Matineh Rahmatbakhsh
| Snapshot Date: 2022-10-18 13:55:19 -0400 (Tue, 18 Oct 2022) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_15 |
| git_last_commit: 06d853c |
| git_last_commit_date: 2022-04-26 12:18:17 -0400 (Tue, 26 Apr 2022) |
| Back to Multiple platform build/check report for BioC 3.15 |
|
This page was generated on 2022-10-19 13:21:38 -0400 (Wed, 19 Oct 2022).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 20.04.5 LTS) | x86_64 | 4.2.1 (2022-06-23) -- "Funny-Looking Kid" | 4386 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.2.1 (2022-06-23 ucrt) -- "Funny-Looking Kid" | 4138 |
| merida1 | macOS 10.14.6 Mojave | x86_64 | 4.2.1 (2022-06-23) -- "Funny-Looking Kid" | 4205 |
| 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 | ||||
|
To the developers/maintainers of the HPiP package: - Please 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 How and When does the builder pull? When will my changes propagate? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 911/2140 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.2.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 20.04.5 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK | | ||||||||
| Package: HPiP |
| Version: 1.2.0 |
| Command: F:\biocbuild\bbs-3.15-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.15-bioc\R\library --no-vignettes --timings HPiP_1.2.0.tar.gz |
| StartedAt: 2022-10-19 01:02:38 -0400 (Wed, 19 Oct 2022) |
| EndedAt: 2022-10-19 01:07:32 -0400 (Wed, 19 Oct 2022) |
| EllapsedTime: 293.4 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.15-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.15-bioc\R\library --no-vignettes --timings HPiP_1.2.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.15-bioc/meat/HPiP.Rcheck'
* using R version 4.2.1 (2022-06-23 ucrt)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.2.0'
* 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 ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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 ... OK
* 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 30.58 1.28 31.95
corr_plot 30.61 1.16 31.77
var_imp 30.28 0.85 31.17
pred_ensembel 13.67 0.50 10.83
enrichfindP 0.41 0.08 11.87
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in 'inst/doc' ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
'F:/biocbuild/bbs-3.15-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.15-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.15-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 4.2.1 (2022-06-23 ucrt) -- "Funny-Looking Kid"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 96.080177
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 96.135603
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 99.105788
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 95.415718
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.697134
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 97.645000
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 104.555913
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 99.063900
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 116.646385
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 112.001370
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 98.211405
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 112.939452
final value 93.836066
converged
Fitting Repeat 3
# weights: 507
initial value 111.021246
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 99.990164
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 105.814244
iter 10 value 93.971976
final value 93.900000
converged
Fitting Repeat 1
# weights: 103
initial value 100.265740
iter 10 value 94.020557
iter 20 value 93.752299
iter 30 value 91.022795
iter 40 value 86.663074
iter 50 value 85.398301
iter 60 value 82.988722
iter 70 value 82.340173
iter 80 value 81.323810
iter 90 value 80.262114
iter 100 value 79.690586
final value 79.690586
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 111.228637
iter 10 value 94.054972
iter 20 value 94.033542
iter 30 value 91.024156
iter 40 value 86.565167
iter 50 value 83.178625
iter 60 value 80.406150
iter 70 value 79.967441
iter 80 value 79.928214
iter 90 value 79.926660
final value 79.926636
converged
Fitting Repeat 3
# weights: 103
initial value 96.906334
iter 10 value 94.063965
iter 20 value 92.276934
iter 30 value 86.162059
iter 40 value 83.560379
iter 50 value 82.849376
iter 60 value 82.581036
iter 70 value 82.554160
final value 82.553308
converged
Fitting Repeat 4
# weights: 103
initial value 98.040642
iter 10 value 93.761315
iter 20 value 85.219799
iter 30 value 81.813020
iter 40 value 80.772243
iter 50 value 80.583812
iter 60 value 80.371571
iter 70 value 79.786137
iter 80 value 79.749975
iter 90 value 79.599667
iter 100 value 79.559030
final value 79.559030
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 98.277581
iter 10 value 94.163038
iter 20 value 86.011429
iter 30 value 85.305937
iter 40 value 83.351918
iter 50 value 82.577432
iter 60 value 82.553463
final value 82.553308
converged
Fitting Repeat 1
# weights: 305
initial value 103.387518
iter 10 value 94.185887
iter 20 value 93.790253
iter 30 value 93.096385
iter 40 value 92.656465
iter 50 value 87.384712
iter 60 value 85.122960
iter 70 value 83.525119
iter 80 value 82.385458
iter 90 value 81.764007
iter 100 value 80.595041
final value 80.595041
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 140.718942
iter 10 value 94.323052
iter 20 value 88.894844
iter 30 value 87.499639
iter 40 value 85.716687
iter 50 value 82.984616
iter 60 value 81.382449
iter 70 value 80.588575
iter 80 value 79.167181
iter 90 value 78.925692
iter 100 value 78.834388
final value 78.834388
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.807583
iter 10 value 94.088212
iter 20 value 93.715137
iter 30 value 84.406405
iter 40 value 83.061930
iter 50 value 82.620336
iter 60 value 82.562456
iter 70 value 82.552853
iter 80 value 82.511156
iter 90 value 82.432243
iter 100 value 82.249736
final value 82.249736
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.859421
iter 10 value 93.992640
iter 20 value 93.746535
iter 30 value 92.750278
iter 40 value 88.019774
iter 50 value 83.935044
iter 60 value 81.249103
iter 70 value 79.725086
iter 80 value 78.612975
iter 90 value 78.121776
iter 100 value 77.866708
final value 77.866708
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 119.530681
iter 10 value 94.099712
iter 20 value 89.881543
iter 30 value 88.204351
iter 40 value 84.220424
iter 50 value 83.301836
iter 60 value 82.416227
iter 70 value 81.728513
iter 80 value 81.506668
iter 90 value 81.384960
iter 100 value 81.311408
final value 81.311408
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 115.221871
iter 10 value 94.028594
iter 20 value 90.056096
iter 30 value 85.103435
iter 40 value 84.463312
iter 50 value 83.356042
iter 60 value 81.003244
iter 70 value 80.488546
iter 80 value 80.420352
iter 90 value 80.227297
iter 100 value 80.113876
final value 80.113876
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 132.266321
iter 10 value 95.573129
iter 20 value 94.332566
iter 30 value 93.471040
iter 40 value 87.506051
iter 50 value 85.727575
iter 60 value 85.219780
iter 70 value 84.984221
iter 80 value 84.335775
iter 90 value 83.321427
iter 100 value 80.150589
final value 80.150589
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 119.662248
iter 10 value 88.211306
iter 20 value 85.409406
iter 30 value 81.167676
iter 40 value 80.565239
iter 50 value 79.681592
iter 60 value 78.630241
iter 70 value 78.388212
iter 80 value 78.007127
iter 90 value 77.915574
iter 100 value 77.766400
final value 77.766400
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.430287
iter 10 value 94.272813
iter 20 value 92.234337
iter 30 value 85.684410
iter 40 value 81.809261
iter 50 value 80.368462
iter 60 value 79.918708
iter 70 value 79.161474
iter 80 value 78.808521
iter 90 value 78.177623
iter 100 value 78.089904
final value 78.089904
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 125.484574
iter 10 value 94.050436
iter 20 value 93.154726
iter 30 value 91.269327
iter 40 value 88.183996
iter 50 value 82.819420
iter 60 value 81.165762
iter 70 value 79.870969
iter 80 value 79.650672
iter 90 value 79.323540
iter 100 value 79.120493
final value 79.120493
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 109.984082
final value 94.054479
converged
Fitting Repeat 2
# weights: 103
initial value 94.415378
iter 10 value 85.348049
iter 20 value 85.152756
iter 30 value 84.994064
iter 40 value 84.929946
iter 50 value 84.928409
iter 60 value 84.395163
iter 70 value 82.889286
iter 80 value 82.642725
iter 90 value 82.638394
iter 100 value 82.637415
final value 82.637415
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 95.452556
final value 94.054479
converged
Fitting Repeat 4
# weights: 103
initial value 96.073709
final value 94.054767
converged
Fitting Repeat 5
# weights: 103
initial value 104.652172
final value 94.054760
converged
Fitting Repeat 1
# weights: 305
initial value 121.091037
iter 10 value 93.775493
iter 20 value 93.637530
iter 30 value 93.633376
iter 40 value 91.826119
iter 50 value 88.116961
iter 60 value 82.389449
iter 70 value 81.580793
iter 80 value 81.575357
final value 81.574708
converged
Fitting Repeat 2
# weights: 305
initial value 102.104974
iter 10 value 94.057601
iter 20 value 88.143536
iter 30 value 82.868857
iter 40 value 82.307454
final value 82.304503
converged
Fitting Repeat 3
# weights: 305
initial value 100.764634
iter 10 value 93.945091
iter 20 value 93.664278
iter 30 value 93.637230
iter 40 value 93.632451
iter 50 value 93.632367
iter 50 value 93.632367
final value 93.632367
converged
Fitting Repeat 4
# weights: 305
initial value 98.218921
iter 10 value 94.055835
iter 20 value 93.669687
iter 30 value 93.634138
final value 93.632418
converged
Fitting Repeat 5
# weights: 305
initial value 94.857406
iter 10 value 94.057604
iter 20 value 94.052928
final value 94.052923
converged
Fitting Repeat 1
# weights: 507
initial value 105.618779
iter 10 value 94.061270
iter 20 value 94.002850
iter 30 value 89.361186
iter 40 value 85.164709
iter 50 value 84.908832
iter 60 value 84.897355
final value 84.897081
converged
Fitting Repeat 2
# weights: 507
initial value 102.763467
iter 10 value 94.060802
iter 20 value 94.052924
final value 94.052913
converged
Fitting Repeat 3
# weights: 507
initial value 107.000778
iter 10 value 93.654800
iter 20 value 93.640573
iter 30 value 93.633431
iter 40 value 89.166763
iter 50 value 84.704573
iter 60 value 77.776628
iter 70 value 77.386456
iter 80 value 77.210916
iter 90 value 77.143385
iter 100 value 77.142223
final value 77.142223
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 95.852541
iter 10 value 93.844549
iter 20 value 93.326682
iter 30 value 90.945765
iter 40 value 90.203397
iter 50 value 81.397286
iter 60 value 81.117600
final value 81.111815
converged
Fitting Repeat 5
# weights: 507
initial value 94.904901
iter 10 value 93.844025
iter 20 value 93.792042
iter 30 value 93.602521
iter 40 value 93.198651
iter 50 value 85.427093
iter 60 value 83.653223
iter 70 value 83.638910
iter 80 value 83.631855
iter 90 value 83.630644
iter 100 value 79.726062
final value 79.726062
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 108.145200
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 103.458677
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 103.559632
iter 10 value 94.275368
final value 94.275362
converged
Fitting Repeat 4
# weights: 103
initial value 97.163630
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 98.913223
iter 10 value 91.006339
final value 89.988316
converged
Fitting Repeat 1
# weights: 305
initial value 96.462285
final value 94.467391
converged
Fitting Repeat 2
# weights: 305
initial value 97.504751
final value 94.467391
converged
Fitting Repeat 3
# weights: 305
initial value 102.042425
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 95.711643
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 99.021872
final value 94.315791
converged
Fitting Repeat 1
# weights: 507
initial value 108.793442
iter 10 value 94.183441
iter 20 value 86.803968
iter 30 value 84.612725
iter 40 value 84.437609
final value 84.437607
converged
Fitting Repeat 2
# weights: 507
initial value 105.828164
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 95.680817
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 100.157889
iter 10 value 94.470705
iter 20 value 94.467396
final value 94.467392
converged
Fitting Repeat 5
# weights: 507
initial value 108.096838
iter 10 value 91.396256
iter 20 value 91.237556
iter 20 value 91.237555
iter 20 value 91.237555
final value 91.237555
converged
Fitting Repeat 1
# weights: 103
initial value 97.327684
iter 10 value 94.371564
iter 20 value 91.202391
iter 30 value 88.824168
iter 40 value 85.488617
iter 50 value 84.857134
iter 60 value 84.355069
iter 70 value 83.742530
iter 80 value 83.448610
iter 90 value 83.433600
final value 83.433281
converged
Fitting Repeat 2
# weights: 103
initial value 97.970524
iter 10 value 94.473342
iter 20 value 94.239130
iter 30 value 88.659975
iter 40 value 85.242659
iter 50 value 84.827482
iter 60 value 84.497347
iter 70 value 83.536086
iter 80 value 82.371627
iter 90 value 82.305354
iter 90 value 82.305354
iter 90 value 82.305354
final value 82.305354
converged
Fitting Repeat 3
# weights: 103
initial value 97.914660
iter 10 value 94.452442
iter 20 value 86.411939
iter 30 value 84.614756
iter 40 value 84.453811
iter 50 value 84.232114
iter 60 value 83.690435
iter 70 value 83.537157
iter 80 value 83.473545
iter 90 value 83.433338
final value 83.433281
converged
Fitting Repeat 4
# weights: 103
initial value 99.805435
iter 10 value 94.489099
iter 20 value 89.984812
iter 30 value 89.470673
iter 40 value 86.103069
iter 50 value 84.969304
iter 60 value 83.208231
iter 70 value 82.227614
iter 80 value 82.143037
iter 90 value 82.070787
iter 90 value 82.070787
iter 90 value 82.070787
final value 82.070787
converged
Fitting Repeat 5
# weights: 103
initial value 97.704053
iter 10 value 94.487766
iter 20 value 92.677665
iter 30 value 91.789481
iter 40 value 91.167936
iter 50 value 90.788758
iter 60 value 90.708768
iter 70 value 84.391623
iter 80 value 83.889264
iter 90 value 83.098628
iter 100 value 82.522187
final value 82.522187
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 102.037146
iter 10 value 94.231919
iter 20 value 90.296694
iter 30 value 85.970650
iter 40 value 83.992886
iter 50 value 83.657730
iter 60 value 82.920623
iter 70 value 81.787271
iter 80 value 81.259562
iter 90 value 81.235106
iter 100 value 81.189551
final value 81.189551
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.085112
iter 10 value 94.610266
iter 20 value 89.833704
iter 30 value 86.315959
iter 40 value 85.941407
iter 50 value 85.594867
iter 60 value 84.285946
iter 70 value 83.732934
iter 80 value 82.989377
iter 90 value 82.456648
iter 100 value 81.924199
final value 81.924199
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 117.782074
iter 10 value 94.285340
iter 20 value 87.381164
iter 30 value 86.406982
iter 40 value 85.082431
iter 50 value 84.705480
iter 60 value 84.186238
iter 70 value 83.908132
iter 80 value 83.272140
iter 90 value 82.989694
iter 100 value 82.598933
final value 82.598933
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.447664
iter 10 value 93.711859
iter 20 value 86.484012
iter 30 value 85.143136
iter 40 value 84.808494
iter 50 value 84.019887
iter 60 value 82.492371
iter 70 value 82.216808
iter 80 value 81.514279
iter 90 value 81.119473
iter 100 value 80.845552
final value 80.845552
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.221401
iter 10 value 90.603833
iter 20 value 85.444147
iter 30 value 84.298043
iter 40 value 83.946029
iter 50 value 83.547804
iter 60 value 83.341511
iter 70 value 83.330052
iter 80 value 82.911187
iter 90 value 82.209245
iter 100 value 82.152359
final value 82.152359
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.064430
iter 10 value 94.520198
iter 20 value 87.428340
iter 30 value 86.713445
iter 40 value 86.263150
iter 50 value 84.632048
iter 60 value 84.375545
iter 70 value 83.946331
iter 80 value 81.498618
iter 90 value 81.133247
iter 100 value 80.970770
final value 80.970770
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.244291
iter 10 value 94.090515
iter 20 value 92.761478
iter 30 value 88.706532
iter 40 value 85.873468
iter 50 value 84.296580
iter 60 value 83.344347
iter 70 value 81.787874
iter 80 value 81.272102
iter 90 value 81.028882
iter 100 value 80.946085
final value 80.946085
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.518735
iter 10 value 93.158103
iter 20 value 86.539689
iter 30 value 84.917534
iter 40 value 84.343776
iter 50 value 84.005854
iter 60 value 83.294468
iter 70 value 82.343729
iter 80 value 81.491227
iter 90 value 81.248629
iter 100 value 80.914438
final value 80.914438
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.874515
iter 10 value 91.906221
iter 20 value 88.434676
iter 30 value 86.750893
iter 40 value 86.285812
iter 50 value 84.913562
iter 60 value 81.750417
iter 70 value 81.443895
iter 80 value 81.304526
iter 90 value 81.174206
iter 100 value 81.111376
final value 81.111376
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 122.664784
iter 10 value 94.961804
iter 20 value 92.026523
iter 30 value 90.890499
iter 40 value 85.864147
iter 50 value 84.556381
iter 60 value 84.318765
iter 70 value 84.075483
iter 80 value 83.644204
iter 90 value 83.244436
iter 100 value 83.043664
final value 83.043664
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 108.816670
final value 94.485884
converged
Fitting Repeat 2
# weights: 103
initial value 101.861710
final value 94.485826
converged
Fitting Repeat 3
# weights: 103
initial value 102.824034
final value 94.469276
converged
Fitting Repeat 4
# weights: 103
initial value 108.103506
final value 94.485990
converged
Fitting Repeat 5
# weights: 103
initial value 97.155682
final value 94.485824
converged
Fitting Repeat 1
# weights: 305
initial value 119.425492
iter 10 value 94.488708
iter 20 value 94.416165
iter 30 value 87.067914
iter 40 value 85.973678
iter 50 value 85.929753
final value 85.929577
converged
Fitting Repeat 2
# weights: 305
initial value 103.186611
iter 10 value 94.490116
iter 20 value 94.459206
iter 30 value 90.098292
iter 40 value 89.757190
iter 50 value 89.751562
iter 60 value 89.743430
iter 70 value 89.742262
iter 80 value 89.738793
final value 89.736575
converged
Fitting Repeat 3
# weights: 305
initial value 103.989973
iter 10 value 91.735962
iter 20 value 89.889241
iter 30 value 89.886566
iter 40 value 89.883648
iter 50 value 85.820399
iter 60 value 85.515223
iter 70 value 85.487074
final value 85.485983
converged
Fitting Repeat 4
# weights: 305
initial value 99.759552
iter 10 value 94.489741
iter 20 value 94.484382
iter 30 value 93.601986
iter 40 value 92.279736
final value 92.277870
converged
Fitting Repeat 5
# weights: 305
initial value 121.080249
iter 10 value 94.479840
iter 20 value 94.471994
iter 30 value 94.467637
iter 40 value 92.281429
iter 50 value 85.785203
iter 60 value 84.425980
iter 70 value 84.423867
final value 84.423698
converged
Fitting Repeat 1
# weights: 507
initial value 99.542924
iter 10 value 94.492774
iter 20 value 94.469964
iter 30 value 91.972736
iter 40 value 91.920740
iter 50 value 91.920653
final value 91.920578
converged
Fitting Repeat 2
# weights: 507
initial value 102.145212
iter 10 value 94.492727
iter 20 value 94.150969
iter 30 value 93.911267
iter 40 value 91.393620
iter 50 value 91.167404
iter 60 value 91.055903
iter 70 value 91.055801
iter 80 value 91.007489
iter 90 value 90.971846
final value 90.971843
converged
Fitting Repeat 3
# weights: 507
initial value 97.250142
iter 10 value 94.283571
final value 94.283422
converged
Fitting Repeat 4
# weights: 507
initial value 114.507834
iter 10 value 94.332005
iter 20 value 91.649471
iter 30 value 89.849227
iter 40 value 89.145103
iter 50 value 88.339604
iter 60 value 87.534919
iter 70 value 87.409248
iter 80 value 87.200728
iter 90 value 87.199439
iter 100 value 87.197811
final value 87.197811
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 110.774099
iter 10 value 94.492348
iter 20 value 94.331253
iter 30 value 94.326336
iter 40 value 94.153183
iter 50 value 92.472688
iter 60 value 91.088495
iter 70 value 91.079021
iter 80 value 91.077308
iter 90 value 90.953667
iter 100 value 90.523561
final value 90.523561
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.796485
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 96.716205
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 97.643145
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 100.146532
final value 93.892857
converged
Fitting Repeat 5
# weights: 103
initial value 97.317333
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 94.792427
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 95.477616
final value 93.836066
converged
Fitting Repeat 3
# weights: 305
initial value 97.121680
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 97.448403
iter 10 value 93.089757
final value 93.086891
converged
Fitting Repeat 5
# weights: 305
initial value 99.249585
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 108.573690
iter 10 value 92.911401
iter 20 value 92.847524
final value 92.844789
converged
Fitting Repeat 2
# weights: 507
initial value 124.437921
iter 10 value 89.641762
iter 20 value 85.863380
iter 30 value 85.753421
iter 40 value 85.656434
final value 85.655649
converged
Fitting Repeat 3
# weights: 507
initial value 96.804967
final value 94.011561
converged
Fitting Repeat 4
# weights: 507
initial value 95.058948
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 97.471391
final value 93.836066
converged
Fitting Repeat 1
# weights: 103
initial value 99.032693
iter 10 value 94.052558
iter 20 value 93.916374
iter 30 value 92.968135
iter 40 value 85.614953
iter 50 value 84.849016
iter 60 value 84.637422
iter 70 value 84.611765
final value 84.611687
converged
Fitting Repeat 2
# weights: 103
initial value 96.903702
iter 10 value 93.997341
iter 20 value 92.252335
iter 30 value 91.828296
iter 40 value 91.430704
iter 50 value 91.247612
final value 91.226030
converged
Fitting Repeat 3
# weights: 103
initial value 97.446681
iter 10 value 94.056712
iter 20 value 93.943780
iter 30 value 93.357335
iter 40 value 87.426397
iter 50 value 86.369964
iter 60 value 85.035301
iter 70 value 83.857905
iter 80 value 83.173544
iter 90 value 82.948103
iter 100 value 82.902200
final value 82.902200
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.818532
iter 10 value 94.055078
iter 20 value 93.470102
iter 30 value 93.322926
iter 40 value 93.299771
iter 50 value 85.112697
iter 60 value 84.721264
iter 70 value 84.616136
final value 84.611686
converged
Fitting Repeat 5
# weights: 103
initial value 99.952636
iter 10 value 94.056706
iter 20 value 93.799342
iter 30 value 93.478086
iter 40 value 93.431356
iter 50 value 93.329637
iter 60 value 92.609470
iter 70 value 86.818086
iter 80 value 86.692655
iter 90 value 84.956759
iter 100 value 84.093575
final value 84.093575
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 114.062389
iter 10 value 92.456896
iter 20 value 88.236556
iter 30 value 85.520061
iter 40 value 83.362346
iter 50 value 82.329650
iter 60 value 82.019827
iter 70 value 81.958512
iter 80 value 81.917743
iter 90 value 81.886523
iter 100 value 81.842990
final value 81.842990
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.874315
iter 10 value 94.002010
iter 20 value 89.148353
iter 30 value 84.904989
iter 40 value 84.353082
iter 50 value 83.051038
iter 60 value 82.776968
iter 70 value 82.550828
iter 80 value 82.305458
iter 90 value 82.180503
iter 100 value 82.141437
final value 82.141437
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.431735
iter 10 value 94.006254
iter 20 value 88.033479
iter 30 value 85.396497
iter 40 value 84.093599
iter 50 value 83.966680
iter 60 value 83.862710
iter 70 value 83.549974
iter 80 value 82.623021
iter 90 value 82.042645
iter 100 value 81.822143
final value 81.822143
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.285598
iter 10 value 94.101612
iter 20 value 93.868462
iter 30 value 92.816318
iter 40 value 87.388215
iter 50 value 84.265974
iter 60 value 82.440682
iter 70 value 82.130600
iter 80 value 81.998599
iter 90 value 81.883733
iter 100 value 81.802909
final value 81.802909
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.337983
iter 10 value 93.995400
iter 20 value 93.444490
iter 30 value 89.700902
iter 40 value 87.549960
iter 50 value 86.707067
iter 60 value 83.752393
iter 70 value 82.836820
iter 80 value 82.666547
iter 90 value 82.449591
iter 100 value 82.207921
final value 82.207921
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 129.336744
iter 10 value 94.095649
iter 20 value 93.170702
iter 30 value 90.821361
iter 40 value 85.848946
iter 50 value 84.980368
iter 60 value 83.529326
iter 70 value 83.343673
iter 80 value 83.332533
iter 90 value 83.319304
iter 100 value 82.948134
final value 82.948134
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 147.564392
iter 10 value 94.167537
iter 20 value 86.535096
iter 30 value 84.743324
iter 40 value 83.011423
iter 50 value 82.624400
iter 60 value 82.287108
iter 70 value 82.100794
iter 80 value 81.816785
iter 90 value 81.676678
iter 100 value 81.565780
final value 81.565780
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.920840
iter 10 value 93.629232
iter 20 value 87.859624
iter 30 value 86.073849
iter 40 value 83.980714
iter 50 value 83.510349
iter 60 value 83.398068
iter 70 value 83.355727
iter 80 value 83.239046
iter 90 value 82.654341
iter 100 value 82.163867
final value 82.163867
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 115.829866
iter 10 value 94.867298
iter 20 value 88.733760
iter 30 value 88.042877
iter 40 value 86.685955
iter 50 value 84.216901
iter 60 value 83.369485
iter 70 value 82.581476
iter 80 value 82.180115
iter 90 value 82.111302
iter 100 value 81.970704
final value 81.970704
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.751550
iter 10 value 93.883816
iter 20 value 89.925781
iter 30 value 84.837606
iter 40 value 83.528272
iter 50 value 82.454503
iter 60 value 82.024503
iter 70 value 81.768119
iter 80 value 81.626360
iter 90 value 81.513615
iter 100 value 81.371384
final value 81.371384
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 112.659752
final value 94.013194
converged
Fitting Repeat 2
# weights: 103
initial value 112.627776
final value 94.054563
converged
Fitting Repeat 3
# weights: 103
initial value 101.575964
final value 94.051683
converged
Fitting Repeat 4
# weights: 103
initial value 94.757280
final value 94.054507
converged
Fitting Repeat 5
# weights: 103
initial value 97.751805
iter 10 value 94.054500
iter 20 value 94.052971
final value 94.052916
converged
Fitting Repeat 1
# weights: 305
initial value 98.052452
iter 10 value 94.057560
iter 20 value 92.756302
iter 30 value 83.964170
iter 40 value 83.836699
iter 50 value 83.821062
iter 50 value 83.821062
iter 50 value 83.821062
final value 83.821062
converged
Fitting Repeat 2
# weights: 305
initial value 113.583219
iter 10 value 94.057066
iter 20 value 94.018994
iter 30 value 93.448312
iter 40 value 92.693167
final value 92.693090
converged
Fitting Repeat 3
# weights: 305
initial value 95.917849
iter 10 value 94.057797
iter 20 value 94.053022
iter 30 value 93.964748
iter 40 value 90.649763
iter 50 value 89.163498
iter 60 value 87.844604
iter 70 value 87.785306
iter 80 value 86.472374
iter 90 value 84.412977
iter 100 value 83.623465
final value 83.623465
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.598283
iter 10 value 89.888314
iter 20 value 83.957968
iter 30 value 83.125397
iter 40 value 83.123736
iter 50 value 83.116847
final value 83.116538
converged
Fitting Repeat 5
# weights: 305
initial value 98.202847
iter 10 value 94.057867
iter 20 value 94.050686
iter 30 value 87.132505
iter 40 value 86.206097
iter 50 value 84.771707
iter 60 value 83.122527
iter 70 value 81.774285
iter 80 value 81.729429
iter 90 value 81.717000
final value 81.682424
converged
Fitting Repeat 1
# weights: 507
initial value 101.858761
iter 10 value 93.844649
iter 20 value 93.272905
iter 30 value 93.087441
iter 40 value 93.068351
final value 93.068304
converged
Fitting Repeat 2
# weights: 507
initial value 98.886392
iter 10 value 93.330319
iter 20 value 92.388925
iter 30 value 92.382084
iter 40 value 86.413329
iter 50 value 85.117971
iter 60 value 83.931069
iter 70 value 81.254545
iter 80 value 81.000625
iter 90 value 80.993777
iter 100 value 80.954812
final value 80.954812
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 99.331815
iter 10 value 93.838882
iter 20 value 93.833497
iter 30 value 93.832563
iter 40 value 93.832400
iter 50 value 93.468491
iter 60 value 93.173611
iter 70 value 93.172852
iter 80 value 92.231626
iter 90 value 91.912802
final value 91.912458
converged
Fitting Repeat 4
# weights: 507
initial value 118.146022
iter 10 value 93.844061
iter 20 value 93.834483
iter 30 value 90.630980
iter 40 value 84.564655
iter 50 value 83.625559
iter 60 value 80.835917
iter 70 value 80.534159
iter 80 value 80.490998
iter 90 value 80.481409
final value 80.481206
converged
Fitting Repeat 5
# weights: 507
initial value 96.183855
iter 10 value 93.543845
iter 20 value 93.507126
iter 30 value 93.472580
iter 40 value 93.302553
iter 50 value 87.416806
iter 60 value 84.698240
iter 70 value 84.436382
iter 80 value 81.243279
iter 90 value 80.861960
iter 100 value 80.860081
final value 80.860081
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.762166
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.913190
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.598304
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 99.955612
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.594125
iter 10 value 94.275374
final value 94.275363
converged
Fitting Repeat 1
# weights: 305
initial value 117.447340
final value 94.354286
converged
Fitting Repeat 2
# weights: 305
initial value 97.905482
final value 94.443182
converged
Fitting Repeat 3
# weights: 305
initial value 99.985040
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 96.056063
final value 94.275362
converged
Fitting Repeat 5
# weights: 305
initial value 104.489315
iter 10 value 94.270312
final value 94.046703
converged
Fitting Repeat 1
# weights: 507
initial value 103.015766
iter 10 value 93.860001
final value 93.859849
converged
Fitting Repeat 2
# weights: 507
initial value 95.018383
iter 10 value 93.123997
iter 20 value 93.075714
iter 20 value 93.075714
iter 20 value 93.075714
final value 93.075714
converged
Fitting Repeat 3
# weights: 507
initial value 101.788151
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 96.873224
iter 10 value 87.121529
final value 86.875143
converged
Fitting Repeat 5
# weights: 507
initial value 96.800637
iter 10 value 94.484942
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 97.086863
iter 10 value 94.491329
iter 20 value 94.409038
iter 30 value 93.749325
iter 40 value 92.338454
iter 50 value 84.806463
iter 60 value 84.222813
iter 70 value 83.475486
iter 80 value 82.432149
iter 90 value 82.298400
iter 100 value 82.192090
final value 82.192090
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 110.703661
iter 10 value 94.450599
iter 20 value 94.167537
iter 30 value 94.076421
iter 40 value 94.069737
iter 50 value 94.069494
iter 50 value 94.069493
iter 50 value 94.069493
final value 94.069493
converged
Fitting Repeat 3
# weights: 103
initial value 98.884092
iter 10 value 94.441416
iter 20 value 88.941207
iter 30 value 86.315253
iter 40 value 84.761789
iter 50 value 84.123297
iter 60 value 84.023723
final value 84.012817
converged
Fitting Repeat 4
# weights: 103
initial value 97.376753
iter 10 value 89.210588
iter 20 value 86.150164
iter 30 value 84.887996
iter 40 value 84.203133
iter 50 value 83.565639
iter 60 value 83.560264
final value 83.560084
converged
Fitting Repeat 5
# weights: 103
initial value 97.482410
iter 10 value 94.480827
iter 20 value 93.901133
iter 30 value 86.897357
iter 40 value 85.166502
iter 50 value 84.323174
iter 60 value 84.219790
iter 70 value 84.014688
final value 84.012817
converged
Fitting Repeat 1
# weights: 305
initial value 102.596761
iter 10 value 94.340673
iter 20 value 90.478097
iter 30 value 88.836604
iter 40 value 87.594185
iter 50 value 84.118756
iter 60 value 82.798245
iter 70 value 82.558977
iter 80 value 82.482457
iter 90 value 82.292562
iter 100 value 82.149699
final value 82.149699
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.907245
iter 10 value 94.669612
iter 20 value 89.311087
iter 30 value 87.378238
iter 40 value 83.030587
iter 50 value 81.686451
iter 60 value 80.993157
iter 70 value 80.898294
iter 80 value 80.671457
iter 90 value 80.602014
iter 100 value 80.597706
final value 80.597706
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.521834
iter 10 value 94.489097
iter 20 value 94.419388
iter 30 value 93.685248
iter 40 value 85.960817
iter 50 value 85.048839
iter 60 value 84.617393
iter 70 value 84.390550
iter 80 value 83.781394
iter 90 value 82.654816
iter 100 value 81.369558
final value 81.369558
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.930556
iter 10 value 95.270215
iter 20 value 93.846111
iter 30 value 89.818400
iter 40 value 85.780906
iter 50 value 84.181923
iter 60 value 83.913929
iter 70 value 83.765019
iter 80 value 83.720453
iter 90 value 83.512952
iter 100 value 83.331954
final value 83.331954
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.154786
iter 10 value 94.631915
iter 20 value 87.624758
iter 30 value 85.214954
iter 40 value 84.945519
iter 50 value 84.477788
iter 60 value 84.227239
iter 70 value 83.961469
iter 80 value 83.842105
iter 90 value 83.812989
iter 100 value 83.773403
final value 83.773403
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 120.308287
iter 10 value 95.549222
iter 20 value 87.464718
iter 30 value 85.221665
iter 40 value 83.979563
iter 50 value 83.518174
iter 60 value 82.675297
iter 70 value 82.101633
iter 80 value 81.374744
iter 90 value 81.275838
iter 100 value 81.069152
final value 81.069152
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.020192
iter 10 value 94.798340
iter 20 value 92.661563
iter 30 value 87.003671
iter 40 value 85.083916
iter 50 value 82.859840
iter 60 value 81.703247
iter 70 value 81.230347
iter 80 value 81.095001
iter 90 value 80.899897
iter 100 value 80.802008
final value 80.802008
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.026218
iter 10 value 93.486896
iter 20 value 84.894573
iter 30 value 83.693172
iter 40 value 82.608373
iter 50 value 82.540103
iter 60 value 82.522008
iter 70 value 82.489672
iter 80 value 82.421719
iter 90 value 81.616373
iter 100 value 81.235107
final value 81.235107
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.390402
iter 10 value 94.227990
iter 20 value 88.258656
iter 30 value 85.042926
iter 40 value 84.292740
iter 50 value 83.187943
iter 60 value 83.057725
iter 70 value 83.007223
iter 80 value 82.980425
iter 90 value 82.640845
iter 100 value 81.880315
final value 81.880315
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 120.523126
iter 10 value 89.701560
iter 20 value 85.974665
iter 30 value 85.688879
iter 40 value 84.760031
iter 50 value 83.124080
iter 60 value 82.820565
iter 70 value 82.596989
iter 80 value 82.428054
iter 90 value 82.325839
iter 100 value 82.153014
final value 82.153014
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.360283
iter 10 value 94.485714
iter 20 value 94.450695
iter 30 value 86.930748
iter 40 value 85.292486
iter 50 value 85.289699
iter 60 value 85.283978
iter 70 value 85.282516
iter 80 value 85.280879
iter 90 value 85.275169
iter 100 value 84.911851
final value 84.911851
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.023350
final value 94.486089
converged
Fitting Repeat 3
# weights: 103
initial value 94.519766
iter 10 value 94.356110
final value 94.356075
converged
Fitting Repeat 4
# weights: 103
initial value 100.266116
final value 94.485753
converged
Fitting Repeat 5
# weights: 103
initial value 98.876589
final value 94.486170
converged
Fitting Repeat 1
# weights: 305
initial value 95.713680
iter 10 value 93.061636
iter 20 value 92.901302
iter 30 value 92.898928
iter 40 value 92.895829
final value 92.895185
converged
Fitting Repeat 2
# weights: 305
initial value 96.642964
iter 10 value 94.282344
iter 20 value 94.279998
iter 30 value 94.274323
iter 40 value 92.131648
iter 50 value 85.131401
iter 60 value 84.857977
iter 70 value 84.634946
iter 80 value 84.457123
iter 90 value 84.350736
iter 100 value 84.281241
final value 84.281241
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 96.215669
iter 10 value 94.280112
iter 20 value 94.178007
iter 30 value 94.166254
final value 94.166129
converged
Fitting Repeat 4
# weights: 305
initial value 101.459426
iter 10 value 94.280182
iter 20 value 94.226636
iter 30 value 93.964721
iter 40 value 86.247874
iter 50 value 84.913609
iter 60 value 84.910304
iter 70 value 84.907891
final value 84.907839
converged
Fitting Repeat 5
# weights: 305
initial value 99.311968
iter 10 value 94.493032
iter 20 value 94.488123
final value 94.488068
converged
Fitting Repeat 1
# weights: 507
initial value 102.234230
iter 10 value 94.284153
iter 20 value 93.887226
iter 30 value 86.713854
iter 40 value 84.735685
iter 50 value 83.604948
iter 60 value 81.837064
iter 70 value 81.253510
iter 80 value 81.242580
iter 90 value 81.236896
iter 100 value 81.226993
final value 81.226993
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.978852
iter 10 value 94.491516
iter 20 value 94.255876
iter 30 value 84.760145
iter 40 value 84.303644
iter 50 value 82.991621
iter 60 value 82.835030
final value 82.834908
converged
Fitting Repeat 3
# weights: 507
initial value 100.421347
iter 10 value 94.206568
iter 20 value 93.725741
iter 30 value 93.287956
iter 40 value 93.280170
final value 93.280082
converged
Fitting Repeat 4
# weights: 507
initial value 94.644994
iter 10 value 86.219115
iter 20 value 84.446291
iter 30 value 83.877259
iter 40 value 83.874277
iter 50 value 83.866865
iter 60 value 83.820889
iter 70 value 83.715923
iter 80 value 83.504902
iter 90 value 83.496086
iter 100 value 83.495851
final value 83.495851
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 100.033266
iter 10 value 94.283499
iter 20 value 94.278793
iter 30 value 94.277799
iter 40 value 94.275724
iter 50 value 94.057617
iter 60 value 93.723804
iter 70 value 85.758289
iter 80 value 82.053029
iter 90 value 80.702599
iter 100 value 79.661590
final value 79.661590
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.931199
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.982732
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 106.672111
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 108.219723
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 97.042822
final value 94.484210
converged
Fitting Repeat 1
# weights: 305
initial value 99.711295
iter 10 value 94.289235
final value 94.289216
converged
Fitting Repeat 2
# weights: 305
initial value 96.519235
iter 10 value 91.791132
iter 20 value 91.654570
final value 91.651099
converged
Fitting Repeat 3
# weights: 305
initial value 99.653854
iter 10 value 93.318986
iter 20 value 93.314524
final value 93.314521
converged
Fitting Repeat 4
# weights: 305
initial value 98.238351
iter 10 value 89.441140
iter 20 value 84.556105
iter 30 value 84.530662
final value 84.530400
converged
Fitting Repeat 5
# weights: 305
initial value 127.960567
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 106.987923
iter 10 value 93.033816
iter 20 value 91.753346
iter 30 value 91.752301
iter 40 value 91.731678
iter 50 value 91.630395
final value 91.630392
converged
Fitting Repeat 2
# weights: 507
initial value 114.313240
iter 10 value 93.376072
iter 20 value 93.140780
final value 93.107521
converged
Fitting Repeat 3
# weights: 507
initial value 111.789594
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 99.299160
iter 10 value 92.605904
iter 20 value 89.554563
iter 30 value 89.539131
iter 40 value 89.538848
final value 89.538826
converged
Fitting Repeat 5
# weights: 507
initial value 96.915778
iter 10 value 94.275363
iter 10 value 94.275363
iter 10 value 94.275363
final value 94.275363
converged
Fitting Repeat 1
# weights: 103
initial value 98.355725
iter 10 value 94.533838
iter 20 value 94.491343
iter 30 value 94.488745
iter 40 value 86.110089
iter 50 value 85.474827
iter 60 value 83.727636
iter 70 value 83.645929
iter 80 value 83.509071
iter 90 value 83.439708
final value 83.439702
converged
Fitting Repeat 2
# weights: 103
initial value 104.416081
iter 10 value 94.135397
iter 20 value 87.766052
iter 30 value 84.092978
iter 40 value 82.964041
iter 50 value 80.963673
iter 60 value 78.935035
iter 70 value 78.731065
iter 80 value 78.486856
iter 90 value 78.287174
final value 78.268938
converged
Fitting Repeat 3
# weights: 103
initial value 101.287930
iter 10 value 94.490615
iter 20 value 92.599087
iter 30 value 84.953499
iter 40 value 84.313707
iter 50 value 84.145916
iter 60 value 83.982346
iter 70 value 83.841002
final value 83.840596
converged
Fitting Repeat 4
# weights: 103
initial value 98.389757
iter 10 value 94.489055
iter 20 value 88.749179
iter 30 value 84.317070
iter 40 value 84.098576
iter 50 value 83.984352
iter 60 value 83.849263
final value 83.840596
converged
Fitting Repeat 5
# weights: 103
initial value 102.067031
iter 10 value 94.460057
iter 20 value 93.418700
iter 30 value 91.231599
iter 40 value 83.950032
iter 50 value 82.696622
iter 60 value 81.737449
iter 70 value 81.229769
final value 81.227877
converged
Fitting Repeat 1
# weights: 305
initial value 107.146077
iter 10 value 91.084554
iter 20 value 86.374148
iter 30 value 85.932833
iter 40 value 82.205348
iter 50 value 80.749033
iter 60 value 80.180624
iter 70 value 79.195038
iter 80 value 77.864881
iter 90 value 77.648986
iter 100 value 77.310778
final value 77.310778
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.643548
iter 10 value 93.640840
iter 20 value 85.468970
iter 30 value 83.771465
iter 40 value 83.675104
iter 50 value 83.507020
iter 60 value 82.839997
iter 70 value 79.826172
iter 80 value 78.711334
iter 90 value 78.371896
iter 100 value 78.330045
final value 78.330045
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.313970
iter 10 value 94.471729
iter 20 value 93.474276
iter 30 value 92.842269
iter 40 value 90.682745
iter 50 value 83.309193
iter 60 value 81.874359
iter 70 value 79.962263
iter 80 value 79.613463
iter 90 value 79.358519
iter 100 value 79.131031
final value 79.131031
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.221719
iter 10 value 94.906476
iter 20 value 86.888337
iter 30 value 84.600037
iter 40 value 84.373456
iter 50 value 83.874122
iter 60 value 82.206547
iter 70 value 79.839996
iter 80 value 78.712342
iter 90 value 78.349239
iter 100 value 78.077228
final value 78.077228
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.105681
iter 10 value 94.718889
iter 20 value 94.340608
iter 30 value 93.300943
iter 40 value 88.459092
iter 50 value 81.011779
iter 60 value 80.538215
iter 70 value 79.975808
iter 80 value 79.152324
iter 90 value 79.064076
iter 100 value 78.931299
final value 78.931299
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.318219
iter 10 value 93.751744
iter 20 value 87.335469
iter 30 value 86.486131
iter 40 value 83.548306
iter 50 value 80.528799
iter 60 value 79.487360
iter 70 value 78.895100
iter 80 value 78.616708
iter 90 value 78.012583
iter 100 value 77.268459
final value 77.268459
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 114.355010
iter 10 value 92.808352
iter 20 value 83.233182
iter 30 value 81.895949
iter 40 value 79.942185
iter 50 value 78.489601
iter 60 value 78.227428
iter 70 value 78.018660
iter 80 value 77.661087
iter 90 value 77.396870
iter 100 value 77.387579
final value 77.387579
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.680851
iter 10 value 94.577383
iter 20 value 86.032704
iter 30 value 83.782594
iter 40 value 82.054317
iter 50 value 80.749263
iter 60 value 80.281839
iter 70 value 80.093769
iter 80 value 79.686533
iter 90 value 79.334302
iter 100 value 78.435651
final value 78.435651
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 129.726420
iter 10 value 92.983753
iter 20 value 92.566489
iter 30 value 87.994894
iter 40 value 80.791027
iter 50 value 78.527098
iter 60 value 77.906814
iter 70 value 77.466844
iter 80 value 76.933505
iter 90 value 76.855406
iter 100 value 76.805733
final value 76.805733
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 111.087288
iter 10 value 94.665494
iter 20 value 94.075181
iter 30 value 91.440559
iter 40 value 82.329086
iter 50 value 80.106282
iter 60 value 79.186722
iter 70 value 78.114920
iter 80 value 76.988138
iter 90 value 76.757210
iter 100 value 76.678650
final value 76.678650
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.010425
final value 94.485637
converged
Fitting Repeat 2
# weights: 103
initial value 101.311970
final value 94.485810
converged
Fitting Repeat 3
# weights: 103
initial value 94.737892
final value 94.485890
converged
Fitting Repeat 4
# weights: 103
initial value 103.495085
final value 94.485788
converged
Fitting Repeat 5
# weights: 103
initial value 100.742001
final value 94.485983
converged
Fitting Repeat 1
# weights: 305
initial value 94.967673
iter 10 value 94.486928
iter 20 value 92.534165
iter 30 value 82.837866
final value 82.587965
converged
Fitting Repeat 2
# weights: 305
initial value 103.651969
iter 10 value 94.489118
iter 20 value 91.572222
iter 30 value 90.225761
iter 40 value 90.224230
iter 50 value 90.210052
iter 60 value 90.172284
iter 70 value 84.837078
iter 80 value 84.594388
iter 90 value 84.592376
iter 100 value 84.590709
final value 84.590709
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.691555
iter 10 value 94.433468
iter 20 value 94.345743
iter 30 value 94.103485
iter 40 value 89.129782
iter 50 value 89.037413
iter 60 value 88.987186
final value 88.986543
converged
Fitting Repeat 4
# weights: 305
initial value 96.254611
iter 10 value 94.149567
iter 20 value 94.070880
iter 30 value 94.069555
iter 40 value 94.066911
final value 94.066815
converged
Fitting Repeat 5
# weights: 305
initial value 110.075687
iter 10 value 94.489417
iter 20 value 94.362677
iter 30 value 92.382291
iter 40 value 92.276968
iter 50 value 92.276501
iter 60 value 92.275802
iter 70 value 92.154284
iter 80 value 90.689554
iter 90 value 81.677239
iter 100 value 78.756230
final value 78.756230
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.337832
iter 10 value 94.172974
iter 20 value 93.647430
iter 30 value 93.436926
iter 40 value 93.410234
iter 50 value 93.394098
iter 60 value 88.988424
iter 70 value 87.983707
iter 80 value 84.054330
iter 90 value 80.412818
iter 100 value 79.830925
final value 79.830925
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 101.314728
iter 10 value 94.283577
iter 20 value 94.276459
iter 30 value 92.314508
iter 40 value 90.249830
iter 50 value 86.909328
iter 60 value 79.429701
iter 70 value 78.544347
iter 80 value 78.530011
iter 90 value 78.205444
iter 100 value 78.099202
final value 78.099202
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 102.973866
iter 10 value 94.492227
iter 20 value 94.478853
iter 30 value 94.082818
final value 94.067210
converged
Fitting Repeat 4
# weights: 507
initial value 106.678963
iter 10 value 94.492449
iter 20 value 94.274808
iter 30 value 87.867316
iter 40 value 87.818662
iter 50 value 87.818344
iter 60 value 87.817712
iter 70 value 87.806338
iter 80 value 86.995038
iter 90 value 83.949503
iter 100 value 83.912643
final value 83.912643
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 100.526948
iter 10 value 92.166916
iter 20 value 90.197525
iter 30 value 90.082099
iter 40 value 90.080138
iter 50 value 90.077808
iter 60 value 88.608460
iter 70 value 87.722217
iter 80 value 79.912862
iter 90 value 79.045866
iter 100 value 78.733314
final value 78.733314
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 127.345456
iter 10 value 117.522894
iter 20 value 117.517906
iter 30 value 117.507449
iter 40 value 117.455151
iter 50 value 109.563245
iter 60 value 105.317274
iter 70 value 105.309273
iter 80 value 105.289470
iter 90 value 104.798347
iter 100 value 103.953639
final value 103.953639
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 142.963101
iter 10 value 117.899149
iter 20 value 117.737145
iter 30 value 107.024677
iter 40 value 107.013098
iter 50 value 107.007378
iter 60 value 104.920791
iter 70 value 104.429691
iter 80 value 102.947472
iter 90 value 101.248602
iter 100 value 101.175695
final value 101.175695
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 123.105496
iter 10 value 117.564094
iter 20 value 117.554595
iter 30 value 117.503688
iter 40 value 115.256120
final value 115.126225
converged
Fitting Repeat 4
# weights: 507
initial value 139.032742
iter 10 value 117.899320
iter 20 value 117.282011
iter 30 value 107.677571
iter 40 value 106.948698
iter 50 value 105.587825
iter 60 value 104.805209
iter 70 value 104.781678
iter 80 value 104.780515
iter 90 value 104.778439
iter 100 value 104.776180
final value 104.776180
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 122.249536
iter 10 value 117.898337
iter 20 value 117.879597
iter 30 value 117.529415
iter 40 value 117.462964
iter 50 value 107.360444
final value 106.832566
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 -- Wed Oct 19 01:07:20 2022
***********************************************
Number of test functions: 8
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 8 test functions, 0 errors, 0 failures
Number of test functions: 8
Number of errors: 0
Number of failures: 0
Warning messages:
1: The `.data` argument of `add_column()` must have unique names as of tibble
3.0.0.
ℹ Use `.name_repair = "minimal"`.
ℹ The deprecated feature was likely used in the tibble package.
Please report the issue at <https://github.com/tidyverse/tibble/issues>.
2: `repeats` has no meaning for this resampling method.
3: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
43.40 2.20 50.42
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 30.58 | 1.28 | 31.95 | |
| FreqInteractors | 0.20 | 0.02 | 0.24 | |
| calculateAAC | 0.08 | 0.00 | 0.08 | |
| calculateAutocor | 0.31 | 0.11 | 0.42 | |
| calculateBE | 0.19 | 0.00 | 0.19 | |
| calculateCTDC | 0.11 | 0.00 | 0.11 | |
| calculateCTDD | 0.73 | 0.06 | 0.80 | |
| calculateCTDT | 0.27 | 0.00 | 0.26 | |
| calculateCTriad | 0.39 | 0.00 | 0.39 | |
| calculateDC | 0.07 | 0.03 | 0.11 | |
| calculateF | 0.35 | 0.00 | 0.35 | |
| calculateKSAAP | 0.06 | 0.03 | 0.09 | |
| calculateQD_Sm | 1.92 | 0.09 | 2.02 | |
| calculateTC | 1.75 | 0.05 | 1.79 | |
| calculateTC_Sm | 0.39 | 0.03 | 0.42 | |
| corr_plot | 30.61 | 1.16 | 31.77 | |
| enrichfindP | 0.41 | 0.08 | 11.87 | |
| enrichfind_hp | 0.06 | 0.00 | 0.80 | |
| enrichplot | 0.20 | 0.01 | 0.22 | |
| filter_missing_values | 0.02 | 0.00 | 0.02 | |
| getFASTA | 0.03 | 0.03 | 2.50 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.05 | 0.02 | 0.11 | |
| pred_ensembel | 13.67 | 0.50 | 10.83 | |
| var_imp | 30.28 | 0.85 | 31.17 | |