Matineh Rahmatbakhsh
| Snapshot Date: 2026-04-03 13:45 -0400 (Fri, 03 Apr 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_22 |
| git_last_commit: 6cf0d22 |
| git_last_commit_date: 2025-12-28 18:31:13 -0400 (Sun, 28 Dec 2025) |
| Back to Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-04-04 11:57 -0400 (Sat, 04 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4897 |
| 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 1006/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.16.1 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | 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. |
| Package: HPiP |
| Version: 1.16.1 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz |
| StartedAt: 2026-04-04 00:21:07 -0400 (Sat, 04 Apr 2026) |
| EndedAt: 2026-04-04 00:36:16 -0400 (Sat, 04 Apr 2026) |
| EllapsedTime: 909.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.2 (2025-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.16.1’
* 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
corr_plot 33.550 0.396 33.948
var_imp 33.429 0.492 33.921
FSmethod 32.839 0.545 33.385
pred_ensembel 13.034 0.134 11.851
enrichfindP 0.519 0.034 17.980
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.16.1’ ** 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 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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 95.615192
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 103.841346
iter 10 value 87.551753
iter 20 value 86.963768
final value 86.955823
converged
Fitting Repeat 3
# weights: 103
initial value 111.894587
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.686261
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.066552
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 100.422681
iter 10 value 93.900640
iter 20 value 92.451327
iter 30 value 92.383300
final value 92.383221
converged
Fitting Repeat 2
# weights: 305
initial value 101.228911
iter 10 value 94.416003
iter 20 value 94.414730
iter 20 value 94.414729
iter 20 value 94.414729
final value 94.414729
converged
Fitting Repeat 3
# weights: 305
initial value 110.518912
final value 94.467391
converged
Fitting Repeat 4
# weights: 305
initial value 96.768375
final value 94.484210
converged
Fitting Repeat 5
# weights: 305
initial value 127.497181
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 96.410384
iter 10 value 94.414729
iter 10 value 94.414729
iter 10 value 94.414729
final value 94.414729
converged
Fitting Repeat 2
# weights: 507
initial value 105.793356
iter 10 value 94.467391
iter 10 value 94.467391
iter 10 value 94.467391
final value 94.467391
converged
Fitting Repeat 3
# weights: 507
initial value 112.919070
iter 10 value 88.322906
iter 20 value 87.291051
iter 30 value 87.284437
final value 87.284404
converged
Fitting Repeat 4
# weights: 507
initial value 107.958371
final value 94.022727
converged
Fitting Repeat 5
# weights: 507
initial value 111.172750
iter 10 value 94.467569
final value 94.467392
converged
Fitting Repeat 1
# weights: 103
initial value 104.843196
iter 10 value 94.440707
iter 20 value 89.806695
iter 30 value 89.387813
iter 40 value 86.391317
iter 50 value 86.021320
iter 60 value 85.962784
iter 70 value 85.938176
iter 80 value 85.598076
iter 90 value 85.445692
final value 85.445358
converged
Fitting Repeat 2
# weights: 103
initial value 97.920605
iter 10 value 89.113078
iter 20 value 86.028194
iter 30 value 84.974664
iter 40 value 84.920385
iter 50 value 84.884430
final value 84.882750
converged
Fitting Repeat 3
# weights: 103
initial value 107.357483
iter 10 value 94.490346
iter 20 value 93.714599
iter 30 value 90.230027
iter 40 value 89.523313
iter 50 value 88.360012
iter 60 value 84.798297
iter 70 value 83.916546
iter 80 value 83.315894
final value 83.312379
converged
Fitting Repeat 4
# weights: 103
initial value 97.862786
iter 10 value 94.495956
iter 20 value 94.424245
iter 30 value 89.752935
iter 40 value 88.814958
iter 50 value 85.688629
iter 60 value 85.240659
iter 70 value 85.190608
iter 80 value 85.129482
final value 85.128643
converged
Fitting Repeat 5
# weights: 103
initial value 96.404323
iter 10 value 94.442992
iter 20 value 92.881790
iter 30 value 89.979104
iter 40 value 85.537106
iter 50 value 85.433963
iter 60 value 85.272452
iter 70 value 85.154631
iter 80 value 84.832420
final value 84.832124
converged
Fitting Repeat 1
# weights: 305
initial value 123.380988
iter 10 value 94.606231
iter 20 value 94.210707
iter 30 value 90.648695
iter 40 value 86.898367
iter 50 value 84.443203
iter 60 value 84.077306
iter 70 value 82.841867
iter 80 value 81.677504
iter 90 value 81.563260
iter 100 value 81.528428
final value 81.528428
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 127.703411
iter 10 value 94.656735
iter 20 value 86.449864
iter 30 value 86.114576
iter 40 value 85.382188
iter 50 value 84.933024
iter 60 value 83.334047
iter 70 value 82.536808
iter 80 value 82.411247
iter 90 value 82.355357
iter 100 value 82.311033
final value 82.311033
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.989024
iter 10 value 94.547633
iter 20 value 93.606807
iter 30 value 89.419441
iter 40 value 85.628853
iter 50 value 83.014784
iter 60 value 82.050795
iter 70 value 81.728748
iter 80 value 81.609089
iter 90 value 81.421393
iter 100 value 81.357800
final value 81.357800
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.881417
iter 10 value 94.436661
iter 20 value 88.635771
iter 30 value 86.491754
iter 40 value 82.981633
iter 50 value 82.710748
iter 60 value 82.632753
iter 70 value 82.545085
iter 80 value 82.107792
iter 90 value 81.937285
iter 100 value 81.904091
final value 81.904091
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.879570
iter 10 value 94.465473
iter 20 value 92.036831
iter 30 value 87.441662
iter 40 value 87.295263
iter 50 value 85.490998
iter 60 value 83.978001
iter 70 value 82.476640
iter 80 value 81.942663
iter 90 value 81.863450
iter 100 value 81.613858
final value 81.613858
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 108.623152
iter 10 value 94.871460
iter 20 value 94.499878
iter 30 value 89.551735
iter 40 value 85.076681
iter 50 value 84.463062
iter 60 value 84.333072
iter 70 value 83.811474
iter 80 value 83.421149
iter 90 value 82.886827
iter 100 value 82.845076
final value 82.845076
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.731757
iter 10 value 94.597991
iter 20 value 94.355807
iter 30 value 93.058623
iter 40 value 88.526905
iter 50 value 85.184065
iter 60 value 84.098033
iter 70 value 82.986957
iter 80 value 82.358175
iter 90 value 81.971615
iter 100 value 81.843494
final value 81.843494
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 107.552392
iter 10 value 95.717930
iter 20 value 93.278595
iter 30 value 87.646445
iter 40 value 87.273827
iter 50 value 84.918680
iter 60 value 84.250160
iter 70 value 83.648328
iter 80 value 83.302582
iter 90 value 83.162707
iter 100 value 83.144434
final value 83.144434
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.469602
iter 10 value 94.612322
iter 20 value 94.279748
iter 30 value 91.364626
iter 40 value 86.934942
iter 50 value 86.348618
iter 60 value 85.292955
iter 70 value 84.419299
iter 80 value 82.970018
iter 90 value 82.719304
iter 100 value 82.180589
final value 82.180589
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.148440
iter 10 value 94.823287
iter 20 value 87.762780
iter 30 value 86.109616
iter 40 value 85.214193
iter 50 value 84.263155
iter 60 value 83.357993
iter 70 value 82.801887
iter 80 value 82.569915
iter 90 value 82.167476
iter 100 value 82.050860
final value 82.050860
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.001657
iter 10 value 94.485657
iter 20 value 94.482522
iter 30 value 87.256850
iter 40 value 84.925134
iter 50 value 84.832431
final value 84.830535
converged
Fitting Repeat 2
# weights: 103
initial value 96.027371
iter 10 value 94.485699
iter 20 value 94.377353
iter 30 value 85.532522
iter 40 value 85.529268
iter 50 value 84.522786
iter 60 value 83.464332
iter 70 value 83.431658
iter 80 value 83.338467
iter 90 value 83.226029
iter 100 value 83.058111
final value 83.058111
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 95.740210
final value 94.485947
converged
Fitting Repeat 4
# weights: 103
initial value 99.984038
iter 10 value 94.485867
iter 20 value 94.484272
iter 30 value 86.894423
iter 40 value 86.651444
iter 50 value 86.645452
iter 60 value 86.644452
iter 70 value 86.640028
iter 80 value 86.556320
iter 90 value 86.531385
final value 86.531305
converged
Fitting Repeat 5
# weights: 103
initial value 96.996337
final value 94.485892
converged
Fitting Repeat 1
# weights: 305
initial value 96.963696
iter 10 value 94.489277
iter 20 value 94.420838
iter 30 value 93.640700
iter 40 value 93.626295
iter 50 value 92.030551
iter 60 value 91.951200
iter 70 value 91.778050
iter 80 value 91.748948
iter 90 value 91.748696
iter 100 value 91.729965
final value 91.729965
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.072815
iter 10 value 94.488480
iter 20 value 94.412875
final value 94.130171
converged
Fitting Repeat 3
# weights: 305
initial value 103.816804
iter 10 value 92.245150
iter 20 value 92.177184
iter 30 value 92.176611
iter 40 value 92.164360
iter 50 value 92.003394
final value 91.976309
converged
Fitting Repeat 4
# weights: 305
initial value 102.840828
iter 10 value 94.488840
iter 20 value 94.484628
iter 30 value 93.221357
iter 40 value 93.196854
iter 50 value 93.194535
final value 93.194039
converged
Fitting Repeat 5
# weights: 305
initial value 97.251096
iter 10 value 94.489342
iter 20 value 94.436917
iter 30 value 87.656380
iter 40 value 87.117893
iter 50 value 87.106308
final value 87.106093
converged
Fitting Repeat 1
# weights: 507
initial value 130.785044
iter 10 value 94.492618
iter 20 value 94.482410
iter 30 value 87.891591
iter 40 value 87.441314
iter 50 value 87.439934
iter 60 value 87.190950
iter 70 value 86.709873
iter 80 value 83.409456
iter 90 value 82.972009
iter 100 value 82.958377
final value 82.958377
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.960038
iter 10 value 94.329621
iter 20 value 89.232076
iter 30 value 86.078943
iter 40 value 86.076128
iter 50 value 85.973296
iter 60 value 85.072578
iter 70 value 85.068906
iter 80 value 85.063403
iter 90 value 84.322347
iter 100 value 82.886759
final value 82.886759
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 99.583339
iter 10 value 94.475543
iter 20 value 94.473731
iter 30 value 94.472808
iter 40 value 94.472090
iter 50 value 94.466122
iter 60 value 94.387712
iter 70 value 94.041634
iter 80 value 94.039446
iter 90 value 94.037112
iter 100 value 94.036747
final value 94.036747
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 98.230617
iter 10 value 93.728585
iter 20 value 90.726238
iter 30 value 90.662764
iter 40 value 86.260637
iter 50 value 85.925025
iter 60 value 85.917212
final value 85.917121
converged
Fitting Repeat 5
# weights: 507
initial value 105.220164
iter 10 value 94.475345
iter 20 value 94.467544
final value 94.467486
converged
Fitting Repeat 1
# weights: 103
initial value 94.792844
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.552732
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.839694
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.426910
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 104.378497
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 109.452714
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 116.577526
iter 10 value 94.476473
final value 94.476471
converged
Fitting Repeat 3
# weights: 305
initial value 109.098103
final value 94.030602
converged
Fitting Repeat 4
# weights: 305
initial value 99.751042
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 105.677098
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 101.149320
iter 10 value 84.709695
iter 20 value 82.675031
iter 30 value 82.237686
iter 40 value 82.164399
iter 50 value 82.024894
iter 60 value 82.023646
iter 60 value 82.023646
final value 82.023646
converged
Fitting Repeat 2
# weights: 507
initial value 101.325317
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 108.183011
iter 10 value 91.637740
iter 20 value 89.731821
iter 30 value 89.717463
final value 89.717400
converged
Fitting Repeat 4
# weights: 507
initial value 95.234574
final value 94.275362
converged
Fitting Repeat 5
# weights: 507
initial value 99.580280
iter 10 value 93.523810
iter 10 value 93.523810
iter 10 value 93.523810
final value 93.523810
converged
Fitting Repeat 1
# weights: 103
initial value 104.551809
iter 10 value 94.486515
iter 20 value 92.565413
iter 30 value 90.599266
iter 40 value 90.377887
iter 50 value 90.327145
iter 60 value 82.962977
iter 70 value 82.274997
iter 80 value 82.092242
iter 90 value 81.065680
iter 100 value 80.761594
final value 80.761594
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 102.222856
iter 10 value 94.485852
iter 20 value 94.306882
iter 30 value 90.037228
iter 40 value 86.919018
iter 50 value 85.052943
iter 60 value 83.046316
iter 70 value 82.734425
iter 80 value 82.319577
iter 90 value 79.914423
iter 100 value 79.592759
final value 79.592759
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.168130
iter 10 value 94.313936
iter 20 value 94.090449
iter 30 value 94.081353
iter 40 value 94.080450
iter 50 value 94.079699
iter 60 value 94.079629
iter 70 value 93.934768
iter 80 value 84.312067
iter 90 value 83.921510
iter 100 value 82.880935
final value 82.880935
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 107.688859
iter 10 value 94.504157
iter 20 value 94.486320
iter 30 value 85.405228
iter 40 value 83.924300
iter 50 value 83.100659
iter 60 value 81.181233
iter 70 value 78.312310
iter 80 value 78.130927
iter 90 value 77.582074
iter 100 value 77.429946
final value 77.429946
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 97.978418
iter 10 value 94.492550
iter 20 value 91.982060
iter 30 value 84.354738
iter 40 value 83.650947
iter 50 value 83.471638
iter 60 value 83.171881
iter 70 value 82.316393
iter 80 value 82.304083
iter 90 value 82.241051
iter 100 value 82.164139
final value 82.164139
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.120055
iter 10 value 92.998876
iter 20 value 85.662353
iter 30 value 84.269405
iter 40 value 82.423076
iter 50 value 80.348484
iter 60 value 79.126908
iter 70 value 78.137137
iter 80 value 77.275656
iter 90 value 76.797388
iter 100 value 76.674807
final value 76.674807
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.708890
iter 10 value 93.574108
iter 20 value 83.231183
iter 30 value 79.800684
iter 40 value 79.596875
iter 50 value 79.519630
iter 60 value 78.277761
iter 70 value 76.625282
iter 80 value 76.284225
iter 90 value 76.237445
iter 100 value 76.210645
final value 76.210645
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.890855
iter 10 value 87.620025
iter 20 value 84.138182
iter 30 value 83.255083
iter 40 value 82.962184
iter 50 value 81.922616
iter 60 value 80.201920
iter 70 value 79.080811
iter 80 value 78.777408
iter 90 value 78.717673
iter 100 value 78.668562
final value 78.668562
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.027369
iter 10 value 94.595617
iter 20 value 90.949786
iter 30 value 82.941087
iter 40 value 82.166037
iter 50 value 81.038564
iter 60 value 78.725149
iter 70 value 77.685522
iter 80 value 77.448785
iter 90 value 77.407526
iter 100 value 77.400166
final value 77.400166
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 127.832282
iter 10 value 99.079512
iter 20 value 93.112912
iter 30 value 90.375998
iter 40 value 90.121799
iter 50 value 85.973020
iter 60 value 84.426908
iter 70 value 82.503657
iter 80 value 79.152787
iter 90 value 77.844537
iter 100 value 77.511469
final value 77.511469
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 135.011051
iter 10 value 95.817635
iter 20 value 87.414887
iter 30 value 82.938730
iter 40 value 81.616253
iter 50 value 79.552690
iter 60 value 78.698890
iter 70 value 78.022436
iter 80 value 77.201071
iter 90 value 76.498676
iter 100 value 76.065228
final value 76.065228
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.639032
iter 10 value 94.076627
iter 20 value 88.262703
iter 30 value 88.081613
iter 40 value 83.629917
iter 50 value 79.210905
iter 60 value 78.542392
iter 70 value 78.322307
iter 80 value 78.281925
iter 90 value 77.893808
iter 100 value 76.713675
final value 76.713675
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 123.824437
iter 10 value 94.315442
iter 20 value 91.702038
iter 30 value 88.800547
iter 40 value 83.207076
iter 50 value 82.074441
iter 60 value 78.465941
iter 70 value 77.165135
iter 80 value 76.544680
iter 90 value 76.077305
iter 100 value 75.715881
final value 75.715881
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.176573
iter 10 value 95.434781
iter 20 value 91.810515
iter 30 value 89.439096
iter 40 value 87.280237
iter 50 value 81.379562
iter 60 value 80.626960
iter 70 value 79.483066
iter 80 value 78.806951
iter 90 value 77.288125
iter 100 value 77.132404
final value 77.132404
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.335687
iter 10 value 95.946168
iter 20 value 90.698520
iter 30 value 81.417902
iter 40 value 80.256614
iter 50 value 78.520407
iter 60 value 77.397014
iter 70 value 76.648881
iter 80 value 75.968622
iter 90 value 75.717809
iter 100 value 75.511227
final value 75.511227
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.128957
iter 10 value 94.277228
iter 20 value 94.275686
iter 30 value 94.029599
iter 40 value 94.023698
final value 94.023690
converged
Fitting Repeat 2
# weights: 103
initial value 100.720286
iter 10 value 94.539932
iter 20 value 94.531772
iter 30 value 94.491901
iter 40 value 94.484304
final value 94.484214
converged
Fitting Repeat 3
# weights: 103
initial value 96.540265
iter 10 value 94.486004
iter 20 value 94.484224
final value 94.484218
converged
Fitting Repeat 4
# weights: 103
initial value 96.523224
final value 94.486143
converged
Fitting Repeat 5
# weights: 103
initial value 97.078046
final value 94.485703
converged
Fitting Repeat 1
# weights: 305
initial value 111.878713
iter 10 value 94.280090
iter 20 value 94.277630
iter 30 value 94.051078
iter 40 value 94.021993
iter 50 value 81.573578
iter 60 value 79.214276
iter 70 value 79.183196
iter 80 value 79.182515
iter 80 value 79.182515
final value 79.182515
converged
Fitting Repeat 2
# weights: 305
initial value 104.359182
iter 10 value 94.489123
iter 20 value 94.482780
iter 30 value 93.488923
iter 40 value 86.171480
iter 50 value 86.091212
iter 60 value 86.090026
iter 70 value 86.089450
iter 80 value 86.087270
iter 90 value 86.027420
iter 100 value 81.819603
final value 81.819603
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.018043
iter 10 value 93.786277
iter 20 value 93.720027
iter 30 value 93.690341
iter 40 value 93.688501
iter 50 value 93.685389
iter 60 value 91.360016
iter 70 value 91.119570
iter 80 value 91.078886
iter 90 value 91.057658
iter 100 value 90.975854
final value 90.975854
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 94.984886
iter 10 value 94.488293
iter 20 value 93.670372
iter 30 value 92.256829
final value 92.244281
converged
Fitting Repeat 5
# weights: 305
initial value 94.660682
iter 10 value 82.414469
iter 20 value 82.115108
iter 30 value 82.112866
iter 40 value 82.109410
iter 50 value 82.108123
iter 60 value 82.106235
iter 70 value 81.911632
iter 80 value 81.908726
iter 90 value 81.908083
iter 100 value 81.907878
final value 81.907878
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 101.169016
iter 10 value 94.208508
iter 20 value 88.722647
iter 30 value 86.630482
iter 40 value 82.096472
iter 50 value 82.088882
iter 60 value 81.856527
iter 70 value 81.855315
iter 80 value 81.853669
iter 90 value 81.852570
iter 100 value 81.836762
final value 81.836762
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.386984
iter 10 value 94.262210
iter 20 value 94.256779
final value 94.256303
converged
Fitting Repeat 3
# weights: 507
initial value 103.505636
iter 10 value 94.322834
iter 20 value 94.282530
iter 30 value 86.191731
iter 40 value 83.409128
iter 50 value 82.090218
iter 60 value 81.634640
iter 70 value 81.629010
iter 80 value 81.624228
iter 90 value 81.623447
iter 100 value 81.622796
final value 81.622796
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.867811
iter 10 value 94.027633
iter 20 value 94.025929
iter 30 value 81.588306
iter 40 value 78.920565
iter 50 value 78.439604
iter 60 value 77.830815
iter 70 value 77.818402
iter 80 value 77.721802
iter 90 value 77.219962
iter 100 value 75.807637
final value 75.807637
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 98.659082
iter 10 value 94.283233
iter 20 value 94.158530
iter 30 value 93.943703
iter 40 value 88.315608
iter 50 value 87.295529
iter 60 value 86.393239
iter 70 value 86.035534
iter 80 value 86.035190
iter 90 value 86.034702
iter 100 value 85.961977
final value 85.961977
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.322742
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.676384
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 99.892193
iter 10 value 94.368533
final value 94.026542
converged
Fitting Repeat 4
# weights: 103
initial value 99.921085
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.375565
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 112.399342
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 105.606896
final value 94.026542
converged
Fitting Repeat 3
# weights: 305
initial value 109.865754
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 102.367977
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 95.462034
final value 94.026542
converged
Fitting Repeat 1
# weights: 507
initial value 104.533647
iter 10 value 93.887988
final value 93.887795
converged
Fitting Repeat 2
# weights: 507
initial value 106.542125
final value 94.484210
converged
Fitting Repeat 3
# weights: 507
initial value 101.434812
iter 10 value 93.850627
iter 20 value 83.934467
iter 30 value 83.829368
iter 40 value 83.037736
iter 50 value 82.919605
final value 82.919550
converged
Fitting Repeat 4
# weights: 507
initial value 100.542681
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 110.999416
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 96.498190
iter 10 value 93.617413
iter 20 value 92.964695
iter 30 value 85.461169
iter 40 value 84.417415
iter 50 value 84.379863
iter 60 value 84.377309
iter 70 value 84.376386
final value 84.376343
converged
Fitting Repeat 2
# weights: 103
initial value 100.599616
iter 10 value 94.161011
iter 20 value 93.905544
iter 30 value 86.280083
iter 40 value 85.561536
iter 50 value 84.992441
iter 60 value 84.246822
iter 70 value 83.862326
final value 83.859133
converged
Fitting Repeat 3
# weights: 103
initial value 98.908675
iter 10 value 94.174309
iter 20 value 88.798100
iter 30 value 85.501849
iter 40 value 84.013469
iter 50 value 83.862938
iter 60 value 83.859166
final value 83.859133
converged
Fitting Repeat 4
# weights: 103
initial value 100.853667
iter 10 value 94.485892
iter 20 value 90.340455
iter 30 value 87.394184
iter 40 value 87.167402
iter 50 value 87.017086
iter 60 value 84.781987
iter 70 value 83.843443
iter 80 value 83.243666
iter 90 value 82.723098
iter 100 value 82.642415
final value 82.642415
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 107.289080
iter 10 value 94.497343
iter 20 value 94.485489
iter 30 value 93.934702
iter 40 value 93.856185
iter 50 value 91.265345
iter 60 value 88.788556
iter 70 value 88.500665
iter 80 value 87.881966
iter 90 value 84.744415
iter 100 value 84.410612
final value 84.410612
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 109.161204
iter 10 value 94.489899
iter 20 value 94.059813
iter 30 value 93.922118
iter 40 value 93.360916
iter 50 value 89.902505
iter 60 value 87.384693
iter 70 value 86.617444
iter 80 value 85.599810
iter 90 value 85.324285
iter 100 value 85.070416
final value 85.070416
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.341274
iter 10 value 94.499660
iter 20 value 87.264053
iter 30 value 86.512714
iter 40 value 86.337621
iter 50 value 86.095942
iter 60 value 85.815585
iter 70 value 83.736201
iter 80 value 82.457054
iter 90 value 81.547431
iter 100 value 81.383022
final value 81.383022
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 115.557659
iter 10 value 94.255652
iter 20 value 90.643378
iter 30 value 87.456721
iter 40 value 84.232044
iter 50 value 82.611305
iter 60 value 82.287408
iter 70 value 82.233136
iter 80 value 82.161859
iter 90 value 81.776902
iter 100 value 81.473811
final value 81.473811
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 121.206573
iter 10 value 94.428030
iter 20 value 88.619735
iter 30 value 85.129949
iter 40 value 83.691913
iter 50 value 82.159551
iter 60 value 81.595112
iter 70 value 81.582266
iter 80 value 81.529748
iter 90 value 81.239437
iter 100 value 81.050373
final value 81.050373
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.461903
iter 10 value 94.402435
iter 20 value 92.447265
iter 30 value 88.955098
iter 40 value 84.931667
iter 50 value 82.347336
iter 60 value 81.946266
iter 70 value 81.454077
iter 80 value 81.197839
iter 90 value 81.063714
iter 100 value 81.024114
final value 81.024114
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 113.540488
iter 10 value 94.358673
iter 20 value 87.977036
iter 30 value 86.850888
iter 40 value 84.095040
iter 50 value 82.152630
iter 60 value 81.746235
iter 70 value 81.434017
iter 80 value 81.341942
iter 90 value 81.213580
iter 100 value 81.035019
final value 81.035019
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 136.667982
iter 10 value 96.542865
iter 20 value 89.666629
iter 30 value 86.001965
iter 40 value 84.411314
iter 50 value 82.761128
iter 60 value 82.385246
iter 70 value 82.158268
iter 80 value 81.865083
iter 90 value 81.298702
iter 100 value 81.138924
final value 81.138924
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.939290
iter 10 value 95.160635
iter 20 value 94.410771
iter 30 value 89.164429
iter 40 value 88.051384
iter 50 value 87.403251
iter 60 value 85.446409
iter 70 value 83.824479
iter 80 value 81.983446
iter 90 value 81.321513
iter 100 value 81.177524
final value 81.177524
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.457371
iter 10 value 94.912558
iter 20 value 89.206212
iter 30 value 87.453891
iter 40 value 86.490350
iter 50 value 86.269111
iter 60 value 85.872157
iter 70 value 84.068916
iter 80 value 82.497839
iter 90 value 82.064574
iter 100 value 81.509542
final value 81.509542
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.515277
iter 10 value 94.683200
iter 20 value 93.448618
iter 30 value 92.086444
iter 40 value 90.540563
iter 50 value 86.087775
iter 60 value 85.045618
iter 70 value 83.307159
iter 80 value 82.642880
iter 90 value 81.717659
iter 100 value 81.575908
final value 81.575908
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.960986
final value 94.327814
converged
Fitting Repeat 2
# weights: 103
initial value 103.373930
final value 94.486228
converged
Fitting Repeat 3
# weights: 103
initial value 98.688043
final value 94.485529
converged
Fitting Repeat 4
# weights: 103
initial value 103.270939
iter 10 value 94.106994
iter 20 value 93.997381
final value 93.955595
converged
Fitting Repeat 5
# weights: 103
initial value 101.166816
final value 94.028265
converged
Fitting Repeat 1
# weights: 305
initial value 97.432509
iter 10 value 94.110456
iter 20 value 94.015884
iter 30 value 87.252997
iter 40 value 83.411004
iter 50 value 83.076267
iter 60 value 83.076103
iter 60 value 83.076103
iter 60 value 83.076103
final value 83.076103
converged
Fitting Repeat 2
# weights: 305
initial value 97.833374
iter 10 value 94.031867
iter 20 value 94.027958
iter 30 value 93.587393
iter 40 value 84.640014
iter 50 value 83.953187
iter 60 value 83.872168
final value 83.871777
converged
Fitting Repeat 3
# weights: 305
initial value 101.616952
iter 10 value 94.489389
iter 20 value 94.439516
iter 30 value 93.251327
iter 40 value 92.911818
iter 50 value 85.684286
iter 60 value 85.396932
iter 70 value 85.396468
iter 80 value 85.394950
iter 90 value 85.209114
iter 100 value 84.952764
final value 84.952764
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 116.795455
iter 10 value 93.811220
iter 20 value 93.713446
iter 30 value 93.709116
iter 40 value 93.706006
iter 50 value 88.380576
iter 60 value 88.106835
final value 87.940034
converged
Fitting Repeat 5
# weights: 305
initial value 109.946313
iter 10 value 94.489339
iter 20 value 94.366178
iter 30 value 93.964450
final value 93.943555
converged
Fitting Repeat 1
# weights: 507
initial value 108.070849
iter 10 value 93.284263
iter 20 value 93.224445
iter 30 value 93.198134
iter 40 value 93.191730
iter 50 value 93.170213
iter 60 value 87.799242
final value 87.227063
converged
Fitting Repeat 2
# weights: 507
initial value 111.862915
iter 10 value 93.818554
iter 20 value 93.799734
final value 93.796204
converged
Fitting Repeat 3
# weights: 507
initial value 96.787158
iter 10 value 94.437161
iter 20 value 91.396132
iter 30 value 88.415206
iter 40 value 87.306987
iter 50 value 86.013119
iter 60 value 85.343468
iter 70 value 85.330585
iter 70 value 85.330585
final value 85.330585
converged
Fitting Repeat 4
# weights: 507
initial value 117.579742
iter 10 value 94.414302
iter 20 value 94.312605
iter 30 value 91.156066
iter 40 value 84.459981
iter 50 value 84.285924
iter 60 value 83.749083
iter 70 value 82.383521
iter 80 value 82.313607
final value 82.313214
converged
Fitting Repeat 5
# weights: 507
initial value 108.531741
iter 10 value 94.492623
iter 20 value 94.476349
iter 30 value 93.871255
iter 40 value 93.796827
final value 93.795562
converged
Fitting Repeat 1
# weights: 103
initial value 109.972221
final value 94.052874
converged
Fitting Repeat 2
# weights: 103
initial value 97.816662
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.927956
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 97.562861
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 96.500148
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 103.069406
final value 94.038251
converged
Fitting Repeat 2
# weights: 305
initial value 102.344561
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 96.515861
final value 94.038251
converged
Fitting Repeat 4
# weights: 305
initial value 96.186800
final value 94.038251
converged
Fitting Repeat 5
# weights: 305
initial value 94.670425
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 116.308078
iter 10 value 94.038251
iter 10 value 94.038251
iter 10 value 94.038251
final value 94.038251
converged
Fitting Repeat 2
# weights: 507
initial value 96.377127
final value 94.047619
converged
Fitting Repeat 3
# weights: 507
initial value 95.498735
final value 93.950289
converged
Fitting Repeat 4
# weights: 507
initial value 110.751023
final value 94.038249
converged
Fitting Repeat 5
# weights: 507
initial value 105.702796
iter 10 value 93.871170
iter 20 value 93.521835
iter 30 value 93.505056
final value 93.504879
converged
Fitting Repeat 1
# weights: 103
initial value 111.215955
iter 10 value 93.964848
iter 20 value 88.825433
iter 30 value 87.135776
iter 40 value 86.684823
iter 50 value 86.234318
iter 60 value 85.977727
final value 85.968258
converged
Fitting Repeat 2
# weights: 103
initial value 100.451311
iter 10 value 94.057930
iter 20 value 93.985278
iter 30 value 88.089538
iter 40 value 87.108747
iter 50 value 86.090276
iter 60 value 84.778645
iter 70 value 84.765408
iter 70 value 84.765407
final value 84.765407
converged
Fitting Repeat 3
# weights: 103
initial value 111.177528
iter 10 value 93.617379
iter 20 value 88.593841
iter 30 value 87.630643
iter 40 value 86.780829
iter 50 value 83.924310
iter 60 value 82.785827
iter 70 value 82.574106
iter 80 value 82.563574
iter 90 value 82.530849
iter 90 value 82.530849
iter 90 value 82.530849
final value 82.530849
converged
Fitting Repeat 4
# weights: 103
initial value 97.776551
iter 10 value 94.060260
iter 20 value 93.990477
iter 30 value 89.349686
iter 40 value 88.799917
iter 50 value 87.040584
iter 60 value 85.493054
iter 70 value 85.250919
iter 80 value 85.117037
iter 90 value 85.093427
iter 100 value 84.880305
final value 84.880305
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 102.749538
iter 10 value 93.995464
iter 20 value 93.973385
iter 30 value 88.000048
iter 40 value 87.107567
iter 50 value 86.415008
iter 60 value 84.289724
iter 70 value 83.703463
iter 80 value 83.404287
iter 90 value 83.312218
iter 100 value 82.569061
final value 82.569061
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 123.996332
iter 10 value 94.064688
iter 20 value 89.932900
iter 30 value 88.617401
iter 40 value 87.397692
iter 50 value 83.551175
iter 60 value 82.574816
iter 70 value 81.965327
iter 80 value 81.865923
iter 90 value 81.532102
iter 100 value 81.492209
final value 81.492209
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.378791
iter 10 value 94.071160
iter 20 value 93.369624
iter 30 value 87.809373
iter 40 value 87.609881
iter 50 value 87.524056
iter 60 value 86.935422
iter 70 value 83.252416
iter 80 value 82.063449
iter 90 value 81.906802
iter 100 value 81.835932
final value 81.835932
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 114.108193
iter 10 value 93.969431
iter 20 value 92.999240
iter 30 value 92.178373
iter 40 value 89.949585
iter 50 value 88.614154
iter 60 value 86.378435
iter 70 value 85.839170
iter 80 value 85.695877
iter 90 value 84.600541
iter 100 value 82.740996
final value 82.740996
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.694051
iter 10 value 94.125585
iter 20 value 87.391372
iter 30 value 86.403433
iter 40 value 86.250855
iter 50 value 86.005515
iter 60 value 85.739992
iter 70 value 85.598934
iter 80 value 85.565920
iter 90 value 85.170113
iter 100 value 84.202189
final value 84.202189
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 117.192452
iter 10 value 93.918988
iter 20 value 92.804415
iter 30 value 89.783630
iter 40 value 85.473076
iter 50 value 84.552259
iter 60 value 83.950023
iter 70 value 83.549238
iter 80 value 83.351279
iter 90 value 83.173763
iter 100 value 83.145736
final value 83.145736
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.787231
iter 10 value 94.185708
iter 20 value 94.068375
iter 30 value 90.406469
iter 40 value 86.602954
iter 50 value 85.663048
iter 60 value 85.330393
iter 70 value 85.191196
iter 80 value 85.124010
iter 90 value 84.744417
iter 100 value 82.417311
final value 82.417311
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.371966
iter 10 value 94.298258
iter 20 value 88.867853
iter 30 value 86.974736
iter 40 value 85.906276
iter 50 value 84.039163
iter 60 value 82.667816
iter 70 value 82.404918
iter 80 value 82.092883
iter 90 value 81.961528
iter 100 value 81.698399
final value 81.698399
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.110416
iter 10 value 94.089415
iter 20 value 93.632478
iter 30 value 88.662866
iter 40 value 85.899985
iter 50 value 84.507748
iter 60 value 81.926950
iter 70 value 81.182533
iter 80 value 81.089937
iter 90 value 81.026584
iter 100 value 80.929719
final value 80.929719
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 114.805330
iter 10 value 94.445507
iter 20 value 87.164816
iter 30 value 86.224805
iter 40 value 85.823313
iter 50 value 85.004131
iter 60 value 84.271000
iter 70 value 84.061228
iter 80 value 83.440884
iter 90 value 83.216320
iter 100 value 82.914009
final value 82.914009
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 108.846182
iter 10 value 94.448424
iter 20 value 92.773482
iter 30 value 89.164772
iter 40 value 87.284560
iter 50 value 84.862103
iter 60 value 83.021035
iter 70 value 82.287050
iter 80 value 82.174283
iter 90 value 82.044007
iter 100 value 81.801802
final value 81.801802
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.153765
final value 94.054409
converged
Fitting Repeat 2
# weights: 103
initial value 99.732058
iter 10 value 94.054546
iter 20 value 94.052102
iter 30 value 93.099305
iter 40 value 92.318948
iter 50 value 91.031239
iter 60 value 90.941569
final value 90.941470
converged
Fitting Repeat 3
# weights: 103
initial value 96.720593
final value 94.054576
converged
Fitting Repeat 4
# weights: 103
initial value 103.626342
final value 94.054464
converged
Fitting Repeat 5
# weights: 103
initial value 100.414339
final value 94.054715
converged
Fitting Repeat 1
# weights: 305
initial value 102.627154
iter 10 value 93.719075
iter 20 value 93.714804
iter 30 value 93.628927
final value 93.628710
converged
Fitting Repeat 2
# weights: 305
initial value 101.827173
iter 10 value 94.057231
iter 20 value 93.358458
iter 30 value 89.071845
iter 40 value 87.250940
iter 50 value 87.249657
iter 60 value 87.249276
final value 87.249244
converged
Fitting Repeat 3
# weights: 305
initial value 108.585525
iter 10 value 94.057779
iter 20 value 92.692102
iter 30 value 87.015424
iter 40 value 81.288036
iter 50 value 80.604838
iter 60 value 80.496451
iter 70 value 80.407034
iter 80 value 80.306102
iter 90 value 80.094287
iter 100 value 79.860027
final value 79.860027
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 98.543224
final value 94.058064
converged
Fitting Repeat 5
# weights: 305
initial value 95.220064
iter 10 value 90.509626
iter 20 value 87.882146
iter 30 value 86.021023
iter 40 value 85.348187
iter 50 value 85.347270
iter 60 value 85.343471
iter 70 value 85.340745
iter 80 value 85.339818
iter 90 value 85.328078
iter 100 value 84.891342
final value 84.891342
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 99.689754
iter 10 value 92.338104
iter 20 value 92.214987
iter 30 value 92.209544
iter 40 value 92.208953
iter 50 value 92.207960
iter 60 value 88.594742
iter 70 value 86.752161
iter 80 value 85.750463
iter 90 value 84.138162
iter 100 value 82.702594
final value 82.702594
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.074568
iter 10 value 89.753059
iter 20 value 89.583348
final value 89.582022
converged
Fitting Repeat 3
# weights: 507
initial value 95.202390
iter 10 value 93.025195
iter 20 value 93.020981
iter 30 value 93.013163
iter 40 value 93.011110
final value 93.010948
converged
Fitting Repeat 4
# weights: 507
initial value 104.160219
iter 10 value 94.060936
iter 20 value 94.027077
iter 30 value 91.011076
iter 40 value 90.785635
final value 90.785415
converged
Fitting Repeat 5
# weights: 507
initial value 100.885496
iter 10 value 94.046344
iter 20 value 94.038812
iter 30 value 93.696264
iter 40 value 93.202742
final value 93.202360
converged
Fitting Repeat 1
# weights: 103
initial value 105.598737
iter 10 value 93.582418
iter 10 value 93.582418
iter 10 value 93.582418
final value 93.582418
converged
Fitting Repeat 2
# weights: 103
initial value 101.992308
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 105.249521
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 100.428737
iter 10 value 93.356685
final value 93.356645
converged
Fitting Repeat 5
# weights: 103
initial value 101.374299
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 106.838841
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 114.989072
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 99.472809
final value 93.582418
converged
Fitting Repeat 4
# weights: 305
initial value 100.358501
final value 93.582418
converged
Fitting Repeat 5
# weights: 305
initial value 118.374311
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 97.006973
iter 10 value 93.559524
iter 10 value 93.559524
iter 10 value 93.559524
final value 93.559524
converged
Fitting Repeat 2
# weights: 507
initial value 117.378338
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 97.069721
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 98.730477
final value 92.892737
converged
Fitting Repeat 5
# weights: 507
initial value 104.410745
final value 93.582418
converged
Fitting Repeat 1
# weights: 103
initial value 106.462194
iter 10 value 94.057264
iter 20 value 94.055131
iter 30 value 94.054908
iter 40 value 93.899818
iter 50 value 88.601953
iter 60 value 87.602291
iter 70 value 85.023266
iter 80 value 83.728508
iter 90 value 83.296505
iter 100 value 83.108158
final value 83.108158
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.571300
iter 10 value 94.026293
iter 20 value 88.816325
iter 30 value 86.801650
iter 40 value 84.567840
iter 50 value 83.893315
iter 60 value 83.280371
iter 70 value 83.157143
iter 80 value 83.121924
iter 90 value 83.100221
iter 100 value 82.196603
final value 82.196603
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 114.055673
iter 10 value 92.932785
iter 20 value 84.735201
iter 30 value 84.274755
iter 40 value 83.658821
iter 50 value 83.471409
final value 83.458154
converged
Fitting Repeat 4
# weights: 103
initial value 96.091529
iter 10 value 91.578930
iter 20 value 85.321059
iter 30 value 84.668628
iter 40 value 84.613783
iter 50 value 84.264037
iter 60 value 83.165527
iter 70 value 82.125960
iter 80 value 81.674893
iter 90 value 81.651258
iter 100 value 81.605620
final value 81.605620
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 97.181321
iter 10 value 94.051382
iter 20 value 90.639102
iter 30 value 85.034523
iter 40 value 83.515735
iter 50 value 82.766516
iter 60 value 81.642827
iter 70 value 81.613578
iter 80 value 81.602779
iter 90 value 81.600923
final value 81.600338
converged
Fitting Repeat 1
# weights: 305
initial value 114.440185
iter 10 value 94.607466
iter 20 value 87.306403
iter 30 value 85.348804
iter 40 value 81.839257
iter 50 value 81.326504
iter 60 value 81.086859
iter 70 value 80.600249
iter 80 value 80.539507
iter 90 value 80.239950
iter 100 value 79.976689
final value 79.976689
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 117.391527
iter 10 value 93.853715
iter 20 value 87.596860
iter 30 value 85.000233
iter 40 value 84.227079
iter 50 value 83.261012
iter 60 value 83.036422
iter 70 value 82.798025
iter 80 value 82.401743
iter 90 value 80.824185
iter 100 value 80.355805
final value 80.355805
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.911557
iter 10 value 94.014554
iter 20 value 86.863663
iter 30 value 83.235967
iter 40 value 82.315890
iter 50 value 81.158056
iter 60 value 80.628159
iter 70 value 80.509483
iter 80 value 80.444374
iter 90 value 80.416932
iter 100 value 80.368989
final value 80.368989
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 118.104526
iter 10 value 94.405315
iter 20 value 86.558173
iter 30 value 85.537971
iter 40 value 83.715523
iter 50 value 81.505749
iter 60 value 81.186618
iter 70 value 80.776745
iter 80 value 80.512751
iter 90 value 80.248603
iter 100 value 80.128938
final value 80.128938
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 134.660302
iter 10 value 93.903890
iter 20 value 93.401071
iter 30 value 88.974765
iter 40 value 85.098453
iter 50 value 84.219803
iter 60 value 83.232403
iter 70 value 81.533598
iter 80 value 81.185328
iter 90 value 80.701667
iter 100 value 80.490323
final value 80.490323
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 118.377378
iter 10 value 94.016208
iter 20 value 92.388433
iter 30 value 86.548945
iter 40 value 85.901291
iter 50 value 84.125445
iter 60 value 83.771412
iter 70 value 83.180394
iter 80 value 82.380423
iter 90 value 81.973214
iter 100 value 81.580124
final value 81.580124
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 123.987171
iter 10 value 94.208485
iter 20 value 90.593276
iter 30 value 84.405534
iter 40 value 83.998517
iter 50 value 83.761087
iter 60 value 83.247821
iter 70 value 82.514559
iter 80 value 81.380704
iter 90 value 80.922521
iter 100 value 80.785148
final value 80.785148
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 116.082362
iter 10 value 93.074092
iter 20 value 86.631313
iter 30 value 84.462753
iter 40 value 84.012730
iter 50 value 83.802062
iter 60 value 83.431653
iter 70 value 83.218377
iter 80 value 82.849693
iter 90 value 81.830975
iter 100 value 81.384598
final value 81.384598
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 117.273605
iter 10 value 95.308832
iter 20 value 90.644531
iter 30 value 86.536253
iter 40 value 82.736067
iter 50 value 81.726481
iter 60 value 80.903885
iter 70 value 80.545618
iter 80 value 80.353044
iter 90 value 80.237293
iter 100 value 80.117882
final value 80.117882
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.714037
iter 10 value 95.101626
iter 20 value 91.667796
iter 30 value 83.664086
iter 40 value 81.144289
iter 50 value 80.848807
iter 60 value 80.391186
iter 70 value 80.143023
iter 80 value 79.967586
iter 90 value 79.818312
iter 100 value 79.724837
final value 79.724837
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.613132
final value 94.054603
converged
Fitting Repeat 2
# weights: 103
initial value 102.035181
final value 94.054627
converged
Fitting Repeat 3
# weights: 103
initial value 102.830058
iter 10 value 94.054554
iter 20 value 94.052972
final value 94.052916
converged
Fitting Repeat 4
# weights: 103
initial value 104.351782
final value 94.054391
converged
Fitting Repeat 5
# weights: 103
initial value 94.431824
final value 93.840920
converged
Fitting Repeat 1
# weights: 305
initial value 98.082524
iter 10 value 94.057302
iter 20 value 94.051503
iter 30 value 92.432698
iter 40 value 91.610212
iter 50 value 91.152915
iter 60 value 86.091116
iter 70 value 86.087388
iter 80 value 86.086453
iter 90 value 82.193222
iter 100 value 80.431964
final value 80.431964
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.087571
iter 10 value 93.587618
iter 20 value 93.523719
iter 30 value 90.005944
iter 40 value 86.866689
iter 50 value 86.195658
iter 60 value 82.066665
iter 70 value 82.010159
iter 80 value 82.008638
final value 82.008611
converged
Fitting Repeat 3
# weights: 305
initial value 100.811747
iter 10 value 94.057425
iter 20 value 92.559984
iter 30 value 84.122539
iter 40 value 83.551098
iter 50 value 83.079192
iter 60 value 82.694890
final value 82.692497
converged
Fitting Repeat 4
# weights: 305
initial value 133.481047
iter 10 value 94.045694
iter 20 value 94.039295
iter 30 value 86.254075
iter 40 value 82.898265
iter 50 value 82.815162
iter 60 value 82.799452
iter 70 value 82.756463
iter 80 value 82.256539
iter 90 value 81.243822
iter 100 value 81.239232
final value 81.239232
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 120.245543
iter 10 value 93.587789
iter 20 value 93.583483
iter 30 value 92.943603
iter 40 value 84.492441
iter 50 value 83.319856
iter 60 value 83.319152
iter 60 value 83.319152
final value 83.319152
converged
Fitting Repeat 1
# weights: 507
initial value 99.989789
iter 10 value 93.996527
iter 20 value 93.701931
iter 30 value 84.288602
iter 40 value 83.274435
iter 50 value 82.808334
iter 60 value 82.725989
final value 82.725898
converged
Fitting Repeat 2
# weights: 507
initial value 100.443031
iter 10 value 86.704984
iter 20 value 85.553764
iter 30 value 84.681988
iter 40 value 84.678802
iter 50 value 84.676908
iter 60 value 83.592235
iter 70 value 82.955297
iter 80 value 82.515303
iter 90 value 81.423906
iter 100 value 80.766418
final value 80.766418
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 97.722479
iter 10 value 93.416486
iter 20 value 93.307231
iter 30 value 93.302685
iter 40 value 93.302318
iter 50 value 93.300941
iter 60 value 92.406916
iter 70 value 85.745927
iter 80 value 85.013468
iter 90 value 84.426132
iter 100 value 84.423626
final value 84.423626
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 140.153010
iter 10 value 94.062015
iter 20 value 94.038338
iter 30 value 93.724392
iter 40 value 93.673211
iter 50 value 93.672275
final value 93.672139
converged
Fitting Repeat 5
# weights: 507
initial value 119.800320
iter 10 value 94.025082
iter 20 value 93.424261
iter 30 value 85.028941
iter 40 value 84.208335
iter 50 value 84.208175
iter 60 value 82.919918
iter 70 value 82.370724
final value 82.370722
converged
Fitting Repeat 1
# weights: 507
initial value 132.214572
iter 10 value 117.409640
iter 20 value 114.486067
iter 30 value 106.999280
iter 40 value 105.908859
iter 50 value 103.831951
iter 60 value 102.190032
iter 70 value 101.749421
iter 80 value 101.435052
iter 90 value 100.974448
iter 100 value 100.850835
final value 100.850835
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 132.436702
iter 10 value 114.730585
iter 20 value 107.946804
iter 30 value 105.993694
iter 40 value 104.921462
iter 50 value 103.362076
iter 60 value 103.186513
iter 70 value 102.890729
iter 80 value 102.499765
iter 90 value 102.104595
iter 100 value 101.930304
final value 101.930304
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 128.289864
iter 10 value 117.924948
iter 20 value 111.360337
iter 30 value 106.645487
iter 40 value 104.008934
iter 50 value 103.007981
iter 60 value 102.324363
iter 70 value 101.978896
iter 80 value 101.880839
iter 90 value 101.812261
iter 100 value 101.663792
final value 101.663792
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 135.269856
iter 10 value 113.290119
iter 20 value 110.592389
iter 30 value 110.071961
iter 40 value 108.968305
iter 50 value 105.220198
iter 60 value 103.772965
iter 70 value 102.150626
iter 80 value 100.806200
iter 90 value 100.475503
iter 100 value 100.347239
final value 100.347239
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 140.182048
iter 10 value 117.817595
iter 20 value 109.028768
iter 30 value 107.700088
iter 40 value 106.128583
iter 50 value 103.112355
iter 60 value 102.083466
iter 70 value 101.565928
iter 80 value 101.347132
iter 90 value 101.039988
iter 100 value 100.916887
final value 100.916887
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 -- Sat Apr 4 00:26:28 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
40.065 1.266 90.917
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 32.839 | 0.545 | 33.385 | |
| FreqInteractors | 0.439 | 0.033 | 0.471 | |
| calculateAAC | 0.031 | 0.002 | 0.032 | |
| calculateAutocor | 0.279 | 0.020 | 0.299 | |
| calculateCTDC | 0.079 | 0.000 | 0.078 | |
| calculateCTDD | 0.536 | 0.001 | 0.537 | |
| calculateCTDT | 0.190 | 0.000 | 0.189 | |
| calculateCTriad | 0.401 | 0.002 | 0.403 | |
| calculateDC | 0.085 | 0.000 | 0.085 | |
| calculateF | 0.315 | 0.001 | 0.316 | |
| calculateKSAAP | 0.105 | 0.000 | 0.105 | |
| calculateQD_Sm | 1.724 | 0.007 | 1.731 | |
| calculateTC | 1.500 | 0.021 | 1.520 | |
| calculateTC_Sm | 0.240 | 0.002 | 0.242 | |
| corr_plot | 33.550 | 0.396 | 33.948 | |
| enrichfindP | 0.519 | 0.034 | 17.980 | |
| enrichfind_hp | 0.077 | 0.003 | 1.962 | |
| enrichplot | 0.473 | 0.003 | 0.477 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.395 | 0.029 | 3.892 | |
| getHPI | 0.001 | 0.000 | 0.001 | |
| get_negativePPI | 0.003 | 0.000 | 0.003 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.002 | 0.000 | 0.003 | |
| plotPPI | 0.1 | 0.0 | 0.1 | |
| pred_ensembel | 13.034 | 0.134 | 11.851 | |
| var_imp | 33.429 | 0.492 | 33.921 | |