Matineh Rahmatbakhsh
| Snapshot Date: 2024-12-23 13:40 -0500 (Mon, 23 Dec 2024) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: 65e718f |
| git_last_commit_date: 2024-10-29 11:04:11 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2024-12-24 11:41 -0500 (Tue, 24 Dec 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences" | 4754 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences" | 4472 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" | 4426 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" | 4381 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | R Under development (unstable) (2024-11-24 r87369) -- "Unsuffered Consequences" | 4373 |
| 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 973/2274 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.13.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.13.0 |
| Command: E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.21-bioc\R\library --no-vignettes --timings HPiP_1.13.0.tar.gz |
| StartedAt: 2024-12-24 01:39:50 -0500 (Tue, 24 Dec 2024) |
| EndedAt: 2024-12-24 01:45:00 -0500 (Tue, 24 Dec 2024) |
| EllapsedTime: 310.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.21-bioc\R\library --no-vignettes --timings HPiP_1.13.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'E:/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck'
* using R Under development (unstable) (2024-10-26 r87273 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 13.2.0
GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.13.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
var_imp 34.81 1.32 36.13
FSmethod 34.25 1.78 36.14
corr_plot 32.06 1.46 33.53
pred_ensembel 14.14 0.39 13.04
enrichfindP 0.61 0.09 13.43
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
'E:/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'E:/biocbuild/bbs-3.21-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 Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 100.063846
iter 10 value 94.049694
final value 93.976244
converged
Fitting Repeat 2
# weights: 103
initial value 98.455378
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 105.063224
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 94.977638
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 101.198283
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 99.086772
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 99.102180
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 96.313847
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 96.299460
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 114.254119
final value 94.026542
converged
Fitting Repeat 1
# weights: 507
initial value 101.523429
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 109.618965
iter 10 value 93.708639
iter 20 value 87.222289
iter 30 value 86.266509
iter 40 value 86.262478
final value 86.262472
converged
Fitting Repeat 3
# weights: 507
initial value 101.030894
final value 94.052432
converged
Fitting Repeat 4
# weights: 507
initial value 98.877832
final value 94.026542
converged
Fitting Repeat 5
# weights: 507
initial value 98.562154
iter 10 value 93.983141
final value 93.976244
converged
Fitting Repeat 1
# weights: 103
initial value 104.112672
iter 10 value 94.488257
iter 20 value 94.379858
iter 30 value 94.048225
iter 40 value 93.895392
iter 50 value 90.851510
iter 60 value 89.095227
iter 70 value 88.960316
iter 80 value 88.602314
iter 90 value 87.988877
iter 100 value 82.550853
final value 82.550853
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 100.839248
iter 10 value 94.573194
iter 20 value 93.194429
iter 30 value 85.881128
iter 40 value 85.578105
iter 50 value 85.236020
iter 60 value 84.026192
iter 70 value 83.660489
iter 80 value 83.632982
iter 90 value 83.403634
iter 100 value 83.160288
final value 83.160288
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 106.732185
iter 10 value 94.565843
iter 20 value 94.273685
iter 30 value 87.867729
iter 40 value 87.161873
iter 50 value 84.564473
iter 60 value 84.178367
iter 70 value 84.166027
final value 84.166023
converged
Fitting Repeat 4
# weights: 103
initial value 96.473045
iter 10 value 94.466947
iter 20 value 94.103363
iter 30 value 94.079091
iter 40 value 94.071843
iter 50 value 93.515754
iter 60 value 89.598102
iter 70 value 86.364819
iter 80 value 86.124749
iter 90 value 85.684851
iter 100 value 85.330671
final value 85.330671
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 117.167105
iter 10 value 94.488115
iter 10 value 94.488115
iter 20 value 94.387765
iter 30 value 93.117788
iter 40 value 90.338863
iter 50 value 85.988048
iter 60 value 84.535920
iter 70 value 84.426424
iter 80 value 83.452412
iter 90 value 83.123491
iter 100 value 83.080043
final value 83.080043
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.130177
iter 10 value 95.258953
iter 20 value 92.936322
iter 30 value 89.539546
iter 40 value 87.469580
iter 50 value 84.799211
iter 60 value 83.512828
iter 70 value 83.346393
iter 80 value 83.000640
iter 90 value 81.937035
iter 100 value 81.252752
final value 81.252752
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.517509
iter 10 value 94.509193
iter 20 value 91.479201
iter 30 value 85.949594
iter 40 value 82.506909
iter 50 value 81.950780
iter 60 value 81.753922
iter 70 value 81.641929
iter 80 value 81.526051
iter 90 value 81.287378
iter 100 value 80.885169
final value 80.885169
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.948420
iter 10 value 94.266933
iter 20 value 87.119400
iter 30 value 85.967723
iter 40 value 84.016363
iter 50 value 83.616086
iter 60 value 83.469476
iter 70 value 83.426820
iter 80 value 82.696620
iter 90 value 81.091604
iter 100 value 80.749995
final value 80.749995
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.727011
iter 10 value 94.516630
iter 20 value 89.077822
iter 30 value 86.905413
iter 40 value 85.272693
iter 50 value 82.962363
iter 60 value 82.216444
iter 70 value 81.465966
iter 80 value 80.885602
iter 90 value 80.813325
iter 100 value 80.630186
final value 80.630186
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 111.351602
iter 10 value 94.415604
iter 20 value 93.138683
iter 30 value 87.489382
iter 40 value 85.952108
iter 50 value 85.641201
iter 60 value 83.893616
iter 70 value 82.194846
iter 80 value 80.827690
iter 90 value 80.505127
iter 100 value 80.372428
final value 80.372428
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 136.192865
iter 10 value 94.506328
iter 20 value 91.115571
iter 30 value 86.191989
iter 40 value 84.970876
iter 50 value 82.015922
iter 60 value 81.450591
iter 70 value 81.350868
iter 80 value 81.273715
iter 90 value 81.181251
iter 100 value 80.722226
final value 80.722226
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.369646
iter 10 value 94.377866
iter 20 value 88.850437
iter 30 value 88.120613
iter 40 value 87.727213
iter 50 value 86.449804
iter 60 value 83.846296
iter 70 value 81.558858
iter 80 value 81.091831
iter 90 value 80.763520
iter 100 value 80.523817
final value 80.523817
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 117.791998
iter 10 value 94.454535
iter 20 value 90.707797
iter 30 value 83.319623
iter 40 value 82.545660
iter 50 value 82.009486
iter 60 value 81.891978
iter 70 value 81.157655
iter 80 value 80.824403
iter 90 value 80.563852
iter 100 value 80.444653
final value 80.444653
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 113.973075
iter 10 value 96.842936
iter 20 value 90.725985
iter 30 value 84.786583
iter 40 value 84.403043
iter 50 value 84.172248
iter 60 value 83.458392
iter 70 value 82.348580
iter 80 value 81.955045
iter 90 value 81.777758
iter 100 value 81.173376
final value 81.173376
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.502759
iter 10 value 94.339245
iter 20 value 90.027696
iter 30 value 83.771932
iter 40 value 82.755946
iter 50 value 82.281606
iter 60 value 80.945275
iter 70 value 80.567237
iter 80 value 80.231098
iter 90 value 79.930821
iter 100 value 79.835713
final value 79.835713
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.031202
final value 94.485945
converged
Fitting Repeat 2
# weights: 103
initial value 99.200594
final value 94.483588
converged
Fitting Repeat 3
# weights: 103
initial value 107.520377
final value 94.485843
converged
Fitting Repeat 4
# weights: 103
initial value 95.761954
final value 94.486901
converged
Fitting Repeat 5
# weights: 103
initial value 106.590889
final value 94.485586
converged
Fitting Repeat 1
# weights: 305
initial value 98.385092
iter 10 value 94.489338
iter 20 value 94.474925
iter 30 value 94.318097
iter 40 value 86.198719
iter 50 value 85.984252
iter 60 value 85.530797
iter 70 value 85.371077
iter 80 value 85.366549
iter 90 value 85.355435
iter 100 value 85.351386
final value 85.351386
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.676994
iter 10 value 94.327668
iter 20 value 94.071512
iter 30 value 86.557416
final value 86.550252
converged
Fitting Repeat 3
# weights: 305
initial value 96.358533
iter 10 value 94.485285
iter 20 value 94.484232
final value 94.484222
converged
Fitting Repeat 4
# weights: 305
initial value 113.188574
iter 10 value 94.031621
iter 20 value 94.008066
iter 30 value 93.853860
iter 40 value 87.489418
iter 50 value 86.582007
iter 60 value 83.672227
iter 70 value 83.327760
iter 80 value 82.683314
iter 90 value 82.356205
iter 100 value 82.318018
final value 82.318018
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 97.424857
iter 10 value 94.454050
iter 20 value 94.449586
iter 30 value 94.309995
iter 40 value 83.580361
iter 50 value 81.964926
iter 60 value 81.958917
iter 70 value 81.902989
iter 80 value 81.890094
final value 81.889998
converged
Fitting Repeat 1
# weights: 507
initial value 98.230268
iter 10 value 94.037371
iter 20 value 94.033650
iter 30 value 94.029951
iter 40 value 93.562998
iter 50 value 92.168087
iter 60 value 92.096392
final value 92.095892
converged
Fitting Repeat 2
# weights: 507
initial value 129.866431
iter 10 value 90.232847
iter 20 value 88.287929
iter 30 value 86.362717
iter 40 value 86.361578
iter 50 value 86.359608
iter 60 value 85.604022
iter 70 value 85.592995
iter 80 value 85.589145
iter 90 value 84.940222
iter 100 value 84.762839
final value 84.762839
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 98.591970
iter 10 value 93.812417
iter 20 value 92.675940
iter 30 value 92.476517
iter 40 value 92.473854
iter 50 value 92.472654
iter 60 value 92.472028
iter 70 value 91.739367
iter 80 value 83.089836
iter 90 value 82.421797
iter 100 value 81.225769
final value 81.225769
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 96.876602
iter 10 value 94.491611
iter 20 value 92.315063
iter 30 value 87.394480
iter 40 value 87.300337
iter 50 value 85.617109
iter 60 value 82.586482
iter 70 value 81.876647
iter 80 value 81.337235
iter 90 value 80.080627
iter 100 value 79.880748
final value 79.880748
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.553954
iter 10 value 88.417108
iter 20 value 86.747432
iter 30 value 86.620108
iter 40 value 86.136437
iter 50 value 86.117282
final value 86.116400
converged
Fitting Repeat 1
# weights: 103
initial value 111.103199
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 98.767124
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 98.746392
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 101.911418
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 101.715573
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 97.633549
final value 94.032967
converged
Fitting Repeat 2
# weights: 305
initial value 106.576130
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 96.716678
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 96.304188
iter 10 value 93.909035
iter 20 value 93.702598
final value 93.702234
converged
Fitting Repeat 5
# weights: 305
initial value 99.537587
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 104.134339
iter 10 value 93.484215
final value 93.484211
converged
Fitting Repeat 2
# weights: 507
initial value 98.113282
iter 10 value 94.032968
iter 10 value 94.032967
iter 10 value 94.032967
final value 94.032967
converged
Fitting Repeat 3
# weights: 507
initial value 119.008680
final value 94.032967
converged
Fitting Repeat 4
# weights: 507
initial value 102.908295
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 106.529783
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 97.999789
iter 10 value 91.941667
iter 20 value 86.173555
iter 30 value 85.183407
iter 40 value 83.112875
iter 50 value 81.056181
iter 60 value 80.488479
iter 70 value 79.870158
iter 80 value 79.745270
iter 90 value 79.517975
final value 79.470344
converged
Fitting Repeat 2
# weights: 103
initial value 102.348334
iter 10 value 94.027896
iter 20 value 93.812763
iter 30 value 92.512365
iter 40 value 92.233407
iter 50 value 89.853730
iter 60 value 82.455146
iter 70 value 81.234502
iter 80 value 80.544580
iter 90 value 79.957540
iter 100 value 79.751409
final value 79.751409
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 99.058424
iter 10 value 94.056900
iter 20 value 94.054776
iter 30 value 88.786374
iter 40 value 86.449326
iter 50 value 85.620349
iter 60 value 85.184678
iter 70 value 84.807635
iter 80 value 84.612503
iter 90 value 82.181004
iter 100 value 82.175812
final value 82.175812
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 107.404820
iter 10 value 94.067490
iter 20 value 94.044641
iter 30 value 83.935575
iter 40 value 83.123356
iter 50 value 82.695558
iter 60 value 82.368174
iter 70 value 82.294930
iter 80 value 82.155386
iter 90 value 82.116903
final value 82.116711
converged
Fitting Repeat 5
# weights: 103
initial value 96.378472
iter 10 value 91.447770
iter 20 value 83.693507
iter 30 value 83.064256
iter 40 value 82.725833
iter 50 value 82.538409
iter 60 value 82.172342
iter 70 value 82.116721
final value 82.116711
converged
Fitting Repeat 1
# weights: 305
initial value 130.381197
iter 10 value 94.123456
iter 20 value 94.034150
iter 30 value 87.596626
iter 40 value 82.541328
iter 50 value 82.118236
iter 60 value 82.036733
iter 70 value 82.003630
iter 80 value 81.900512
iter 90 value 81.867074
iter 100 value 81.837471
final value 81.837471
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 112.050949
iter 10 value 94.060989
iter 20 value 87.174791
iter 30 value 85.498739
iter 40 value 83.680552
iter 50 value 80.765935
iter 60 value 79.319581
iter 70 value 78.698535
iter 80 value 78.126704
iter 90 value 77.703828
iter 100 value 77.552289
final value 77.552289
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.418549
iter 10 value 94.250772
iter 20 value 91.439928
iter 30 value 85.981417
iter 40 value 83.767453
iter 50 value 82.397718
iter 60 value 81.480640
iter 70 value 81.401627
iter 80 value 81.328500
iter 90 value 81.264906
iter 100 value 81.262963
final value 81.262963
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.553397
iter 10 value 94.069922
iter 20 value 87.629894
iter 30 value 83.006001
iter 40 value 82.186663
iter 50 value 81.410660
iter 60 value 79.175713
iter 70 value 78.451358
iter 80 value 78.301172
iter 90 value 77.861728
iter 100 value 77.642590
final value 77.642590
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.854226
iter 10 value 94.094707
iter 20 value 93.973367
iter 30 value 84.181981
iter 40 value 83.585419
iter 50 value 82.117988
iter 60 value 81.368719
iter 70 value 80.716618
iter 80 value 80.121750
iter 90 value 78.942997
iter 100 value 77.915191
final value 77.915191
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.174215
iter 10 value 94.057602
iter 20 value 86.112820
iter 30 value 83.333803
iter 40 value 82.325412
iter 50 value 81.883657
iter 60 value 81.667754
iter 70 value 81.565709
iter 80 value 80.916569
iter 90 value 80.311571
iter 100 value 79.595682
final value 79.595682
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.815068
iter 10 value 92.809801
iter 20 value 84.126367
iter 30 value 82.382258
iter 40 value 80.447309
iter 50 value 80.071116
iter 60 value 79.059183
iter 70 value 78.104010
iter 80 value 77.526776
iter 90 value 77.208035
iter 100 value 77.047622
final value 77.047622
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.197627
iter 10 value 94.119624
iter 20 value 93.958648
iter 30 value 86.719760
iter 40 value 85.565370
iter 50 value 85.436904
iter 60 value 84.689734
iter 70 value 80.549606
iter 80 value 79.467841
iter 90 value 78.016090
iter 100 value 77.669002
final value 77.669002
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 124.888109
iter 10 value 94.211232
iter 20 value 93.806985
iter 30 value 86.162502
iter 40 value 84.678166
iter 50 value 80.338077
iter 60 value 79.743527
iter 70 value 79.451261
iter 80 value 79.367440
iter 90 value 79.335383
iter 100 value 79.324723
final value 79.324723
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 119.410767
iter 10 value 96.609878
iter 20 value 94.027219
iter 30 value 93.241276
iter 40 value 92.814233
iter 50 value 91.727552
iter 60 value 91.503637
iter 70 value 90.609574
iter 80 value 85.584011
iter 90 value 83.771091
iter 100 value 82.878418
final value 82.878418
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 109.340813
final value 94.034502
converged
Fitting Repeat 2
# weights: 103
initial value 108.359237
final value 94.054724
converged
Fitting Repeat 3
# weights: 103
initial value 95.579584
final value 94.054443
converged
Fitting Repeat 4
# weights: 103
initial value 95.589583
iter 10 value 94.054594
iter 20 value 94.052920
iter 20 value 94.052919
iter 20 value 94.052919
final value 94.052919
converged
Fitting Repeat 5
# weights: 103
initial value 101.804089
iter 10 value 94.054630
iter 20 value 94.052705
iter 30 value 84.702699
iter 40 value 84.659736
iter 50 value 83.534523
iter 60 value 83.490895
iter 70 value 83.327877
iter 80 value 81.170647
iter 90 value 81.157080
final value 81.157049
converged
Fitting Repeat 1
# weights: 305
initial value 103.268806
iter 10 value 94.057821
iter 20 value 93.470834
iter 30 value 91.325530
iter 40 value 91.280294
iter 50 value 87.998266
iter 60 value 84.255915
iter 70 value 84.252932
iter 80 value 84.120744
final value 84.120257
converged
Fitting Repeat 2
# weights: 305
initial value 119.206349
iter 10 value 94.037991
iter 20 value 94.036396
iter 30 value 94.036153
iter 40 value 94.035418
iter 50 value 94.000623
iter 60 value 93.969158
iter 70 value 85.306916
final value 84.655806
converged
Fitting Repeat 3
# weights: 305
initial value 99.196925
iter 10 value 94.058145
iter 20 value 93.872414
iter 30 value 87.016547
iter 40 value 87.009908
iter 50 value 86.801467
iter 60 value 85.827823
iter 70 value 84.094505
iter 80 value 83.366878
iter 90 value 82.163665
iter 100 value 82.093849
final value 82.093849
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.890123
iter 10 value 94.057637
iter 20 value 91.877942
iter 30 value 85.190571
iter 40 value 85.160363
iter 50 value 85.143524
iter 60 value 85.143217
final value 85.143159
converged
Fitting Repeat 5
# weights: 305
initial value 104.749229
iter 10 value 94.057903
iter 20 value 94.052961
iter 20 value 94.052960
iter 20 value 94.052960
final value 94.052960
converged
Fitting Repeat 1
# weights: 507
initial value 98.997356
iter 10 value 94.040612
iter 20 value 94.034227
iter 30 value 93.981586
iter 40 value 84.666834
iter 50 value 84.662398
iter 60 value 84.660283
iter 70 value 84.658624
iter 80 value 84.466299
iter 90 value 82.673298
iter 100 value 78.653445
final value 78.653445
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 127.246095
iter 10 value 93.581124
iter 20 value 84.130200
iter 30 value 83.280594
iter 40 value 83.277164
iter 50 value 83.200542
iter 60 value 83.197667
iter 70 value 82.549080
iter 80 value 82.496111
iter 90 value 82.475186
iter 100 value 81.376391
final value 81.376391
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 116.240999
iter 10 value 93.976955
iter 20 value 93.970325
iter 30 value 93.394255
iter 40 value 82.735111
iter 50 value 80.226295
iter 60 value 78.127085
iter 70 value 78.100384
iter 80 value 77.077081
iter 90 value 76.985778
iter 100 value 76.985482
final value 76.985482
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 102.486824
iter 10 value 94.040824
iter 20 value 93.955467
iter 30 value 89.540767
iter 40 value 87.055096
iter 50 value 83.454503
iter 60 value 83.212170
iter 70 value 82.844201
iter 80 value 82.820661
iter 90 value 82.820535
final value 82.820517
converged
Fitting Repeat 5
# weights: 507
initial value 99.062453
iter 10 value 93.977272
iter 20 value 93.876361
iter 30 value 88.425645
iter 40 value 87.396823
iter 50 value 87.366322
iter 60 value 87.365881
final value 87.365864
converged
Fitting Repeat 1
# weights: 103
initial value 97.259741
final value 94.052909
converged
Fitting Repeat 2
# weights: 103
initial value 104.464708
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 100.563681
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 94.547673
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 102.617714
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 94.295163
final value 93.904720
converged
Fitting Repeat 2
# weights: 305
initial value 98.193230
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 96.658564
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 102.653406
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 95.633113
final value 94.043234
converged
Fitting Repeat 1
# weights: 507
initial value 102.321855
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 97.884900
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 126.964679
iter 10 value 94.043253
final value 94.043243
converged
Fitting Repeat 4
# weights: 507
initial value 101.077438
iter 10 value 93.887628
final value 93.887626
converged
Fitting Repeat 5
# weights: 507
initial value 111.306031
iter 10 value 93.954701
final value 93.887627
converged
Fitting Repeat 1
# weights: 103
initial value 100.219775
iter 10 value 94.095932
iter 20 value 94.054051
iter 30 value 88.945559
iter 40 value 88.678478
iter 50 value 88.627857
iter 60 value 86.074454
iter 70 value 85.547754
iter 80 value 85.129629
iter 90 value 85.116571
final value 85.115742
converged
Fitting Repeat 2
# weights: 103
initial value 97.393439
iter 10 value 93.048532
iter 20 value 86.908603
iter 30 value 86.136181
iter 40 value 86.122995
iter 50 value 86.018199
iter 60 value 86.007823
final value 86.007816
converged
Fitting Repeat 3
# weights: 103
initial value 96.137630
iter 10 value 93.814310
iter 20 value 89.964461
iter 30 value 87.935180
iter 40 value 85.250296
iter 50 value 85.220687
final value 85.219730
converged
Fitting Repeat 4
# weights: 103
initial value 97.638682
iter 10 value 94.056688
iter 20 value 93.873512
iter 30 value 93.796754
iter 40 value 93.787437
iter 50 value 93.603707
iter 60 value 92.151067
iter 70 value 86.781394
iter 80 value 85.055692
iter 90 value 84.705095
iter 100 value 84.651586
final value 84.651586
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 95.988674
iter 10 value 94.119653
iter 20 value 88.642736
iter 30 value 84.989213
iter 40 value 84.395162
iter 50 value 83.837154
iter 60 value 83.564553
iter 70 value 83.338378
iter 80 value 83.296821
iter 80 value 83.296821
iter 80 value 83.296821
final value 83.296821
converged
Fitting Repeat 1
# weights: 305
initial value 117.923690
iter 10 value 94.058262
iter 20 value 89.032741
iter 30 value 88.258884
iter 40 value 84.655887
iter 50 value 83.384336
iter 60 value 82.671335
iter 70 value 82.455454
iter 80 value 82.230757
iter 90 value 82.166495
iter 100 value 81.984226
final value 81.984226
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 114.047463
iter 10 value 94.093849
iter 20 value 89.284056
iter 30 value 85.614646
iter 40 value 84.356162
iter 50 value 83.697263
iter 60 value 83.365339
iter 70 value 83.257477
iter 80 value 83.216326
iter 90 value 83.204975
iter 100 value 83.052111
final value 83.052111
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.686832
iter 10 value 94.806845
iter 20 value 86.402385
iter 30 value 86.072090
iter 40 value 86.037041
iter 50 value 85.891570
iter 60 value 84.668879
iter 70 value 84.118683
iter 80 value 82.957697
iter 90 value 82.760422
iter 100 value 82.715640
final value 82.715640
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.063616
iter 10 value 94.521160
iter 20 value 92.439147
iter 30 value 88.443423
iter 40 value 86.424205
iter 50 value 86.260131
iter 60 value 85.511981
iter 70 value 84.429528
iter 80 value 82.787658
iter 90 value 82.452460
iter 100 value 82.174710
final value 82.174710
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 117.915683
iter 10 value 94.041656
iter 20 value 92.201367
iter 30 value 85.898722
iter 40 value 84.889877
iter 50 value 83.506290
iter 60 value 83.041765
iter 70 value 82.076057
iter 80 value 81.914696
iter 90 value 81.825633
iter 100 value 81.781191
final value 81.781191
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.333056
iter 10 value 95.066471
iter 20 value 93.611142
iter 30 value 90.535426
iter 40 value 86.793431
iter 50 value 83.559549
iter 60 value 82.885755
iter 70 value 82.663925
iter 80 value 82.515183
iter 90 value 82.317332
iter 100 value 82.201719
final value 82.201719
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.438764
iter 10 value 95.850382
iter 20 value 89.338396
iter 30 value 86.240523
iter 40 value 85.291018
iter 50 value 84.930603
iter 60 value 84.844950
iter 70 value 84.006845
iter 80 value 83.333996
iter 90 value 82.894811
iter 100 value 82.291291
final value 82.291291
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 120.825059
iter 10 value 94.411294
iter 20 value 93.560802
iter 30 value 86.823874
iter 40 value 86.277202
iter 50 value 86.235687
iter 60 value 85.814282
iter 70 value 83.637350
iter 80 value 82.415676
iter 90 value 82.360134
iter 100 value 82.159226
final value 82.159226
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 127.601706
iter 10 value 94.481311
iter 20 value 94.133119
iter 30 value 90.948935
iter 40 value 88.734248
iter 50 value 85.167041
iter 60 value 84.264290
iter 70 value 83.411369
iter 80 value 82.850808
iter 90 value 82.419401
iter 100 value 82.277527
final value 82.277527
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.697607
iter 10 value 93.956143
iter 20 value 88.445465
iter 30 value 86.200444
iter 40 value 85.994476
iter 50 value 85.640673
iter 60 value 83.385710
iter 70 value 82.877500
iter 80 value 82.635236
iter 90 value 82.458014
iter 100 value 82.302379
final value 82.302379
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.769274
final value 94.054589
converged
Fitting Repeat 2
# weights: 103
initial value 99.552503
iter 10 value 88.430233
iter 20 value 88.197315
iter 30 value 88.196772
iter 40 value 87.915857
final value 87.885929
converged
Fitting Repeat 3
# weights: 103
initial value 95.464682
iter 10 value 94.044901
iter 20 value 94.043508
final value 94.043267
converged
Fitting Repeat 4
# weights: 103
initial value 100.196218
iter 10 value 94.054667
iter 20 value 94.052733
iter 30 value 85.635681
iter 40 value 85.634344
iter 50 value 85.633343
iter 60 value 85.632274
iter 70 value 85.245586
final value 85.245521
converged
Fitting Repeat 5
# weights: 103
initial value 101.368131
final value 94.054537
converged
Fitting Repeat 1
# weights: 305
initial value 96.742198
iter 10 value 94.056895
final value 94.053685
converged
Fitting Repeat 2
# weights: 305
initial value 108.702834
iter 10 value 94.047880
iter 20 value 94.037085
iter 30 value 93.382740
iter 40 value 93.180534
iter 50 value 93.157870
iter 60 value 93.157625
iter 60 value 93.157625
final value 93.157625
converged
Fitting Repeat 3
# weights: 305
initial value 112.853384
iter 10 value 94.048835
iter 20 value 94.044328
final value 94.044176
converged
Fitting Repeat 4
# weights: 305
initial value 102.616350
iter 10 value 94.057410
iter 20 value 92.716304
iter 30 value 86.126032
iter 40 value 86.073546
iter 50 value 86.069468
iter 60 value 86.068823
iter 70 value 86.067165
iter 80 value 86.066957
iter 90 value 85.253957
iter 100 value 85.232723
final value 85.232723
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 95.908004
iter 10 value 90.283469
iter 20 value 86.753256
iter 30 value 86.746107
iter 40 value 86.743432
iter 50 value 86.716732
iter 60 value 86.700977
iter 70 value 86.700835
final value 86.700815
converged
Fitting Repeat 1
# weights: 507
initial value 109.776447
iter 10 value 94.060753
iter 20 value 94.035368
iter 30 value 92.158163
iter 40 value 85.461475
iter 50 value 83.413681
iter 60 value 83.180158
final value 83.168743
converged
Fitting Repeat 2
# weights: 507
initial value 95.623723
iter 10 value 94.060891
iter 20 value 91.978078
iter 30 value 87.832287
iter 40 value 85.534149
final value 85.534140
converged
Fitting Repeat 3
# weights: 507
initial value 108.104415
iter 10 value 93.908994
iter 20 value 93.908421
iter 30 value 91.828189
iter 40 value 86.798774
iter 50 value 86.775115
iter 60 value 86.749225
final value 86.748906
converged
Fitting Repeat 4
# weights: 507
initial value 103.264140
iter 10 value 94.060434
iter 20 value 93.971602
iter 30 value 93.541172
iter 40 value 93.529044
final value 93.528927
converged
Fitting Repeat 5
# weights: 507
initial value 104.240794
iter 10 value 93.908280
iter 20 value 93.900577
iter 30 value 92.315549
iter 40 value 88.465702
iter 40 value 88.465702
iter 40 value 88.465702
final value 88.465702
converged
Fitting Repeat 1
# weights: 103
initial value 103.729033
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 99.845104
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 100.224695
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.319567
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 103.642679
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.353153
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 97.782697
iter 10 value 91.477127
iter 20 value 84.535773
iter 30 value 84.245910
iter 40 value 84.244441
iter 50 value 84.215778
iter 60 value 82.703148
iter 70 value 81.615199
final value 81.614943
converged
Fitting Repeat 3
# weights: 305
initial value 96.256506
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 99.206034
iter 10 value 93.313566
final value 93.313054
converged
Fitting Repeat 5
# weights: 305
initial value 96.756941
final value 94.305882
converged
Fitting Repeat 1
# weights: 507
initial value 114.282890
iter 10 value 94.305873
iter 10 value 94.305873
final value 94.305873
converged
Fitting Repeat 2
# weights: 507
initial value 113.205129
iter 10 value 90.337281
iter 20 value 89.574653
iter 30 value 89.394375
final value 89.392231
converged
Fitting Repeat 3
# weights: 507
initial value 98.240670
final value 92.906854
converged
Fitting Repeat 4
# weights: 507
initial value 147.313238
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 110.030927
iter 10 value 93.972249
final value 93.969901
converged
Fitting Repeat 1
# weights: 103
initial value 97.887441
iter 10 value 94.471738
iter 20 value 93.962093
iter 30 value 91.425286
iter 40 value 90.236878
iter 50 value 89.593364
iter 60 value 89.121906
iter 70 value 88.516840
iter 80 value 87.307648
iter 90 value 83.897646
iter 100 value 83.611969
final value 83.611969
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 104.810649
iter 10 value 94.459404
iter 20 value 93.345832
iter 30 value 93.159449
iter 40 value 93.072247
iter 50 value 91.253116
iter 60 value 83.219841
iter 70 value 82.404838
iter 80 value 81.073012
iter 90 value 80.890309
final value 80.882854
converged
Fitting Repeat 3
# weights: 103
initial value 97.260104
iter 10 value 94.488395
iter 20 value 92.654806
iter 30 value 86.232884
iter 40 value 84.770801
iter 50 value 84.407871
iter 60 value 83.789505
iter 70 value 83.386197
iter 80 value 83.268442
final value 83.260900
converged
Fitting Repeat 4
# weights: 103
initial value 100.214671
iter 10 value 94.538283
iter 20 value 94.358445
iter 30 value 93.629065
iter 40 value 90.858956
iter 50 value 90.068898
iter 60 value 89.962494
iter 70 value 88.407078
iter 80 value 86.431147
iter 90 value 84.590552
iter 100 value 83.517556
final value 83.517556
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 101.268606
iter 10 value 94.494830
iter 20 value 93.941763
iter 30 value 91.703144
iter 40 value 90.376292
iter 50 value 89.694462
iter 60 value 89.449338
iter 70 value 89.379653
iter 80 value 89.378689
iter 80 value 89.378688
iter 80 value 89.378688
final value 89.378688
converged
Fitting Repeat 1
# weights: 305
initial value 121.820930
iter 10 value 94.453772
iter 20 value 93.829138
iter 30 value 89.880189
iter 40 value 87.664683
iter 50 value 86.995756
iter 60 value 84.547480
iter 70 value 80.884149
iter 80 value 80.490991
iter 90 value 80.234680
iter 100 value 80.165290
final value 80.165290
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.172298
iter 10 value 94.578327
iter 20 value 89.119405
iter 30 value 84.782710
iter 40 value 84.655773
iter 50 value 84.231809
iter 60 value 83.460817
iter 70 value 80.984704
iter 80 value 80.213116
iter 90 value 79.957494
iter 100 value 79.868950
final value 79.868950
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 110.924671
iter 10 value 94.518720
iter 20 value 93.660220
iter 30 value 90.674650
iter 40 value 84.777524
iter 50 value 83.432278
iter 60 value 80.881514
iter 70 value 80.203822
iter 80 value 79.955428
iter 90 value 79.802095
iter 100 value 79.756466
final value 79.756466
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 118.104998
iter 10 value 94.340878
iter 20 value 88.778773
iter 30 value 85.145243
iter 40 value 80.807975
iter 50 value 80.055839
iter 60 value 79.941605
iter 70 value 79.732968
iter 80 value 79.277242
iter 90 value 79.201640
iter 100 value 79.180880
final value 79.180880
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 121.361576
iter 10 value 93.602070
iter 20 value 87.223946
iter 30 value 86.967584
iter 40 value 86.234062
iter 50 value 81.313703
iter 60 value 80.605348
iter 70 value 80.276121
iter 80 value 79.859752
iter 90 value 79.758565
iter 100 value 79.625208
final value 79.625208
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.248970
iter 10 value 94.611031
iter 20 value 94.006549
iter 30 value 86.531958
iter 40 value 85.437278
iter 50 value 84.217221
iter 60 value 82.040525
iter 70 value 80.382034
iter 80 value 79.812375
iter 90 value 79.291356
iter 100 value 79.214205
final value 79.214205
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.438602
iter 10 value 94.424246
iter 20 value 93.449371
iter 30 value 84.702819
iter 40 value 84.173004
iter 50 value 82.355254
iter 60 value 81.454786
iter 70 value 81.049481
iter 80 value 80.720937
iter 90 value 80.652580
iter 100 value 80.631831
final value 80.631831
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.007268
iter 10 value 96.600744
iter 20 value 92.489450
iter 30 value 85.102135
iter 40 value 84.938457
iter 50 value 84.396226
iter 60 value 83.066470
iter 70 value 80.329922
iter 80 value 79.716261
iter 90 value 79.617674
iter 100 value 79.383607
final value 79.383607
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.950251
iter 10 value 94.625487
iter 20 value 86.634381
iter 30 value 84.393834
iter 40 value 81.819077
iter 50 value 81.176469
iter 60 value 80.425860
iter 70 value 80.150657
iter 80 value 80.022218
iter 90 value 79.887217
iter 100 value 79.626107
final value 79.626107
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.173995
iter 10 value 95.602275
iter 20 value 94.161885
iter 30 value 86.621346
iter 40 value 85.353184
iter 50 value 83.481504
iter 60 value 83.199872
iter 70 value 81.685441
iter 80 value 81.389585
iter 90 value 81.189076
iter 100 value 80.974496
final value 80.974496
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.698475
final value 93.301979
converged
Fitting Repeat 2
# weights: 103
initial value 95.990950
final value 94.486167
converged
Fitting Repeat 3
# weights: 103
initial value 106.008769
iter 10 value 94.486069
final value 94.484237
converged
Fitting Repeat 4
# weights: 103
initial value 94.809110
iter 10 value 92.588984
iter 20 value 92.574522
iter 30 value 92.574391
final value 92.574154
converged
Fitting Repeat 5
# weights: 103
initial value 101.330954
final value 94.485705
converged
Fitting Repeat 1
# weights: 305
initial value 101.893822
iter 10 value 94.031319
iter 20 value 94.009715
iter 30 value 88.983711
final value 88.912594
converged
Fitting Repeat 2
# weights: 305
initial value 103.083403
iter 10 value 94.488256
iter 20 value 93.051498
iter 30 value 86.048813
iter 40 value 85.263050
iter 50 value 84.756999
iter 60 value 84.204990
final value 84.173244
converged
Fitting Repeat 3
# weights: 305
initial value 99.521946
iter 10 value 92.172491
iter 20 value 84.339399
iter 30 value 84.225349
iter 40 value 84.224579
iter 50 value 84.222651
iter 60 value 83.282759
iter 70 value 81.454718
iter 80 value 80.581370
iter 90 value 80.580603
final value 80.580442
converged
Fitting Repeat 4
# weights: 305
initial value 95.681848
iter 10 value 94.489175
iter 20 value 94.484223
final value 94.484217
converged
Fitting Repeat 5
# weights: 305
initial value 95.937951
iter 10 value 93.077220
iter 20 value 83.511281
iter 30 value 82.776032
iter 40 value 82.775042
final value 82.773912
converged
Fitting Repeat 1
# weights: 507
initial value 106.811631
iter 10 value 94.493122
iter 20 value 94.484539
iter 30 value 94.023065
iter 40 value 92.373226
iter 50 value 88.337405
iter 60 value 88.324185
iter 70 value 88.320512
iter 80 value 88.319845
iter 90 value 88.318820
iter 100 value 87.545037
final value 87.545037
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 99.983425
iter 10 value 94.491939
iter 20 value 94.484236
final value 94.484232
converged
Fitting Repeat 3
# weights: 507
initial value 95.979431
iter 10 value 90.720064
iter 20 value 88.428193
iter 30 value 88.427262
iter 40 value 88.425001
iter 50 value 88.421486
iter 60 value 86.595900
iter 70 value 79.785498
iter 80 value 79.421064
iter 90 value 79.311832
iter 100 value 79.190672
final value 79.190672
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.347800
iter 10 value 94.400419
iter 20 value 94.037222
iter 30 value 94.034733
iter 40 value 94.029093
iter 50 value 94.027755
iter 60 value 93.717305
iter 70 value 90.753669
iter 80 value 89.748214
iter 90 value 89.707851
iter 100 value 89.706044
final value 89.706044
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.337315
iter 10 value 94.035550
iter 20 value 94.032451
iter 30 value 94.031592
final value 94.031577
converged
Fitting Repeat 1
# weights: 103
initial value 106.389222
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 102.829863
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 105.247461
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.903646
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 112.553709
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 96.567149
iter 10 value 91.190406
iter 20 value 91.158566
iter 30 value 91.158462
final value 91.158461
converged
Fitting Repeat 2
# weights: 305
initial value 109.906872
iter 10 value 89.230097
iter 20 value 87.936711
final value 87.936688
converged
Fitting Repeat 3
# weights: 305
initial value 103.387650
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 98.117433
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 113.961763
iter 10 value 93.141328
iter 20 value 87.686379
iter 30 value 85.689386
iter 40 value 84.214521
final value 84.114374
converged
Fitting Repeat 1
# weights: 507
initial value 100.284998
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 98.394846
iter 10 value 93.868542
final value 91.683261
converged
Fitting Repeat 3
# weights: 507
initial value 102.458704
final value 94.484210
converged
Fitting Repeat 4
# weights: 507
initial value 99.401515
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 116.227046
iter 10 value 93.885022
iter 20 value 87.397150
iter 30 value 82.159169
iter 40 value 80.591580
iter 50 value 80.416189
final value 80.416055
converged
Fitting Repeat 1
# weights: 103
initial value 101.539633
iter 10 value 94.492171
iter 20 value 94.173930
iter 30 value 89.288057
iter 40 value 86.139322
iter 50 value 83.673516
iter 60 value 83.192847
iter 70 value 82.428159
iter 80 value 82.270162
iter 90 value 81.962520
iter 100 value 81.779084
final value 81.779084
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.175287
iter 10 value 94.480201
iter 20 value 87.185457
iter 30 value 86.317596
iter 40 value 86.134067
iter 50 value 85.068975
iter 60 value 84.180059
iter 70 value 84.024649
iter 80 value 83.972707
final value 83.971800
converged
Fitting Repeat 3
# weights: 103
initial value 96.859506
iter 10 value 94.488294
iter 20 value 86.259988
iter 30 value 84.965107
iter 40 value 84.914171
iter 50 value 84.674288
iter 60 value 84.394097
iter 70 value 84.352588
iter 80 value 84.345185
final value 84.345172
converged
Fitting Repeat 4
# weights: 103
initial value 96.101159
iter 10 value 94.486470
iter 10 value 94.486469
iter 20 value 91.063625
iter 30 value 87.828094
iter 40 value 86.923123
iter 50 value 84.736299
iter 60 value 84.357829
iter 70 value 84.351475
iter 80 value 84.345190
final value 84.345172
converged
Fitting Repeat 5
# weights: 103
initial value 96.360293
iter 10 value 94.486625
iter 20 value 94.486461
iter 30 value 88.342843
iter 40 value 85.944017
iter 50 value 84.646212
iter 60 value 84.156300
iter 70 value 84.017257
iter 80 value 83.990617
iter 80 value 83.990616
iter 80 value 83.990616
final value 83.990616
converged
Fitting Repeat 1
# weights: 305
initial value 101.253662
iter 10 value 94.525471
iter 20 value 94.456830
iter 30 value 94.195041
iter 40 value 92.120590
iter 50 value 83.921447
iter 60 value 82.967666
iter 70 value 81.921434
iter 80 value 81.299488
iter 90 value 81.274216
iter 100 value 81.200733
final value 81.200733
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.858257
iter 10 value 94.842951
iter 20 value 94.482645
iter 30 value 93.435795
iter 40 value 92.906610
iter 50 value 85.293033
iter 60 value 84.399290
iter 70 value 83.408798
iter 80 value 83.175073
iter 90 value 82.866818
iter 100 value 81.799116
final value 81.799116
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.956651
iter 10 value 94.615778
iter 20 value 85.142313
iter 30 value 84.230709
iter 40 value 82.790913
iter 50 value 81.748458
iter 60 value 81.347690
iter 70 value 81.026354
iter 80 value 80.911752
iter 90 value 80.863302
iter 100 value 80.850697
final value 80.850697
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.949260
iter 10 value 94.050186
iter 20 value 87.358983
iter 30 value 85.200753
iter 40 value 84.497564
iter 50 value 84.331821
iter 60 value 84.191222
iter 70 value 84.152317
iter 80 value 84.084912
iter 90 value 82.490501
iter 100 value 81.835193
final value 81.835193
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.899281
iter 10 value 94.357547
iter 20 value 88.271833
iter 30 value 85.041425
iter 40 value 84.307493
iter 50 value 83.103124
iter 60 value 82.292595
iter 70 value 81.951952
iter 80 value 81.840319
iter 90 value 81.654882
iter 100 value 81.639107
final value 81.639107
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.000125
iter 10 value 94.471506
iter 20 value 92.587439
iter 30 value 89.627984
iter 40 value 85.543597
iter 50 value 83.433664
iter 60 value 82.282627
iter 70 value 81.709805
iter 80 value 81.476137
iter 90 value 81.204068
iter 100 value 81.011208
final value 81.011208
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.679382
iter 10 value 94.527195
iter 20 value 86.210503
iter 30 value 85.091164
iter 40 value 84.767263
iter 50 value 83.470715
iter 60 value 82.681742
iter 70 value 81.490433
iter 80 value 80.901513
iter 90 value 80.671160
iter 100 value 80.643572
final value 80.643572
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.830110
iter 10 value 94.776401
iter 20 value 94.209213
iter 30 value 88.137997
iter 40 value 85.652167
iter 50 value 85.318927
iter 60 value 84.505603
iter 70 value 83.493741
iter 80 value 83.402543
iter 90 value 82.846610
iter 100 value 82.341480
final value 82.341480
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.701845
iter 10 value 94.522913
iter 20 value 88.530073
iter 30 value 85.739714
iter 40 value 83.565560
iter 50 value 82.999624
iter 60 value 82.517120
iter 70 value 82.157685
iter 80 value 81.895478
iter 90 value 81.211973
iter 100 value 80.954976
final value 80.954976
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.336512
iter 10 value 93.789691
iter 20 value 85.692718
iter 30 value 85.340507
iter 40 value 84.968402
iter 50 value 84.610662
iter 60 value 83.080936
iter 70 value 81.762420
iter 80 value 81.439359
iter 90 value 80.506250
iter 100 value 80.342879
final value 80.342879
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.894346
iter 10 value 94.485859
iter 20 value 94.483504
iter 30 value 84.218980
iter 40 value 82.387340
iter 50 value 82.289412
iter 60 value 81.679132
iter 70 value 81.425721
iter 80 value 81.425134
final value 81.424613
converged
Fitting Repeat 2
# weights: 103
initial value 97.756190
final value 94.485818
converged
Fitting Repeat 3
# weights: 103
initial value 102.338349
final value 94.485808
converged
Fitting Repeat 4
# weights: 103
initial value 94.723749
final value 94.485853
converged
Fitting Repeat 5
# weights: 103
initial value 102.193936
iter 10 value 94.485917
iter 20 value 94.484214
iter 30 value 94.145982
iter 40 value 91.963072
iter 40 value 91.963071
iter 40 value 91.963071
final value 91.963071
converged
Fitting Repeat 1
# weights: 305
initial value 99.432047
iter 10 value 94.488527
iter 20 value 94.483951
iter 30 value 94.214089
final value 94.214077
converged
Fitting Repeat 2
# weights: 305
initial value 100.018016
iter 10 value 94.488595
iter 20 value 94.466414
iter 30 value 89.547645
iter 40 value 88.390037
iter 50 value 85.739526
iter 60 value 85.621834
iter 70 value 84.893708
iter 80 value 84.858746
iter 90 value 84.850884
iter 100 value 84.842432
final value 84.842432
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 96.941238
iter 10 value 94.263347
iter 20 value 94.217188
iter 30 value 94.214652
iter 40 value 89.269897
iter 50 value 89.229410
iter 60 value 89.227995
iter 70 value 89.179357
iter 80 value 87.813356
iter 90 value 87.770978
iter 100 value 87.770381
final value 87.770381
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 94.855985
iter 10 value 93.150679
iter 20 value 93.115666
iter 30 value 93.054636
iter 40 value 90.638632
iter 50 value 90.334646
final value 90.334563
converged
Fitting Repeat 5
# weights: 305
initial value 103.580560
iter 10 value 94.480504
iter 20 value 94.434114
iter 30 value 94.429461
final value 94.428916
converged
Fitting Repeat 1
# weights: 507
initial value 99.435299
iter 10 value 94.492717
iter 20 value 94.433607
iter 30 value 89.183432
iter 40 value 88.686361
iter 50 value 81.829890
iter 60 value 81.273161
iter 70 value 81.235463
iter 80 value 81.138875
iter 90 value 81.131960
iter 100 value 81.127371
final value 81.127371
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 99.185770
iter 10 value 93.487379
iter 20 value 93.302301
iter 30 value 86.460005
iter 40 value 86.458428
iter 50 value 86.456945
iter 60 value 86.455028
iter 70 value 86.453414
iter 80 value 86.452974
iter 90 value 86.444007
iter 100 value 86.443407
final value 86.443407
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 98.372462
iter 10 value 89.857681
iter 20 value 86.025455
iter 30 value 83.861558
iter 40 value 83.671387
final value 83.671220
converged
Fitting Repeat 4
# weights: 507
initial value 113.114405
iter 10 value 94.417873
iter 20 value 90.005362
iter 30 value 86.768780
iter 40 value 83.815841
final value 83.815594
converged
Fitting Repeat 5
# weights: 507
initial value 100.774417
iter 10 value 94.475049
iter 20 value 93.787155
iter 30 value 84.722626
iter 40 value 83.531085
iter 50 value 83.500301
iter 60 value 83.461860
iter 70 value 83.457039
iter 80 value 83.013950
iter 90 value 81.498281
iter 100 value 81.135063
final value 81.135063
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 126.188927
iter 10 value 117.898252
iter 20 value 117.715471
iter 30 value 114.333667
iter 40 value 114.327047
final value 114.326748
converged
Fitting Repeat 2
# weights: 507
initial value 119.651775
iter 10 value 117.213558
iter 20 value 117.208458
final value 117.208381
converged
Fitting Repeat 3
# weights: 507
initial value 126.929213
iter 10 value 117.698780
iter 20 value 117.602407
iter 30 value 117.542995
iter 40 value 117.542458
iter 50 value 117.471253
iter 60 value 117.469867
iter 70 value 106.764390
iter 80 value 102.094761
iter 90 value 101.611142
iter 100 value 101.460599
final value 101.460599
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 152.752782
iter 10 value 117.898472
iter 20 value 117.881632
iter 30 value 117.553830
iter 40 value 109.489729
iter 50 value 107.459760
iter 60 value 106.626976
iter 70 value 105.239108
iter 80 value 104.893282
iter 90 value 104.891930
iter 100 value 104.877830
final value 104.877830
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 133.670407
iter 10 value 117.892168
iter 20 value 117.798801
iter 30 value 117.209055
iter 40 value 115.709939
final value 113.781513
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Tue Dec 24 01:44:48 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
42.93 1.32 58.29
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 34.25 | 1.78 | 36.14 | |
| FreqInteractors | 0.34 | 0.02 | 0.39 | |
| calculateAAC | 0.03 | 0.01 | 0.05 | |
| calculateAutocor | 0.36 | 0.09 | 0.45 | |
| calculateCTDC | 0.09 | 0.00 | 0.10 | |
| calculateCTDD | 0.61 | 0.07 | 0.67 | |
| calculateCTDT | 0.33 | 0.01 | 0.34 | |
| calculateCTriad | 0.42 | 0.00 | 0.42 | |
| calculateDC | 0.12 | 0.02 | 0.14 | |
| calculateF | 0.44 | 0.00 | 0.44 | |
| calculateKSAAP | 0.1 | 0.0 | 0.1 | |
| calculateQD_Sm | 2.23 | 0.20 | 2.43 | |
| calculateTC | 1.91 | 0.13 | 2.03 | |
| calculateTC_Sm | 0.25 | 0.07 | 0.33 | |
| corr_plot | 32.06 | 1.46 | 33.53 | |
| enrichfindP | 0.61 | 0.09 | 13.43 | |
| enrichfind_hp | 0.05 | 0.02 | 1.01 | |
| enrichplot | 0.37 | 0.01 | 0.39 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.00 | 0.03 | 1.95 | |
| getHPI | 0.02 | 0.00 | 0.02 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.11 | 0.00 | 0.16 | |
| pred_ensembel | 14.14 | 0.39 | 13.04 | |
| var_imp | 34.81 | 1.32 | 36.13 | |