60 value 92.809610
iter 60 value 92.809609
final value 92.809609
converged
Fitting Repeat 3
# weights: 305
initial value 97.579348
iter 10 value 88.587058
iter 20 value 88.356412
iter 30 value 88.312978
iter 40 value 88.311242
iter 50 value 88.310676
iter 60 value 88.309834
iter 70 value 88.308611
iter 80 value 88.308546
final value 88.308542
converged
Fitting Repeat 4
# weights: 305
initial value 97.000913
iter 10 value 93.915518
iter 20 value 93.588868
iter 30 value 93.585108
iter 40 value 93.538268
iter 50 value 93.306065
iter 60 value 93.003551
final value 92.819491
converged
Fitting Repeat 5
# weights: 305
initial value 103.206717
iter 10 value 93.116035
iter 20 value 92.864373
iter 30 value 92.857716
iter 40 value 92.821726
iter 50 value 92.819986
iter 60 value 92.809589
iter 60 value 92.809589
iter 60 value 92.809589
final value 92.809589
converged
Fitting Repeat 1
# weights: 507
initial value 97.419748
iter 10 value 93.590554
iter 20 value 93.586373
iter 30 value 93.584671
iter 40 value 92.920386
iter 50 value 92.853816
iter 60 value 92.852355
final value 92.852327
converged
Fitting Repeat 2
# weights: 507
initial value 96.587802
iter 10 value 93.571135
iter 20 value 93.567825
iter 30 value 93.559061
iter 40 value 92.791688
iter 50 value 92.612241
iter 60 value 92.447313
iter 70 value 92.444817
final value 92.444446
converged
Fitting Repeat 3
# weights: 507
initial value 106.598636
iter 10 value 93.908000
iter 20 value 93.906363
iter 30 value 93.454791
final value 93.452241
converged
Fitting Repeat 4
# weights: 507
initial value 118.095678
iter 10 value 93.593049
iter 20 value 93.586794
iter 30 value 93.585104
final value 93.584895
converged
Fitting Repeat 5
# weights: 507
initial value 95.637507
iter 10 value 92.869863
iter 20 value 92.858467
iter 30 value 92.852448
iter 40 value 92.834022
iter 50 value 92.809571
final value 92.809570
converged
Fitting Repeat 1
# weights: 305
initial value 136.987953
iter 10 value 117.954925
iter 20 value 111.636875
iter 30 value 107.764569
iter 40 value 106.745706
iter 50 value 106.575050
iter 60 value 106.482161
iter 70 value 105.909106
iter 80 value 104.321240
iter 90 value 103.923341
iter 100 value 103.754377
final value 103.754377
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 125.574676
iter 10 value 118.047914
iter 20 value 115.123533
iter 30 value 109.923064
iter 40 value 109.778237
iter 50 value 106.409140
iter 60 value 104.444653
iter 70 value 104.219575
iter 80 value 102.629507
iter 90 value 101.989607
iter 100 value 101.696852
final value 101.696852
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 131.682367
iter 10 value 117.832411
iter 20 value 116.992401
iter 30 value 112.397289
iter 40 value 106.020663
iter 50 value 103.681210
iter 60 value 103.003127
iter 70 value 102.868651
iter 80 value 102.498448
iter 90 value 101.886372
iter 100 value 101.714608
final value 101.714608
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 123.815215
iter 10 value 117.758400
iter 20 value 111.458785
iter 30 value 109.200757
iter 40 value 108.456459
iter 50 value 105.602193
iter 60 value 105.016370
iter 70 value 105.013764
iter 80 value 104.965768
iter 90 value 104.662725
iter 100 value 103.618677
final value 103.618677
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 125.545262
iter 10 value 117.867895
iter 20 value 109.180446
iter 30 value 107.333151
iter 40 value 106.721305
iter 50 value 106.038531
iter 60 value 105.366108
iter 70 value 103.523781
iter 80 value 102.996207
iter 90 value 102.796112
iter 100 value 102.563659
final value 102.563659
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Fri Mar 21 04:29:43 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
77.012 2.135 120.924
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 50.522 | 1.751 | 54.687 | |
| FreqInteractors | 0.473 | 0.027 | 0.526 | |
| calculateAAC | 0.070 | 0.015 | 0.087 | |
| calculateAutocor | 0.878 | 0.115 | 1.034 | |
| calculateCTDC | 0.146 | 0.007 | 0.159 | |
| calculateCTDD | 1.232 | 0.035 | 1.382 | |
| calculateCTDT | 0.437 | 0.017 | 0.477 | |
| calculateCTriad | 0.773 | 0.043 | 0.872 | |
| calculateDC | 0.250 | 0.027 | 0.286 | |
| calculateF | 0.704 | 0.022 | 0.753 | |
| calculateKSAAP | 0.281 | 0.025 | 0.310 | |
| calculateQD_Sm | 3.552 | 0.179 | 3.898 | |
| calculateTC | 4.725 | 0.451 | 5.421 | |
| calculateTC_Sm | 0.595 | 0.045 | 0.672 | |
| corr_plot | 50.432 | 1.737 | 55.343 | |
| enrichfindP | 0.908 | 0.086 | 13.554 | |
| enrichfind_hp | 0.129 | 0.028 | 1.114 | |
| enrichplot | 0.827 | 0.019 | 0.984 | |
| filter_missing_values | 0.002 | 0.000 | 0.003 | |
| getFASTA | 0.123 | 0.023 | 3.016 | |
| getHPI | 0.001 | 0.001 | 0.002 | |
| get_negativePPI | 0.003 | 0.001 | 0.004 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.002 | 0.001 | 0.003 | |
| plotPPI | 0.136 | 0.005 | 0.140 | |
| pred_ensembel | 25.270 | 0.474 | 24.488 | |
| var_imp | 50.689 | 1.721 | 57.319 | |