Matineh Rahmatbakhsh
| Snapshot Date: 2026-04-17 13:40 -0400 (Fri, 17 Apr 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: 68bd9a1 |
| git_last_commit_date: 2025-12-28 18:34:02 -0400 (Sun, 28 Dec 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-04-18 11:37 -0400 (Sat, 18 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 alpha (2026-04-05 r89794) | 4957 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.6.0 alpha (2026-04-08 r89818) | 4686 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4627 |
| 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 1023/2404 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.17.2 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
| See other builds for HPiP in R Universe. | ||||||||||||||
|
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. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: HPiP |
| Version: 1.17.2 |
| Command: /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.17.2.tar.gz |
| StartedAt: 2026-04-17 04:18:20 -0000 (Fri, 17 Apr 2026) |
| EndedAt: 2026-04-17 04:25:24 -0000 (Fri, 17 Apr 2026) |
| EllapsedTime: 423.4 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.17.2.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* 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 for sufficient/correct file permissions ... 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 loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
var_imp 38.067 0.455 38.748
corr_plot 37.399 0.211 37.696
FSmethod 36.469 0.367 36.924
pred_ensembel 18.350 0.731 17.992
enrichfindP 0.569 0.008 22.238
getFASTA 0.091 0.024 6.317
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘runTests.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/R/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.17.2’ ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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 99.511717
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.420944
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 94.546637
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.907436
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 101.549687
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 103.400644
iter 10 value 93.936405
iter 20 value 90.165968
iter 30 value 88.782709
iter 40 value 88.361572
iter 50 value 88.327648
iter 60 value 88.327365
final value 88.327363
converged
Fitting Repeat 2
# weights: 305
initial value 98.661188
iter 10 value 85.923483
iter 20 value 83.614159
iter 30 value 83.199548
iter 40 value 82.169937
final value 82.168831
converged
Fitting Repeat 3
# weights: 305
initial value 95.121273
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 100.992715
final value 94.354396
converged
Fitting Repeat 5
# weights: 305
initial value 95.813758
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 123.797821
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 111.374879
final value 94.354396
converged
Fitting Repeat 3
# weights: 507
initial value 94.936553
iter 10 value 94.172518
iter 20 value 94.164246
iter 20 value 94.164245
final value 94.164201
converged
Fitting Repeat 4
# weights: 507
initial value 112.217012
iter 10 value 93.880319
final value 93.205814
converged
Fitting Repeat 5
# weights: 507
initial value 115.230566
final value 94.484210
converged
Fitting Repeat 1
# weights: 103
initial value 102.083057
iter 10 value 94.486432
iter 20 value 90.474937
iter 30 value 85.663449
iter 40 value 85.303848
iter 50 value 85.150620
iter 60 value 83.910163
iter 70 value 83.614403
iter 80 value 83.579923
iter 90 value 83.229008
iter 100 value 82.955344
final value 82.955344
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 105.945023
iter 10 value 94.471372
iter 20 value 86.228875
iter 30 value 85.560860
iter 40 value 83.581828
iter 50 value 83.294730
iter 60 value 83.143299
iter 70 value 82.925121
iter 80 value 82.832484
iter 90 value 82.805791
final value 82.802160
converged
Fitting Repeat 3
# weights: 103
initial value 99.308252
iter 10 value 94.175761
iter 20 value 90.322306
iter 30 value 89.403183
iter 40 value 85.879045
iter 50 value 83.511191
iter 60 value 83.475191
iter 70 value 83.211615
iter 80 value 82.875508
iter 90 value 82.806585
iter 100 value 82.802215
final value 82.802215
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.907061
iter 10 value 94.527410
iter 20 value 93.152757
iter 30 value 86.141696
iter 40 value 84.908868
iter 50 value 82.672776
iter 60 value 82.418531
iter 70 value 82.383958
final value 82.383223
converged
Fitting Repeat 5
# weights: 103
initial value 107.134173
iter 10 value 94.503157
iter 20 value 94.488688
iter 30 value 94.292495
iter 40 value 93.949760
iter 50 value 93.620838
iter 60 value 88.104178
iter 70 value 83.458490
iter 80 value 83.258601
iter 90 value 83.190635
iter 100 value 83.134843
final value 83.134843
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 106.255617
iter 10 value 96.810051
iter 20 value 86.484091
iter 30 value 83.538220
iter 40 value 83.148702
iter 50 value 82.752132
iter 60 value 82.525074
iter 70 value 82.513769
iter 80 value 82.422135
iter 90 value 82.077561
iter 100 value 81.184831
final value 81.184831
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.102164
iter 10 value 94.332162
iter 20 value 90.521794
iter 30 value 86.976222
iter 40 value 83.593175
iter 50 value 83.103527
iter 60 value 83.046594
iter 70 value 82.802868
iter 80 value 81.862079
iter 90 value 81.625152
iter 100 value 81.496481
final value 81.496481
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 128.706498
iter 10 value 94.118871
iter 20 value 90.939906
iter 30 value 87.062493
iter 40 value 83.700824
iter 50 value 82.205008
iter 60 value 81.402785
iter 70 value 81.254844
iter 80 value 81.128367
iter 90 value 81.057449
iter 100 value 80.980414
final value 80.980414
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.662220
iter 10 value 94.024984
iter 20 value 83.500727
iter 30 value 82.996898
iter 40 value 82.730896
iter 50 value 82.672760
iter 60 value 82.644532
iter 70 value 82.590966
iter 80 value 81.582175
iter 90 value 81.285611
iter 100 value 80.895994
final value 80.895994
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.759471
iter 10 value 90.776062
iter 20 value 85.610777
iter 30 value 83.096840
iter 40 value 81.931537
iter 50 value 81.111861
iter 60 value 80.863909
iter 70 value 80.719156
iter 80 value 80.545678
iter 90 value 80.383139
iter 100 value 80.263877
final value 80.263877
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.929987
iter 10 value 94.737726
iter 20 value 93.822001
iter 30 value 89.766653
iter 40 value 85.706162
iter 50 value 82.101148
iter 60 value 81.826944
iter 70 value 81.406548
iter 80 value 81.119461
iter 90 value 81.068423
iter 100 value 81.011549
final value 81.011549
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 116.252737
iter 10 value 94.417060
iter 20 value 90.346750
iter 30 value 85.977246
iter 40 value 85.150825
iter 50 value 84.274957
iter 60 value 82.326489
iter 70 value 80.816590
iter 80 value 80.514922
iter 90 value 80.344531
iter 100 value 80.283790
final value 80.283790
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.690149
iter 10 value 94.572684
iter 20 value 93.971671
iter 30 value 84.335579
iter 40 value 83.063131
iter 50 value 82.619848
iter 60 value 81.718144
iter 70 value 81.103216
iter 80 value 80.829795
iter 90 value 80.493949
iter 100 value 80.434471
final value 80.434471
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.666209
iter 10 value 96.650413
iter 20 value 88.718786
iter 30 value 87.561035
iter 40 value 84.771851
iter 50 value 81.921332
iter 60 value 81.481558
iter 70 value 81.290337
iter 80 value 81.083456
iter 90 value 80.779403
iter 100 value 80.654957
final value 80.654957
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 121.347717
iter 10 value 93.793370
iter 20 value 84.626394
iter 30 value 83.527048
iter 40 value 83.004123
iter 50 value 82.621588
iter 60 value 82.490851
iter 70 value 82.316451
iter 80 value 81.847217
iter 90 value 81.013388
iter 100 value 80.678152
final value 80.678152
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 104.187615
final value 94.485597
converged
Fitting Repeat 2
# weights: 103
initial value 101.858496
final value 94.485950
converged
Fitting Repeat 3
# weights: 103
initial value 97.305692
final value 94.485807
converged
Fitting Repeat 4
# weights: 103
initial value 97.383532
final value 94.485900
converged
Fitting Repeat 5
# weights: 103
initial value 98.736536
iter 10 value 94.486439
final value 94.484549
converged
Fitting Repeat 1
# weights: 305
initial value 103.286357
iter 10 value 94.488973
iter 20 value 94.484227
iter 30 value 92.953681
iter 40 value 89.156586
iter 50 value 86.698369
final value 84.291495
converged
Fitting Repeat 2
# weights: 305
initial value 123.215727
iter 10 value 94.359401
iter 20 value 93.749741
iter 30 value 85.304895
iter 40 value 85.165008
iter 50 value 85.130572
iter 60 value 85.117651
iter 70 value 84.982381
iter 80 value 84.976198
final value 84.975675
converged
Fitting Repeat 3
# weights: 305
initial value 115.653306
iter 10 value 94.363152
iter 20 value 94.358077
iter 30 value 94.356785
iter 40 value 93.889438
final value 93.871910
converged
Fitting Repeat 4
# weights: 305
initial value 103.839785
iter 10 value 94.171038
iter 20 value 94.170044
iter 30 value 93.918099
iter 40 value 90.983318
iter 50 value 83.191693
iter 60 value 82.666521
iter 70 value 82.475470
iter 80 value 82.399050
final value 82.396946
converged
Fitting Repeat 5
# weights: 305
initial value 101.893901
iter 10 value 94.488648
iter 20 value 94.484281
iter 20 value 94.484281
iter 20 value 94.484281
final value 94.484281
converged
Fitting Repeat 1
# weights: 507
initial value 95.095017
iter 10 value 94.505271
iter 20 value 93.942009
iter 30 value 84.601017
iter 40 value 83.425265
iter 50 value 83.347363
final value 83.347120
converged
Fitting Repeat 2
# weights: 507
initial value 107.842548
iter 10 value 94.493152
iter 20 value 94.437401
iter 30 value 84.423060
iter 40 value 84.299964
iter 50 value 84.297478
iter 60 value 84.262206
iter 70 value 82.690991
iter 80 value 81.682001
iter 90 value 81.628649
iter 100 value 81.603322
final value 81.603322
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 94.597380
iter 10 value 94.491833
iter 20 value 94.385792
iter 30 value 93.871830
iter 30 value 93.871830
final value 93.871827
converged
Fitting Repeat 4
# weights: 507
initial value 100.620357
iter 10 value 91.023105
iter 20 value 89.615103
iter 30 value 89.395173
iter 40 value 89.293649
iter 50 value 89.292093
iter 60 value 87.450009
iter 70 value 86.924461
iter 80 value 86.923513
iter 90 value 86.863451
iter 100 value 86.459847
final value 86.459847
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 97.646623
iter 10 value 94.493686
iter 20 value 94.486787
iter 30 value 94.475659
iter 40 value 84.238795
iter 50 value 82.733167
iter 60 value 82.285619
iter 70 value 82.282228
iter 80 value 82.268557
iter 90 value 81.828199
iter 100 value 81.306424
final value 81.306424
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 114.561442
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.675305
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.717124
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 110.222102
iter 10 value 94.275363
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 5
# weights: 103
initial value 99.531253
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 107.578934
iter 10 value 94.385584
iter 10 value 94.385584
iter 10 value 94.385584
final value 94.385584
converged
Fitting Repeat 2
# weights: 305
initial value 120.888254
final value 94.275362
converged
Fitting Repeat 3
# weights: 305
initial value 103.349170
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 113.964317
iter 10 value 94.275362
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 5
# weights: 305
initial value 96.162145
final value 94.482478
converged
Fitting Repeat 1
# weights: 507
initial value 106.511800
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 108.636122
iter 10 value 94.289636
final value 94.275362
converged
Fitting Repeat 3
# weights: 507
initial value 101.678038
final value 94.275362
converged
Fitting Repeat 4
# weights: 507
initial value 97.002960
final value 94.275362
converged
Fitting Repeat 5
# weights: 507
initial value 97.539551
iter 10 value 90.639681
iter 20 value 90.310926
iter 30 value 87.891989
iter 40 value 87.119304
iter 50 value 87.115343
iter 60 value 87.115242
iter 60 value 87.115242
iter 60 value 87.115242
final value 87.115242
converged
Fitting Repeat 1
# weights: 103
initial value 105.991591
iter 10 value 94.399008
iter 20 value 89.873410
iter 30 value 88.611534
iter 40 value 88.243681
iter 50 value 88.221295
final value 88.221291
converged
Fitting Repeat 2
# weights: 103
initial value 110.315909
iter 10 value 95.502219
iter 20 value 94.488395
iter 30 value 90.479019
iter 40 value 86.355651
iter 50 value 80.578098
iter 60 value 78.849686
iter 70 value 78.548588
iter 80 value 78.467835
iter 90 value 78.102344
iter 100 value 77.938915
final value 77.938915
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 102.707848
iter 10 value 94.439195
iter 20 value 90.091724
iter 30 value 89.581131
iter 40 value 89.570263
iter 50 value 82.028952
iter 60 value 80.605885
iter 70 value 80.360182
iter 80 value 80.163280
iter 90 value 80.135417
final value 80.135274
converged
Fitting Repeat 4
# weights: 103
initial value 99.334926
iter 10 value 94.313876
iter 20 value 84.461715
iter 30 value 81.430144
iter 40 value 79.398531
iter 50 value 78.560973
iter 60 value 78.469217
iter 70 value 78.397329
iter 80 value 78.059961
iter 90 value 77.953500
iter 100 value 77.941744
final value 77.941744
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 103.890659
iter 10 value 94.488288
iter 20 value 94.486570
iter 30 value 85.416695
iter 40 value 81.954729
iter 50 value 78.677274
iter 60 value 78.403982
iter 70 value 78.004137
iter 80 value 77.938414
iter 90 value 77.927869
iter 90 value 77.927869
iter 90 value 77.927869
final value 77.927869
converged
Fitting Repeat 1
# weights: 305
initial value 110.786898
iter 10 value 94.493973
iter 20 value 93.123275
iter 30 value 85.479608
iter 40 value 81.607805
iter 50 value 79.847579
iter 60 value 78.535845
iter 70 value 77.644438
iter 80 value 77.518476
iter 90 value 77.399483
iter 100 value 77.211913
final value 77.211913
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.023935
iter 10 value 94.072262
iter 20 value 84.836715
iter 30 value 83.676748
iter 40 value 83.463078
iter 50 value 82.130213
iter 60 value 81.617786
iter 70 value 81.506897
iter 80 value 81.394847
iter 90 value 80.657716
iter 100 value 78.664862
final value 78.664862
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.817455
iter 10 value 93.029815
iter 20 value 82.261223
iter 30 value 79.825234
iter 40 value 78.524965
iter 50 value 78.469957
iter 60 value 78.268787
iter 70 value 77.936195
iter 80 value 77.713198
iter 90 value 77.258026
iter 100 value 76.941005
final value 76.941005
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.171014
iter 10 value 94.549273
iter 20 value 93.976023
iter 30 value 84.374616
iter 40 value 80.537666
iter 50 value 80.444561
iter 60 value 78.520865
iter 70 value 77.713904
iter 80 value 77.629924
iter 90 value 77.612388
iter 100 value 77.569221
final value 77.569221
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.870377
iter 10 value 94.478646
iter 20 value 90.382241
iter 30 value 83.509986
iter 40 value 81.368118
iter 50 value 81.126639
iter 60 value 80.784299
iter 70 value 80.106286
iter 80 value 79.383959
iter 90 value 77.717130
iter 100 value 76.784101
final value 76.784101
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.651290
iter 10 value 94.760740
iter 20 value 82.535952
iter 30 value 81.387920
iter 40 value 80.532115
iter 50 value 80.405865
iter 60 value 80.152716
iter 70 value 78.453513
iter 80 value 77.727940
iter 90 value 76.928210
iter 100 value 76.682722
final value 76.682722
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 122.617778
iter 10 value 94.516185
iter 20 value 83.118868
iter 30 value 81.412830
iter 40 value 79.531734
iter 50 value 79.081802
iter 60 value 78.423922
iter 70 value 77.570586
iter 80 value 77.161747
iter 90 value 76.762499
iter 100 value 76.305793
final value 76.305793
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.688003
iter 10 value 87.041315
iter 20 value 82.396785
iter 30 value 80.076045
iter 40 value 79.685500
iter 50 value 79.115222
iter 60 value 77.915710
iter 70 value 77.569304
iter 80 value 77.386712
iter 90 value 77.341331
iter 100 value 77.231561
final value 77.231561
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.259096
iter 10 value 94.369303
iter 20 value 90.146831
iter 30 value 87.898789
iter 40 value 80.554846
iter 50 value 80.304204
iter 60 value 79.607638
iter 70 value 78.120997
iter 80 value 77.796722
iter 90 value 77.748839
iter 100 value 77.679961
final value 77.679961
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 127.276793
iter 10 value 93.877036
iter 20 value 90.305159
iter 30 value 80.301040
iter 40 value 79.245558
iter 50 value 78.043048
iter 60 value 77.688324
iter 70 value 77.370891
iter 80 value 77.064570
iter 90 value 76.495272
iter 100 value 76.297252
final value 76.297252
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.734246
final value 94.485745
converged
Fitting Repeat 2
# weights: 103
initial value 104.451412
final value 94.485873
converged
Fitting Repeat 3
# weights: 103
initial value 107.338882
final value 94.485920
converged
Fitting Repeat 4
# weights: 103
initial value 101.443129
final value 94.276796
converged
Fitting Repeat 5
# weights: 103
initial value 95.694588
final value 94.486043
converged
Fitting Repeat 1
# weights: 305
initial value 97.785397
iter 10 value 94.486271
final value 94.484296
converged
Fitting Repeat 2
# weights: 305
initial value 104.138600
iter 10 value 90.157016
iter 20 value 82.993758
iter 30 value 82.992502
iter 40 value 82.970195
iter 50 value 80.320235
iter 60 value 79.637904
iter 70 value 79.593448
iter 80 value 79.044539
iter 90 value 78.610218
iter 100 value 77.073442
final value 77.073442
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 116.580655
iter 10 value 94.280297
iter 20 value 94.276422
iter 30 value 94.273562
iter 40 value 94.271778
final value 94.271773
converged
Fitting Repeat 4
# weights: 305
initial value 96.524115
iter 10 value 94.280039
iter 20 value 94.263596
iter 30 value 88.626258
final value 88.523378
converged
Fitting Repeat 5
# weights: 305
initial value 96.021770
iter 10 value 84.221278
iter 20 value 82.720896
iter 30 value 82.580026
iter 40 value 82.438301
iter 50 value 82.377192
final value 82.377127
converged
Fitting Repeat 1
# weights: 507
initial value 105.755656
iter 10 value 94.469703
iter 20 value 93.555567
iter 30 value 89.858253
iter 40 value 89.616140
final value 89.616123
converged
Fitting Repeat 2
# weights: 507
initial value 96.660266
iter 10 value 92.528383
iter 20 value 92.232105
iter 30 value 91.671894
iter 40 value 91.463505
iter 50 value 91.397059
iter 60 value 91.363654
final value 91.363621
converged
Fitting Repeat 3
# weights: 507
initial value 101.543444
iter 10 value 94.283182
iter 20 value 94.275706
iter 30 value 81.361666
iter 40 value 80.536254
iter 50 value 78.418182
iter 60 value 78.272044
iter 70 value 78.271109
iter 80 value 78.270210
iter 80 value 78.270210
final value 78.270207
converged
Fitting Repeat 4
# weights: 507
initial value 126.270153
iter 10 value 94.492951
iter 20 value 94.485020
iter 30 value 93.392585
iter 40 value 79.006964
iter 50 value 78.514077
iter 60 value 78.498254
final value 78.496880
converged
Fitting Repeat 5
# weights: 507
initial value 111.158804
iter 10 value 94.492358
iter 20 value 94.452140
iter 30 value 89.344263
iter 40 value 87.700225
iter 50 value 87.613907
iter 60 value 87.559668
iter 70 value 87.495848
iter 80 value 87.494220
iter 90 value 87.462621
iter 100 value 87.430825
final value 87.430825
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.475984
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 100.554083
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 96.465886
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 96.752445
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 101.290906
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 103.094352
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 128.617645
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 108.206214
final value 94.032967
converged
Fitting Repeat 4
# weights: 305
initial value 97.372552
final value 94.050051
converged
Fitting Repeat 5
# weights: 305
initial value 95.137413
final value 94.032967
converged
Fitting Repeat 1
# weights: 507
initial value 110.687223
iter 10 value 91.591228
iter 20 value 91.590957
final value 91.590949
converged
Fitting Repeat 2
# weights: 507
initial value 128.036534
iter 10 value 93.278311
final value 93.278282
converged
Fitting Repeat 3
# weights: 507
initial value 117.607266
iter 10 value 92.774643
iter 20 value 87.614966
iter 30 value 83.097103
iter 40 value 81.946557
iter 50 value 81.769801
iter 60 value 81.768071
final value 81.767891
converged
Fitting Repeat 4
# weights: 507
initial value 98.638908
final value 94.052911
converged
Fitting Repeat 5
# weights: 507
initial value 95.374167
iter 10 value 93.811188
iter 20 value 93.811150
iter 20 value 93.811149
iter 20 value 93.811149
final value 93.811149
converged
Fitting Repeat 1
# weights: 103
initial value 107.263717
iter 10 value 93.984369
iter 20 value 93.527409
iter 30 value 87.444499
iter 40 value 84.604083
iter 50 value 83.641298
iter 60 value 82.850604
iter 70 value 82.536419
iter 80 value 82.355927
final value 82.355741
converged
Fitting Repeat 2
# weights: 103
initial value 99.071263
iter 10 value 94.032942
iter 20 value 85.992246
iter 30 value 84.810886
iter 40 value 84.438663
iter 50 value 84.187784
iter 60 value 83.261706
iter 70 value 82.773467
iter 80 value 82.296762
iter 90 value 82.205531
iter 100 value 82.202889
final value 82.202889
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.356469
iter 10 value 94.054943
iter 20 value 93.862660
iter 30 value 93.246029
iter 40 value 93.043899
iter 50 value 93.010896
iter 60 value 89.059295
iter 70 value 85.068428
iter 80 value 83.453931
iter 90 value 82.715449
iter 100 value 82.220547
final value 82.220547
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 111.833204
iter 10 value 94.009552
iter 20 value 93.579599
iter 30 value 92.924136
iter 40 value 85.953422
iter 50 value 85.334196
iter 60 value 85.024685
iter 70 value 84.626979
iter 80 value 83.863374
iter 90 value 83.298079
iter 100 value 82.341088
final value 82.341088
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 105.508315
iter 10 value 93.876679
iter 20 value 87.382293
iter 30 value 85.792505
iter 40 value 85.658868
iter 50 value 85.571202
iter 60 value 85.533219
iter 70 value 85.531528
iter 80 value 85.524326
final value 85.522935
converged
Fitting Repeat 1
# weights: 305
initial value 101.606735
iter 10 value 94.053660
iter 20 value 87.701952
iter 30 value 85.451801
iter 40 value 82.864490
iter 50 value 82.450979
iter 60 value 82.416732
iter 70 value 82.297844
iter 80 value 82.097168
iter 90 value 81.901078
iter 100 value 81.380564
final value 81.380564
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 120.380787
iter 10 value 94.112885
iter 20 value 88.691928
iter 30 value 86.467655
iter 40 value 86.045328
iter 50 value 85.675346
iter 60 value 85.530594
iter 70 value 85.435232
iter 80 value 84.921714
iter 90 value 83.338343
iter 100 value 82.732019
final value 82.732019
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.225392
iter 10 value 95.965682
iter 20 value 93.893253
iter 30 value 89.895392
iter 40 value 87.053918
iter 50 value 83.665686
iter 60 value 82.982704
iter 70 value 81.813853
iter 80 value 81.642130
iter 90 value 81.293583
iter 100 value 80.958865
final value 80.958865
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.981525
iter 10 value 93.494093
iter 20 value 88.849403
iter 30 value 84.055850
iter 40 value 83.600009
iter 50 value 82.982228
iter 60 value 82.330329
iter 70 value 81.506337
iter 80 value 81.196621
iter 90 value 80.651283
iter 100 value 80.568982
final value 80.568982
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.978663
iter 10 value 93.598917
iter 20 value 92.009949
iter 30 value 89.726422
iter 40 value 88.819345
iter 50 value 86.955029
iter 60 value 85.448011
iter 70 value 84.813340
iter 80 value 83.957514
iter 90 value 83.694660
iter 100 value 82.454613
final value 82.454613
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 126.579489
iter 10 value 96.338389
iter 20 value 92.472169
iter 30 value 86.770552
iter 40 value 84.819561
iter 50 value 84.075594
iter 60 value 82.064533
iter 70 value 81.764148
iter 80 value 81.463369
iter 90 value 81.106469
iter 100 value 80.677284
final value 80.677284
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.099751
iter 10 value 95.819074
iter 20 value 88.532216
iter 30 value 86.783147
iter 40 value 85.395410
iter 50 value 85.279854
iter 60 value 84.496605
iter 70 value 82.506911
iter 80 value 81.585478
iter 90 value 81.349423
iter 100 value 81.234190
final value 81.234190
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 134.871706
iter 10 value 94.764440
iter 20 value 94.060456
iter 30 value 93.641523
iter 40 value 89.073911
iter 50 value 85.595912
iter 60 value 84.479726
iter 70 value 82.604395
iter 80 value 82.110831
iter 90 value 81.869973
iter 100 value 81.741747
final value 81.741747
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.111856
iter 10 value 94.494073
iter 20 value 93.051921
iter 30 value 86.731491
iter 40 value 86.052811
iter 50 value 84.172351
iter 60 value 83.251907
iter 70 value 82.503241
iter 80 value 82.001631
iter 90 value 81.619355
iter 100 value 81.320236
final value 81.320236
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.577159
iter 10 value 95.023850
iter 20 value 91.394692
iter 30 value 88.723712
iter 40 value 83.908906
iter 50 value 83.026540
iter 60 value 82.439262
iter 70 value 81.637939
iter 80 value 81.322616
iter 90 value 80.860649
iter 100 value 80.825937
final value 80.825937
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.081344
iter 10 value 94.054493
iter 20 value 94.053006
iter 30 value 93.850499
iter 40 value 91.188638
iter 50 value 85.405923
iter 60 value 85.272842
iter 70 value 84.862070
iter 80 value 84.704128
iter 90 value 84.223467
iter 100 value 84.220506
final value 84.220506
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.525035
final value 94.054606
converged
Fitting Repeat 3
# weights: 103
initial value 103.332692
final value 94.054422
converged
Fitting Repeat 4
# weights: 103
initial value 104.016709
final value 94.054335
converged
Fitting Repeat 5
# weights: 103
initial value 101.142217
iter 10 value 94.054647
iter 20 value 94.052124
iter 30 value 93.290127
iter 30 value 93.290126
iter 30 value 93.290126
final value 93.290126
converged
Fitting Repeat 1
# weights: 305
initial value 95.686192
iter 10 value 94.057359
iter 20 value 94.050878
iter 30 value 93.922068
iter 40 value 86.645010
iter 50 value 86.010471
final value 86.010402
converged
Fitting Repeat 2
# weights: 305
initial value 96.244428
iter 10 value 90.592299
iter 20 value 87.502323
iter 30 value 87.311371
iter 40 value 87.308211
iter 50 value 87.306764
final value 87.306645
converged
Fitting Repeat 3
# weights: 305
initial value 101.174445
iter 10 value 94.057367
iter 20 value 94.044904
iter 30 value 92.850103
iter 40 value 89.182267
iter 50 value 83.969409
iter 60 value 83.045462
iter 70 value 82.843399
iter 80 value 82.682820
iter 90 value 82.646541
final value 82.646526
converged
Fitting Repeat 4
# weights: 305
initial value 94.075563
final value 94.058326
converged
Fitting Repeat 5
# weights: 305
initial value 104.042887
iter 10 value 94.058808
iter 20 value 94.053831
iter 30 value 89.885054
iter 40 value 87.038910
iter 50 value 85.213964
iter 60 value 83.941747
iter 70 value 83.226535
iter 80 value 82.632673
iter 90 value 82.419396
iter 100 value 82.418580
final value 82.418580
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.653363
iter 10 value 94.060785
iter 20 value 94.051705
iter 30 value 86.024163
iter 40 value 85.097090
iter 50 value 85.079511
iter 60 value 85.078697
iter 60 value 85.078697
final value 85.078697
converged
Fitting Repeat 2
# weights: 507
initial value 114.233118
iter 10 value 94.060958
iter 20 value 93.919127
iter 30 value 87.823649
iter 40 value 85.947070
iter 50 value 85.846678
iter 60 value 83.378484
iter 70 value 81.612137
iter 80 value 80.704119
iter 90 value 80.005101
iter 100 value 79.854227
final value 79.854227
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 95.367239
iter 10 value 93.499696
iter 20 value 93.493910
iter 30 value 93.429219
iter 40 value 92.893565
iter 40 value 92.893565
iter 40 value 92.893565
final value 92.893565
converged
Fitting Repeat 4
# weights: 507
initial value 100.222192
iter 10 value 89.804561
iter 20 value 86.053732
iter 30 value 86.039110
iter 40 value 85.891765
iter 50 value 85.887408
iter 60 value 85.406849
iter 70 value 85.365318
final value 85.364842
converged
Fitting Repeat 5
# weights: 507
initial value 97.090587
iter 10 value 93.864086
iter 20 value 93.819299
iter 30 value 93.541149
iter 40 value 88.980006
iter 50 value 88.072376
iter 60 value 87.146306
iter 70 value 87.076871
iter 80 value 87.071190
iter 90 value 84.715575
iter 100 value 83.698963
final value 83.698963
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.761445
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 96.987161
final value 92.892737
converged
Fitting Repeat 3
# weights: 103
initial value 101.661377
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 100.107619
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 97.751174
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 102.132267
final value 94.052911
converged
Fitting Repeat 2
# weights: 305
initial value 95.485314
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 97.355378
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 103.874159
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 94.940306
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 99.990235
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 118.156875
final value 94.025289
converged
Fitting Repeat 3
# weights: 507
initial value 106.805969
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 105.514155
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 105.511319
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 99.075475
iter 10 value 94.056330
iter 20 value 92.756717
iter 30 value 85.846445
iter 40 value 84.321485
iter 50 value 83.654899
iter 60 value 82.923764
iter 70 value 82.821454
iter 80 value 82.813711
iter 90 value 82.813192
iter 100 value 82.812232
final value 82.812232
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.445818
iter 10 value 94.056080
iter 20 value 93.202506
iter 30 value 85.800664
iter 40 value 83.983839
iter 50 value 83.224530
iter 60 value 82.819718
final value 82.812087
converged
Fitting Repeat 3
# weights: 103
initial value 102.476192
iter 10 value 94.274435
iter 20 value 91.232693
iter 30 value 83.783878
iter 40 value 83.419175
iter 50 value 82.908986
iter 60 value 82.667308
iter 70 value 82.601834
final value 82.601789
converged
Fitting Repeat 4
# weights: 103
initial value 101.557700
iter 10 value 93.890724
iter 20 value 84.092752
iter 30 value 83.213141
iter 40 value 83.008437
iter 50 value 82.787227
iter 60 value 82.601237
iter 70 value 82.525620
final value 82.525515
converged
Fitting Repeat 5
# weights: 103
initial value 108.589867
iter 10 value 94.023079
iter 20 value 93.635701
iter 30 value 93.529184
iter 40 value 93.262786
iter 50 value 87.628508
iter 60 value 85.399247
iter 70 value 84.207080
iter 80 value 82.374002
iter 90 value 81.393183
iter 100 value 81.171750
final value 81.171750
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 116.619381
iter 10 value 94.030266
iter 20 value 93.326679
iter 30 value 92.717008
iter 40 value 84.841453
iter 50 value 83.880827
iter 60 value 83.571531
iter 70 value 83.222794
iter 80 value 83.129005
iter 90 value 82.976718
iter 100 value 82.308128
final value 82.308128
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.468711
iter 10 value 92.900302
iter 20 value 87.468569
iter 30 value 86.912178
iter 40 value 85.545746
iter 50 value 82.411528
iter 60 value 80.569346
iter 70 value 80.015681
iter 80 value 79.704409
iter 90 value 79.351053
iter 100 value 79.343072
final value 79.343072
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.759334
iter 10 value 94.033868
iter 20 value 93.256201
iter 30 value 86.799004
iter 40 value 86.256773
iter 50 value 83.020993
iter 60 value 82.731310
iter 70 value 82.630021
iter 80 value 82.593813
iter 90 value 82.495231
iter 100 value 80.849402
final value 80.849402
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 117.495746
iter 10 value 94.099536
iter 20 value 85.582205
iter 30 value 85.193740
iter 40 value 83.263979
iter 50 value 83.224968
iter 60 value 81.269842
iter 70 value 79.897715
iter 80 value 79.394035
iter 90 value 79.210410
iter 100 value 79.116857
final value 79.116857
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.081345
iter 10 value 94.177316
iter 20 value 87.187648
iter 30 value 85.988388
iter 40 value 83.962199
iter 50 value 82.117484
iter 60 value 80.404418
iter 70 value 79.959817
iter 80 value 79.360202
iter 90 value 79.207582
iter 100 value 79.188896
final value 79.188896
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.050483
iter 10 value 93.700556
iter 20 value 92.694630
iter 30 value 86.566622
iter 40 value 84.516555
iter 50 value 83.382606
iter 60 value 81.889964
iter 70 value 81.756350
iter 80 value 81.667566
iter 90 value 80.959712
iter 100 value 79.694316
final value 79.694316
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 122.740218
iter 10 value 101.368066
iter 20 value 99.673188
iter 30 value 97.149008
iter 40 value 96.179287
iter 50 value 89.449299
iter 60 value 86.607091
iter 70 value 83.999547
iter 80 value 83.320164
iter 90 value 83.084734
iter 100 value 82.640687
final value 82.640687
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 121.802550
iter 10 value 93.744635
iter 20 value 88.950124
iter 30 value 85.106267
iter 40 value 83.429791
iter 50 value 83.168003
iter 60 value 82.247689
iter 70 value 80.798856
iter 80 value 80.629196
iter 90 value 80.486980
iter 100 value 79.847531
final value 79.847531
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.222467
iter 10 value 93.328701
iter 20 value 92.933965
iter 30 value 86.566919
iter 40 value 85.621970
iter 50 value 83.279633
iter 60 value 82.763896
iter 70 value 82.507041
iter 80 value 82.256144
iter 90 value 81.357039
iter 100 value 81.208982
final value 81.208982
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 130.484854
iter 10 value 93.461780
iter 20 value 88.418123
iter 30 value 87.559237
iter 40 value 84.513935
iter 50 value 83.263688
iter 60 value 80.875967
iter 70 value 80.585214
iter 80 value 80.422075
iter 90 value 80.307807
iter 100 value 80.181462
final value 80.181462
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.194702
final value 94.054429
converged
Fitting Repeat 2
# weights: 103
initial value 95.608381
final value 94.054652
converged
Fitting Repeat 3
# weights: 103
initial value 127.818247
final value 94.054657
converged
Fitting Repeat 4
# weights: 103
initial value 96.584755
final value 94.054779
converged
Fitting Repeat 5
# weights: 103
initial value 96.704755
iter 10 value 93.601989
iter 20 value 93.413018
final value 93.393337
converged
Fitting Repeat 1
# weights: 305
initial value 103.160413
iter 10 value 94.058136
iter 20 value 94.022594
iter 30 value 92.894244
iter 30 value 92.894244
iter 30 value 92.894244
final value 92.894244
converged
Fitting Repeat 2
# weights: 305
initial value 96.045531
iter 10 value 93.841225
iter 20 value 93.810917
iter 30 value 91.129293
iter 40 value 87.206738
iter 50 value 87.144225
iter 50 value 87.144225
iter 50 value 87.144225
final value 87.144225
converged
Fitting Repeat 3
# weights: 305
initial value 122.149754
iter 10 value 94.058405
iter 20 value 94.045312
iter 30 value 88.091275
iter 40 value 87.452872
iter 50 value 87.452745
iter 50 value 87.452744
iter 50 value 87.452744
final value 87.452744
converged
Fitting Repeat 4
# weights: 305
initial value 115.211830
iter 10 value 94.057280
iter 20 value 94.052859
iter 30 value 93.041288
iter 40 value 84.580481
iter 50 value 82.452632
iter 60 value 82.416162
iter 70 value 82.415586
iter 80 value 82.332626
iter 90 value 80.911824
iter 100 value 78.182162
final value 78.182162
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 122.421423
iter 10 value 94.057550
iter 20 value 94.039918
iter 30 value 93.619697
final value 93.473899
converged
Fitting Repeat 1
# weights: 507
initial value 102.294000
iter 10 value 93.844273
iter 20 value 93.827898
iter 30 value 86.264271
iter 40 value 82.588278
iter 50 value 82.301266
iter 60 value 82.172303
iter 70 value 82.106231
iter 80 value 82.041894
iter 90 value 82.040439
iter 100 value 82.040089
final value 82.040089
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 101.977227
iter 10 value 93.269232
iter 20 value 92.467788
iter 30 value 92.425805
iter 40 value 92.094970
iter 50 value 92.052488
iter 60 value 92.051119
iter 70 value 92.049388
iter 80 value 92.046292
iter 90 value 92.045174
iter 100 value 92.039025
final value 92.039025
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 134.932613
iter 10 value 93.844719
iter 20 value 93.839273
iter 30 value 93.838435
iter 40 value 92.026483
iter 50 value 87.585619
final value 87.585552
converged
Fitting Repeat 4
# weights: 507
initial value 94.819144
iter 10 value 93.844110
iter 20 value 93.472007
iter 30 value 93.391926
final value 93.391923
converged
Fitting Repeat 5
# weights: 507
initial value 101.574497
iter 10 value 93.115162
iter 20 value 93.112984
iter 30 value 93.105197
iter 40 value 93.102745
iter 50 value 91.817428
iter 60 value 89.628382
iter 70 value 84.113345
iter 80 value 80.370845
iter 90 value 78.984981
iter 100 value 78.330533
final value 78.330533
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 105.504357
final value 94.484137
converged
Fitting Repeat 2
# weights: 103
initial value 95.576559
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.511077
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 94.583826
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 99.160120
iter 10 value 94.313817
iter 10 value 94.313817
iter 10 value 94.313817
final value 94.313817
converged
Fitting Repeat 1
# weights: 305
initial value 97.471723
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 113.593053
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 97.878685
iter 10 value 93.768039
iter 20 value 92.934294
iter 30 value 92.563052
iter 40 value 92.557709
final value 92.557651
converged
Fitting Repeat 4
# weights: 305
initial value 99.483937
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 96.777001
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 110.643129
final value 94.400000
converged
Fitting Repeat 2
# weights: 507
initial value 109.973333
iter 10 value 94.277989
iter 10 value 94.277989
iter 10 value 94.277989
final value 94.277989
converged
Fitting Repeat 3
# weights: 507
initial value 117.358274
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 98.383074
iter 10 value 93.057489
final value 92.898987
converged
Fitting Repeat 5
# weights: 507
initial value 106.575655
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 105.793632
iter 10 value 94.490023
iter 20 value 88.402138
iter 30 value 85.207761
iter 40 value 84.779181
iter 50 value 84.559157
iter 60 value 83.752526
iter 70 value 83.426495
iter 80 value 83.096157
iter 90 value 83.041247
final value 83.041230
converged
Fitting Repeat 2
# weights: 103
initial value 121.779186
iter 10 value 94.486430
iter 20 value 93.694763
iter 30 value 88.722726
iter 40 value 88.646697
iter 50 value 87.831930
iter 60 value 85.055089
iter 70 value 83.727009
iter 80 value 83.449763
iter 90 value 83.227088
iter 100 value 83.051383
final value 83.051383
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 105.060657
iter 10 value 94.484373
iter 20 value 90.702135
iter 30 value 87.438360
iter 40 value 86.848160
iter 50 value 86.469878
iter 60 value 86.330755
iter 70 value 86.223121
iter 80 value 86.167250
iter 90 value 86.165176
final value 86.165140
converged
Fitting Repeat 4
# weights: 103
initial value 98.330359
iter 10 value 94.486745
iter 20 value 94.429057
iter 30 value 90.120450
iter 40 value 86.018913
iter 50 value 85.573446
iter 60 value 85.138141
iter 70 value 85.002693
iter 80 value 84.861012
iter 90 value 84.619673
iter 100 value 84.535150
final value 84.535150
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 98.830259
iter 10 value 94.506662
iter 20 value 94.488608
iter 30 value 94.117518
iter 40 value 86.354656
iter 50 value 85.920666
iter 60 value 85.450260
iter 70 value 84.785713
iter 80 value 84.736781
iter 80 value 84.736781
iter 80 value 84.736781
final value 84.736781
converged
Fitting Repeat 1
# weights: 305
initial value 105.881491
iter 10 value 94.500948
iter 20 value 94.433212
iter 30 value 92.262638
iter 40 value 88.511511
iter 50 value 88.293019
iter 60 value 87.448317
iter 70 value 87.263291
iter 80 value 87.107861
iter 90 value 84.128060
iter 100 value 83.292302
final value 83.292302
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.950214
iter 10 value 94.467309
iter 20 value 94.401349
iter 30 value 90.316947
iter 40 value 86.023227
iter 50 value 84.396478
iter 60 value 83.418918
iter 70 value 82.676282
iter 80 value 82.447519
iter 90 value 82.184711
iter 100 value 82.081221
final value 82.081221
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.229321
iter 10 value 94.504564
iter 20 value 93.692278
iter 30 value 88.285527
iter 40 value 87.325384
iter 50 value 87.024893
iter 60 value 85.787311
iter 70 value 84.844382
iter 80 value 84.681755
iter 90 value 84.464409
iter 100 value 84.053976
final value 84.053976
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 115.420742
iter 10 value 94.527796
iter 20 value 90.942221
iter 30 value 87.237957
iter 40 value 85.711907
iter 50 value 84.985395
iter 60 value 83.654558
iter 70 value 82.845902
iter 80 value 82.586185
iter 90 value 82.472392
iter 100 value 82.172144
final value 82.172144
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.628602
iter 10 value 94.510534
iter 20 value 94.428880
iter 30 value 88.443754
iter 40 value 86.115832
iter 50 value 85.892828
iter 60 value 85.722995
iter 70 value 85.573156
iter 80 value 85.238552
iter 90 value 84.865076
iter 100 value 83.564654
final value 83.564654
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 115.455654
iter 10 value 94.900038
iter 20 value 91.169213
iter 30 value 88.483568
iter 40 value 87.898405
iter 50 value 87.820245
iter 60 value 86.525874
iter 70 value 84.224155
iter 80 value 83.820871
iter 90 value 83.498311
iter 100 value 83.135424
final value 83.135424
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.802879
iter 10 value 94.642705
iter 20 value 93.763815
iter 30 value 89.257832
iter 40 value 88.502550
iter 50 value 87.833838
iter 60 value 86.998540
iter 70 value 86.351202
iter 80 value 85.845418
iter 90 value 85.483521
iter 100 value 85.343182
final value 85.343182
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.954265
iter 10 value 94.521783
iter 20 value 92.340962
iter 30 value 86.002182
iter 40 value 85.520304
iter 50 value 84.697388
iter 60 value 83.355559
iter 70 value 82.698538
iter 80 value 82.181749
iter 90 value 81.772375
iter 100 value 81.539010
final value 81.539010
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.750813
iter 10 value 94.971822
iter 20 value 94.512814
iter 30 value 90.023596
iter 40 value 86.194815
iter 50 value 85.465831
iter 60 value 83.237118
iter 70 value 82.559128
iter 80 value 82.275142
iter 90 value 82.090797
iter 100 value 81.992066
final value 81.992066
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.561956
iter 10 value 95.370691
iter 20 value 88.447305
iter 30 value 85.322659
iter 40 value 82.988003
iter 50 value 82.296931
iter 60 value 81.898960
iter 70 value 81.443963
iter 80 value 81.356695
iter 90 value 81.318088
iter 100 value 81.283199
final value 81.283199
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.137294
iter 10 value 89.479233
iter 20 value 88.452433
iter 30 value 88.450929
iter 40 value 88.181659
iter 50 value 88.159552
final value 88.159407
converged
Fitting Repeat 2
# weights: 103
initial value 100.505914
final value 94.485892
converged
Fitting Repeat 3
# weights: 103
initial value 96.187027
final value 94.485982
converged
Fitting Repeat 4
# weights: 103
initial value 97.009640
final value 94.485817
converged
Fitting Repeat 5
# weights: 103
initial value 99.795953
iter 10 value 93.615592
iter 20 value 93.449686
iter 30 value 93.407309
final value 93.407303
converged
Fitting Repeat 1
# weights: 305
initial value 101.403480
iter 10 value 94.491747
iter 20 value 88.303363
iter 30 value 85.522469
iter 40 value 85.459788
iter 50 value 85.455905
final value 85.455825
converged
Fitting Repeat 2
# weights: 305
initial value 114.317491
iter 10 value 94.489161
iter 20 value 94.480062
iter 30 value 86.569967
iter 40 value 86.022126
final value 86.019109
converged
Fitting Repeat 3
# weights: 305
initial value 102.514380
iter 10 value 94.274133
iter 20 value 92.981908
iter 30 value 92.979301
iter 40 value 92.979097
iter 50 value 92.978575
iter 50 value 92.978574
iter 60 value 92.978377
iter 70 value 92.977152
iter 80 value 91.469408
iter 90 value 91.437335
iter 100 value 91.428393
final value 91.428393
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.834226
iter 10 value 94.488552
iter 20 value 92.256365
iter 30 value 88.308598
iter 40 value 88.283951
final value 88.283678
converged
Fitting Repeat 5
# weights: 305
initial value 105.551429
iter 10 value 94.490626
iter 20 value 94.102081
iter 30 value 85.846679
iter 40 value 85.457162
iter 50 value 85.456243
iter 60 value 85.454642
iter 70 value 85.453204
iter 80 value 85.451917
iter 90 value 85.451768
final value 85.451678
converged
Fitting Repeat 1
# weights: 507
initial value 98.536524
iter 10 value 94.450843
iter 20 value 94.445342
final value 94.444656
converged
Fitting Repeat 2
# weights: 507
initial value 114.419128
iter 10 value 94.492338
iter 20 value 94.440226
iter 30 value 87.316756
iter 40 value 86.958613
iter 50 value 86.941403
iter 60 value 86.802349
iter 70 value 84.245609
iter 80 value 82.592370
iter 90 value 81.894535
iter 100 value 81.827597
final value 81.827597
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 96.487005
iter 10 value 87.185706
iter 20 value 85.578186
iter 30 value 85.457329
iter 40 value 85.456329
iter 50 value 85.440907
iter 60 value 84.408186
iter 70 value 84.289099
iter 80 value 84.287375
iter 90 value 84.287074
final value 84.287012
converged
Fitting Repeat 4
# weights: 507
initial value 111.225713
iter 10 value 94.493080
iter 20 value 94.480175
iter 30 value 86.165265
iter 40 value 85.511756
iter 50 value 85.468923
iter 60 value 85.450290
iter 70 value 85.450191
iter 80 value 85.449939
iter 90 value 85.340445
iter 100 value 85.245199
final value 85.245199
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 100.288184
iter 10 value 94.492541
iter 20 value 94.465685
iter 30 value 88.804244
iter 40 value 85.558582
iter 50 value 85.510819
iter 60 value 85.486916
iter 70 value 85.480654
iter 80 value 85.452831
final value 85.449778
converged
Fitting Repeat 1
# weights: 305
initial value 122.066949
iter 10 value 111.211825
iter 20 value 111.164482
iter 30 value 108.297116
iter 40 value 107.194193
iter 50 value 107.185895
iter 60 value 107.149863
iter 70 value 106.715864
iter 80 value 105.082798
iter 90 value 102.412598
iter 100 value 101.521632
final value 101.521632
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 136.330666
iter 10 value 117.210862
iter 20 value 116.398001
iter 30 value 111.137629
iter 40 value 109.947345
iter 50 value 109.894169
iter 60 value 109.836875
iter 70 value 109.713721
iter 80 value 109.155036
iter 90 value 108.356317
iter 100 value 108.324610
final value 108.324610
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 121.943055
iter 10 value 117.895217
iter 20 value 117.575633
iter 30 value 117.511390
iter 30 value 117.511390
iter 30 value 117.511390
final value 117.511390
converged
Fitting Repeat 4
# weights: 305
initial value 139.827198
iter 10 value 117.895489
iter 20 value 117.890571
iter 30 value 117.792446
iter 40 value 113.327350
iter 50 value 107.467473
iter 60 value 106.281659
iter 70 value 104.254478
iter 80 value 103.673694
iter 90 value 101.921819
iter 100 value 101.489810
final value 101.489810
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 139.134897
iter 10 value 117.896295
iter 20 value 117.893108
iter 30 value 117.409483
iter 40 value 116.884601
final value 116.884586
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 -- Fri Apr 17 04:25:20 2026
***********************************************
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
55.596 1.706 124.837
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 36.469 | 0.367 | 36.924 | |
| FreqInteractors | 0.597 | 0.028 | 0.629 | |
| calculateAAC | 0.044 | 0.000 | 0.045 | |
| calculateAutocor | 0.643 | 0.020 | 0.667 | |
| calculateCTDC | 0.092 | 0.000 | 0.092 | |
| calculateCTDD | 0.727 | 0.004 | 0.733 | |
| calculateCTDT | 0.259 | 0.000 | 0.261 | |
| calculateCTriad | 0.439 | 0.004 | 0.444 | |
| calculateDC | 0.127 | 0.004 | 0.132 | |
| calculateF | 0.446 | 0.000 | 0.446 | |
| calculateKSAAP | 0.153 | 0.000 | 0.154 | |
| calculateQD_Sm | 2.264 | 0.004 | 2.273 | |
| calculateTC | 2.356 | 0.032 | 2.394 | |
| calculateTC_Sm | 0.326 | 0.000 | 0.327 | |
| corr_plot | 37.399 | 0.211 | 37.696 | |
| enrichfindP | 0.569 | 0.008 | 22.238 | |
| enrichfind_hp | 0.056 | 0.000 | 2.431 | |
| enrichplot | 0.712 | 0.012 | 0.943 | |
| filter_missing_values | 0.002 | 0.000 | 0.001 | |
| getFASTA | 0.091 | 0.024 | 6.317 | |
| getHPI | 0.000 | 0.001 | 0.002 | |
| get_negativePPI | 0.004 | 0.001 | 0.005 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.002 | 0.002 | 0.003 | |
| plotPPI | 0.073 | 0.054 | 0.127 | |
| pred_ensembel | 18.350 | 0.731 | 17.992 | |
| var_imp | 38.067 | 0.455 | 38.748 | |