Matineh Rahmatbakhsh
| Snapshot Date: 2024-04-15 14:05:01 -0400 (Mon, 15 Apr 2024) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_18 |
| git_last_commit: 677208a |
| git_last_commit_date: 2023-10-24 11:36:21 -0400 (Tue, 24 Oct 2023) |
| Back to Multiple platform build/check report for BioC 3.18: simplified long |
|
This page was generated on 2024-04-17 11:36:52 -0400 (Wed, 17 Apr 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4676 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.3.3 (2024-02-29 ucrt) -- "Angel Food Cake" | 4414 |
| merida1 | macOS 12.7.1 Monterey | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4437 |
| 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 974/2266 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.8.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson1 | macOS 13.6.1 Ventura / arm64 | see weekly results here | ||||||||||||
|
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: 1.8.0 |
| Command: F:\biocbuild\bbs-3.18-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.18-bioc\R\library --no-vignettes --timings HPiP_1.8.0.tar.gz |
| StartedAt: 2024-04-16 01:43:12 -0400 (Tue, 16 Apr 2024) |
| EndedAt: 2024-04-16 01:47:59 -0400 (Tue, 16 Apr 2024) |
| EllapsedTime: 287.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.18-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.18-bioc\R\library --no-vignettes --timings HPiP_1.8.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck'
* using R version 4.3.3 (2024-02-29 ucrt)
* using platform: x86_64-w64-mingw32 (64-bit)
* R was compiled by
gcc.exe (GCC) 12.3.0
GNU Fortran (GCC) 12.3.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.8.0'
* 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
var_imp 33.15 0.67 33.84
FSmethod 32.17 1.43 33.66
corr_plot 31.09 1.01 32.14
pred_ensembel 14.38 0.50 11.02
enrichfindP 0.61 0.11 12.60
* 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-3.18-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.18-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.18-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 4.3.3 (2024-02-29 ucrt) -- "Angel Food Cake"
Copyright (C) 2024 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
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 97.011207
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 99.479167
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 116.776749
final value 94.466823
converged
Fitting Repeat 4
# weights: 103
initial value 97.589488
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 106.123682
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 95.963116
iter 10 value 92.268713
iter 20 value 92.165892
iter 30 value 92.144061
iter 40 value 92.125032
final value 92.124987
converged
Fitting Repeat 2
# weights: 305
initial value 99.072641
iter 10 value 94.484193
iter 20 value 94.471352
final value 94.466823
converged
Fitting Repeat 3
# weights: 305
initial value 95.640859
iter 10 value 89.675543
iter 20 value 88.211695
iter 30 value 88.041342
iter 40 value 87.991126
final value 87.991037
converged
Fitting Repeat 4
# weights: 305
initial value 95.170934
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 94.643152
final value 94.466823
converged
Fitting Repeat 1
# weights: 507
initial value 95.715258
iter 10 value 93.205204
final value 93.203896
converged
Fitting Repeat 2
# weights: 507
initial value 110.010126
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 102.951819
final value 94.165117
converged
Fitting Repeat 4
# weights: 507
initial value 101.240326
final value 94.466823
converged
Fitting Repeat 5
# weights: 507
initial value 109.998775
final value 94.464735
converged
Fitting Repeat 1
# weights: 103
initial value 116.251083
iter 10 value 95.231684
iter 20 value 94.205320
iter 30 value 86.842180
iter 40 value 85.248303
iter 50 value 85.119982
iter 60 value 84.802379
iter 70 value 84.571535
iter 80 value 84.379149
final value 84.377597
converged
Fitting Repeat 2
# weights: 103
initial value 99.324901
iter 10 value 94.129908
iter 20 value 93.978752
iter 30 value 90.909519
iter 40 value 89.037174
iter 50 value 88.123260
iter 60 value 83.652979
iter 70 value 83.007426
iter 80 value 82.738172
iter 90 value 82.419023
iter 100 value 82.353656
final value 82.353656
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 99.516292
iter 10 value 94.522885
iter 20 value 94.446229
iter 30 value 87.524007
iter 40 value 86.516738
iter 50 value 86.011731
iter 60 value 85.887514
iter 70 value 85.793653
iter 80 value 84.573522
iter 90 value 84.338002
iter 100 value 84.336154
final value 84.336154
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 121.223328
iter 10 value 94.486679
iter 20 value 90.878327
iter 30 value 89.725393
iter 40 value 87.147853
iter 50 value 86.689629
iter 60 value 86.473051
iter 70 value 86.374699
iter 80 value 85.943557
iter 90 value 85.886761
iter 100 value 85.788428
final value 85.788428
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 96.471123
iter 10 value 94.488553
iter 20 value 92.863941
iter 30 value 86.319213
iter 40 value 83.732041
iter 50 value 83.306084
iter 60 value 82.712281
iter 70 value 82.655263
iter 80 value 82.579437
iter 90 value 82.338910
final value 82.335594
converged
Fitting Repeat 1
# weights: 305
initial value 118.647907
iter 10 value 92.921782
iter 20 value 91.509533
iter 30 value 91.265653
iter 40 value 90.440928
iter 50 value 86.967576
iter 60 value 84.230694
iter 70 value 82.984377
iter 80 value 82.767837
iter 90 value 82.460124
iter 100 value 82.073502
final value 82.073502
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 127.067107
iter 10 value 94.841302
iter 20 value 94.069762
iter 30 value 86.271453
iter 40 value 84.520701
iter 50 value 83.289217
iter 60 value 82.510710
iter 70 value 81.941410
iter 80 value 81.474509
iter 90 value 81.248410
iter 100 value 81.213236
final value 81.213236
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.065044
iter 10 value 90.399139
iter 20 value 87.100388
iter 30 value 86.129768
iter 40 value 84.685223
iter 50 value 84.476780
iter 60 value 84.027344
iter 70 value 82.856241
iter 80 value 82.066421
iter 90 value 81.433459
iter 100 value 81.054398
final value 81.054398
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.253952
iter 10 value 94.542801
iter 20 value 94.090592
iter 30 value 93.928615
iter 40 value 93.336468
iter 50 value 84.811977
iter 60 value 84.326432
iter 70 value 83.412647
iter 80 value 82.586268
iter 90 value 82.452803
iter 100 value 82.243227
final value 82.243227
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.715866
iter 10 value 94.578896
iter 20 value 94.453288
iter 30 value 91.194413
iter 40 value 88.077500
iter 50 value 86.429509
iter 60 value 84.370189
iter 70 value 83.066642
iter 80 value 81.551867
iter 90 value 81.090519
iter 100 value 80.806725
final value 80.806725
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.907867
iter 10 value 95.276641
iter 20 value 93.109005
iter 30 value 88.340805
iter 40 value 85.747332
iter 50 value 84.404457
iter 60 value 82.943170
iter 70 value 82.320436
iter 80 value 81.565807
iter 90 value 81.409994
iter 100 value 81.169300
final value 81.169300
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.279885
iter 10 value 94.836452
iter 20 value 87.206866
iter 30 value 85.986149
iter 40 value 85.540995
iter 50 value 85.399437
iter 60 value 84.558973
iter 70 value 83.815312
iter 80 value 83.219701
iter 90 value 82.362273
iter 100 value 81.932641
final value 81.932641
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 121.477491
iter 10 value 98.001641
iter 20 value 88.707198
iter 30 value 85.133572
iter 40 value 84.574653
iter 50 value 82.592013
iter 60 value 82.139354
iter 70 value 81.411403
iter 80 value 81.193125
iter 90 value 81.154074
iter 100 value 81.092155
final value 81.092155
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 125.040193
iter 10 value 94.722855
iter 20 value 91.966649
iter 30 value 87.605947
iter 40 value 85.946847
iter 50 value 84.868884
iter 60 value 83.945105
iter 70 value 82.124064
iter 80 value 81.504338
iter 90 value 81.329702
iter 100 value 81.220135
final value 81.220135
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.419143
iter 10 value 95.268934
iter 20 value 88.062138
iter 30 value 86.190423
iter 40 value 85.888642
iter 50 value 85.788192
iter 60 value 85.338968
iter 70 value 83.427279
iter 80 value 83.110506
iter 90 value 81.798448
iter 100 value 81.632729
final value 81.632729
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.148684
final value 94.485791
converged
Fitting Repeat 2
# weights: 103
initial value 108.816951
iter 10 value 94.439627
iter 20 value 94.014673
iter 30 value 93.944279
final value 93.944078
converged
Fitting Repeat 3
# weights: 103
initial value 105.335667
iter 10 value 94.468096
iter 20 value 93.880179
iter 20 value 93.880179
iter 20 value 93.880179
final value 93.880179
converged
Fitting Repeat 4
# weights: 103
initial value 102.429489
iter 10 value 94.166764
iter 20 value 93.922817
iter 30 value 93.879434
iter 40 value 93.879168
final value 93.879166
converged
Fitting Repeat 5
# weights: 103
initial value 109.881398
final value 94.485837
converged
Fitting Repeat 1
# weights: 305
initial value 98.017913
iter 10 value 86.088877
iter 20 value 85.864402
iter 30 value 85.072559
iter 40 value 85.064689
iter 50 value 84.738285
iter 60 value 84.173399
final value 84.173368
converged
Fitting Repeat 2
# weights: 305
initial value 98.504449
iter 10 value 94.488875
iter 20 value 94.462039
iter 30 value 94.208460
iter 40 value 94.148309
iter 50 value 85.564715
iter 60 value 84.773585
iter 70 value 84.207258
iter 80 value 84.004965
iter 90 value 84.003493
iter 100 value 83.492506
final value 83.492506
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 97.853541
iter 10 value 94.489669
iter 20 value 93.590175
iter 30 value 92.368388
iter 40 value 91.325895
final value 91.324678
converged
Fitting Repeat 4
# weights: 305
initial value 101.778051
iter 10 value 93.883238
iter 20 value 93.863634
iter 30 value 93.413699
iter 40 value 91.644369
iter 50 value 86.309463
iter 60 value 85.508663
iter 60 value 85.508663
iter 60 value 85.508663
final value 85.508663
converged
Fitting Repeat 5
# weights: 305
initial value 99.085886
iter 10 value 93.611454
iter 20 value 93.252431
iter 30 value 92.841977
iter 40 value 92.796214
iter 50 value 92.789359
iter 60 value 92.788687
iter 70 value 92.786690
iter 80 value 92.461494
iter 90 value 92.254689
final value 92.254685
converged
Fitting Repeat 1
# weights: 507
initial value 104.235770
iter 10 value 94.474876
iter 20 value 94.467950
iter 30 value 94.466976
final value 94.466968
converged
Fitting Repeat 2
# weights: 507
initial value 96.999390
iter 10 value 87.154650
iter 20 value 85.941274
iter 30 value 85.917066
iter 40 value 85.915088
iter 50 value 84.429283
iter 60 value 81.825844
iter 70 value 81.825655
iter 80 value 81.792833
iter 90 value 81.716776
iter 100 value 81.715569
final value 81.715569
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.027242
iter 10 value 93.709738
iter 20 value 93.704898
iter 30 value 93.703439
iter 40 value 86.738251
iter 50 value 85.342284
iter 60 value 85.068658
final value 85.068565
converged
Fitting Repeat 4
# weights: 507
initial value 95.346688
iter 10 value 94.491561
iter 20 value 94.405903
iter 30 value 91.514599
iter 40 value 89.140312
iter 50 value 86.361834
iter 60 value 86.321475
iter 70 value 85.923823
iter 80 value 85.834843
iter 90 value 84.955932
iter 100 value 84.113936
final value 84.113936
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 123.721784
iter 10 value 94.492017
iter 20 value 94.424835
iter 30 value 92.553244
iter 40 value 92.551053
iter 50 value 92.497934
iter 60 value 86.105668
iter 70 value 86.050834
iter 80 value 85.888603
iter 90 value 85.037497
iter 100 value 84.239092
final value 84.239092
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.570097
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 109.124281
final value 94.484210
converged
Fitting Repeat 3
# weights: 103
initial value 104.973044
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 102.895791
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 108.983262
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 112.200165
iter 10 value 94.481317
iter 20 value 88.381259
iter 30 value 88.342105
final value 88.341724
converged
Fitting Repeat 2
# weights: 305
initial value 102.451610
iter 10 value 94.458008
iter 20 value 94.455565
final value 94.455556
converged
Fitting Repeat 3
# weights: 305
initial value 108.308287
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 104.503220
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 96.616833
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 103.412946
final value 94.445714
converged
Fitting Repeat 2
# weights: 507
initial value 93.979010
iter 10 value 90.862190
iter 20 value 90.768478
iter 30 value 90.764074
iter 40 value 87.778822
iter 50 value 86.219423
iter 60 value 86.133595
final value 86.133333
converged
Fitting Repeat 3
# weights: 507
initial value 103.719113
final value 94.466823
converged
Fitting Repeat 4
# weights: 507
initial value 99.065704
final value 94.466823
converged
Fitting Repeat 5
# weights: 507
initial value 98.715149
final value 94.466823
converged
Fitting Repeat 1
# weights: 103
initial value 100.206416
iter 10 value 94.477836
iter 20 value 91.973198
iter 30 value 86.039052
iter 40 value 85.313691
iter 50 value 85.059853
iter 60 value 85.007486
iter 70 value 84.747849
iter 80 value 84.608590
final value 84.608577
converged
Fitting Repeat 2
# weights: 103
initial value 98.896102
iter 10 value 94.287142
iter 20 value 89.208988
iter 30 value 86.158069
iter 40 value 85.674242
iter 50 value 85.635583
final value 85.633436
converged
Fitting Repeat 3
# weights: 103
initial value 119.639698
iter 10 value 94.484827
iter 20 value 94.201072
iter 30 value 94.163599
iter 40 value 93.787961
iter 50 value 88.464630
iter 60 value 86.589718
iter 70 value 86.126288
iter 80 value 86.047824
iter 90 value 85.540704
iter 100 value 85.276487
final value 85.276487
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 106.701366
iter 10 value 94.411769
iter 20 value 92.536387
iter 30 value 91.474030
iter 40 value 86.183286
iter 50 value 85.813199
iter 60 value 85.693300
iter 70 value 85.633473
final value 85.633436
converged
Fitting Repeat 5
# weights: 103
initial value 101.337416
iter 10 value 94.488523
iter 20 value 92.863890
iter 30 value 89.297985
iter 40 value 86.495758
iter 50 value 86.268108
iter 60 value 86.040507
iter 70 value 85.961711
iter 80 value 85.333484
iter 90 value 85.183411
iter 100 value 85.183159
final value 85.183159
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 108.214450
iter 10 value 94.474525
iter 20 value 88.358935
iter 30 value 86.352950
iter 40 value 85.991867
iter 50 value 83.635181
iter 60 value 82.788056
iter 70 value 82.539140
iter 80 value 82.404636
iter 90 value 81.741403
iter 100 value 80.691397
final value 80.691397
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.848456
iter 10 value 94.368217
iter 20 value 87.495050
iter 30 value 85.374235
iter 40 value 84.856992
iter 50 value 84.380849
iter 60 value 82.887765
iter 70 value 82.593761
iter 80 value 82.522050
iter 90 value 82.143742
iter 100 value 81.986227
final value 81.986227
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 114.527643
iter 10 value 95.173506
iter 20 value 94.147146
iter 30 value 92.046341
iter 40 value 87.081695
iter 50 value 83.616847
iter 60 value 83.116511
iter 70 value 82.785894
iter 80 value 82.534886
iter 90 value 82.464271
iter 100 value 82.439605
final value 82.439605
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.471159
iter 10 value 94.458749
iter 20 value 88.907680
iter 30 value 86.030920
iter 40 value 85.798329
iter 50 value 85.660600
iter 60 value 85.646638
iter 70 value 85.371567
iter 80 value 83.845013
iter 90 value 81.724884
iter 100 value 80.835276
final value 80.835276
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.138213
iter 10 value 94.752996
iter 20 value 94.562983
iter 30 value 92.766782
iter 40 value 85.896333
iter 50 value 85.867207
iter 60 value 85.656577
iter 70 value 85.213806
iter 80 value 84.767039
iter 90 value 83.279945
iter 100 value 83.072317
final value 83.072317
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 115.410867
iter 10 value 94.599085
iter 20 value 92.613811
iter 30 value 90.764706
iter 40 value 87.123826
iter 50 value 84.902634
iter 60 value 83.526423
iter 70 value 81.895089
iter 80 value 81.052515
iter 90 value 80.712994
iter 100 value 80.544014
final value 80.544014
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.902440
iter 10 value 95.040957
iter 20 value 93.987779
iter 30 value 87.883455
iter 40 value 85.771854
iter 50 value 83.619170
iter 60 value 83.223026
iter 70 value 82.712354
iter 80 value 82.564097
iter 90 value 81.579897
iter 100 value 80.983219
final value 80.983219
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 107.510680
iter 10 value 95.137620
iter 20 value 94.422742
iter 30 value 85.584438
iter 40 value 82.668805
iter 50 value 81.903866
iter 60 value 81.653431
iter 70 value 81.506313
iter 80 value 80.687322
iter 90 value 80.392664
iter 100 value 80.210972
final value 80.210972
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.888953
iter 10 value 94.577470
iter 20 value 94.314311
iter 30 value 88.156802
iter 40 value 84.436780
iter 50 value 83.179228
iter 60 value 82.585679
iter 70 value 82.281334
iter 80 value 81.113104
iter 90 value 80.772730
iter 100 value 80.300397
final value 80.300397
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.697594
iter 10 value 93.559145
iter 20 value 86.405839
iter 30 value 85.971591
iter 40 value 85.643241
iter 50 value 85.173036
iter 60 value 84.419998
iter 70 value 82.961742
iter 80 value 81.737999
iter 90 value 81.031816
iter 100 value 80.654272
final value 80.654272
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.934146
final value 94.485764
converged
Fitting Repeat 2
# weights: 103
initial value 96.869067
iter 10 value 94.468544
iter 20 value 94.462548
iter 30 value 84.435951
iter 40 value 84.431770
iter 50 value 84.421870
iter 60 value 84.421328
iter 60 value 84.421328
final value 84.421316
converged
Fitting Repeat 3
# weights: 103
initial value 112.242198
final value 94.485933
converged
Fitting Repeat 4
# weights: 103
initial value 95.291632
iter 10 value 94.486159
final value 94.484333
converged
Fitting Repeat 5
# weights: 103
initial value 104.063955
final value 94.485695
converged
Fitting Repeat 1
# weights: 305
initial value 95.623530
iter 10 value 94.471658
iter 20 value 94.468996
iter 30 value 94.467828
iter 40 value 93.555409
iter 50 value 92.105842
iter 60 value 92.102144
final value 92.101422
converged
Fitting Repeat 2
# weights: 305
initial value 117.464918
iter 10 value 90.201610
iter 20 value 84.522835
iter 30 value 84.487234
iter 40 value 84.354731
iter 50 value 84.340635
iter 60 value 84.321751
iter 70 value 84.319334
iter 80 value 84.307101
iter 90 value 84.300362
iter 100 value 84.299592
final value 84.299592
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.340989
iter 10 value 94.488948
iter 20 value 94.178512
iter 30 value 88.169369
iter 40 value 87.009117
iter 50 value 86.388555
iter 60 value 83.768886
iter 70 value 82.917321
iter 80 value 82.909715
iter 90 value 82.579889
iter 100 value 82.317828
final value 82.317828
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 98.957158
iter 10 value 94.484937
iter 20 value 94.132611
iter 30 value 94.109765
iter 40 value 94.109570
iter 40 value 94.109570
iter 40 value 94.109570
final value 94.109570
converged
Fitting Repeat 5
# weights: 305
initial value 97.078320
iter 10 value 94.489341
iter 20 value 94.484416
iter 30 value 94.480889
iter 40 value 91.002324
iter 50 value 83.859057
iter 60 value 83.612757
iter 70 value 83.475663
iter 80 value 83.475322
iter 90 value 83.473135
iter 100 value 83.462512
final value 83.462512
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.862621
iter 10 value 94.492249
iter 20 value 94.443525
iter 30 value 84.695852
iter 40 value 84.300974
iter 50 value 84.300682
iter 60 value 84.247732
iter 70 value 84.006519
iter 80 value 81.550790
iter 90 value 80.630932
iter 100 value 80.575233
final value 80.575233
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 98.989643
iter 10 value 94.370108
iter 20 value 94.337275
iter 30 value 94.166753
iter 40 value 93.402002
iter 50 value 92.538079
iter 60 value 92.498135
final value 92.498049
converged
Fitting Repeat 3
# weights: 507
initial value 108.517864
iter 10 value 94.484005
iter 20 value 94.224805
iter 30 value 86.339890
iter 40 value 86.334618
final value 86.332257
converged
Fitting Repeat 4
# weights: 507
initial value 111.669031
iter 10 value 94.491266
iter 20 value 94.467649
iter 30 value 87.542361
iter 40 value 86.405085
iter 50 value 86.400642
iter 60 value 86.287563
iter 70 value 83.990847
iter 80 value 83.986815
iter 90 value 83.833817
iter 100 value 83.737207
final value 83.737207
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 94.825730
iter 10 value 94.491594
iter 20 value 94.483364
iter 30 value 84.448319
iter 40 value 84.241331
iter 50 value 81.576165
iter 60 value 81.370152
iter 70 value 80.806721
iter 80 value 80.803034
iter 90 value 80.595234
iter 100 value 79.822802
final value 79.822802
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 107.876594
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.531510
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.608343
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.120616
final value 94.443243
converged
Fitting Repeat 5
# weights: 103
initial value 96.368385
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 97.325299
iter 10 value 91.049917
iter 20 value 85.000819
iter 30 value 84.267347
final value 84.267322
converged
Fitting Repeat 2
# weights: 305
initial value 99.271484
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 99.957111
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 95.050207
final value 94.443243
converged
Fitting Repeat 5
# weights: 305
initial value 99.297033
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 97.269586
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 104.006661
iter 10 value 94.322907
final value 94.322898
converged
Fitting Repeat 3
# weights: 507
initial value 107.098002
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 121.276848
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 105.980774
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 97.741634
iter 10 value 94.477571
iter 20 value 88.742471
iter 30 value 86.265469
iter 40 value 86.070845
iter 50 value 85.411364
iter 60 value 85.021701
iter 70 value 84.971695
iter 80 value 84.933663
final value 84.933538
converged
Fitting Repeat 2
# weights: 103
initial value 105.240800
iter 10 value 91.984396
iter 20 value 86.131151
iter 30 value 84.795461
iter 40 value 83.887689
iter 50 value 82.706411
iter 60 value 82.615799
iter 70 value 82.614153
iter 70 value 82.614153
iter 70 value 82.614153
final value 82.614153
converged
Fitting Repeat 3
# weights: 103
initial value 104.414377
iter 10 value 94.314724
iter 20 value 91.206316
iter 30 value 87.552047
iter 40 value 87.370780
iter 50 value 85.399000
iter 60 value 84.354777
iter 70 value 84.132503
iter 80 value 83.799734
iter 90 value 83.136897
iter 100 value 82.876523
final value 82.876523
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 99.296408
iter 10 value 94.463260
iter 20 value 93.333260
iter 30 value 89.869002
iter 40 value 89.372626
iter 50 value 88.087129
iter 60 value 85.954856
iter 70 value 85.372144
iter 80 value 84.941959
final value 84.940784
converged
Fitting Repeat 5
# weights: 103
initial value 98.972569
iter 10 value 94.716661
iter 20 value 88.406941
iter 30 value 85.023116
iter 40 value 84.409967
iter 50 value 84.141256
iter 60 value 83.999089
iter 70 value 83.475349
iter 80 value 83.266749
iter 90 value 82.876724
iter 100 value 82.660514
final value 82.660514
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 106.891110
iter 10 value 94.537872
iter 20 value 89.752493
iter 30 value 87.531709
iter 40 value 84.812996
iter 50 value 82.837060
iter 60 value 82.186747
iter 70 value 81.885846
iter 80 value 81.635294
iter 90 value 81.518789
iter 100 value 81.368384
final value 81.368384
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.540439
iter 10 value 94.555995
iter 20 value 94.486642
iter 30 value 94.327230
iter 40 value 88.389042
iter 50 value 86.710132
iter 60 value 84.978258
iter 70 value 84.063913
iter 80 value 83.887816
iter 90 value 83.755485
iter 100 value 83.711789
final value 83.711789
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.164921
iter 10 value 91.674243
iter 20 value 88.983481
iter 30 value 88.705306
iter 40 value 88.166533
iter 50 value 85.589622
iter 60 value 85.136232
iter 70 value 84.924570
iter 80 value 84.731370
iter 90 value 84.677972
iter 100 value 84.568251
final value 84.568251
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 114.542115
iter 10 value 94.433641
iter 20 value 88.307114
iter 30 value 85.302044
iter 40 value 84.380258
iter 50 value 83.832154
iter 60 value 83.564630
iter 70 value 82.906692
iter 80 value 82.325059
iter 90 value 82.040496
iter 100 value 81.928930
final value 81.928930
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.365638
iter 10 value 93.677240
iter 20 value 86.658356
iter 30 value 85.506369
iter 40 value 84.906614
iter 50 value 83.782000
iter 60 value 82.725424
iter 70 value 82.013702
iter 80 value 81.661083
iter 90 value 81.486932
iter 100 value 81.457366
final value 81.457366
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 121.216634
iter 10 value 95.815659
iter 20 value 87.164186
iter 30 value 85.474880
iter 40 value 84.167754
iter 50 value 82.362724
iter 60 value 82.134613
iter 70 value 82.083056
iter 80 value 81.791517
iter 90 value 81.689535
iter 100 value 81.380054
final value 81.380054
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 125.448695
iter 10 value 94.866088
iter 20 value 93.175610
iter 30 value 91.671784
iter 40 value 91.481084
iter 50 value 90.461664
iter 60 value 86.102566
iter 70 value 84.974224
iter 80 value 84.300718
iter 90 value 82.763076
iter 100 value 82.211955
final value 82.211955
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 122.193909
iter 10 value 94.392231
iter 20 value 88.866785
iter 30 value 86.281585
iter 40 value 84.698947
iter 50 value 83.696509
iter 60 value 82.851028
iter 70 value 82.418433
iter 80 value 82.129056
iter 90 value 82.032758
iter 100 value 81.954669
final value 81.954669
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.746488
iter 10 value 94.598628
iter 20 value 94.287054
iter 30 value 92.727458
iter 40 value 90.538062
iter 50 value 87.170360
iter 60 value 85.306865
iter 70 value 82.565435
iter 80 value 81.764796
iter 90 value 81.597003
iter 100 value 81.314050
final value 81.314050
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.496035
iter 10 value 97.664466
iter 20 value 88.933267
iter 30 value 85.835960
iter 40 value 83.907065
iter 50 value 82.658604
iter 60 value 82.051002
iter 70 value 81.548198
iter 80 value 81.171466
iter 90 value 81.045765
iter 100 value 80.939785
final value 80.939785
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.564776
final value 94.486003
converged
Fitting Repeat 2
# weights: 103
initial value 96.535796
iter 10 value 94.444838
iter 20 value 94.442837
iter 30 value 92.085028
final value 91.889643
converged
Fitting Repeat 3
# weights: 103
initial value 109.037001
final value 94.485585
converged
Fitting Repeat 4
# weights: 103
initial value 105.688207
final value 94.485531
converged
Fitting Repeat 5
# weights: 103
initial value 100.535216
iter 10 value 92.425971
iter 20 value 92.422789
iter 30 value 92.302315
iter 40 value 91.866212
final value 91.856778
converged
Fitting Repeat 1
# weights: 305
initial value 94.724627
iter 10 value 94.448155
iter 20 value 94.443564
iter 30 value 90.683200
iter 40 value 86.065861
iter 50 value 86.065018
iter 60 value 86.058293
iter 70 value 84.491843
iter 80 value 84.311945
iter 90 value 84.310494
iter 90 value 84.310493
iter 90 value 84.310493
final value 84.310493
converged
Fitting Repeat 2
# weights: 305
initial value 108.566274
iter 10 value 94.488556
iter 20 value 93.729837
iter 30 value 88.045147
iter 40 value 87.658204
iter 50 value 87.633210
iter 60 value 87.631541
iter 70 value 87.592764
iter 80 value 85.239044
iter 90 value 84.709930
iter 100 value 84.673313
final value 84.673313
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 95.122952
iter 10 value 94.488631
iter 20 value 92.001194
iter 30 value 91.051125
iter 40 value 90.907829
iter 50 value 90.885583
final value 90.885289
converged
Fitting Repeat 4
# weights: 305
initial value 112.516271
iter 10 value 91.826405
iter 20 value 89.308357
iter 30 value 89.156110
iter 40 value 88.399247
iter 50 value 88.393079
iter 60 value 88.391218
iter 70 value 88.390505
iter 80 value 88.388798
iter 80 value 88.388798
final value 88.388798
converged
Fitting Repeat 5
# weights: 305
initial value 103.339053
iter 10 value 94.448793
iter 20 value 94.136164
iter 30 value 91.452897
iter 40 value 91.427737
final value 91.427664
converged
Fitting Repeat 1
# weights: 507
initial value 97.257215
iter 10 value 94.491967
iter 20 value 94.475015
iter 30 value 89.430879
iter 40 value 89.037881
iter 50 value 88.724327
iter 60 value 88.399893
iter 70 value 86.412138
iter 80 value 86.208319
iter 90 value 86.074758
iter 100 value 85.791946
final value 85.791946
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 101.835565
iter 10 value 94.450969
iter 20 value 93.514642
iter 30 value 85.058829
iter 40 value 85.018349
iter 50 value 84.998803
iter 60 value 84.982633
iter 70 value 84.980768
iter 80 value 84.980094
iter 90 value 84.804101
iter 100 value 84.102931
final value 84.102931
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 101.085715
iter 10 value 94.451779
iter 20 value 94.451650
iter 30 value 94.302661
iter 40 value 94.232956
iter 50 value 92.270600
iter 60 value 92.059334
iter 70 value 91.495687
iter 80 value 91.467110
iter 90 value 91.465715
iter 100 value 91.455903
final value 91.455903
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 100.704049
iter 10 value 94.331128
iter 20 value 94.329139
iter 30 value 94.323520
final value 94.323498
converged
Fitting Repeat 5
# weights: 507
initial value 98.791178
iter 10 value 94.451334
iter 20 value 94.281176
iter 30 value 89.402350
iter 40 value 88.679051
iter 50 value 88.519490
iter 60 value 88.517184
final value 88.517118
converged
Fitting Repeat 1
# weights: 103
initial value 96.601705
iter 10 value 94.053143
final value 94.052911
converged
Fitting Repeat 2
# weights: 103
initial value 98.251225
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 94.141377
final value 93.836066
converged
Fitting Repeat 4
# weights: 103
initial value 97.305260
final value 93.836066
converged
Fitting Repeat 5
# weights: 103
initial value 100.829353
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 95.492796
final value 93.836066
converged
Fitting Repeat 2
# weights: 305
initial value 94.274598
iter 10 value 82.494824
iter 20 value 79.688256
final value 79.673660
converged
Fitting Repeat 3
# weights: 305
initial value 113.056667
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 113.984830
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 94.419675
final value 94.028176
converged
Fitting Repeat 1
# weights: 507
initial value 95.132968
final value 93.836066
converged
Fitting Repeat 2
# weights: 507
initial value 119.910955
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 114.771896
iter 10 value 93.836066
iter 10 value 93.836066
iter 10 value 93.836066
final value 93.836066
converged
Fitting Repeat 4
# weights: 507
initial value 94.507389
iter 10 value 89.391566
iter 20 value 88.788932
iter 30 value 88.788582
iter 40 value 88.788459
iter 50 value 88.720858
final value 88.720494
converged
Fitting Repeat 5
# weights: 507
initial value 98.342133
iter 10 value 91.066001
iter 20 value 89.566631
iter 30 value 89.411539
iter 30 value 89.411539
iter 30 value 89.411539
final value 89.411539
converged
Fitting Repeat 1
# weights: 103
initial value 98.333172
iter 10 value 94.065354
iter 20 value 94.049917
iter 30 value 93.961876
iter 40 value 91.277427
iter 50 value 81.377717
iter 60 value 80.828036
iter 70 value 80.715313
iter 80 value 79.948946
iter 90 value 79.793770
iter 100 value 78.998320
final value 78.998320
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 95.871746
iter 10 value 93.998762
iter 20 value 92.851287
iter 30 value 92.706954
iter 40 value 88.818431
iter 50 value 79.889569
iter 60 value 79.497004
iter 70 value 77.780503
iter 80 value 77.617444
iter 90 value 77.484195
iter 100 value 77.386934
final value 77.386934
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.183592
iter 10 value 92.525505
iter 20 value 84.854736
iter 30 value 80.929851
iter 40 value 80.687829
iter 50 value 79.736250
iter 60 value 79.195317
iter 70 value 78.775956
final value 78.775906
converged
Fitting Repeat 4
# weights: 103
initial value 99.799914
iter 10 value 94.101364
iter 20 value 93.992121
iter 30 value 93.063667
iter 40 value 92.910356
iter 50 value 87.675976
iter 60 value 81.713962
iter 70 value 81.629245
iter 80 value 81.467477
iter 90 value 81.308000
iter 100 value 80.888590
final value 80.888590
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 100.373525
iter 10 value 91.516816
iter 20 value 90.597641
iter 30 value 86.881691
iter 40 value 81.801438
iter 50 value 80.926290
iter 60 value 80.758862
iter 70 value 80.730675
iter 80 value 80.730515
final value 80.730498
converged
Fitting Repeat 1
# weights: 305
initial value 113.489937
iter 10 value 93.998064
iter 20 value 83.153546
iter 30 value 80.918132
iter 40 value 78.246871
iter 50 value 77.058615
iter 60 value 76.796853
iter 70 value 76.520393
iter 80 value 76.266165
iter 90 value 76.040145
iter 100 value 75.753712
final value 75.753712
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 107.993722
iter 10 value 94.527805
iter 20 value 88.622983
iter 30 value 81.870176
iter 40 value 79.935274
iter 50 value 78.314860
iter 60 value 76.861770
iter 70 value 76.449100
iter 80 value 76.007317
iter 90 value 75.929397
iter 100 value 75.911528
final value 75.911528
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.981270
iter 10 value 94.054711
iter 20 value 93.400173
iter 30 value 89.179960
iter 40 value 87.906705
iter 50 value 87.862220
iter 60 value 87.281732
iter 70 value 81.783037
iter 80 value 78.322858
iter 90 value 77.616347
iter 100 value 76.424547
final value 76.424547
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.733831
iter 10 value 94.152001
iter 20 value 93.393297
iter 30 value 86.029955
iter 40 value 84.400981
iter 50 value 83.997518
iter 60 value 81.744222
iter 70 value 79.459909
iter 80 value 77.855228
iter 90 value 76.629840
iter 100 value 75.984627
final value 75.984627
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.295309
iter 10 value 93.958155
iter 20 value 93.743617
iter 30 value 91.835114
iter 40 value 91.606497
iter 50 value 85.508737
iter 60 value 83.861036
iter 70 value 83.379622
iter 80 value 83.089863
iter 90 value 82.651875
iter 100 value 82.053542
final value 82.053542
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 130.332994
iter 10 value 94.488021
iter 20 value 92.668404
iter 30 value 83.678390
iter 40 value 81.553740
iter 50 value 80.354210
iter 60 value 79.200988
iter 70 value 78.447322
iter 80 value 77.653440
iter 90 value 77.561927
iter 100 value 77.523362
final value 77.523362
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.575466
iter 10 value 100.313957
iter 20 value 87.087597
iter 30 value 82.333935
iter 40 value 79.704794
iter 50 value 77.961421
iter 60 value 77.585865
iter 70 value 77.323990
iter 80 value 77.195680
iter 90 value 76.864707
iter 100 value 76.437096
final value 76.437096
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 137.312693
iter 10 value 92.951332
iter 20 value 84.240054
iter 30 value 82.488332
iter 40 value 78.017983
iter 50 value 77.110901
iter 60 value 76.684123
iter 70 value 75.966090
iter 80 value 75.658117
iter 90 value 75.573286
iter 100 value 75.475256
final value 75.475256
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.691159
iter 10 value 94.019651
iter 20 value 84.258817
iter 30 value 82.934552
iter 40 value 80.986003
iter 50 value 78.957793
iter 60 value 78.221984
iter 70 value 77.144458
iter 80 value 76.704814
iter 90 value 76.580026
iter 100 value 76.449615
final value 76.449615
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 125.471408
iter 10 value 93.895200
iter 20 value 84.725476
iter 30 value 82.974730
iter 40 value 81.243273
iter 50 value 78.686473
iter 60 value 76.574198
iter 70 value 76.127214
iter 80 value 76.033805
iter 90 value 75.962910
iter 100 value 75.922046
final value 75.922046
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.296887
final value 94.054410
converged
Fitting Repeat 2
# weights: 103
initial value 103.213097
final value 94.054383
converged
Fitting Repeat 3
# weights: 103
initial value 95.012164
final value 94.054476
converged
Fitting Repeat 4
# weights: 103
initial value 103.777627
final value 94.054992
converged
Fitting Repeat 5
# weights: 103
initial value 104.980985
final value 94.054621
converged
Fitting Repeat 1
# weights: 305
initial value 106.028487
iter 10 value 94.057725
iter 20 value 93.942339
iter 30 value 90.305187
iter 40 value 88.619040
iter 50 value 88.616350
iter 60 value 88.430019
iter 70 value 87.915490
iter 80 value 87.913803
iter 90 value 86.481559
iter 100 value 86.469012
final value 86.469012
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.756287
iter 10 value 94.058028
iter 20 value 93.871494
iter 30 value 84.467470
iter 40 value 84.455907
iter 50 value 84.436079
iter 60 value 81.679044
iter 70 value 80.966378
iter 80 value 80.932630
iter 90 value 80.912574
final value 80.911525
converged
Fitting Repeat 3
# weights: 305
initial value 111.211425
iter 10 value 91.886455
iter 20 value 88.334068
iter 30 value 88.284433
iter 40 value 87.654078
iter 50 value 87.588340
final value 87.587191
converged
Fitting Repeat 4
# weights: 305
initial value 103.111539
iter 10 value 93.840914
iter 20 value 92.913958
iter 30 value 91.020160
iter 40 value 88.542683
iter 50 value 87.243150
iter 60 value 83.512571
iter 70 value 80.344723
iter 80 value 79.253371
iter 90 value 78.249921
iter 100 value 77.620204
final value 77.620204
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.612419
iter 10 value 89.859563
iter 20 value 80.485805
iter 30 value 80.058738
iter 40 value 80.017039
iter 50 value 80.008270
iter 60 value 80.006754
iter 70 value 80.006595
iter 70 value 80.006595
final value 80.006595
converged
Fitting Repeat 1
# weights: 507
initial value 100.701311
iter 10 value 93.267239
iter 20 value 89.529195
iter 30 value 86.527826
iter 40 value 86.353807
iter 50 value 81.918556
iter 60 value 80.317129
iter 70 value 80.157373
iter 80 value 80.156146
iter 90 value 80.006830
iter 100 value 79.988289
final value 79.988289
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 94.833271
iter 10 value 90.034643
iter 20 value 88.705188
iter 30 value 87.624825
iter 40 value 86.831963
iter 50 value 86.558713
iter 60 value 86.475581
iter 70 value 86.464368
iter 80 value 86.425849
iter 90 value 85.344324
iter 100 value 80.108791
final value 80.108791
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.301810
iter 10 value 94.061019
iter 20 value 93.534129
iter 30 value 92.564088
final value 92.564056
converged
Fitting Repeat 4
# weights: 507
initial value 97.090447
iter 10 value 94.061089
iter 20 value 94.053735
iter 30 value 85.109563
iter 40 value 83.059256
iter 50 value 82.810676
final value 82.758626
converged
Fitting Repeat 5
# weights: 507
initial value 98.933595
iter 10 value 93.861880
iter 20 value 93.843076
iter 30 value 93.803455
iter 40 value 80.837918
iter 50 value 80.087706
iter 60 value 77.028416
iter 70 value 76.440008
iter 80 value 75.608319
iter 90 value 75.350993
iter 100 value 75.350063
final value 75.350063
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.730419
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 97.101721
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 99.660578
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 105.541946
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 95.842665
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 106.740354
iter 10 value 93.601520
final value 93.601516
converged
Fitting Repeat 2
# weights: 305
initial value 94.819828
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 96.703164
iter 10 value 93.604520
iter 10 value 93.604520
iter 10 value 93.604520
final value 93.604520
converged
Fitting Repeat 4
# weights: 305
initial value 113.546000
final value 93.582418
converged
Fitting Repeat 5
# weights: 305
initial value 98.619439
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 111.411718
iter 10 value 89.561518
iter 20 value 84.465749
iter 30 value 82.171159
iter 40 value 81.452948
iter 50 value 81.424593
iter 60 value 80.994313
iter 70 value 80.501919
iter 80 value 80.501845
iter 80 value 80.501845
iter 80 value 80.501845
final value 80.501845
converged
Fitting Repeat 2
# weights: 507
initial value 101.531559
iter 10 value 93.602535
final value 93.502241
converged
Fitting Repeat 3
# weights: 507
initial value 96.459672
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 99.665173
final value 93.582418
converged
Fitting Repeat 5
# weights: 507
initial value 103.606958
final value 94.052911
converged
Fitting Repeat 1
# weights: 103
initial value 102.795451
iter 10 value 93.048530
iter 20 value 90.186848
iter 30 value 89.881346
iter 40 value 89.845665
final value 89.845549
converged
Fitting Repeat 2
# weights: 103
initial value 102.924286
iter 10 value 94.063447
iter 20 value 93.260517
iter 30 value 89.686805
iter 40 value 84.801369
iter 50 value 83.651856
iter 60 value 83.539724
iter 70 value 83.271910
iter 80 value 83.165414
final value 83.165183
converged
Fitting Repeat 3
# weights: 103
initial value 98.950623
iter 10 value 94.055212
iter 20 value 93.769936
iter 30 value 93.634025
iter 40 value 93.555338
iter 50 value 91.670339
iter 60 value 86.016662
iter 70 value 85.976650
iter 80 value 85.879752
iter 90 value 83.901421
iter 100 value 83.639070
final value 83.639070
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.265684
iter 10 value 94.058938
iter 20 value 93.862080
iter 30 value 93.693176
iter 40 value 93.576423
iter 50 value 85.237745
iter 60 value 84.006558
iter 70 value 83.230623
iter 80 value 82.775314
iter 90 value 81.939912
iter 100 value 81.876859
final value 81.876859
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 101.114474
iter 10 value 93.812590
iter 20 value 91.227033
iter 30 value 90.750882
iter 40 value 90.668730
iter 50 value 90.093191
iter 60 value 89.857550
iter 70 value 89.845631
iter 80 value 84.394297
iter 90 value 83.948184
iter 100 value 83.579594
final value 83.579594
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 104.040273
iter 10 value 94.118214
iter 20 value 93.138580
iter 30 value 93.103122
iter 40 value 88.496945
iter 50 value 87.903811
iter 60 value 85.761649
iter 70 value 84.299760
iter 80 value 83.414566
iter 90 value 82.817825
iter 100 value 82.783536
final value 82.783536
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.265177
iter 10 value 93.899898
iter 20 value 89.902115
iter 30 value 88.738764
iter 40 value 83.770346
iter 50 value 83.548869
iter 60 value 83.254678
iter 70 value 83.075694
iter 80 value 82.757937
iter 90 value 81.500636
iter 100 value 81.438703
final value 81.438703
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.933507
iter 10 value 94.199219
iter 20 value 91.699693
iter 30 value 86.608900
iter 40 value 85.035306
iter 50 value 83.894580
iter 60 value 83.635563
iter 70 value 83.440125
iter 80 value 83.382474
iter 90 value 83.124879
iter 100 value 82.894789
final value 82.894789
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.631642
iter 10 value 94.475705
iter 20 value 87.038465
iter 30 value 84.078471
iter 40 value 83.173276
iter 50 value 81.896805
iter 60 value 80.983338
iter 70 value 80.279337
iter 80 value 80.222856
iter 90 value 80.081881
iter 100 value 79.896090
final value 79.896090
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 113.182372
iter 10 value 94.904360
iter 20 value 93.948628
iter 30 value 90.168808
iter 40 value 87.108774
iter 50 value 84.125799
iter 60 value 83.432399
iter 70 value 83.249442
iter 80 value 83.228772
iter 90 value 83.175210
iter 100 value 82.089509
final value 82.089509
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.704170
iter 10 value 94.928060
iter 20 value 88.420880
iter 30 value 85.844680
iter 40 value 83.688467
iter 50 value 80.960403
iter 60 value 80.543456
iter 70 value 80.418126
iter 80 value 80.413382
iter 90 value 80.405372
iter 100 value 80.277874
final value 80.277874
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 119.007392
iter 10 value 93.819159
iter 20 value 93.598769
iter 30 value 91.628854
iter 40 value 84.290488
iter 50 value 83.863626
iter 60 value 83.447709
iter 70 value 83.098757
iter 80 value 82.788992
iter 90 value 82.226229
iter 100 value 80.638598
final value 80.638598
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 124.253200
iter 10 value 93.475299
iter 20 value 85.254685
iter 30 value 83.612774
iter 40 value 82.314905
iter 50 value 81.866575
iter 60 value 81.605040
iter 70 value 81.345010
iter 80 value 81.176350
iter 90 value 80.839312
iter 100 value 80.628902
final value 80.628902
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 132.461291
iter 10 value 93.892963
iter 20 value 86.169386
iter 30 value 84.984210
iter 40 value 81.398015
iter 50 value 80.772897
iter 60 value 80.258707
iter 70 value 79.964798
iter 80 value 79.884033
iter 90 value 79.876734
iter 100 value 79.846875
final value 79.846875
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.369536
iter 10 value 94.123863
iter 20 value 91.990901
iter 30 value 89.220261
iter 40 value 87.983827
iter 50 value 85.479690
iter 60 value 84.659055
iter 70 value 82.447391
iter 80 value 82.211693
iter 90 value 81.480095
iter 100 value 81.041448
final value 81.041448
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 109.207210
final value 94.054465
converged
Fitting Repeat 2
# weights: 103
initial value 108.555500
final value 94.054616
converged
Fitting Repeat 3
# weights: 103
initial value 96.525761
final value 94.054679
converged
Fitting Repeat 4
# weights: 103
initial value 104.145714
final value 94.054155
converged
Fitting Repeat 5
# weights: 103
initial value 96.813879
final value 94.054407
converged
Fitting Repeat 1
# weights: 305
initial value 97.041679
iter 10 value 94.057811
iter 20 value 89.497882
iter 30 value 84.519003
iter 40 value 84.324863
iter 50 value 84.217596
iter 60 value 84.184810
final value 84.184706
converged
Fitting Repeat 2
# weights: 305
initial value 93.473167
iter 10 value 87.206073
iter 20 value 82.576291
iter 30 value 82.410965
iter 40 value 82.409741
iter 50 value 82.400132
final value 82.392512
converged
Fitting Repeat 3
# weights: 305
initial value 94.305323
iter 10 value 94.055099
iter 20 value 93.082912
iter 30 value 85.263473
iter 40 value 85.260383
iter 50 value 85.247866
iter 60 value 85.147511
iter 70 value 85.138795
iter 80 value 85.132681
iter 90 value 82.672226
iter 100 value 82.640158
final value 82.640158
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.671967
iter 10 value 92.864862
iter 20 value 89.881165
iter 30 value 89.620754
iter 40 value 89.611225
iter 50 value 89.574160
iter 60 value 88.296745
iter 70 value 85.219022
iter 80 value 84.926364
iter 90 value 82.861769
iter 100 value 81.071768
final value 81.071768
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.429670
iter 10 value 91.515907
iter 20 value 91.429750
iter 30 value 91.429231
iter 40 value 88.540349
iter 50 value 85.807832
iter 60 value 85.766083
iter 70 value 85.751721
iter 80 value 85.704055
iter 90 value 85.699650
final value 85.699247
converged
Fitting Repeat 1
# weights: 507
initial value 108.722266
iter 10 value 93.936657
iter 20 value 93.879171
iter 30 value 92.901220
iter 40 value 92.893659
iter 50 value 88.420172
iter 60 value 82.716904
iter 70 value 82.509566
iter 80 value 82.265054
iter 80 value 82.265054
final value 82.265054
converged
Fitting Repeat 2
# weights: 507
initial value 98.009217
iter 10 value 94.060707
iter 20 value 93.905468
iter 30 value 87.387494
iter 40 value 84.334088
iter 50 value 84.333007
iter 60 value 84.142985
final value 84.116852
converged
Fitting Repeat 3
# weights: 507
initial value 109.222092
iter 10 value 93.590991
iter 20 value 93.055371
iter 30 value 86.897947
iter 40 value 81.791394
iter 50 value 80.147112
iter 60 value 78.981987
iter 70 value 78.597131
iter 80 value 78.458984
iter 90 value 78.380019
iter 100 value 78.266079
final value 78.266079
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 99.230327
iter 10 value 94.057569
iter 20 value 92.938721
iter 30 value 92.835710
iter 40 value 92.560236
final value 92.560223
converged
Fitting Repeat 5
# weights: 507
initial value 106.685920
iter 10 value 90.605026
iter 20 value 85.652104
iter 30 value 85.571535
iter 40 value 85.570840
iter 50 value 85.551625
iter 60 value 85.372113
iter 70 value 85.230057
iter 80 value 85.138508
iter 90 value 85.134584
iter 100 value 84.033109
final value 84.033109
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 127.726192
iter 10 value 117.895330
iter 20 value 117.889894
iter 30 value 115.912867
iter 40 value 114.727097
final value 114.727094
converged
Fitting Repeat 2
# weights: 305
initial value 121.599528
iter 10 value 117.891755
iter 20 value 110.767142
final value 110.078716
converged
Fitting Repeat 3
# weights: 305
initial value 128.150844
iter 10 value 117.721382
iter 20 value 117.677127
iter 30 value 117.671348
iter 40 value 117.301834
iter 50 value 117.159615
iter 60 value 117.155962
iter 70 value 116.659421
iter 80 value 116.653557
final value 116.653502
converged
Fitting Repeat 4
# weights: 305
initial value 140.435480
iter 10 value 117.895329
iter 20 value 117.890531
iter 30 value 117.788694
iter 40 value 117.511501
final value 117.511413
converged
Fitting Repeat 5
# weights: 305
initial value 132.239493
iter 10 value 109.175922
iter 20 value 108.513207
iter 30 value 105.323887
iter 40 value 104.624961
iter 50 value 102.854144
iter 60 value 102.634564
iter 70 value 102.473875
iter 80 value 102.379062
iter 90 value 102.024626
iter 100 value 100.884081
final value 100.884081
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 -- Tue Apr 16 01:47:49 2024
***********************************************
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
45.21 1.54 47.60
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 32.17 | 1.43 | 33.66 | |
| FreqInteractors | 0.38 | 0.00 | 0.40 | |
| calculateAAC | 0.07 | 0.00 | 0.06 | |
| calculateAutocor | 0.51 | 0.10 | 0.61 | |
| calculateCTDC | 0.1 | 0.0 | 0.1 | |
| calculateCTDD | 0.84 | 0.06 | 0.90 | |
| calculateCTDT | 0.41 | 0.02 | 0.42 | |
| calculateCTriad | 0.48 | 0.06 | 0.55 | |
| calculateDC | 0.14 | 0.00 | 0.14 | |
| calculateF | 0.45 | 0.03 | 0.49 | |
| calculateKSAAP | 0.14 | 0.02 | 0.15 | |
| calculateQD_Sm | 2.44 | 0.04 | 2.49 | |
| calculateTC | 2.20 | 0.10 | 2.29 | |
| calculateTC_Sm | 0.24 | 0.00 | 0.24 | |
| corr_plot | 31.09 | 1.01 | 32.14 | |
| enrichfindP | 0.61 | 0.11 | 12.60 | |
| enrichfind_hp | 0.09 | 0.02 | 1.14 | |
| enrichplot | 0.47 | 0.01 | 0.48 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.01 | 0.02 | 2.31 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.11 | 0.02 | 0.12 | |
| pred_ensembel | 14.38 | 0.50 | 11.02 | |
| var_imp | 33.15 | 0.67 | 33.84 | |