Matineh Rahmatbakhsh
| Snapshot Date: 2024-07-10 14:00 -0400 (Wed, 10 Jul 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 2024-07-12 17:39 -0400 (Fri, 12 Jul 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4741 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4483 |
| merida1 | macOS 12.7.4 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4512 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4461 |
| 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 | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
| merida1 | macOS 12.7.4 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | 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: E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz |
| StartedAt: 2024-07-12 01:17:41 -0400 (Fri, 12 Jul 2024) |
| EndedAt: 2024-07-12 01:22:41 -0400 (Fri, 12 Jul 2024) |
| EllapsedTime: 300.7 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'E:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck'
* using R version 4.4.1 (2024-06-14 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 34.33 0.98 35.33
corr_plot 33.22 1.97 35.24
FSmethod 33.15 1.84 35.15
pred_ensembel 15.30 0.46 11.38
enrichfindP 0.72 0.10 13.88
* 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
'E:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'E:/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 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"
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 97.154228
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 101.803999
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.952570
iter 10 value 94.026543
iter 10 value 94.026542
iter 10 value 94.026542
final value 94.026542
converged
Fitting Repeat 4
# weights: 103
initial value 94.561723
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.868456
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 116.824679
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 98.307565
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 97.661683
final value 94.484214
converged
Fitting Repeat 4
# weights: 305
initial value 100.987362
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 100.477508
final value 94.026542
converged
Fitting Repeat 1
# weights: 507
initial value 96.225923
final value 94.484212
converged
Fitting Repeat 2
# weights: 507
initial value 114.004089
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 99.850755
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 98.090164
iter 10 value 93.974643
final value 93.974641
converged
Fitting Repeat 5
# weights: 507
initial value 139.910603
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 100.182289
iter 10 value 94.299354
iter 20 value 94.086025
iter 30 value 94.077126
iter 40 value 89.984564
iter 50 value 88.385723
iter 60 value 88.118913
iter 70 value 88.098506
iter 80 value 88.040743
iter 90 value 88.035503
iter 100 value 88.029053
final value 88.029053
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.435339
iter 10 value 94.545569
iter 20 value 94.459993
iter 30 value 93.438666
iter 40 value 86.147565
iter 50 value 85.242567
iter 60 value 85.155189
iter 70 value 85.140279
iter 80 value 85.115276
iter 90 value 85.060743
iter 100 value 85.041623
final value 85.041623
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 104.790481
iter 10 value 94.449083
iter 20 value 88.100145
iter 30 value 86.303237
iter 40 value 85.547768
iter 50 value 85.254446
iter 60 value 85.181923
iter 70 value 85.145047
iter 80 value 85.140050
iter 90 value 85.044524
iter 100 value 85.041607
final value 85.041607
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 103.652959
iter 10 value 94.488729
iter 20 value 94.151048
iter 30 value 89.910593
iter 40 value 89.517470
iter 50 value 88.872170
iter 60 value 85.029796
iter 70 value 83.935370
iter 80 value 83.693114
iter 90 value 83.553322
iter 100 value 83.487844
final value 83.487844
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 110.361401
iter 10 value 94.477843
iter 20 value 94.139849
iter 30 value 94.077872
final value 94.076724
converged
Fitting Repeat 1
# weights: 305
initial value 101.257145
iter 10 value 94.493438
iter 20 value 92.789473
iter 30 value 90.918707
iter 40 value 86.871971
iter 50 value 85.799705
iter 60 value 85.538597
iter 70 value 84.883275
iter 80 value 84.154647
iter 90 value 83.967976
iter 100 value 83.586350
final value 83.586350
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.371763
iter 10 value 94.509450
iter 20 value 94.156960
iter 30 value 94.076219
iter 40 value 94.047807
iter 50 value 92.911639
iter 60 value 86.993048
iter 70 value 85.116079
iter 80 value 84.585562
iter 90 value 84.320141
iter 100 value 83.897871
final value 83.897871
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.260894
iter 10 value 94.466591
iter 20 value 94.274793
iter 30 value 87.170230
iter 40 value 86.235309
iter 50 value 85.843159
iter 60 value 85.815853
iter 70 value 85.264185
iter 80 value 85.122711
iter 90 value 85.101047
iter 100 value 85.034017
final value 85.034017
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 115.750026
iter 10 value 94.417340
iter 20 value 94.045175
iter 30 value 90.784719
iter 40 value 88.375350
iter 50 value 87.697946
iter 60 value 86.845412
iter 70 value 85.188581
iter 80 value 83.078667
iter 90 value 82.333369
iter 100 value 82.061166
final value 82.061166
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.367821
iter 10 value 94.551508
iter 20 value 89.615948
iter 30 value 85.388764
iter 40 value 84.677566
iter 50 value 84.226753
iter 60 value 83.699425
iter 70 value 83.578527
iter 80 value 83.524798
iter 90 value 83.508432
iter 100 value 83.439927
final value 83.439927
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.088061
iter 10 value 94.468878
iter 20 value 92.139605
iter 30 value 88.745771
iter 40 value 86.091600
iter 50 value 85.240650
iter 60 value 84.864401
iter 70 value 84.149932
iter 80 value 83.671405
iter 90 value 83.311203
iter 100 value 82.771255
final value 82.771255
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.574238
iter 10 value 94.470887
iter 20 value 93.178561
iter 30 value 89.126683
iter 40 value 86.582524
iter 50 value 85.332330
iter 60 value 83.666378
iter 70 value 82.518983
iter 80 value 82.046580
iter 90 value 81.802023
iter 100 value 81.742747
final value 81.742747
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.359559
iter 10 value 99.934792
iter 20 value 92.788835
iter 30 value 88.059593
iter 40 value 86.638208
iter 50 value 86.224141
iter 60 value 85.439631
iter 70 value 83.858688
iter 80 value 82.472583
iter 90 value 82.074267
iter 100 value 81.932381
final value 81.932381
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 117.737969
iter 10 value 95.821711
iter 20 value 94.696216
iter 30 value 90.970306
iter 40 value 88.383662
iter 50 value 87.631505
iter 60 value 84.965903
iter 70 value 83.633507
iter 80 value 83.257993
iter 90 value 82.542761
iter 100 value 82.421189
final value 82.421189
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.711480
iter 10 value 94.200512
iter 20 value 94.087528
iter 30 value 88.587184
iter 40 value 88.299114
iter 50 value 87.484704
iter 60 value 85.880609
iter 70 value 85.289760
iter 80 value 84.661217
iter 90 value 83.374543
iter 100 value 82.959928
final value 82.959928
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.529879
final value 94.483810
converged
Fitting Repeat 2
# weights: 103
initial value 102.324521
final value 94.486021
converged
Fitting Repeat 3
# weights: 103
initial value 106.812671
iter 10 value 94.675472
iter 20 value 94.631874
iter 30 value 94.489541
final value 94.484220
converged
Fitting Repeat 4
# weights: 103
initial value 97.334364
final value 94.485758
converged
Fitting Repeat 5
# weights: 103
initial value 99.490938
final value 94.485699
converged
Fitting Repeat 1
# weights: 305
initial value 103.293968
iter 10 value 94.489197
iter 20 value 94.484347
iter 30 value 94.343210
iter 40 value 94.165898
iter 50 value 94.165228
iter 50 value 94.165227
iter 50 value 94.165227
final value 94.165227
converged
Fitting Repeat 2
# weights: 305
initial value 107.383262
iter 10 value 94.489224
iter 20 value 94.350900
final value 94.026725
converged
Fitting Repeat 3
# weights: 305
initial value 102.507528
iter 10 value 94.488608
iter 20 value 94.046479
iter 30 value 93.866646
iter 40 value 89.369510
iter 50 value 89.247676
final value 89.247120
converged
Fitting Repeat 4
# weights: 305
initial value 103.930670
iter 10 value 94.024480
iter 20 value 94.023029
iter 30 value 90.272074
iter 40 value 89.424569
iter 50 value 87.953076
iter 60 value 86.656634
final value 86.620444
converged
Fitting Repeat 5
# weights: 305
initial value 100.417980
iter 10 value 94.501050
iter 20 value 94.490127
iter 30 value 90.107874
iter 40 value 90.102617
iter 50 value 90.097788
iter 60 value 90.084457
iter 70 value 90.075729
iter 80 value 89.998271
iter 90 value 89.998016
iter 100 value 89.997945
final value 89.997945
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.381698
iter 10 value 94.034308
iter 20 value 94.027533
iter 30 value 94.026735
iter 40 value 88.898221
iter 50 value 87.693642
iter 60 value 85.201621
iter 70 value 84.814573
iter 80 value 84.019515
iter 90 value 83.144938
iter 100 value 82.287442
final value 82.287442
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 100.435372
iter 10 value 91.059753
iter 20 value 90.955999
iter 30 value 90.482531
iter 40 value 90.283278
iter 50 value 90.276263
iter 60 value 90.268491
iter 70 value 87.076212
iter 80 value 84.368634
iter 90 value 84.114218
iter 100 value 84.098887
final value 84.098887
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 101.394619
iter 10 value 93.827389
iter 20 value 93.723171
iter 30 value 93.689818
iter 40 value 93.684373
iter 50 value 92.965417
iter 60 value 86.335453
iter 70 value 86.333783
iter 80 value 86.333633
iter 90 value 86.333569
final value 86.333209
converged
Fitting Repeat 4
# weights: 507
initial value 114.719061
iter 10 value 94.491471
iter 20 value 94.484174
iter 30 value 94.390345
iter 40 value 85.549717
iter 50 value 84.220358
iter 60 value 84.075758
final value 84.075168
converged
Fitting Repeat 5
# weights: 507
initial value 96.484841
iter 10 value 94.034739
iter 20 value 94.027791
iter 30 value 93.942854
iter 40 value 86.066174
iter 50 value 84.914495
iter 60 value 84.191585
iter 70 value 84.177265
iter 80 value 83.062426
iter 90 value 82.911009
iter 100 value 82.298799
final value 82.298799
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.685859
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 120.200402
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 97.539640
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 95.691723
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 95.756179
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 94.428422
iter 10 value 87.285956
iter 20 value 84.692016
iter 30 value 84.691175
iter 30 value 84.691175
final value 84.691175
converged
Fitting Repeat 2
# weights: 305
initial value 97.643750
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 95.107990
iter 10 value 93.437794
iter 20 value 93.326639
final value 93.326531
converged
Fitting Repeat 4
# weights: 305
initial value 102.175443
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 100.362670
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 95.178161
iter 10 value 93.391893
final value 93.391892
converged
Fitting Repeat 2
# weights: 507
initial value 108.739008
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 101.491710
iter 10 value 93.869755
iter 10 value 93.869755
iter 10 value 93.869755
final value 93.869755
converged
Fitting Repeat 4
# weights: 507
initial value 110.085241
final value 93.869755
converged
Fitting Repeat 5
# weights: 507
initial value 104.750964
iter 10 value 93.406703
final value 93.391892
converged
Fitting Repeat 1
# weights: 103
initial value 109.294476
iter 10 value 94.006436
iter 20 value 92.901434
iter 30 value 89.660181
iter 40 value 85.696206
iter 50 value 82.882374
iter 60 value 82.750226
final value 82.746832
converged
Fitting Repeat 2
# weights: 103
initial value 103.301256
iter 10 value 94.056732
iter 20 value 92.689705
iter 30 value 91.093430
iter 40 value 85.185199
iter 50 value 84.374852
iter 60 value 84.101338
iter 70 value 84.064397
iter 80 value 83.914939
final value 83.914678
converged
Fitting Repeat 3
# weights: 103
initial value 95.397444
iter 10 value 88.478480
iter 20 value 86.567043
iter 30 value 86.143946
iter 40 value 84.946068
iter 50 value 83.967618
iter 60 value 83.915158
final value 83.914678
converged
Fitting Repeat 4
# weights: 103
initial value 101.476813
iter 10 value 94.054887
iter 20 value 89.340895
iter 30 value 86.947330
iter 40 value 86.341820
iter 50 value 85.969561
iter 60 value 85.362165
iter 70 value 85.292416
iter 80 value 84.208714
iter 90 value 84.109112
final value 84.104733
converged
Fitting Repeat 5
# weights: 103
initial value 96.680132
iter 10 value 91.013828
iter 20 value 88.443676
iter 30 value 87.167436
iter 40 value 86.954029
iter 50 value 85.056084
iter 60 value 84.240745
iter 70 value 84.225444
iter 80 value 84.113800
iter 90 value 84.111549
iter 100 value 84.107323
final value 84.107323
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 108.689996
iter 10 value 94.115000
iter 20 value 93.720356
iter 30 value 91.616419
iter 40 value 91.020052
iter 50 value 86.429346
iter 60 value 83.973830
iter 70 value 83.375910
iter 80 value 83.139193
iter 90 value 82.367441
iter 100 value 82.167119
final value 82.167119
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.217614
iter 10 value 89.825579
iter 20 value 85.620930
iter 30 value 84.284207
iter 40 value 83.073759
iter 50 value 82.422581
iter 60 value 81.974711
iter 70 value 81.870948
iter 80 value 81.769221
iter 90 value 81.745476
iter 100 value 81.738315
final value 81.738315
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.477265
iter 10 value 87.036034
iter 20 value 85.722227
iter 30 value 84.245274
iter 40 value 83.994185
iter 50 value 83.917350
iter 60 value 83.822191
iter 70 value 83.791842
iter 80 value 83.553867
iter 90 value 83.090578
iter 100 value 82.400434
final value 82.400434
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.787758
iter 10 value 92.945083
iter 20 value 89.857175
iter 30 value 86.946969
iter 40 value 84.598254
iter 50 value 84.050258
iter 60 value 83.598297
iter 70 value 82.653390
iter 80 value 82.606319
iter 90 value 82.413390
iter 100 value 81.756452
final value 81.756452
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.297061
iter 10 value 94.024997
iter 20 value 91.753462
iter 30 value 87.291407
iter 40 value 85.081416
iter 50 value 84.293193
iter 60 value 84.268022
iter 70 value 84.166303
iter 80 value 84.115099
iter 90 value 83.989567
iter 100 value 83.950313
final value 83.950313
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 114.866773
iter 10 value 94.037045
iter 20 value 88.190349
iter 30 value 85.114375
iter 40 value 84.165054
iter 50 value 83.323282
iter 60 value 82.570405
iter 70 value 82.384757
iter 80 value 82.270150
iter 90 value 82.076557
iter 100 value 81.893391
final value 81.893391
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.734628
iter 10 value 93.698265
iter 20 value 92.679298
iter 30 value 91.145862
iter 40 value 87.406795
iter 50 value 83.305262
iter 60 value 82.441836
iter 70 value 82.228029
iter 80 value 81.925976
iter 90 value 81.587678
iter 100 value 81.273619
final value 81.273619
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.121056
iter 10 value 94.484022
iter 20 value 90.841193
iter 30 value 89.503779
iter 40 value 85.935275
iter 50 value 84.626606
iter 60 value 83.885975
iter 70 value 83.178784
iter 80 value 82.276670
iter 90 value 82.064513
iter 100 value 81.680416
final value 81.680416
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 124.288960
iter 10 value 95.557342
iter 20 value 94.056475
iter 30 value 90.694674
iter 40 value 86.070841
iter 50 value 85.063535
iter 60 value 84.531371
iter 70 value 83.962239
iter 80 value 82.646205
iter 90 value 82.347806
iter 100 value 82.133160
final value 82.133160
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 110.332048
iter 10 value 94.149450
iter 20 value 92.239716
iter 30 value 91.033624
iter 40 value 86.430459
iter 50 value 83.625815
iter 60 value 82.839109
iter 70 value 81.972200
iter 80 value 81.586047
iter 90 value 81.250199
iter 100 value 81.185866
final value 81.185866
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.289985
final value 94.054648
converged
Fitting Repeat 2
# weights: 103
initial value 97.983777
final value 94.054531
converged
Fitting Repeat 3
# weights: 103
initial value 96.719011
final value 94.054315
converged
Fitting Repeat 4
# weights: 103
initial value 95.106833
final value 94.054455
converged
Fitting Repeat 5
# weights: 103
initial value 103.742559
iter 10 value 93.393804
iter 20 value 93.239078
iter 30 value 88.403629
iter 40 value 87.320606
iter 50 value 87.319922
iter 60 value 87.319223
iter 70 value 86.423174
final value 86.339813
converged
Fitting Repeat 1
# weights: 305
initial value 103.920177
iter 10 value 94.057978
iter 20 value 93.024478
iter 30 value 87.592599
iter 40 value 87.590780
iter 50 value 85.632948
final value 85.632918
converged
Fitting Repeat 2
# weights: 305
initial value 96.582674
iter 10 value 94.057576
iter 20 value 93.932035
iter 30 value 85.633081
iter 40 value 85.629802
final value 85.629717
converged
Fitting Repeat 3
# weights: 305
initial value 98.539000
iter 10 value 93.396945
iter 20 value 93.394378
iter 30 value 93.268177
iter 40 value 92.580797
iter 50 value 92.566139
iter 60 value 92.565956
iter 70 value 92.552209
iter 80 value 92.534509
final value 92.534072
converged
Fitting Repeat 4
# weights: 305
initial value 99.283362
iter 10 value 94.057901
iter 20 value 93.944680
iter 30 value 84.048319
iter 40 value 84.038552
final value 84.038547
converged
Fitting Repeat 5
# weights: 305
initial value 96.420313
iter 10 value 94.057516
iter 20 value 94.045474
iter 30 value 86.884627
iter 40 value 84.479538
iter 50 value 84.467841
iter 60 value 83.792755
iter 70 value 83.684777
final value 83.684758
converged
Fitting Repeat 1
# weights: 507
initial value 105.449299
iter 10 value 93.400263
iter 20 value 93.395118
iter 30 value 93.392404
iter 40 value 85.300566
iter 50 value 84.774072
iter 60 value 84.747090
iter 70 value 84.633163
final value 84.633111
converged
Fitting Repeat 2
# weights: 507
initial value 103.357371
iter 10 value 94.060885
iter 20 value 94.031648
iter 30 value 88.262315
iter 40 value 86.145757
final value 86.144046
converged
Fitting Repeat 3
# weights: 507
initial value 99.977253
iter 10 value 93.400177
iter 20 value 93.393646
iter 30 value 93.271006
iter 40 value 93.235892
iter 50 value 93.235747
iter 60 value 93.235712
iter 70 value 93.233434
iter 80 value 84.721706
iter 90 value 84.047656
iter 100 value 84.036217
final value 84.036217
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 101.368931
iter 10 value 94.055206
iter 20 value 92.721521
iter 30 value 90.246119
iter 40 value 82.929304
iter 50 value 82.019353
iter 60 value 81.318668
iter 70 value 81.021411
iter 80 value 80.403506
iter 90 value 79.935120
iter 100 value 79.906204
final value 79.906204
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 102.826745
iter 10 value 93.402802
iter 20 value 93.396662
iter 30 value 90.642065
iter 40 value 85.647139
iter 50 value 85.592447
iter 60 value 85.590081
iter 70 value 84.955675
iter 80 value 84.328389
iter 90 value 84.318286
iter 100 value 84.134122
final value 84.134122
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 113.294954
final value 94.484212
converged
Fitting Repeat 2
# weights: 103
initial value 96.891165
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 94.748707
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 100.455846
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 102.370347
final value 94.484210
converged
Fitting Repeat 1
# weights: 305
initial value 113.044447
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 101.721469
iter 10 value 93.208299
iter 20 value 90.721573
iter 30 value 90.720842
iter 30 value 90.720842
final value 90.720837
converged
Fitting Repeat 3
# weights: 305
initial value 105.859728
final value 94.165117
converged
Fitting Repeat 4
# weights: 305
initial value 99.428685
final value 94.026542
converged
Fitting Repeat 5
# weights: 305
initial value 97.324252
iter 10 value 87.838461
iter 20 value 86.757422
final value 86.757191
converged
Fitting Repeat 1
# weights: 507
initial value 99.201268
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 102.550424
final value 94.448052
converged
Fitting Repeat 3
# weights: 507
initial value 99.991032
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 107.033333
iter 10 value 94.026542
iter 10 value 94.026542
iter 10 value 94.026542
final value 94.026542
converged
Fitting Repeat 5
# weights: 507
initial value 117.818055
iter 10 value 89.140745
iter 20 value 89.134465
final value 89.134443
converged
Fitting Repeat 1
# weights: 103
initial value 102.750257
iter 10 value 94.422440
iter 20 value 89.669715
iter 30 value 85.009716
iter 40 value 82.721126
iter 50 value 82.566432
iter 60 value 82.536539
iter 70 value 82.470128
iter 80 value 82.467350
iter 90 value 79.127336
iter 100 value 78.397142
final value 78.397142
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.409940
iter 10 value 94.484051
iter 20 value 92.901985
iter 30 value 86.570005
iter 40 value 85.926366
iter 50 value 85.671509
iter 60 value 82.036439
iter 70 value 82.005594
iter 80 value 81.989738
iter 90 value 81.940944
iter 100 value 81.926029
final value 81.926029
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 110.626745
iter 10 value 94.399962
iter 20 value 92.219143
iter 30 value 83.422544
iter 40 value 82.469066
iter 50 value 82.114767
iter 60 value 81.960909
iter 70 value 81.926293
final value 81.926002
converged
Fitting Repeat 4
# weights: 103
initial value 103.983181
iter 10 value 94.575455
iter 20 value 91.928463
iter 30 value 82.800068
iter 40 value 82.547666
iter 50 value 82.536933
iter 60 value 82.495116
final value 82.490787
converged
Fitting Repeat 5
# weights: 103
initial value 101.196292
iter 10 value 94.494074
iter 20 value 94.406523
iter 30 value 84.783279
iter 40 value 84.543800
iter 50 value 82.543069
iter 60 value 82.428692
iter 70 value 82.155015
iter 80 value 81.990506
iter 90 value 81.977620
iter 100 value 81.947532
final value 81.947532
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 110.410345
iter 10 value 94.653351
iter 20 value 93.991508
iter 30 value 91.604816
iter 40 value 85.410009
iter 50 value 82.526019
iter 60 value 81.373535
iter 70 value 78.803745
iter 80 value 78.110231
iter 90 value 77.881034
iter 100 value 77.145800
final value 77.145800
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 110.527045
iter 10 value 94.607416
iter 20 value 93.188373
iter 30 value 83.444690
iter 40 value 79.664330
iter 50 value 78.580752
iter 60 value 77.933185
iter 70 value 77.749585
iter 80 value 77.389889
iter 90 value 77.311117
iter 100 value 77.240115
final value 77.240115
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.275555
iter 10 value 94.321781
iter 20 value 85.081823
iter 30 value 84.721899
iter 40 value 82.215391
iter 50 value 81.032105
iter 60 value 79.038229
iter 70 value 78.631877
iter 80 value 78.221038
iter 90 value 77.919588
iter 100 value 77.767024
final value 77.767024
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.817769
iter 10 value 94.877676
iter 20 value 94.172055
iter 30 value 93.826558
iter 40 value 86.749948
iter 50 value 78.963006
iter 60 value 77.884579
iter 70 value 77.590536
iter 80 value 77.240901
iter 90 value 77.130379
iter 100 value 77.059459
final value 77.059459
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 135.406778
iter 10 value 93.505572
iter 20 value 85.063237
iter 30 value 82.381751
iter 40 value 80.702026
iter 50 value 78.985116
iter 60 value 78.322117
iter 70 value 78.127740
iter 80 value 77.827603
iter 90 value 77.749037
iter 100 value 77.643296
final value 77.643296
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 111.312610
iter 10 value 94.267229
iter 20 value 84.615336
iter 30 value 81.141617
iter 40 value 79.685045
iter 50 value 78.204621
iter 60 value 77.511417
iter 70 value 77.450012
iter 80 value 77.370184
iter 90 value 77.265502
iter 100 value 77.092802
final value 77.092802
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.322034
iter 10 value 94.861967
iter 20 value 89.777949
iter 30 value 86.819442
iter 40 value 81.325445
iter 50 value 79.563171
iter 60 value 79.365779
iter 70 value 79.248975
iter 80 value 78.935559
iter 90 value 78.773102
iter 100 value 78.722488
final value 78.722488
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.444541
iter 10 value 93.642868
iter 20 value 84.431060
iter 30 value 79.730800
iter 40 value 78.488729
iter 50 value 78.231333
iter 60 value 78.073746
iter 70 value 78.057529
iter 80 value 77.996799
iter 90 value 77.860536
iter 100 value 77.576739
final value 77.576739
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.367669
iter 10 value 94.641142
iter 20 value 94.477272
iter 30 value 82.355949
iter 40 value 81.482508
iter 50 value 80.966175
iter 60 value 79.951585
iter 70 value 78.554159
iter 80 value 77.117466
iter 90 value 76.889056
iter 100 value 76.455426
final value 76.455426
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.913297
iter 10 value 94.885888
iter 20 value 94.519159
iter 30 value 86.063453
iter 40 value 84.214281
iter 50 value 82.758275
iter 60 value 79.969298
iter 70 value 78.243205
iter 80 value 77.026863
iter 90 value 76.749912
iter 100 value 76.635357
final value 76.635357
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 109.745769
final value 94.485746
converged
Fitting Repeat 2
# weights: 103
initial value 95.935603
final value 94.485658
converged
Fitting Repeat 3
# weights: 103
initial value 95.006964
final value 94.486063
converged
Fitting Repeat 4
# weights: 103
initial value 95.020171
iter 10 value 92.138673
iter 20 value 90.619078
iter 30 value 90.610503
iter 40 value 90.610227
iter 50 value 90.609476
iter 60 value 89.315785
iter 70 value 88.715340
final value 88.715326
converged
Fitting Repeat 5
# weights: 103
initial value 97.883979
final value 94.485708
converged
Fitting Repeat 1
# weights: 305
initial value 101.300740
iter 10 value 94.488790
iter 20 value 94.319940
iter 30 value 85.179232
iter 40 value 85.173011
iter 50 value 85.172638
iter 60 value 83.559014
iter 70 value 81.118699
iter 80 value 79.750029
iter 90 value 77.187104
iter 100 value 77.057267
final value 77.057267
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.631391
iter 10 value 94.489122
iter 20 value 94.468039
iter 30 value 93.485751
final value 93.300841
converged
Fitting Repeat 3
# weights: 305
initial value 99.306203
iter 10 value 94.488708
iter 20 value 94.072778
iter 30 value 91.399235
iter 40 value 83.683310
iter 50 value 83.319809
iter 60 value 82.593290
iter 70 value 82.135142
iter 80 value 82.134693
iter 80 value 82.134693
final value 82.134693
converged
Fitting Repeat 4
# weights: 305
initial value 111.650943
iter 10 value 93.799950
iter 20 value 93.796112
final value 93.731492
converged
Fitting Repeat 5
# weights: 305
initial value 101.833646
iter 10 value 94.170016
iter 20 value 94.160098
iter 30 value 94.133178
iter 40 value 91.154673
iter 50 value 84.990268
iter 60 value 84.965351
iter 70 value 84.911172
iter 80 value 83.931437
iter 90 value 83.923339
iter 100 value 83.922706
final value 83.922706
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 96.356545
iter 10 value 86.569430
iter 20 value 80.297512
iter 30 value 80.276428
final value 80.276422
converged
Fitting Repeat 2
# weights: 507
initial value 100.253867
iter 10 value 84.752373
iter 20 value 81.313129
iter 30 value 81.309478
iter 40 value 81.302879
iter 50 value 81.270861
iter 60 value 81.269319
iter 70 value 81.268832
iter 80 value 81.268755
iter 90 value 81.246283
iter 100 value 81.202004
final value 81.202004
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.401586
iter 10 value 93.308564
iter 20 value 93.301591
final value 93.301570
converged
Fitting Repeat 4
# weights: 507
initial value 112.336423
iter 10 value 93.672824
iter 20 value 93.309016
iter 30 value 87.121013
iter 40 value 83.820107
iter 50 value 81.346512
iter 60 value 81.277473
iter 70 value 81.272325
iter 80 value 81.162648
iter 90 value 81.051579
iter 100 value 80.536002
final value 80.536002
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.984138
iter 10 value 94.490535
iter 20 value 93.950052
iter 30 value 93.305084
iter 40 value 93.302291
iter 50 value 88.568446
iter 60 value 84.992666
iter 70 value 84.945830
iter 80 value 84.940464
iter 90 value 81.425981
iter 100 value 81.234016
final value 81.234016
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.864791
iter 10 value 92.228977
final value 92.227953
converged
Fitting Repeat 2
# weights: 103
initial value 105.088716
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.521135
final value 94.026542
converged
Fitting Repeat 4
# weights: 103
initial value 100.743537
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.528317
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 99.871302
iter 10 value 94.026743
final value 94.026542
converged
Fitting Repeat 2
# weights: 305
initial value 112.411554
iter 10 value 94.482150
final value 94.482149
converged
Fitting Repeat 3
# weights: 305
initial value 98.297815
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 105.098855
iter 10 value 93.718448
iter 20 value 93.668704
iter 20 value 93.668704
iter 20 value 93.668704
final value 93.668704
converged
Fitting Repeat 5
# weights: 305
initial value 110.704920
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 112.270328
iter 10 value 94.298182
iter 10 value 94.298182
iter 10 value 94.298182
final value 94.298182
converged
Fitting Repeat 2
# weights: 507
initial value 119.104459
final value 94.026542
converged
Fitting Repeat 3
# weights: 507
initial value 109.772660
final value 94.026542
converged
Fitting Repeat 4
# weights: 507
initial value 116.163442
iter 10 value 93.461655
final value 93.461534
converged
Fitting Repeat 5
# weights: 507
initial value 97.014951
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 97.456715
iter 10 value 94.488614
iter 10 value 94.488614
iter 20 value 91.218422
iter 30 value 87.636868
iter 40 value 84.505156
iter 50 value 82.322244
iter 60 value 80.980547
iter 70 value 80.844737
iter 80 value 80.814167
final value 80.814104
converged
Fitting Repeat 2
# weights: 103
initial value 105.938862
iter 10 value 94.798157
iter 20 value 92.595804
iter 30 value 89.122458
iter 40 value 85.104997
iter 50 value 84.744916
iter 60 value 84.081971
iter 70 value 83.258449
final value 83.256383
converged
Fitting Repeat 3
# weights: 103
initial value 100.848959
iter 10 value 94.543356
iter 20 value 94.488322
iter 30 value 88.821319
iter 40 value 85.113866
iter 50 value 83.771549
iter 60 value 83.435709
iter 70 value 83.033722
iter 80 value 82.926567
iter 90 value 82.325649
final value 82.298620
converged
Fitting Repeat 4
# weights: 103
initial value 102.752781
iter 10 value 94.291235
iter 20 value 86.061248
iter 30 value 83.844357
iter 40 value 81.830794
iter 50 value 80.900049
iter 60 value 80.863528
iter 70 value 80.831890
iter 80 value 80.814172
final value 80.814159
converged
Fitting Repeat 5
# weights: 103
initial value 98.263555
iter 10 value 94.489578
iter 20 value 94.457324
iter 30 value 93.416085
iter 40 value 88.613626
iter 50 value 86.480341
iter 60 value 86.115258
iter 70 value 84.585286
iter 80 value 81.804469
iter 90 value 80.987914
iter 100 value 80.808180
final value 80.808180
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 116.809947
iter 10 value 94.246529
iter 20 value 89.147042
iter 30 value 88.595904
iter 40 value 84.217701
iter 50 value 83.846291
iter 60 value 83.216667
iter 70 value 80.960662
iter 80 value 79.899539
iter 90 value 79.590467
iter 100 value 79.298169
final value 79.298169
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 110.707489
iter 10 value 94.503730
iter 20 value 94.152215
iter 30 value 93.960223
iter 40 value 93.005495
iter 50 value 89.260434
iter 60 value 83.399563
iter 70 value 81.163200
iter 80 value 80.315630
iter 90 value 79.475219
iter 100 value 79.329973
final value 79.329973
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.561829
iter 10 value 93.576795
iter 20 value 84.003813
iter 30 value 82.379342
iter 40 value 82.327889
iter 50 value 82.136436
iter 60 value 82.017267
iter 70 value 81.925730
iter 80 value 81.835258
iter 90 value 80.383835
iter 100 value 79.488557
final value 79.488557
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 117.975242
iter 10 value 94.268480
iter 20 value 90.756350
iter 30 value 84.163601
iter 40 value 83.796122
iter 50 value 82.693960
iter 60 value 81.493816
iter 70 value 81.204071
iter 80 value 80.133988
iter 90 value 79.711067
iter 100 value 79.466455
final value 79.466455
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.248971
iter 10 value 94.578478
iter 20 value 87.198627
iter 30 value 86.550777
iter 40 value 86.186453
iter 50 value 85.249408
iter 60 value 82.457164
iter 70 value 80.274738
iter 80 value 79.924752
iter 90 value 79.488826
iter 100 value 78.959022
final value 78.959022
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.004109
iter 10 value 94.040636
iter 20 value 91.924865
iter 30 value 86.815288
iter 40 value 86.255111
iter 50 value 84.104899
iter 60 value 82.177235
iter 70 value 81.767172
iter 80 value 81.104685
iter 90 value 80.675500
iter 100 value 79.491359
final value 79.491359
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.284928
iter 10 value 93.924594
iter 20 value 89.115621
iter 30 value 84.711686
iter 40 value 82.763873
iter 50 value 82.344381
iter 60 value 81.334659
iter 70 value 80.912406
iter 80 value 80.129356
iter 90 value 80.061194
iter 100 value 79.937913
final value 79.937913
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.192346
iter 10 value 91.201826
iter 20 value 84.022464
iter 30 value 83.317224
iter 40 value 79.972099
iter 50 value 79.215925
iter 60 value 78.793027
iter 70 value 78.673044
iter 80 value 78.413909
iter 90 value 78.187040
iter 100 value 78.119562
final value 78.119562
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.406999
iter 10 value 93.907953
iter 20 value 91.601916
iter 30 value 90.254478
iter 40 value 85.886517
iter 50 value 81.225257
iter 60 value 80.261183
iter 70 value 79.557265
iter 80 value 79.454373
iter 90 value 79.393549
iter 100 value 79.378687
final value 79.378687
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 124.254880
iter 10 value 94.296528
iter 20 value 92.171691
iter 30 value 92.012812
iter 40 value 83.740217
iter 50 value 82.229314
iter 60 value 81.030679
iter 70 value 79.900714
iter 80 value 79.534405
iter 90 value 79.402975
iter 100 value 79.296117
final value 79.296117
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 104.877550
final value 94.486040
converged
Fitting Repeat 2
# weights: 103
initial value 96.191719
final value 94.486021
converged
Fitting Repeat 3
# weights: 103
initial value 100.592436
final value 94.486073
converged
Fitting Repeat 4
# weights: 103
initial value 99.964762
final value 94.485976
converged
Fitting Repeat 5
# weights: 103
initial value 100.757765
iter 10 value 94.485715
iter 20 value 94.434241
iter 30 value 92.826795
iter 40 value 81.682227
iter 50 value 80.412407
iter 60 value 79.706976
iter 70 value 79.703174
final value 79.703043
converged
Fitting Repeat 1
# weights: 305
initial value 99.919932
iter 10 value 94.489077
iter 20 value 94.330098
final value 94.026880
converged
Fitting Repeat 2
# weights: 305
initial value 108.849985
iter 10 value 94.488411
iter 20 value 94.484208
iter 30 value 94.026797
iter 30 value 94.026797
iter 30 value 94.026797
final value 94.026797
converged
Fitting Repeat 3
# weights: 305
initial value 117.777888
iter 10 value 94.489148
iter 20 value 94.379849
iter 30 value 93.797992
iter 40 value 86.499912
iter 50 value 86.497509
final value 86.497505
converged
Fitting Repeat 4
# weights: 305
initial value 96.278391
iter 10 value 94.489468
iter 20 value 94.484246
iter 30 value 94.043378
iter 40 value 93.908080
iter 50 value 86.045393
iter 60 value 80.239427
iter 70 value 78.885923
iter 80 value 78.260801
iter 90 value 78.259111
iter 100 value 78.258331
final value 78.258331
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.790293
iter 10 value 94.031469
iter 20 value 93.816581
iter 30 value 86.315767
iter 40 value 86.311948
iter 50 value 85.895901
iter 60 value 84.091723
iter 70 value 80.553997
iter 80 value 79.961600
iter 90 value 79.954282
iter 100 value 79.953483
final value 79.953483
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.363737
iter 10 value 94.492305
iter 20 value 94.484388
iter 30 value 93.527943
iter 40 value 82.847625
iter 50 value 82.791230
iter 60 value 82.670855
final value 82.670759
converged
Fitting Repeat 2
# weights: 507
initial value 98.760726
iter 10 value 94.492140
iter 20 value 94.325309
iter 30 value 88.488895
iter 40 value 84.393969
iter 50 value 84.338028
iter 60 value 83.857314
iter 70 value 83.582379
iter 80 value 83.153404
iter 90 value 82.437662
iter 100 value 82.432242
final value 82.432242
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.354972
iter 10 value 93.709974
iter 20 value 93.705916
iter 30 value 87.132536
iter 40 value 83.446349
iter 50 value 83.339884
iter 60 value 83.338680
iter 70 value 83.337852
iter 80 value 83.242326
iter 90 value 82.456453
iter 100 value 79.647935
final value 79.647935
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 102.824146
iter 10 value 94.492439
iter 20 value 94.417561
iter 30 value 88.707876
iter 40 value 82.175522
iter 50 value 82.162395
iter 60 value 82.152489
iter 70 value 82.150332
iter 80 value 81.643933
final value 81.643881
converged
Fitting Repeat 5
# weights: 507
initial value 107.833608
iter 10 value 94.103312
iter 20 value 94.096843
iter 30 value 88.597626
iter 40 value 83.072002
iter 50 value 83.068638
final value 83.068617
converged
Fitting Repeat 1
# weights: 103
initial value 97.177346
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 96.197744
iter 10 value 93.764380
iter 20 value 93.763752
iter 20 value 93.763751
iter 20 value 93.763751
final value 93.763751
converged
Fitting Repeat 3
# weights: 103
initial value 97.489914
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 100.763119
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.375852
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 94.083284
final value 93.860355
converged
Fitting Repeat 2
# weights: 305
initial value 105.004093
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 103.105648
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 103.258946
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 99.995423
final value 94.032967
converged
Fitting Repeat 1
# weights: 507
initial value 99.004425
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 95.364455
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 102.110407
iter 10 value 94.003143
iter 10 value 94.003143
iter 10 value 94.003143
final value 94.003143
converged
Fitting Repeat 4
# weights: 507
initial value 100.586936
iter 10 value 93.860356
final value 93.860355
converged
Fitting Repeat 5
# weights: 507
initial value 95.933560
iter 10 value 93.183456
iter 20 value 93.156031
iter 30 value 92.946181
iter 40 value 92.929494
iter 50 value 92.928724
final value 92.928330
converged
Fitting Repeat 1
# weights: 103
initial value 98.912277
iter 10 value 94.111869
iter 20 value 94.047005
iter 30 value 93.619362
iter 40 value 93.580177
iter 50 value 87.964578
iter 60 value 87.610756
iter 70 value 87.239337
iter 80 value 85.731761
iter 90 value 85.187563
iter 100 value 84.873369
final value 84.873369
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 98.539920
iter 10 value 93.257059
iter 20 value 87.875591
iter 30 value 86.444018
iter 40 value 84.909108
iter 50 value 84.028397
iter 60 value 83.967040
iter 70 value 83.907826
iter 80 value 83.886595
final value 83.886581
converged
Fitting Repeat 3
# weights: 103
initial value 102.367770
iter 10 value 93.690587
iter 20 value 88.591863
iter 30 value 86.311045
iter 40 value 85.823089
iter 50 value 84.536644
iter 60 value 84.364555
iter 70 value 84.155073
iter 80 value 83.841184
iter 90 value 83.467372
iter 100 value 83.424506
final value 83.424506
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.808615
iter 10 value 94.017596
iter 20 value 93.370762
iter 30 value 85.574080
iter 40 value 84.561428
iter 50 value 84.017841
iter 60 value 83.762806
iter 70 value 83.733910
iter 80 value 83.646441
iter 90 value 82.044392
iter 100 value 81.734802
final value 81.734802
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 96.882182
iter 10 value 94.056430
iter 20 value 93.695969
iter 30 value 93.572655
iter 40 value 92.481185
iter 50 value 88.154851
iter 60 value 86.030161
iter 70 value 85.155794
iter 80 value 83.686165
iter 90 value 82.111911
iter 100 value 80.930168
final value 80.930168
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 113.185814
iter 10 value 94.054413
iter 20 value 93.103318
iter 30 value 88.922575
iter 40 value 85.292780
iter 50 value 84.804113
iter 60 value 84.198511
iter 70 value 83.827527
iter 80 value 82.079165
iter 90 value 81.519533
iter 100 value 80.242484
final value 80.242484
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.667839
iter 10 value 93.960025
iter 20 value 90.540365
iter 30 value 87.986200
iter 40 value 86.182913
iter 50 value 81.331754
iter 60 value 80.758542
iter 70 value 80.421836
iter 80 value 80.095321
iter 90 value 79.406515
iter 100 value 79.038755
final value 79.038755
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.880646
iter 10 value 94.145219
iter 20 value 93.602474
iter 30 value 92.913361
iter 40 value 90.015942
iter 50 value 87.155185
iter 60 value 86.698574
iter 70 value 84.531783
iter 80 value 81.550563
iter 90 value 81.242976
iter 100 value 80.150283
final value 80.150283
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 114.895142
iter 10 value 94.050580
iter 20 value 89.021501
iter 30 value 86.444722
iter 40 value 84.957224
iter 50 value 82.726566
iter 60 value 82.170659
iter 70 value 80.333100
iter 80 value 79.833219
iter 90 value 79.664429
iter 100 value 79.561742
final value 79.561742
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.179747
iter 10 value 93.897999
iter 20 value 88.772839
iter 30 value 88.128171
iter 40 value 87.627533
iter 50 value 85.324078
iter 60 value 81.829882
iter 70 value 81.088741
iter 80 value 80.294421
iter 90 value 79.854885
iter 100 value 79.740036
final value 79.740036
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.411173
iter 10 value 94.337224
iter 20 value 92.608381
iter 30 value 87.788329
iter 40 value 86.765801
iter 50 value 85.992501
iter 60 value 83.179093
iter 70 value 81.204567
iter 80 value 80.493481
iter 90 value 80.312674
iter 100 value 80.197026
final value 80.197026
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.739497
iter 10 value 93.956672
iter 20 value 86.774377
iter 30 value 84.935928
iter 40 value 83.845247
iter 50 value 83.488286
iter 60 value 83.202195
iter 70 value 83.032301
iter 80 value 82.404934
iter 90 value 80.393018
iter 100 value 79.453745
final value 79.453745
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 112.227846
iter 10 value 94.197307
iter 20 value 93.257001
iter 30 value 87.951830
iter 40 value 83.508134
iter 50 value 82.267207
iter 60 value 81.713852
iter 70 value 80.844496
iter 80 value 79.775551
iter 90 value 79.550977
iter 100 value 79.450865
final value 79.450865
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 123.986871
iter 10 value 94.158774
iter 20 value 86.971473
iter 30 value 86.037672
iter 40 value 85.083828
iter 50 value 84.630899
iter 60 value 83.159549
iter 70 value 82.304977
iter 80 value 80.731237
iter 90 value 80.098669
iter 100 value 79.848683
final value 79.848683
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.516274
iter 10 value 94.436230
iter 20 value 90.186104
iter 30 value 87.073849
iter 40 value 84.945401
iter 50 value 83.140185
iter 60 value 82.704451
iter 70 value 81.062288
iter 80 value 80.870936
iter 90 value 80.470306
iter 100 value 80.232942
final value 80.232942
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.945116
final value 94.054814
converged
Fitting Repeat 2
# weights: 103
initial value 96.567841
final value 94.054470
converged
Fitting Repeat 3
# weights: 103
initial value 102.491908
iter 10 value 93.989629
iter 20 value 93.988281
final value 93.869985
converged
Fitting Repeat 4
# weights: 103
initial value 97.849216
final value 94.054555
converged
Fitting Repeat 5
# weights: 103
initial value 106.675692
final value 94.054576
converged
Fitting Repeat 1
# weights: 305
initial value 103.085948
iter 10 value 94.058327
iter 20 value 94.029161
iter 30 value 93.550595
final value 93.507232
converged
Fitting Repeat 2
# weights: 305
initial value 102.397139
iter 10 value 94.038866
iter 20 value 94.034018
iter 30 value 90.083777
iter 40 value 87.540173
iter 50 value 87.455142
iter 60 value 87.363436
iter 70 value 87.358293
iter 80 value 87.358162
iter 90 value 87.357661
final value 87.357460
converged
Fitting Repeat 3
# weights: 305
initial value 97.114752
iter 10 value 94.057400
iter 20 value 89.203541
iter 30 value 87.320101
iter 40 value 86.586717
iter 50 value 82.008858
iter 60 value 81.982873
iter 70 value 81.979737
iter 80 value 81.969086
iter 90 value 81.962315
iter 100 value 81.961697
final value 81.961697
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 94.249075
iter 10 value 94.037574
iter 20 value 94.033665
final value 94.033323
converged
Fitting Repeat 5
# weights: 305
initial value 96.963342
iter 10 value 94.057418
iter 20 value 93.998570
iter 30 value 87.170637
iter 40 value 86.939867
iter 50 value 86.806111
final value 86.777074
converged
Fitting Repeat 1
# weights: 507
initial value 103.014712
iter 10 value 94.061819
iter 20 value 94.018937
iter 30 value 91.709786
iter 40 value 88.684415
iter 50 value 88.670583
iter 60 value 88.665160
iter 70 value 88.590264
iter 80 value 88.585747
iter 90 value 86.413180
iter 100 value 86.409242
final value 86.409242
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 100.964799
iter 10 value 93.868778
iter 20 value 93.866711
iter 30 value 93.848579
final value 93.842915
converged
Fitting Repeat 3
# weights: 507
initial value 101.687079
iter 10 value 94.065056
iter 20 value 94.054662
iter 30 value 92.821023
iter 40 value 91.439314
iter 50 value 91.436292
iter 60 value 91.435361
iter 70 value 91.435233
final value 91.435231
converged
Fitting Repeat 4
# weights: 507
initial value 93.276437
iter 10 value 89.292726
iter 20 value 84.537678
iter 30 value 83.629120
iter 40 value 83.228627
iter 50 value 83.210909
iter 60 value 82.059553
iter 70 value 81.294283
iter 80 value 81.028047
final value 80.932072
converged
Fitting Repeat 5
# weights: 507
initial value 110.397748
iter 10 value 94.040764
iter 20 value 93.951951
iter 30 value 87.069249
iter 40 value 82.732591
iter 50 value 82.538736
iter 60 value 82.532786
iter 70 value 82.532577
iter 80 value 82.523916
final value 82.522124
converged
Fitting Repeat 1
# weights: 507
initial value 154.975954
iter 10 value 117.778798
iter 20 value 117.768608
iter 30 value 117.731463
iter 40 value 117.725579
iter 50 value 114.727792
iter 60 value 108.737193
iter 70 value 108.527915
final value 108.527836
converged
Fitting Repeat 2
# weights: 507
initial value 144.468704
iter 10 value 117.616150
iter 20 value 117.612935
iter 30 value 117.611603
iter 40 value 117.610553
iter 50 value 117.304316
iter 60 value 108.153917
iter 70 value 105.522199
iter 80 value 103.337182
iter 90 value 100.914598
iter 100 value 100.562500
final value 100.562500
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 129.661018
iter 10 value 117.896153
iter 20 value 117.790032
iter 30 value 117.533060
iter 40 value 107.154334
iter 50 value 106.765822
final value 106.765813
converged
Fitting Repeat 4
# weights: 507
initial value 126.982594
iter 10 value 117.897793
iter 20 value 117.059065
iter 30 value 106.936799
iter 40 value 106.905085
iter 50 value 105.063981
iter 60 value 104.090661
iter 70 value 103.812336
iter 80 value 103.777279
iter 90 value 102.803058
iter 100 value 102.403627
final value 102.403627
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 122.354781
iter 10 value 117.873555
iter 20 value 115.623955
iter 30 value 106.619883
iter 40 value 106.581124
iter 50 value 106.561485
iter 60 value 105.770054
iter 70 value 105.451022
iter 80 value 105.437495
iter 90 value 105.436965
iter 100 value 104.208920
final value 104.208920
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Fri Jul 12 01:22:30 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
47.48 2.10 49.18
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.15 | 1.84 | 35.15 | |
| FreqInteractors | 0.35 | 0.00 | 0.36 | |
| calculateAAC | 0.05 | 0.02 | 0.06 | |
| calculateAutocor | 0.48 | 0.09 | 0.58 | |
| calculateCTDC | 0.08 | 0.02 | 0.10 | |
| calculateCTDD | 0.83 | 0.01 | 0.83 | |
| calculateCTDT | 0.36 | 0.02 | 0.38 | |
| calculateCTriad | 0.37 | 0.03 | 0.40 | |
| calculateDC | 0.13 | 0.02 | 0.14 | |
| calculateF | 0.34 | 0.03 | 0.38 | |
| calculateKSAAP | 0.09 | 0.01 | 0.11 | |
| calculateQD_Sm | 2.37 | 0.22 | 2.60 | |
| calculateTC | 2.35 | 0.14 | 2.48 | |
| calculateTC_Sm | 0.36 | 0.00 | 0.36 | |
| corr_plot | 33.22 | 1.97 | 35.24 | |
| enrichfindP | 0.72 | 0.10 | 13.88 | |
| enrichfind_hp | 0.11 | 0.03 | 1.12 | |
| enrichplot | 0.53 | 0.01 | 0.55 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.00 | 0.03 | 2.31 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.09 | 0.00 | 0.09 | |
| pred_ensembel | 15.30 | 0.46 | 11.38 | |
| var_imp | 34.33 | 0.98 | 35.33 | |