Matineh Rahmatbakhsh
| Snapshot Date: 2024-06-02 14:00:17 -0400 (Sun, 02 Jun 2024) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_19 |
| git_last_commit: 09dc3c1 |
| git_last_commit_date: 2024-04-30 11:37:16 -0400 (Tue, 30 Apr 2024) |
| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-06-04 11:35:50 -0400 (Tue, 04 Jun 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4753 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" | 4487 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4518 |
| 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 987/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.10.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | 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: 1.10.0 |
| Command: F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz |
| StartedAt: 2024-06-03 02:26:12 -0400 (Mon, 03 Jun 2024) |
| EndedAt: 2024-06-03 02:30:56 -0400 (Mon, 03 Jun 2024) |
| EllapsedTime: 283.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck'
* using R version 4.4.0 (2024-04-24 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 '1.10.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
var_imp 32.93 1.21 34.20
corr_plot 30.55 1.83 32.39
FSmethod 29.68 1.91 31.73
pred_ensembel 14.19 0.67 11.00
enrichfindP 0.53 0.05 13.50
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 3 NOTEs
See
'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.19-bioc/R/library' * installing *source* package 'HPiP' ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup"
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 100.045925
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.911054
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.720361
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.741903
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.721702
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 113.975307
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 96.473921
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 101.429677
iter 10 value 94.159657
iter 20 value 94.132576
iter 20 value 94.132576
iter 20 value 94.132576
final value 94.132576
converged
Fitting Repeat 4
# weights: 305
initial value 112.370106
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 101.938101
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 111.630546
final value 94.275362
converged
Fitting Repeat 2
# weights: 507
initial value 109.687534
iter 10 value 94.158871
final value 94.105596
converged
Fitting Repeat 3
# weights: 507
initial value 95.969667
iter 10 value 94.295041
iter 20 value 94.291302
final value 94.291298
converged
Fitting Repeat 4
# weights: 507
initial value 105.103925
iter 10 value 94.082942
final value 94.082834
converged
Fitting Repeat 5
# weights: 507
initial value 111.209933
iter 10 value 94.275363
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 1
# weights: 103
initial value 111.579763
iter 10 value 94.256182
iter 20 value 89.009148
iter 30 value 83.437899
iter 40 value 83.131402
iter 50 value 81.416905
iter 60 value 81.017425
iter 70 value 80.811709
iter 80 value 80.803852
final value 80.803808
converged
Fitting Repeat 2
# weights: 103
initial value 96.701563
iter 10 value 94.388964
iter 20 value 91.707191
iter 30 value 86.469566
iter 40 value 82.977325
iter 50 value 82.627240
iter 60 value 82.622962
iter 60 value 82.622962
iter 60 value 82.622962
final value 82.622962
converged
Fitting Repeat 3
# weights: 103
initial value 118.359922
iter 10 value 93.906110
iter 20 value 87.736527
iter 30 value 87.408493
iter 40 value 86.362804
iter 50 value 84.906765
iter 60 value 84.857589
iter 70 value 84.855906
iter 80 value 83.945147
iter 90 value 82.098927
iter 100 value 81.479097
final value 81.479097
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.645244
iter 10 value 94.408221
iter 20 value 85.702143
iter 30 value 84.345652
iter 40 value 83.584221
iter 50 value 83.304779
iter 60 value 83.166897
iter 70 value 83.127000
final value 83.126994
converged
Fitting Repeat 5
# weights: 103
initial value 101.619129
iter 10 value 94.488554
iter 20 value 93.874907
iter 30 value 85.534406
iter 40 value 83.859725
iter 50 value 83.020600
iter 60 value 82.783323
iter 70 value 82.655228
iter 80 value 82.623575
final value 82.622962
converged
Fitting Repeat 1
# weights: 305
initial value 101.845457
iter 10 value 94.575703
iter 20 value 89.804487
iter 30 value 88.610006
iter 40 value 86.976583
iter 50 value 84.111177
iter 60 value 83.781190
iter 70 value 83.327850
iter 80 value 82.739681
iter 90 value 81.180805
iter 100 value 80.023688
final value 80.023688
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.875620
iter 10 value 94.201057
iter 20 value 86.339311
iter 30 value 84.064052
iter 40 value 82.005605
iter 50 value 81.154314
iter 60 value 80.534364
iter 70 value 80.306182
iter 80 value 80.233965
iter 90 value 80.179993
iter 100 value 80.046483
final value 80.046483
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.294166
iter 10 value 95.237655
iter 20 value 94.453170
iter 30 value 89.315010
iter 40 value 88.266133
iter 50 value 87.493923
iter 60 value 86.496067
iter 70 value 84.959876
iter 80 value 84.726610
iter 90 value 83.702542
iter 100 value 83.136578
final value 83.136578
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.788555
iter 10 value 94.404130
iter 20 value 91.602537
iter 30 value 90.874088
iter 40 value 89.631202
iter 50 value 82.198367
iter 60 value 80.517660
iter 70 value 80.232470
iter 80 value 80.217137
iter 90 value 80.201359
iter 100 value 80.198320
final value 80.198320
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.054906
iter 10 value 94.475502
iter 20 value 84.521842
iter 30 value 83.231310
iter 40 value 80.474935
iter 50 value 79.996947
iter 60 value 79.891746
iter 70 value 79.761871
iter 80 value 79.639684
iter 90 value 79.501554
iter 100 value 79.438666
final value 79.438666
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.364332
iter 10 value 94.361517
iter 20 value 94.204154
iter 30 value 92.778689
iter 40 value 86.654741
iter 50 value 84.310786
iter 60 value 82.626395
iter 70 value 80.995671
iter 80 value 80.044657
iter 90 value 79.626325
iter 100 value 79.341034
final value 79.341034
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 119.968690
iter 10 value 94.460071
iter 20 value 91.588634
iter 30 value 85.435522
iter 40 value 82.478248
iter 50 value 82.006957
iter 60 value 81.288629
iter 70 value 80.615316
iter 80 value 79.661525
iter 90 value 79.557239
iter 100 value 79.471684
final value 79.471684
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 116.742549
iter 10 value 94.615821
iter 20 value 89.981098
iter 30 value 84.894047
iter 40 value 82.370176
iter 50 value 81.021556
iter 60 value 80.785568
iter 70 value 80.538046
iter 80 value 80.363658
iter 90 value 80.331565
iter 100 value 80.268489
final value 80.268489
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.791154
iter 10 value 90.089790
iter 20 value 87.492537
iter 30 value 83.104072
iter 40 value 81.823649
iter 50 value 81.033615
iter 60 value 80.308188
iter 70 value 79.634662
iter 80 value 79.402653
iter 90 value 79.243982
iter 100 value 79.032356
final value 79.032356
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.021413
iter 10 value 94.018480
iter 20 value 91.059942
iter 30 value 88.961857
iter 40 value 84.998043
iter 50 value 83.259917
iter 60 value 82.418369
iter 70 value 81.142556
iter 80 value 79.892416
iter 90 value 79.504611
iter 100 value 79.232747
final value 79.232747
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.531714
final value 94.485806
converged
Fitting Repeat 2
# weights: 103
initial value 99.203380
iter 10 value 93.226414
iter 20 value 93.223120
iter 30 value 92.059624
iter 40 value 91.919891
final value 91.919452
converged
Fitting Repeat 3
# weights: 103
initial value 101.369050
final value 94.486087
converged
Fitting Repeat 4
# weights: 103
initial value 95.559971
final value 94.485856
converged
Fitting Repeat 5
# weights: 103
initial value 96.440323
final value 94.485585
converged
Fitting Repeat 1
# weights: 305
initial value 100.563047
iter 10 value 94.280802
iter 20 value 94.276332
iter 30 value 94.111533
iter 40 value 85.647343
iter 50 value 85.435353
iter 60 value 85.434368
final value 85.434100
converged
Fitting Repeat 2
# weights: 305
initial value 100.118529
iter 10 value 94.279602
iter 20 value 94.244901
iter 30 value 94.233286
iter 40 value 94.228985
iter 50 value 93.034084
iter 60 value 88.560420
iter 70 value 86.065601
iter 80 value 81.956062
iter 90 value 81.551372
iter 100 value 81.302770
final value 81.302770
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 96.879649
iter 10 value 94.484416
iter 20 value 86.530495
iter 30 value 81.871869
iter 40 value 81.771921
iter 50 value 81.729674
iter 60 value 81.716639
iter 70 value 81.692783
iter 80 value 81.690582
iter 90 value 81.690486
iter 100 value 81.690330
final value 81.690330
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 115.363939
iter 10 value 94.280034
iter 20 value 94.276038
final value 94.275707
converged
Fitting Repeat 5
# weights: 305
initial value 114.711477
iter 10 value 94.489517
iter 20 value 94.484209
iter 30 value 92.106565
iter 40 value 88.937624
iter 50 value 88.098004
iter 60 value 87.866934
iter 70 value 87.866370
iter 80 value 85.364845
iter 90 value 81.798127
iter 100 value 81.731083
final value 81.731083
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.230677
iter 10 value 94.291632
iter 20 value 94.261894
iter 30 value 94.257761
iter 40 value 94.254774
final value 94.254544
converged
Fitting Repeat 2
# weights: 507
initial value 101.687872
iter 10 value 94.141190
iter 20 value 94.135024
iter 30 value 93.713433
iter 40 value 88.587669
iter 50 value 84.149401
iter 60 value 84.145377
iter 70 value 84.144292
iter 80 value 84.144000
final value 84.143994
converged
Fitting Repeat 3
# weights: 507
initial value 108.722001
iter 10 value 94.449548
iter 20 value 94.399323
iter 30 value 94.391401
iter 40 value 94.390618
iter 50 value 93.957092
iter 60 value 83.609748
iter 70 value 83.453854
iter 80 value 83.428838
iter 90 value 83.387031
iter 100 value 83.329574
final value 83.329574
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.625132
iter 10 value 91.092524
iter 20 value 91.074017
iter 30 value 91.064490
iter 40 value 90.993214
iter 50 value 90.991134
iter 60 value 90.736057
iter 70 value 89.723507
iter 80 value 89.718296
iter 90 value 89.718173
iter 100 value 89.717467
final value 89.717467
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.080093
iter 10 value 94.152914
iter 20 value 94.138101
iter 30 value 94.135456
iter 40 value 94.098351
iter 50 value 88.119390
iter 60 value 81.916736
iter 70 value 81.682732
iter 80 value 81.674110
iter 80 value 81.674109
final value 81.674109
converged
Fitting Repeat 1
# weights: 103
initial value 99.552925
iter 10 value 93.395676
final value 93.394928
converged
Fitting Repeat 2
# weights: 103
initial value 100.444969
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.835763
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.276320
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.487684
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 96.569464
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 96.423391
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 109.450787
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 102.258934
iter 10 value 93.499178
iter 20 value 93.007719
final value 93.007577
converged
Fitting Repeat 5
# weights: 305
initial value 103.762152
iter 10 value 93.803052
final value 93.783647
converged
Fitting Repeat 1
# weights: 507
initial value 112.962309
iter 10 value 93.395171
final value 93.394928
converged
Fitting Repeat 2
# weights: 507
initial value 101.599063
iter 10 value 93.394936
final value 93.394928
converged
Fitting Repeat 3
# weights: 507
initial value 96.427018
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 103.242388
iter 10 value 93.334648
iter 20 value 91.937234
iter 30 value 86.634213
iter 40 value 82.240342
iter 50 value 82.191860
iter 60 value 82.043268
iter 70 value 82.038227
iter 70 value 82.038227
iter 70 value 82.038227
final value 82.038227
converged
Fitting Repeat 5
# weights: 507
initial value 105.916644
iter 10 value 93.143908
final value 93.133332
converged
Fitting Repeat 1
# weights: 103
initial value 97.931554
final value 94.488533
converged
Fitting Repeat 2
# weights: 103
initial value 107.954085
iter 10 value 94.281781
iter 20 value 93.572006
iter 30 value 87.928378
iter 40 value 86.477409
iter 50 value 86.089102
iter 60 value 82.216324
iter 70 value 81.021618
final value 81.020574
converged
Fitting Repeat 3
# weights: 103
initial value 96.314941
iter 10 value 93.328709
iter 20 value 89.677398
iter 30 value 84.277085
iter 40 value 83.341341
iter 50 value 82.235581
iter 60 value 81.732379
iter 70 value 81.235919
iter 80 value 81.024064
iter 90 value 81.020603
final value 81.020573
converged
Fitting Repeat 4
# weights: 103
initial value 105.718033
iter 10 value 94.489468
iter 20 value 93.615850
iter 30 value 92.398098
iter 40 value 87.794572
iter 50 value 86.365504
iter 60 value 84.431636
iter 70 value 83.157455
iter 80 value 82.286882
iter 90 value 81.229447
iter 100 value 81.021092
final value 81.021092
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 105.718132
iter 10 value 94.411627
iter 20 value 89.836770
iter 30 value 89.353478
iter 40 value 89.317481
iter 50 value 87.549967
iter 60 value 86.706255
iter 70 value 85.370229
iter 80 value 81.801948
iter 90 value 81.665453
iter 100 value 81.490731
final value 81.490731
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 100.120112
iter 10 value 94.523960
iter 20 value 93.853056
iter 30 value 86.033481
iter 40 value 83.045384
iter 50 value 82.710712
iter 60 value 82.400713
iter 70 value 80.878119
iter 80 value 80.298400
iter 90 value 79.997010
iter 100 value 79.792417
final value 79.792417
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 125.966628
iter 10 value 94.524540
iter 20 value 93.713107
iter 30 value 93.433125
iter 40 value 85.976138
iter 50 value 81.861015
iter 60 value 80.984902
iter 70 value 80.818089
iter 80 value 80.265872
iter 90 value 79.717461
iter 100 value 79.636807
final value 79.636807
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 127.812253
iter 10 value 94.555774
iter 20 value 93.654686
iter 30 value 91.413003
iter 40 value 85.299923
iter 50 value 84.529681
iter 60 value 83.744525
iter 70 value 82.452810
iter 80 value 80.262310
iter 90 value 79.806202
iter 100 value 79.634766
final value 79.634766
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.752998
iter 10 value 94.815586
iter 20 value 92.869284
iter 30 value 84.812327
iter 40 value 84.440070
iter 50 value 84.341445
iter 60 value 83.161551
iter 70 value 81.378392
iter 80 value 80.403777
iter 90 value 80.292043
iter 100 value 80.252107
final value 80.252107
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 122.731375
iter 10 value 94.619512
iter 20 value 86.416420
iter 30 value 84.211076
iter 40 value 83.791389
iter 50 value 83.575843
iter 60 value 83.470249
iter 70 value 82.708788
iter 80 value 81.237778
iter 90 value 80.725033
iter 100 value 80.458491
final value 80.458491
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.249247
iter 10 value 94.381963
iter 20 value 93.142668
iter 30 value 89.899277
iter 40 value 83.613957
iter 50 value 81.435926
iter 60 value 80.666963
iter 70 value 80.561765
iter 80 value 80.178083
iter 90 value 79.780036
iter 100 value 79.219450
final value 79.219450
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 117.414317
iter 10 value 93.724012
iter 20 value 87.313288
iter 30 value 86.098471
iter 40 value 84.315143
iter 50 value 82.787523
iter 60 value 81.536401
iter 70 value 80.663521
iter 80 value 79.915753
iter 90 value 79.533113
iter 100 value 79.271570
final value 79.271570
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.470395
iter 10 value 96.532806
iter 20 value 87.212803
iter 30 value 83.592863
iter 40 value 81.468398
iter 50 value 80.815119
iter 60 value 79.817414
iter 70 value 79.578823
iter 80 value 79.524629
iter 90 value 79.366962
iter 100 value 79.305767
final value 79.305767
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 132.797797
iter 10 value 101.480246
iter 20 value 100.593856
iter 30 value 91.389551
iter 40 value 88.298580
iter 50 value 83.164543
iter 60 value 80.469228
iter 70 value 80.014002
iter 80 value 79.755882
iter 90 value 79.719275
iter 100 value 79.616685
final value 79.616685
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 111.400269
iter 10 value 93.932643
iter 20 value 84.585960
iter 30 value 83.892487
iter 40 value 83.383304
iter 50 value 83.022456
iter 60 value 82.792318
iter 70 value 80.840849
iter 80 value 80.046177
iter 90 value 79.728655
iter 100 value 79.576616
final value 79.576616
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.748490
iter 10 value 94.486038
iter 20 value 94.484218
iter 30 value 94.113968
iter 40 value 93.389811
iter 50 value 93.316498
iter 60 value 93.273714
final value 93.272394
converged
Fitting Repeat 2
# weights: 103
initial value 97.872148
final value 94.486103
converged
Fitting Repeat 3
# weights: 103
initial value 95.247517
final value 94.485819
converged
Fitting Repeat 4
# weights: 103
initial value 106.912131
final value 94.485851
converged
Fitting Repeat 5
# weights: 103
initial value 95.562241
final value 94.485617
converged
Fitting Repeat 1
# weights: 305
initial value 100.622017
iter 10 value 94.488920
iter 20 value 94.484663
final value 94.484638
converged
Fitting Repeat 2
# weights: 305
initial value 97.259747
iter 10 value 93.398232
iter 20 value 93.397225
iter 30 value 92.451340
final value 92.363886
converged
Fitting Repeat 3
# weights: 305
initial value 94.836523
iter 10 value 94.489102
iter 20 value 94.476370
iter 30 value 88.425814
final value 88.420536
converged
Fitting Repeat 4
# weights: 305
initial value 94.583714
iter 10 value 94.488834
iter 20 value 93.974031
iter 30 value 85.186009
iter 40 value 83.797463
iter 50 value 83.788417
iter 60 value 83.554784
iter 70 value 83.049898
iter 80 value 82.216030
iter 90 value 81.506376
iter 100 value 81.080700
final value 81.080700
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 115.604991
iter 10 value 94.488194
iter 20 value 88.969248
iter 30 value 83.791440
iter 40 value 82.596156
iter 50 value 82.592651
final value 82.592641
converged
Fitting Repeat 1
# weights: 507
initial value 96.998558
iter 10 value 91.966916
iter 20 value 91.627438
iter 30 value 91.606554
iter 40 value 91.604868
iter 50 value 91.599875
final value 91.599706
converged
Fitting Repeat 2
# weights: 507
initial value 105.466243
iter 10 value 94.492631
iter 20 value 94.484946
iter 30 value 93.599635
iter 40 value 83.959881
iter 50 value 83.958053
iter 60 value 83.957448
final value 83.957007
converged
Fitting Repeat 3
# weights: 507
initial value 98.418437
iter 10 value 93.791885
iter 20 value 93.074963
iter 30 value 93.072760
iter 40 value 92.211699
iter 50 value 91.906687
iter 60 value 91.891546
iter 70 value 91.886950
iter 80 value 91.353246
iter 90 value 91.265990
final value 91.265988
converged
Fitting Repeat 4
# weights: 507
initial value 110.099944
iter 10 value 92.581141
iter 20 value 83.747838
iter 30 value 83.738725
iter 40 value 83.465296
iter 50 value 83.451459
iter 60 value 83.448020
iter 70 value 83.323071
iter 80 value 83.235662
iter 90 value 83.107005
iter 100 value 83.053197
final value 83.053197
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 110.123783
iter 10 value 94.492542
iter 20 value 94.267083
iter 30 value 91.571992
iter 40 value 89.309945
iter 50 value 89.259576
iter 60 value 89.253294
iter 60 value 89.253293
final value 89.253293
converged
Fitting Repeat 1
# weights: 103
initial value 95.784796
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 97.891158
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 94.071057
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 104.113739
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.726886
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 98.048695
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 94.848562
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 117.119704
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 99.184919
iter 10 value 94.032969
final value 94.032967
converged
Fitting Repeat 5
# weights: 305
initial value 95.561494
final value 94.000000
converged
Fitting Repeat 1
# weights: 507
initial value 108.096716
final value 94.000000
converged
Fitting Repeat 2
# weights: 507
initial value 99.053367
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 96.887026
iter 10 value 94.032967
iter 10 value 94.032967
iter 10 value 94.032967
final value 94.032967
converged
Fitting Repeat 4
# weights: 507
initial value 107.756097
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 126.478651
iter 10 value 94.032967
iter 10 value 94.032967
iter 10 value 94.032967
final value 94.032967
converged
Fitting Repeat 1
# weights: 103
initial value 95.665663
iter 10 value 94.046923
iter 20 value 89.750822
iter 30 value 87.984382
iter 40 value 87.251497
iter 50 value 87.158348
iter 60 value 87.043596
iter 70 value 86.710658
iter 80 value 86.617304
iter 90 value 84.291466
iter 100 value 83.890189
final value 83.890189
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 99.750969
iter 10 value 94.055347
iter 20 value 94.008971
iter 30 value 87.568170
iter 40 value 85.823759
iter 50 value 84.732745
iter 60 value 84.069009
iter 70 value 83.755089
iter 80 value 83.726410
iter 90 value 83.715319
iter 100 value 83.703389
final value 83.703389
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.504339
iter 10 value 94.058572
iter 20 value 93.991397
iter 30 value 85.695540
iter 40 value 85.141894
iter 50 value 84.456322
iter 60 value 83.838289
iter 70 value 83.594161
iter 80 value 83.521392
final value 83.521271
converged
Fitting Repeat 4
# weights: 103
initial value 98.233062
iter 10 value 93.451969
iter 20 value 86.360693
iter 30 value 84.759026
iter 40 value 83.834278
iter 50 value 83.765543
iter 60 value 82.583490
iter 70 value 82.284757
iter 80 value 81.982842
iter 90 value 81.854065
iter 100 value 81.805356
final value 81.805356
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 103.720958
iter 10 value 94.055366
iter 20 value 93.892646
iter 30 value 85.730449
iter 40 value 85.153101
iter 50 value 84.755743
iter 60 value 83.792555
iter 70 value 83.767619
iter 80 value 83.719572
final value 83.713115
converged
Fitting Repeat 1
# weights: 305
initial value 100.555297
iter 10 value 93.577953
iter 20 value 89.861136
iter 30 value 86.367500
iter 40 value 84.163393
iter 50 value 83.446394
iter 60 value 83.289793
iter 70 value 82.886059
iter 80 value 82.360936
iter 90 value 82.192640
iter 100 value 81.655540
final value 81.655540
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.223350
iter 10 value 94.175826
iter 20 value 93.982560
iter 30 value 88.235435
iter 40 value 86.564942
iter 50 value 85.656864
iter 60 value 85.096097
iter 70 value 82.813477
iter 80 value 81.409064
iter 90 value 81.263976
iter 100 value 81.019704
final value 81.019704
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 124.265680
iter 10 value 98.675027
iter 20 value 95.839784
iter 30 value 92.813191
iter 40 value 89.164159
iter 50 value 87.276779
iter 60 value 84.398107
iter 70 value 83.257782
iter 80 value 82.154933
iter 90 value 81.652259
iter 100 value 81.330971
final value 81.330971
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.701250
iter 10 value 94.113851
iter 20 value 93.942606
iter 30 value 88.132200
iter 40 value 86.914836
iter 50 value 84.816323
iter 60 value 82.648688
iter 70 value 82.283422
iter 80 value 82.171703
iter 90 value 82.058002
iter 100 value 81.659361
final value 81.659361
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 124.354667
iter 10 value 94.192737
iter 20 value 94.057594
iter 30 value 93.211188
iter 40 value 93.098200
iter 50 value 86.199868
iter 60 value 82.961698
iter 70 value 81.967108
iter 80 value 81.600092
iter 90 value 81.445528
iter 100 value 81.018809
final value 81.018809
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.835302
iter 10 value 92.874505
iter 20 value 88.145817
iter 30 value 86.667249
iter 40 value 85.513437
iter 50 value 85.053313
iter 60 value 84.083835
iter 70 value 83.260078
iter 80 value 81.521269
iter 90 value 80.733463
iter 100 value 80.494047
final value 80.494047
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.823707
iter 10 value 93.804999
iter 20 value 88.268524
iter 30 value 85.184275
iter 40 value 84.680919
iter 50 value 84.156544
iter 60 value 82.617536
iter 70 value 81.124167
iter 80 value 80.602542
iter 90 value 80.447234
iter 100 value 80.376183
final value 80.376183
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.882808
iter 10 value 94.283202
iter 20 value 94.075934
iter 30 value 93.887091
iter 40 value 93.113008
iter 50 value 92.616891
iter 60 value 89.462809
iter 70 value 88.937955
iter 80 value 88.027347
iter 90 value 85.959407
iter 100 value 82.225836
final value 82.225836
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 124.723934
iter 10 value 94.313687
iter 20 value 89.972814
iter 30 value 87.132428
iter 40 value 85.573398
iter 50 value 81.238851
iter 60 value 80.772576
iter 70 value 80.696031
iter 80 value 80.516970
iter 90 value 80.353959
iter 100 value 80.302047
final value 80.302047
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.723262
iter 10 value 94.068023
iter 20 value 93.772433
iter 30 value 86.321872
iter 40 value 85.682720
iter 50 value 84.838397
iter 60 value 84.345014
iter 70 value 83.014776
iter 80 value 81.496279
iter 90 value 81.008621
iter 100 value 80.793002
final value 80.793002
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.061264
iter 10 value 94.034480
iter 20 value 93.184662
iter 30 value 85.719750
iter 40 value 85.716072
iter 50 value 85.530944
iter 60 value 83.829249
iter 70 value 83.532620
iter 80 value 83.503826
final value 83.503584
converged
Fitting Repeat 2
# weights: 103
initial value 98.853685
final value 94.054367
converged
Fitting Repeat 3
# weights: 103
initial value 96.019989
final value 94.054370
converged
Fitting Repeat 4
# weights: 103
initial value 100.914424
final value 94.054742
converged
Fitting Repeat 5
# weights: 103
initial value 103.575465
final value 94.054541
converged
Fitting Repeat 1
# weights: 305
initial value 114.066370
iter 10 value 94.061348
iter 20 value 94.051742
iter 30 value 92.897838
iter 40 value 92.896674
iter 50 value 85.453945
iter 60 value 85.189872
iter 70 value 85.172705
final value 85.172530
converged
Fitting Repeat 2
# weights: 305
initial value 97.285540
iter 10 value 94.013235
iter 20 value 94.000530
iter 30 value 90.472005
iter 40 value 90.470896
iter 50 value 90.372199
iter 60 value 88.659003
iter 70 value 88.605314
iter 80 value 88.588550
iter 90 value 84.640378
final value 84.634702
converged
Fitting Repeat 3
# weights: 305
initial value 98.960290
iter 10 value 94.052328
iter 20 value 94.041909
iter 30 value 85.737186
iter 40 value 84.421270
iter 50 value 84.398446
iter 60 value 84.330542
iter 70 value 82.481978
iter 80 value 82.029083
iter 90 value 81.992995
iter 100 value 81.921028
final value 81.921028
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.538283
iter 10 value 89.927798
iter 20 value 84.499841
iter 30 value 84.494225
iter 40 value 84.423063
iter 50 value 84.422388
iter 60 value 84.420967
iter 70 value 84.420718
iter 80 value 84.419727
iter 90 value 84.419466
final value 84.419461
converged
Fitting Repeat 5
# weights: 305
initial value 100.061428
iter 10 value 94.058020
iter 20 value 94.053044
iter 30 value 93.198131
iter 40 value 86.836439
iter 50 value 86.833288
iter 60 value 84.351876
iter 70 value 84.337262
final value 84.331557
converged
Fitting Repeat 1
# weights: 507
initial value 99.465805
iter 10 value 92.901604
iter 20 value 92.855684
iter 30 value 86.603540
iter 40 value 86.155925
iter 50 value 85.850899
final value 85.850829
converged
Fitting Repeat 2
# weights: 507
initial value 95.083282
iter 10 value 93.999762
iter 20 value 91.768336
iter 30 value 84.189151
iter 40 value 84.182307
iter 50 value 83.587813
iter 60 value 82.204460
iter 70 value 82.199418
final value 82.199248
converged
Fitting Repeat 3
# weights: 507
initial value 110.858612
iter 10 value 94.061035
iter 20 value 94.041304
iter 30 value 93.249577
iter 40 value 89.848671
iter 50 value 88.753243
iter 60 value 83.684846
iter 70 value 83.095576
iter 80 value 82.642021
final value 82.381722
converged
Fitting Repeat 4
# weights: 507
initial value 103.362232
iter 10 value 94.061257
iter 20 value 90.866145
iter 30 value 87.354237
iter 40 value 87.353959
iter 50 value 86.922136
iter 60 value 85.633698
iter 70 value 85.619182
iter 80 value 85.618769
iter 90 value 82.332764
iter 100 value 80.422294
final value 80.422294
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.820577
iter 10 value 94.041157
final value 94.037544
converged
Fitting Repeat 1
# weights: 103
initial value 109.984723
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 110.401931
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 100.122986
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 103.428792
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 107.934316
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 105.531820
iter 10 value 93.662173
iter 10 value 93.662173
iter 10 value 93.662173
final value 93.662173
converged
Fitting Repeat 2
# weights: 305
initial value 103.937351
final value 93.867391
converged
Fitting Repeat 3
# weights: 305
initial value 94.451732
iter 10 value 86.059430
iter 20 value 85.099973
final value 85.098772
converged
Fitting Repeat 4
# weights: 305
initial value 96.790825
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 105.638772
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 138.621575
final value 93.867391
converged
Fitting Repeat 2
# weights: 507
initial value 120.818033
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 115.720463
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 100.477097
iter 10 value 93.848936
final value 93.841751
converged
Fitting Repeat 5
# weights: 507
initial value 94.044926
iter 10 value 90.488602
iter 20 value 90.302246
final value 90.297665
converged
Fitting Repeat 1
# weights: 103
initial value 107.163444
iter 10 value 94.005801
iter 20 value 91.531697
iter 30 value 85.092555
iter 40 value 84.713111
iter 50 value 83.256025
iter 60 value 82.989197
iter 70 value 82.873819
final value 82.873784
converged
Fitting Repeat 2
# weights: 103
initial value 117.096188
iter 10 value 94.016490
iter 20 value 88.071873
iter 30 value 85.523325
iter 40 value 84.182031
iter 50 value 83.181861
iter 60 value 83.009723
iter 70 value 82.874645
final value 82.873784
converged
Fitting Repeat 3
# weights: 103
initial value 97.877409
iter 10 value 94.439383
iter 20 value 93.277002
iter 30 value 88.233946
iter 40 value 86.888513
iter 50 value 85.091677
iter 60 value 84.144584
iter 70 value 83.640613
iter 80 value 83.292055
iter 90 value 82.864613
iter 100 value 82.749244
final value 82.749244
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.971389
iter 10 value 93.923424
iter 20 value 93.919342
iter 30 value 93.864682
iter 40 value 92.495865
iter 50 value 91.217236
iter 60 value 90.942407
iter 70 value 88.481485
iter 80 value 83.909128
iter 90 value 82.825996
iter 100 value 81.491284
final value 81.491284
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.509180
iter 10 value 93.394092
iter 20 value 84.129539
iter 30 value 83.709409
iter 40 value 82.867440
iter 50 value 81.674954
iter 60 value 80.883326
iter 70 value 80.392100
iter 80 value 80.237136
iter 90 value 80.235381
iter 90 value 80.235380
iter 90 value 80.235380
final value 80.235380
converged
Fitting Repeat 1
# weights: 305
initial value 107.830205
iter 10 value 93.790478
iter 20 value 90.335227
iter 30 value 87.192887
iter 40 value 82.825650
iter 50 value 82.123658
iter 60 value 81.556041
iter 70 value 81.339755
iter 80 value 80.750476
iter 90 value 80.246046
iter 100 value 79.811390
final value 79.811390
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.679474
iter 10 value 94.150212
iter 20 value 93.919598
iter 30 value 90.912732
iter 40 value 85.866547
iter 50 value 83.164724
iter 60 value 80.338816
iter 70 value 79.768094
iter 80 value 79.458555
iter 90 value 79.237001
iter 100 value 79.190217
final value 79.190217
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 112.745918
iter 10 value 94.093080
iter 20 value 85.873122
iter 30 value 84.552616
iter 40 value 84.008725
iter 50 value 83.585099
iter 60 value 83.226183
iter 70 value 83.037356
iter 80 value 82.810906
iter 90 value 81.235394
iter 100 value 80.834354
final value 80.834354
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.600897
iter 10 value 94.191224
iter 20 value 93.772034
iter 30 value 90.000998
iter 40 value 84.921056
iter 50 value 82.456879
iter 60 value 81.761193
iter 70 value 81.483209
iter 80 value 81.363206
iter 90 value 80.586847
iter 100 value 80.364091
final value 80.364091
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.924025
iter 10 value 93.883558
iter 20 value 91.538589
iter 30 value 85.338170
iter 40 value 81.949290
iter 50 value 81.073038
iter 60 value 80.589446
iter 70 value 80.109763
iter 80 value 80.074190
iter 90 value 80.071684
iter 100 value 80.046187
final value 80.046187
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.000034
iter 10 value 94.696117
iter 20 value 90.494264
iter 30 value 89.708729
iter 40 value 88.798850
iter 50 value 85.184839
iter 60 value 83.920388
iter 70 value 83.763757
iter 80 value 82.831867
iter 90 value 81.920536
iter 100 value 81.317294
final value 81.317294
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.728849
iter 10 value 91.734876
iter 20 value 89.322194
iter 30 value 85.315519
iter 40 value 84.389059
iter 50 value 83.891258
iter 60 value 83.706257
iter 70 value 83.627961
iter 80 value 82.713551
iter 90 value 81.556209
iter 100 value 81.265635
final value 81.265635
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 101.926565
iter 10 value 88.977985
iter 20 value 87.744327
iter 30 value 86.626388
iter 40 value 84.995293
iter 50 value 82.725715
iter 60 value 82.071566
iter 70 value 80.684800
iter 80 value 80.321944
iter 90 value 79.921777
iter 100 value 79.673414
final value 79.673414
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.124748
iter 10 value 93.962742
iter 20 value 89.376548
iter 30 value 83.705305
iter 40 value 82.336233
iter 50 value 81.765969
iter 60 value 81.512363
iter 70 value 81.357609
iter 80 value 80.967143
iter 90 value 80.466815
iter 100 value 79.229679
final value 79.229679
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.980668
iter 10 value 94.058773
iter 20 value 93.765790
iter 30 value 93.381326
iter 40 value 83.045980
iter 50 value 81.289739
iter 60 value 79.998515
iter 70 value 79.505128
iter 80 value 79.328033
iter 90 value 79.220080
iter 100 value 79.196782
final value 79.196782
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.582257
final value 94.054406
converged
Fitting Repeat 2
# weights: 103
initial value 95.680355
final value 94.054723
converged
Fitting Repeat 3
# weights: 103
initial value 100.825504
iter 10 value 93.869262
iter 20 value 93.867913
iter 30 value 93.867495
iter 30 value 93.867495
iter 30 value 93.867495
final value 93.867495
converged
Fitting Repeat 4
# weights: 103
initial value 109.640716
final value 94.054679
converged
Fitting Repeat 5
# weights: 103
initial value 94.519090
iter 10 value 94.054820
iter 20 value 90.314979
iter 30 value 84.043492
iter 40 value 84.002194
iter 50 value 84.002013
iter 60 value 84.001908
iter 70 value 83.866541
iter 70 value 83.866541
iter 70 value 83.866541
final value 83.866541
converged
Fitting Repeat 1
# weights: 305
initial value 96.945309
iter 10 value 86.815743
iter 20 value 86.238569
iter 30 value 85.947726
iter 40 value 85.945850
iter 50 value 85.943935
final value 85.943860
converged
Fitting Repeat 2
# weights: 305
initial value 94.974636
iter 10 value 93.872296
iter 20 value 93.867760
iter 30 value 93.865846
iter 40 value 93.320979
iter 50 value 92.409876
iter 60 value 92.409049
iter 70 value 92.405741
iter 80 value 92.403942
iter 90 value 92.403447
iter 100 value 90.337521
final value 90.337521
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.094454
iter 10 value 94.059514
final value 94.055198
converged
Fitting Repeat 4
# weights: 305
initial value 97.098925
iter 10 value 94.057709
iter 20 value 92.406913
iter 30 value 87.825408
iter 40 value 87.811430
iter 50 value 87.785310
iter 60 value 87.783987
iter 70 value 87.354347
iter 80 value 87.211752
final value 87.210632
converged
Fitting Repeat 5
# weights: 305
initial value 114.285406
iter 10 value 94.058217
iter 20 value 93.930595
final value 93.868251
converged
Fitting Repeat 1
# weights: 507
initial value 98.160485
iter 10 value 94.054225
iter 20 value 94.053132
iter 30 value 92.010786
iter 40 value 90.176338
iter 50 value 90.167216
iter 60 value 90.141227
iter 70 value 81.287698
iter 80 value 80.938856
iter 90 value 79.612827
iter 100 value 78.970978
final value 78.970978
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 131.261523
iter 10 value 94.061283
iter 20 value 94.050284
iter 30 value 84.040589
iter 40 value 84.010630
iter 50 value 81.896536
iter 60 value 81.872686
iter 70 value 81.868779
iter 80 value 81.739471
iter 90 value 81.733215
final value 81.732860
converged
Fitting Repeat 3
# weights: 507
initial value 96.348367
iter 10 value 87.532890
iter 20 value 87.303650
iter 30 value 87.296728
iter 40 value 84.651466
iter 50 value 84.477713
iter 60 value 84.477355
iter 70 value 84.420259
iter 80 value 84.418089
iter 90 value 84.416786
iter 100 value 81.023199
final value 81.023199
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.393568
iter 10 value 93.919970
iter 20 value 93.854360
iter 30 value 93.847800
iter 40 value 91.551344
iter 50 value 90.374108
iter 60 value 90.324083
iter 70 value 90.087361
iter 80 value 82.187111
iter 90 value 80.397282
iter 100 value 79.628766
final value 79.628766
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 99.164331
iter 10 value 93.875566
iter 20 value 92.772440
iter 30 value 91.773728
final value 91.750121
converged
Fitting Repeat 1
# weights: 103
initial value 101.957124
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 103.001354
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.692527
final value 94.354396
converged
Fitting Repeat 4
# weights: 103
initial value 101.967227
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.797580
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 113.031407
final value 94.354396
converged
Fitting Repeat 2
# weights: 305
initial value 103.752733
final value 94.354396
converged
Fitting Repeat 3
# weights: 305
initial value 96.199815
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 95.099411
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 98.740216
final value 94.354396
converged
Fitting Repeat 1
# weights: 507
initial value 100.391159
final value 94.354396
converged
Fitting Repeat 2
# weights: 507
initial value 99.149360
iter 10 value 94.022132
iter 20 value 93.783692
final value 93.783647
converged
Fitting Repeat 3
# weights: 507
initial value 99.589307
final value 94.354396
converged
Fitting Repeat 4
# weights: 507
initial value 106.125094
iter 10 value 91.579986
iter 20 value 91.513435
iter 20 value 91.513435
iter 20 value 91.513435
final value 91.513435
converged
Fitting Repeat 5
# weights: 507
initial value 104.278584
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 103.762668
iter 10 value 94.507833
iter 20 value 94.049317
iter 30 value 93.722538
iter 40 value 93.634181
iter 50 value 89.981387
iter 60 value 85.505781
iter 70 value 85.031630
iter 80 value 84.949492
iter 90 value 84.932574
iter 100 value 84.927461
final value 84.927461
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 104.343169
iter 10 value 94.314728
iter 20 value 93.591587
iter 30 value 87.227016
iter 40 value 86.665478
iter 50 value 86.485686
iter 60 value 86.472183
iter 70 value 85.317072
iter 80 value 84.966242
iter 90 value 84.931821
final value 84.931556
converged
Fitting Repeat 3
# weights: 103
initial value 113.022933
iter 10 value 94.056382
iter 20 value 91.854246
iter 30 value 91.441521
iter 40 value 91.278762
iter 50 value 91.170439
iter 60 value 87.439211
iter 70 value 83.918100
iter 80 value 83.529132
iter 90 value 82.910151
iter 100 value 82.686479
final value 82.686479
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 112.299301
iter 10 value 97.858082
iter 20 value 94.398123
iter 30 value 93.736537
iter 40 value 93.706989
iter 50 value 93.483328
iter 60 value 87.551122
iter 70 value 86.862423
iter 80 value 86.198845
iter 90 value 85.069940
iter 100 value 84.955177
final value 84.955177
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 96.358056
iter 10 value 93.756082
iter 20 value 89.250664
iter 30 value 88.981928
iter 40 value 88.837962
iter 50 value 85.144972
iter 60 value 85.035984
iter 70 value 85.029476
iter 80 value 84.954154
final value 84.926618
converged
Fitting Repeat 1
# weights: 305
initial value 108.523457
iter 10 value 94.362678
iter 20 value 86.856713
iter 30 value 85.306796
iter 40 value 84.581843
iter 50 value 84.231454
iter 60 value 83.863073
iter 70 value 83.627809
iter 80 value 83.339529
iter 90 value 82.891392
iter 100 value 82.056478
final value 82.056478
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.475749
iter 10 value 94.526969
iter 20 value 94.099926
iter 30 value 91.392222
iter 40 value 91.272098
iter 50 value 88.147965
iter 60 value 83.706671
iter 70 value 82.848478
iter 80 value 82.418845
iter 90 value 82.230145
iter 100 value 82.218121
final value 82.218121
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 110.668839
iter 10 value 94.394496
iter 20 value 85.884878
iter 30 value 85.130739
iter 40 value 84.680265
iter 50 value 84.184770
iter 60 value 83.368842
iter 70 value 82.432561
iter 80 value 82.298375
iter 90 value 81.693055
iter 100 value 80.979909
final value 80.979909
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 112.992880
iter 10 value 94.575229
iter 20 value 90.705189
iter 30 value 88.202237
iter 40 value 87.828546
iter 50 value 87.064031
iter 60 value 85.228706
iter 70 value 84.647110
iter 80 value 84.570766
iter 90 value 84.480604
iter 100 value 84.354696
final value 84.354696
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.553215
iter 10 value 96.175930
iter 20 value 91.914531
iter 30 value 87.738432
iter 40 value 83.341611
iter 50 value 82.520584
iter 60 value 81.758458
iter 70 value 81.367941
iter 80 value 81.275569
iter 90 value 81.198740
iter 100 value 81.055405
final value 81.055405
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.206129
iter 10 value 93.302531
iter 20 value 88.170339
iter 30 value 84.977745
iter 40 value 83.342157
iter 50 value 82.201902
iter 60 value 81.410236
iter 70 value 81.158971
iter 80 value 81.041974
iter 90 value 80.977462
iter 100 value 80.822602
final value 80.822602
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.680846
iter 10 value 94.583058
iter 20 value 94.189771
iter 30 value 93.581552
iter 40 value 91.439925
iter 50 value 85.144493
iter 60 value 84.931579
iter 70 value 84.148174
iter 80 value 82.818035
iter 90 value 82.413500
iter 100 value 81.946723
final value 81.946723
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.279704
iter 10 value 93.983995
iter 20 value 91.131249
iter 30 value 87.834019
iter 40 value 85.731792
iter 50 value 84.380295
iter 60 value 82.679310
iter 70 value 82.404730
iter 80 value 82.212703
iter 90 value 82.075216
iter 100 value 81.560942
final value 81.560942
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.155196
iter 10 value 98.197423
iter 20 value 88.629653
iter 30 value 85.427933
iter 40 value 84.788800
iter 50 value 84.726722
iter 60 value 84.660702
iter 70 value 84.470174
iter 80 value 83.484295
iter 90 value 82.973814
iter 100 value 82.331142
final value 82.331142
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 108.223567
iter 10 value 94.411107
iter 20 value 93.224622
iter 30 value 84.598116
iter 40 value 83.799357
iter 50 value 83.289755
iter 60 value 83.034036
iter 70 value 82.822274
iter 80 value 82.768783
iter 90 value 82.756854
iter 100 value 82.732803
final value 82.732803
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.322749
final value 94.485844
converged
Fitting Repeat 2
# weights: 103
initial value 97.472198
iter 10 value 94.356004
iter 10 value 94.356003
iter 10 value 94.356003
final value 94.356003
converged
Fitting Repeat 3
# weights: 103
initial value 98.969701
iter 10 value 94.317415
iter 20 value 94.316992
iter 30 value 93.784485
final value 93.784137
converged
Fitting Repeat 4
# weights: 103
initial value 104.871549
final value 94.485947
converged
Fitting Repeat 5
# weights: 103
initial value 96.050343
final value 94.486136
converged
Fitting Repeat 1
# weights: 305
initial value 101.184432
iter 10 value 94.492079
iter 20 value 94.413238
iter 30 value 85.184841
iter 40 value 85.176947
iter 50 value 85.170694
iter 60 value 85.169969
iter 70 value 85.169883
iter 80 value 85.168660
iter 90 value 85.168533
iter 100 value 85.168123
final value 85.168123
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.392220
iter 10 value 88.320175
iter 20 value 87.364272
iter 30 value 87.352196
iter 40 value 87.328734
iter 50 value 87.273581
iter 60 value 87.256916
iter 70 value 87.252632
iter 80 value 87.250421
iter 90 value 87.249771
iter 100 value 84.938314
final value 84.938314
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.746716
iter 10 value 94.168867
iter 20 value 94.165170
iter 30 value 89.766647
iter 40 value 86.391978
iter 50 value 86.033350
final value 86.025701
converged
Fitting Repeat 4
# weights: 305
initial value 100.741170
iter 10 value 94.488834
iter 20 value 94.484246
iter 30 value 93.797555
final value 93.659754
converged
Fitting Repeat 5
# weights: 305
initial value 105.548569
iter 10 value 94.489131
iter 20 value 94.480375
iter 30 value 93.809884
iter 40 value 93.582764
iter 50 value 93.256124
iter 60 value 86.155119
final value 86.147987
converged
Fitting Repeat 1
# weights: 507
initial value 105.548644
iter 10 value 86.763717
iter 20 value 85.175198
iter 30 value 85.168525
iter 40 value 85.160537
iter 50 value 84.939929
iter 60 value 84.732733
iter 70 value 84.693408
iter 80 value 84.682044
iter 90 value 84.681020
final value 84.681002
converged
Fitting Repeat 2
# weights: 507
initial value 101.825871
iter 10 value 92.007290
iter 20 value 91.726155
iter 30 value 91.724879
iter 40 value 91.718465
iter 50 value 84.547742
iter 60 value 83.223465
iter 70 value 83.180600
iter 80 value 83.178664
iter 90 value 83.177215
iter 100 value 83.172275
final value 83.172275
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.126574
iter 10 value 94.362333
iter 20 value 93.704797
iter 30 value 93.660556
iter 40 value 93.659804
iter 50 value 93.633455
iter 60 value 92.084790
iter 70 value 91.027873
iter 80 value 90.800336
iter 90 value 86.432081
iter 100 value 83.811387
final value 83.811387
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 96.815452
iter 10 value 92.622632
iter 20 value 92.619229
iter 30 value 85.170422
iter 40 value 85.001892
iter 50 value 83.635035
iter 60 value 83.628774
iter 70 value 83.628173
final value 83.627763
converged
Fitting Repeat 5
# weights: 507
initial value 97.598539
iter 10 value 93.762444
iter 20 value 93.754389
iter 30 value 87.324268
iter 40 value 86.971134
iter 50 value 85.361749
iter 60 value 85.145989
final value 85.137804
converged
Fitting Repeat 1
# weights: 507
initial value 123.882938
iter 10 value 117.898543
iter 20 value 117.851324
iter 30 value 117.354758
iter 40 value 116.235257
iter 50 value 107.819736
iter 60 value 104.894726
iter 70 value 104.812280
iter 80 value 104.811888
iter 90 value 104.615657
iter 100 value 102.776247
final value 102.776247
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 118.553904
iter 10 value 117.892141
iter 20 value 112.896529
iter 30 value 107.794379
iter 40 value 107.763647
iter 50 value 107.762959
iter 60 value 107.668912
iter 70 value 107.237661
iter 80 value 107.116836
iter 90 value 106.753787
iter 100 value 105.984324
final value 105.984324
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 142.228578
iter 10 value 117.898426
iter 20 value 117.769514
iter 30 value 113.152110
iter 40 value 112.797118
iter 50 value 106.025901
iter 60 value 105.107955
iter 70 value 104.119544
iter 80 value 103.194027
iter 90 value 102.735616
iter 100 value 102.437110
final value 102.437110
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 130.731993
iter 10 value 117.778461
iter 20 value 117.761046
final value 117.728844
converged
Fitting Repeat 5
# weights: 507
initial value 124.875623
iter 10 value 117.766439
iter 20 value 117.753133
final value 117.600342
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 -- Mon Jun 3 02:30:45 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
45.06 2.06 46.53
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 29.68 | 1.91 | 31.73 | |
| FreqInteractors | 0.27 | 0.03 | 0.31 | |
| calculateAAC | 0.03 | 0.03 | 0.06 | |
| calculateAutocor | 0.44 | 0.08 | 0.51 | |
| calculateCTDC | 0.06 | 0.03 | 0.10 | |
| calculateCTDD | 0.57 | 0.03 | 0.59 | |
| calculateCTDT | 0.25 | 0.00 | 0.25 | |
| calculateCTriad | 0.35 | 0.02 | 0.38 | |
| calculateDC | 0.08 | 0.00 | 0.07 | |
| calculateF | 0.32 | 0.05 | 0.36 | |
| calculateKSAAP | 0.09 | 0.01 | 0.11 | |
| calculateQD_Sm | 1.92 | 0.25 | 2.18 | |
| calculateTC | 2.08 | 0.11 | 2.20 | |
| calculateTC_Sm | 0.47 | 0.06 | 0.54 | |
| corr_plot | 30.55 | 1.83 | 32.39 | |
| enrichfindP | 0.53 | 0.05 | 13.50 | |
| enrichfind_hp | 0.13 | 0.00 | 1.04 | |
| enrichplot | 0.32 | 0.01 | 0.35 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.02 | 0.02 | 2.16 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.08 | 0.00 | 0.10 | |
| pred_ensembel | 14.19 | 0.67 | 11.00 | |
| var_imp | 32.93 | 1.21 | 34.20 | |