Matineh Rahmatbakhsh
| Snapshot Date: 2025-12-03 13:40 -0500 (Wed, 03 Dec 2025) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: e6c77ab |
| git_last_commit_date: 2025-11-23 15:13:33 -0500 (Sun, 23 Nov 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2025-12-04 11:35 -0500 (Thu, 04 Dec 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences" | 4869 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4576 |
| 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 995/2331 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.17.1 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | WARNINGS | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.17.1 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.1.tar.gz |
| StartedAt: 2025-12-04 02:29:45 -0500 (Thu, 04 Dec 2025) |
| EndedAt: 2025-12-04 02:45:24 -0500 (Thu, 04 Dec 2025) |
| EllapsedTime: 939.4 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: HPiP.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-10-20 r88955)
* 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 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.1’
* 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 ... WARNING
Codoc mismatches from Rd file 'pred_ensembel.Rd':
pred_ensembel
Code: function(features, gold_standard, classifier = c("avNNet",
"svmRadial", "ranger"), resampling.method = "cv",
ncross = 2, repeats = 2, verboseIter = TRUE, plots =
FALSE, filename = "plots.pdf")
Docs: function(features, gold_standard, classifier = c("avNNet",
"svmRadial", "ranger"), resampling.method = "cv",
ncross = 2, repeats = 2, verboseIter = TRUE, plots =
TRUE, filename = "plots.pdf")
Mismatches in argument default values:
Name: 'plots' Code: FALSE Docs: TRUE
* 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 33.427 0.508 33.937
var_imp 32.800 0.423 33.226
FSmethod 32.587 0.586 33.175
pred_ensembel 12.769 0.119 11.519
enrichfindP 0.517 0.044 15.689
getFASTA 0.337 0.007 6.877
* 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: 1 WARNING, 2 NOTEs
See
‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.17.1’ ** 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 Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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 97.592141
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 96.345801
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 94.415604
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 96.566279
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.323207
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 107.825754
iter 10 value 93.574853
final value 93.574847
converged
Fitting Repeat 2
# weights: 305
initial value 95.072515
iter 10 value 85.948080
iter 20 value 84.978128
iter 30 value 84.190499
iter 40 value 83.962656
iter 50 value 83.952774
final value 83.952298
converged
Fitting Repeat 3
# weights: 305
initial value 97.666269
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 109.538349
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 104.344341
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 100.903253
iter 10 value 93.371832
final value 93.371808
converged
Fitting Repeat 2
# weights: 507
initial value 95.384363
final value 94.050051
converged
Fitting Repeat 3
# weights: 507
initial value 110.110551
iter 10 value 93.583701
iter 20 value 92.953940
final value 92.953900
converged
Fitting Repeat 4
# weights: 507
initial value 97.350329
iter 10 value 93.689199
final value 93.582418
converged
Fitting Repeat 5
# weights: 507
initial value 102.703826
iter 10 value 93.582418
iter 10 value 93.582418
iter 10 value 93.582418
final value 93.582418
converged
Fitting Repeat 1
# weights: 103
initial value 99.638380
iter 10 value 93.742000
iter 20 value 93.682655
iter 30 value 86.820505
iter 40 value 85.900682
iter 50 value 85.859214
iter 60 value 85.782167
iter 70 value 85.710687
iter 80 value 85.440512
iter 90 value 84.316477
iter 100 value 83.339695
final value 83.339695
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 107.194051
iter 10 value 94.060699
iter 20 value 90.626302
iter 30 value 85.390412
iter 40 value 84.617034
iter 50 value 84.437068
iter 60 value 84.302609
iter 70 value 84.107254
iter 80 value 82.958368
iter 90 value 82.415219
iter 100 value 82.318061
final value 82.318061
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.811544
iter 10 value 93.951731
iter 20 value 93.688136
iter 30 value 93.686504
iter 40 value 93.684560
iter 50 value 93.677362
iter 60 value 90.642278
iter 70 value 88.153468
iter 80 value 87.945486
iter 90 value 87.412872
iter 100 value 85.911592
final value 85.911592
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 95.649777
iter 10 value 94.051717
iter 20 value 93.486439
iter 30 value 89.024679
iter 40 value 87.645625
iter 50 value 86.564584
iter 60 value 86.166343
iter 70 value 85.704687
iter 80 value 85.257242
iter 90 value 84.838817
iter 100 value 83.334968
final value 83.334968
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 97.729039
iter 10 value 92.843265
iter 20 value 88.020810
iter 30 value 85.530853
iter 40 value 85.386404
iter 50 value 85.298545
iter 60 value 83.818404
iter 70 value 83.783849
final value 83.783840
converged
Fitting Repeat 1
# weights: 305
initial value 102.639884
iter 10 value 93.638623
iter 20 value 92.941487
iter 30 value 87.724117
iter 40 value 86.098199
iter 50 value 83.668664
iter 60 value 82.517246
iter 70 value 81.725999
iter 80 value 81.661716
iter 90 value 81.385684
iter 100 value 81.214705
final value 81.214705
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.817577
iter 10 value 92.894926
iter 20 value 88.030947
iter 30 value 87.015640
iter 40 value 85.903891
iter 50 value 84.098640
iter 60 value 82.490359
iter 70 value 81.831056
iter 80 value 81.600535
iter 90 value 81.378818
iter 100 value 81.234647
final value 81.234647
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.948936
iter 10 value 94.056004
iter 20 value 93.457649
iter 30 value 88.195617
iter 40 value 84.629439
iter 50 value 83.751932
iter 60 value 83.408905
iter 70 value 82.880653
iter 80 value 82.327453
iter 90 value 81.847483
iter 100 value 81.650504
final value 81.650504
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.626080
iter 10 value 94.095249
iter 20 value 93.980311
iter 30 value 93.239994
iter 40 value 87.104375
iter 50 value 86.183348
iter 60 value 85.689419
iter 70 value 85.603432
iter 80 value 85.226009
iter 90 value 83.216303
iter 100 value 82.532422
final value 82.532422
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.671005
iter 10 value 93.795293
iter 20 value 90.657212
iter 30 value 85.081082
iter 40 value 84.657132
iter 50 value 84.510768
iter 60 value 84.329945
iter 70 value 83.965539
iter 80 value 83.115201
iter 90 value 81.973947
iter 100 value 81.541521
final value 81.541521
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.974417
iter 10 value 94.130694
iter 20 value 93.950602
iter 30 value 91.938578
iter 40 value 86.208410
iter 50 value 85.140634
iter 60 value 84.973535
iter 70 value 84.041942
iter 80 value 82.557513
iter 90 value 82.008247
iter 100 value 81.396046
final value 81.396046
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.780847
iter 10 value 94.406957
iter 20 value 92.498699
iter 30 value 87.227427
iter 40 value 85.851304
iter 50 value 82.247060
iter 60 value 81.456576
iter 70 value 80.804993
iter 80 value 80.657025
iter 90 value 80.566145
iter 100 value 80.484993
final value 80.484993
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 122.936286
iter 10 value 89.171007
iter 20 value 87.432413
iter 30 value 86.192144
iter 40 value 85.659634
iter 50 value 83.868890
iter 60 value 83.035169
iter 70 value 82.036171
iter 80 value 81.374348
iter 90 value 81.086095
iter 100 value 81.014400
final value 81.014400
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 114.755795
iter 10 value 93.988861
iter 20 value 88.153470
iter 30 value 87.835713
iter 40 value 87.352954
iter 50 value 86.167617
iter 60 value 82.747730
iter 70 value 81.889618
iter 80 value 81.274872
iter 90 value 80.845826
iter 100 value 80.455096
final value 80.455096
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.958513
iter 10 value 100.070614
iter 20 value 93.063831
iter 30 value 92.663953
iter 40 value 90.845369
iter 50 value 89.313224
iter 60 value 85.697056
iter 70 value 84.433143
iter 80 value 83.833861
iter 90 value 83.552000
iter 100 value 83.443564
final value 83.443564
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.278435
final value 94.054540
converged
Fitting Repeat 2
# weights: 103
initial value 96.986902
final value 94.054570
converged
Fitting Repeat 3
# weights: 103
initial value 94.325137
final value 94.054555
converged
Fitting Repeat 4
# weights: 103
initial value 107.767093
iter 10 value 94.054458
iter 20 value 93.949772
iter 30 value 93.582609
final value 93.582602
converged
Fitting Repeat 5
# weights: 103
initial value 97.329665
final value 94.054517
converged
Fitting Repeat 1
# weights: 305
initial value 95.321992
iter 10 value 94.057679
iter 20 value 93.652856
iter 30 value 86.744305
iter 40 value 83.784656
iter 50 value 83.734846
iter 60 value 83.519271
iter 70 value 81.667816
iter 80 value 81.636185
iter 90 value 81.605364
iter 100 value 81.603615
final value 81.603615
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 95.141327
iter 10 value 94.057528
iter 20 value 94.041359
iter 30 value 85.758901
final value 85.739745
converged
Fitting Repeat 3
# weights: 305
initial value 103.660582
iter 10 value 94.057786
iter 20 value 93.982690
iter 30 value 93.808996
iter 40 value 93.748089
final value 93.748057
converged
Fitting Repeat 4
# weights: 305
initial value 95.350084
iter 10 value 94.057173
iter 20 value 94.050879
final value 94.050351
converged
Fitting Repeat 5
# weights: 305
initial value 104.016427
iter 10 value 93.588216
iter 20 value 93.585254
iter 30 value 93.583409
final value 93.583381
converged
Fitting Repeat 1
# weights: 507
initial value 97.503987
iter 10 value 94.060139
iter 20 value 93.479681
iter 30 value 88.918947
iter 40 value 88.573994
iter 50 value 88.134786
iter 60 value 88.098530
iter 70 value 87.529240
iter 80 value 87.528553
iter 90 value 87.441764
iter 100 value 84.697887
final value 84.697887
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 97.562699
iter 10 value 94.060411
iter 20 value 94.052943
iter 30 value 90.576597
iter 40 value 84.063570
iter 50 value 83.207876
iter 60 value 82.825012
iter 70 value 80.324321
iter 80 value 80.151696
iter 90 value 80.136750
iter 100 value 80.131932
final value 80.131932
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 102.408502
iter 10 value 93.433350
iter 20 value 92.362484
iter 30 value 91.399628
iter 40 value 91.395454
iter 50 value 91.393740
iter 60 value 91.393452
iter 70 value 91.390673
iter 80 value 91.255549
iter 90 value 91.132605
iter 100 value 91.113200
final value 91.113200
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.975877
iter 10 value 94.061107
iter 20 value 94.039421
iter 30 value 93.587803
iter 40 value 93.017956
iter 50 value 86.937915
iter 60 value 84.937767
final value 84.926353
converged
Fitting Repeat 5
# weights: 507
initial value 99.487753
iter 10 value 93.743961
iter 20 value 93.739470
iter 30 value 93.374334
iter 40 value 93.372187
final value 93.372183
converged
Fitting Repeat 1
# weights: 103
initial value 97.523668
final value 94.052911
converged
Fitting Repeat 2
# weights: 103
initial value 98.042212
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 102.309736
iter 10 value 92.791577
iter 20 value 83.387812
iter 30 value 82.467289
final value 82.459401
converged
Fitting Repeat 4
# weights: 103
initial value 94.131357
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 108.082952
final value 93.502849
converged
Fitting Repeat 1
# weights: 305
initial value 98.790484
iter 10 value 87.032384
iter 20 value 86.933498
iter 30 value 85.261551
iter 40 value 85.261029
iter 50 value 84.626013
final value 84.625540
converged
Fitting Repeat 2
# weights: 305
initial value 96.997157
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 101.611202
final value 94.038251
converged
Fitting Repeat 4
# weights: 305
initial value 101.813211
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 102.564572
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 123.050341
iter 10 value 90.174071
iter 20 value 86.290214
iter 30 value 86.265742
iter 40 value 86.261017
final value 86.261005
converged
Fitting Repeat 2
# weights: 507
initial value 114.933466
final value 94.038251
converged
Fitting Repeat 3
# weights: 507
initial value 110.516383
iter 10 value 94.100041
iter 20 value 94.021029
iter 30 value 93.691146
final value 93.655754
converged
Fitting Repeat 4
# weights: 507
initial value 96.321307
iter 10 value 93.999155
iter 10 value 93.999155
iter 10 value 93.999155
final value 93.999155
converged
Fitting Repeat 5
# weights: 507
initial value 94.974437
iter 10 value 93.117122
iter 20 value 91.189079
iter 30 value 91.183556
iter 30 value 91.183556
iter 30 value 91.183556
final value 91.183556
converged
Fitting Repeat 1
# weights: 103
initial value 99.713088
iter 10 value 93.004050
iter 20 value 86.915866
iter 30 value 85.798539
iter 40 value 83.675150
iter 50 value 83.064962
iter 60 value 82.540198
iter 70 value 81.795155
iter 80 value 81.366033
iter 90 value 81.214379
final value 81.208071
converged
Fitting Repeat 2
# weights: 103
initial value 103.364752
iter 10 value 93.606434
iter 20 value 90.061798
iter 30 value 84.739931
iter 40 value 83.561977
iter 50 value 83.052208
iter 60 value 82.554254
iter 70 value 81.577600
iter 80 value 81.499896
iter 90 value 81.255066
iter 100 value 81.208127
final value 81.208127
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.981905
iter 10 value 94.056513
iter 20 value 86.952145
iter 30 value 86.749587
iter 40 value 86.614079
iter 50 value 86.076959
iter 60 value 84.372605
iter 70 value 83.594133
iter 80 value 83.009236
iter 90 value 82.989627
iter 100 value 82.953764
final value 82.953764
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 102.723618
iter 10 value 93.869840
iter 20 value 87.645306
iter 30 value 85.137223
iter 40 value 84.550235
iter 50 value 83.500499
iter 60 value 81.370829
iter 70 value 81.114586
iter 80 value 81.105434
final value 81.104876
converged
Fitting Repeat 5
# weights: 103
initial value 105.155624
iter 10 value 93.950975
iter 20 value 89.824233
iter 30 value 86.558836
iter 40 value 82.895210
iter 50 value 82.093052
iter 60 value 81.923656
iter 70 value 81.392545
iter 80 value 81.285941
final value 81.208071
converged
Fitting Repeat 1
# weights: 305
initial value 100.589073
iter 10 value 94.046755
iter 20 value 93.927557
iter 30 value 92.177302
iter 40 value 90.669675
iter 50 value 83.667945
iter 60 value 81.307682
iter 70 value 80.955561
iter 80 value 80.828070
iter 90 value 80.401902
iter 100 value 80.008220
final value 80.008220
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.604970
iter 10 value 93.492115
iter 20 value 88.025985
iter 30 value 86.864360
iter 40 value 86.349523
iter 50 value 84.068761
iter 60 value 83.359949
iter 70 value 83.169465
iter 80 value 83.137518
iter 90 value 83.124511
iter 100 value 83.109593
final value 83.109593
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.899050
iter 10 value 91.834460
iter 20 value 85.735532
iter 30 value 84.528678
iter 40 value 82.643246
iter 50 value 82.014506
iter 60 value 81.757850
iter 70 value 81.573753
iter 80 value 81.508762
iter 90 value 80.706306
iter 100 value 80.507723
final value 80.507723
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.791926
iter 10 value 94.023017
iter 20 value 91.171474
iter 30 value 86.234633
iter 40 value 84.388072
iter 50 value 82.462565
iter 60 value 81.466979
iter 70 value 80.576415
iter 80 value 79.968751
iter 90 value 79.786050
iter 100 value 79.519120
final value 79.519120
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 110.266156
iter 10 value 92.059620
iter 20 value 86.783633
iter 30 value 84.899873
iter 40 value 83.227732
iter 50 value 82.075202
iter 60 value 81.609898
iter 70 value 81.139957
iter 80 value 80.677320
iter 90 value 80.538159
iter 100 value 80.436082
final value 80.436082
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.129675
iter 10 value 94.647175
iter 20 value 94.099205
iter 30 value 93.174652
iter 40 value 89.757700
iter 50 value 86.427720
iter 60 value 84.967386
iter 70 value 81.417155
iter 80 value 80.131884
iter 90 value 79.819413
iter 100 value 79.614533
final value 79.614533
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.859430
iter 10 value 94.489907
iter 20 value 88.702659
iter 30 value 85.560921
iter 40 value 85.175777
iter 50 value 82.343023
iter 60 value 81.033367
iter 70 value 80.741350
iter 80 value 79.926933
iter 90 value 79.609776
iter 100 value 79.513723
final value 79.513723
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.449622
iter 10 value 94.242653
iter 20 value 92.374398
iter 30 value 86.231512
iter 40 value 85.724606
iter 50 value 85.131906
iter 60 value 83.838116
iter 70 value 82.098433
iter 80 value 81.290655
iter 90 value 80.551963
iter 100 value 80.084111
final value 80.084111
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 155.316784
iter 10 value 94.384321
iter 20 value 87.348631
iter 30 value 84.305874
iter 40 value 82.962784
iter 50 value 81.934554
iter 60 value 80.867030
iter 70 value 80.371390
iter 80 value 80.094205
iter 90 value 79.992419
iter 100 value 79.868550
final value 79.868550
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.667554
iter 10 value 95.204754
iter 20 value 94.098773
iter 30 value 89.196474
iter 40 value 85.136169
iter 50 value 84.642146
iter 60 value 84.558160
iter 70 value 83.774208
iter 80 value 82.271207
iter 90 value 80.963429
iter 100 value 80.520987
final value 80.520987
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.419793
final value 94.054565
converged
Fitting Repeat 2
# weights: 103
initial value 98.135302
final value 94.054830
converged
Fitting Repeat 3
# weights: 103
initial value 103.114012
iter 10 value 94.054632
iter 20 value 94.027573
iter 30 value 92.757899
iter 40 value 92.248364
iter 50 value 83.678625
iter 60 value 83.329472
iter 70 value 82.933607
final value 82.933549
converged
Fitting Repeat 4
# weights: 103
initial value 101.090134
final value 94.054736
converged
Fitting Repeat 5
# weights: 103
initial value 102.113722
iter 10 value 94.039951
iter 20 value 94.038443
iter 30 value 84.918381
iter 40 value 84.779747
final value 84.779466
converged
Fitting Repeat 1
# weights: 305
initial value 94.726842
iter 10 value 94.042695
iter 20 value 94.040695
iter 30 value 94.038568
iter 40 value 93.630670
iter 50 value 85.437070
iter 60 value 82.545668
iter 70 value 81.641327
iter 80 value 81.607382
iter 90 value 81.500569
iter 100 value 81.499742
final value 81.499742
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.183246
iter 10 value 94.061010
iter 20 value 94.059582
iter 30 value 94.049482
iter 40 value 92.469501
iter 50 value 85.991777
iter 60 value 85.978217
iter 70 value 85.964413
iter 80 value 85.947525
iter 90 value 85.840864
iter 100 value 85.839065
final value 85.839065
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.511201
iter 10 value 94.057850
iter 20 value 94.051755
iter 30 value 90.006848
iter 40 value 87.641542
iter 50 value 85.513506
iter 60 value 84.266694
iter 70 value 84.264508
iter 80 value 84.255185
iter 90 value 84.216583
iter 100 value 84.216124
final value 84.216124
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.498778
iter 10 value 93.950946
iter 20 value 93.949027
iter 30 value 93.942219
iter 40 value 88.066617
iter 50 value 86.224820
iter 60 value 86.203311
iter 70 value 86.192776
iter 80 value 85.133985
iter 90 value 85.097229
iter 100 value 85.092625
final value 85.092625
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 97.854671
iter 10 value 93.808714
iter 20 value 93.515387
iter 30 value 93.513629
iter 40 value 85.142933
iter 50 value 84.619008
iter 60 value 84.153798
iter 70 value 83.920517
final value 83.919900
converged
Fitting Repeat 1
# weights: 507
initial value 95.507307
iter 10 value 92.589743
iter 20 value 92.449656
iter 30 value 92.247278
iter 40 value 92.245368
final value 92.245099
converged
Fitting Repeat 2
# weights: 507
initial value 95.213112
iter 10 value 94.017579
iter 20 value 94.013258
iter 30 value 93.961436
iter 40 value 85.478465
iter 50 value 83.892578
iter 60 value 83.835729
iter 70 value 83.798815
iter 80 value 83.509109
iter 90 value 81.329883
iter 100 value 80.433261
final value 80.433261
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.087599
iter 10 value 94.006827
iter 20 value 94.002237
iter 30 value 93.979558
iter 40 value 87.137165
iter 50 value 86.786804
iter 60 value 84.670740
iter 70 value 83.400004
iter 80 value 83.387586
final value 83.387231
converged
Fitting Repeat 4
# weights: 507
initial value 108.714091
iter 10 value 94.061619
iter 20 value 94.053911
iter 30 value 91.896640
iter 40 value 83.508776
iter 50 value 82.320949
iter 60 value 82.223995
iter 70 value 82.223475
final value 82.223366
converged
Fitting Repeat 5
# weights: 507
initial value 102.392293
iter 10 value 94.046762
iter 20 value 94.039261
iter 30 value 93.968467
iter 40 value 84.117308
iter 50 value 84.070738
final value 84.069649
converged
Fitting Repeat 1
# weights: 103
initial value 103.968016
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 105.290514
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 105.561051
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.058471
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.746379
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 121.160689
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 95.595123
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 116.550180
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 99.596444
iter 10 value 88.687771
iter 20 value 87.603064
iter 30 value 87.576817
iter 40 value 87.564236
iter 50 value 87.564051
iter 50 value 87.564050
iter 50 value 87.564050
final value 87.564050
converged
Fitting Repeat 5
# weights: 305
initial value 111.752209
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 97.224576
final value 94.443243
converged
Fitting Repeat 2
# weights: 507
initial value 99.486928
iter 10 value 87.105060
iter 20 value 85.109641
iter 30 value 84.969970
iter 40 value 84.916433
final value 84.916364
converged
Fitting Repeat 3
# weights: 507
initial value 114.587422
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 103.992138
iter 10 value 94.338030
final value 94.337732
converged
Fitting Repeat 5
# weights: 507
initial value 95.592853
iter 10 value 94.337794
final value 94.337729
converged
Fitting Repeat 1
# weights: 103
initial value 111.027528
iter 10 value 94.318682
iter 20 value 93.406045
iter 30 value 92.775227
iter 40 value 92.253387
iter 50 value 91.911107
iter 60 value 91.818201
iter 70 value 91.798491
iter 80 value 84.032276
iter 90 value 83.187722
iter 100 value 83.137279
final value 83.137279
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 108.996860
iter 10 value 94.278511
iter 20 value 88.573787
iter 30 value 88.074487
iter 40 value 87.393724
iter 50 value 86.462854
iter 60 value 84.999223
iter 70 value 84.734563
iter 80 value 84.727220
iter 90 value 84.702630
iter 100 value 84.635540
final value 84.635540
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.999923
iter 10 value 94.464053
iter 20 value 93.905043
iter 30 value 93.039537
iter 40 value 90.329182
iter 50 value 85.855548
iter 60 value 84.649072
iter 70 value 84.059343
iter 80 value 83.941520
iter 90 value 83.533748
iter 100 value 83.146631
final value 83.146631
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 115.576618
iter 10 value 94.448723
iter 20 value 93.538888
iter 30 value 92.607720
iter 40 value 92.150281
iter 50 value 92.104850
iter 50 value 92.104849
iter 50 value 92.104849
final value 92.104849
converged
Fitting Repeat 5
# weights: 103
initial value 102.742343
iter 10 value 94.280703
iter 20 value 90.564177
iter 30 value 89.117897
iter 40 value 88.477018
iter 50 value 88.196073
iter 60 value 86.185260
iter 70 value 85.488381
iter 80 value 85.480675
iter 90 value 85.479362
final value 85.479353
converged
Fitting Repeat 1
# weights: 305
initial value 102.483321
iter 10 value 94.500989
iter 20 value 90.159803
iter 30 value 86.690922
iter 40 value 86.274858
iter 50 value 84.865995
iter 60 value 83.002347
iter 70 value 82.382185
iter 80 value 82.093226
iter 90 value 82.013332
iter 100 value 81.988202
final value 81.988202
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.301057
iter 10 value 94.408946
iter 20 value 92.001888
iter 30 value 87.358641
iter 40 value 84.571480
iter 50 value 84.078535
iter 60 value 83.105935
iter 70 value 82.465510
iter 80 value 82.402754
iter 90 value 82.243299
iter 100 value 82.152004
final value 82.152004
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 110.520310
iter 10 value 94.693967
iter 20 value 93.168268
iter 30 value 90.687817
iter 40 value 87.561426
iter 50 value 85.581570
iter 60 value 84.945909
iter 70 value 84.463692
iter 80 value 83.724189
iter 90 value 82.652981
iter 100 value 82.167352
final value 82.167352
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 120.636232
iter 10 value 96.823033
iter 20 value 94.676816
iter 30 value 92.771265
iter 40 value 89.875332
iter 50 value 85.036181
iter 60 value 84.195505
iter 70 value 83.847754
iter 80 value 82.583951
iter 90 value 82.237592
iter 100 value 82.064966
final value 82.064966
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.878048
iter 10 value 95.009936
iter 20 value 91.532290
iter 30 value 88.429934
iter 40 value 84.430157
iter 50 value 83.055489
iter 60 value 82.627377
iter 70 value 82.092596
iter 80 value 81.915468
iter 90 value 81.829476
iter 100 value 81.796635
final value 81.796635
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.600391
iter 10 value 95.017397
iter 20 value 91.225617
iter 30 value 89.679430
iter 40 value 87.288298
iter 50 value 85.658497
iter 60 value 84.030169
iter 70 value 83.718247
iter 80 value 82.762040
iter 90 value 82.368028
iter 100 value 82.196950
final value 82.196950
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.364284
iter 10 value 94.512572
iter 20 value 93.454084
iter 30 value 92.088868
iter 40 value 91.794443
iter 50 value 86.959652
iter 60 value 85.669726
iter 70 value 85.192006
iter 80 value 84.052156
iter 90 value 83.396786
iter 100 value 83.101680
final value 83.101680
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 145.915441
iter 10 value 97.527626
iter 20 value 94.970857
iter 30 value 93.531273
iter 40 value 87.975702
iter 50 value 84.540330
iter 60 value 84.264598
iter 70 value 82.637641
iter 80 value 81.923344
iter 90 value 81.700795
iter 100 value 81.625063
final value 81.625063
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 138.142616
iter 10 value 94.375700
iter 20 value 93.894646
iter 30 value 88.015471
iter 40 value 86.432592
iter 50 value 84.983553
iter 60 value 83.558708
iter 70 value 82.211867
iter 80 value 82.029068
iter 90 value 81.832139
iter 100 value 81.704899
final value 81.704899
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.148203
iter 10 value 94.657999
iter 20 value 94.463672
iter 30 value 93.251898
iter 40 value 89.682906
iter 50 value 85.759803
iter 60 value 84.040279
iter 70 value 82.877143
iter 80 value 82.589147
iter 90 value 82.291243
iter 100 value 82.121254
final value 82.121254
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.278711
final value 94.485929
converged
Fitting Repeat 2
# weights: 103
initial value 109.402820
final value 94.444978
converged
Fitting Repeat 3
# weights: 103
initial value 111.796928
final value 94.485940
converged
Fitting Repeat 4
# weights: 103
initial value 97.016004
final value 94.485663
converged
Fitting Repeat 5
# weights: 103
initial value 105.872142
final value 94.355821
converged
Fitting Repeat 1
# weights: 305
initial value 115.563364
iter 10 value 94.490070
iter 20 value 94.441729
iter 30 value 87.094603
iter 40 value 84.412697
iter 50 value 84.280372
iter 60 value 84.072359
iter 70 value 84.068141
iter 80 value 84.014261
iter 90 value 84.014063
iter 90 value 84.014063
final value 84.014063
converged
Fitting Repeat 2
# weights: 305
initial value 110.170833
iter 10 value 94.489163
iter 20 value 94.453737
iter 30 value 87.113109
iter 40 value 86.690515
iter 50 value 86.688509
iter 60 value 86.688386
iter 70 value 86.390701
iter 80 value 83.788975
iter 90 value 83.641520
iter 100 value 83.631391
final value 83.631391
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.592565
iter 10 value 94.448060
iter 20 value 94.432966
iter 30 value 94.428730
iter 40 value 94.008363
iter 50 value 86.683462
iter 60 value 84.736518
iter 70 value 84.490978
iter 80 value 84.417869
iter 90 value 84.408475
final value 84.408035
converged
Fitting Repeat 4
# weights: 305
initial value 107.234966
iter 10 value 94.449100
iter 20 value 94.445439
iter 30 value 94.443700
iter 40 value 93.126297
iter 50 value 93.084903
iter 60 value 92.643635
iter 70 value 92.642514
iter 80 value 92.633898
iter 90 value 92.220014
iter 100 value 92.133689
final value 92.133689
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.862861
iter 10 value 94.488938
iter 20 value 94.461979
iter 30 value 92.308243
final value 92.302888
converged
Fitting Repeat 1
# weights: 507
initial value 100.005342
iter 10 value 94.456963
iter 20 value 89.662162
iter 30 value 89.638390
iter 40 value 88.216803
iter 50 value 88.210300
final value 88.210275
converged
Fitting Repeat 2
# weights: 507
initial value 95.979098
iter 10 value 94.451776
iter 20 value 93.397597
iter 30 value 86.551458
iter 40 value 86.519363
iter 50 value 86.518278
iter 60 value 86.418852
iter 70 value 86.348240
iter 80 value 85.979044
final value 85.978854
converged
Fitting Repeat 3
# weights: 507
initial value 101.282835
iter 10 value 94.451346
iter 20 value 94.290097
iter 30 value 87.648915
iter 40 value 86.569614
final value 86.565488
converged
Fitting Repeat 4
# weights: 507
initial value 97.684431
iter 10 value 94.451783
iter 20 value 93.865165
iter 30 value 89.763836
iter 40 value 89.375759
iter 50 value 89.220195
iter 60 value 89.219314
iter 70 value 89.218255
iter 80 value 88.662376
iter 90 value 86.680177
iter 100 value 85.558967
final value 85.558967
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 102.227094
iter 10 value 86.335672
iter 20 value 85.761884
iter 30 value 85.758562
iter 40 value 84.690128
iter 50 value 84.478694
iter 60 value 83.481949
iter 70 value 81.241958
iter 80 value 81.079700
iter 90 value 80.832399
iter 100 value 80.784137
final value 80.784137
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 113.607256
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.985136
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 103.464303
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 103.110838
final value 94.466823
converged
Fitting Repeat 5
# weights: 103
initial value 97.916685
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 117.154436
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 108.066353
iter 10 value 91.695602
iter 20 value 87.804697
iter 30 value 87.732084
iter 40 value 87.728143
final value 87.728141
converged
Fitting Repeat 3
# weights: 305
initial value 106.502362
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 109.796498
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 97.003927
final value 94.466823
converged
Fitting Repeat 1
# weights: 507
initial value 96.778711
iter 10 value 94.470230
iter 20 value 94.466831
final value 94.466824
converged
Fitting Repeat 2
# weights: 507
initial value 94.685601
iter 10 value 91.965382
iter 20 value 91.538149
final value 91.533919
converged
Fitting Repeat 3
# weights: 507
initial value 95.434968
final value 94.466823
converged
Fitting Repeat 4
# weights: 507
initial value 98.896269
iter 10 value 93.676351
iter 20 value 91.685607
iter 30 value 90.275104
iter 40 value 89.902431
iter 50 value 89.759205
iter 60 value 89.754910
final value 89.754867
converged
Fitting Repeat 5
# weights: 507
initial value 105.279635
final value 94.466823
converged
Fitting Repeat 1
# weights: 103
initial value 110.167375
iter 10 value 94.486494
iter 20 value 93.768779
iter 30 value 93.290003
iter 40 value 90.018799
iter 50 value 89.422796
iter 60 value 88.808028
iter 70 value 84.851745
iter 80 value 84.836548
iter 90 value 84.834979
final value 84.834959
converged
Fitting Repeat 2
# weights: 103
initial value 97.110870
iter 10 value 90.557475
iter 20 value 86.532337
iter 30 value 85.483102
iter 40 value 85.274916
iter 50 value 84.857407
iter 60 value 84.835051
final value 84.834959
converged
Fitting Repeat 3
# weights: 103
initial value 100.507303
iter 10 value 94.489014
iter 20 value 87.076341
iter 30 value 85.613924
iter 40 value 85.530202
iter 50 value 85.520522
final value 85.517772
converged
Fitting Repeat 4
# weights: 103
initial value 109.209975
iter 10 value 94.314483
iter 20 value 88.439372
iter 30 value 87.548003
iter 40 value 86.400461
iter 50 value 85.744542
iter 60 value 85.386671
final value 85.370714
converged
Fitting Repeat 5
# weights: 103
initial value 102.954123
iter 10 value 94.637810
iter 20 value 88.988675
iter 30 value 85.728155
iter 40 value 84.552756
iter 50 value 84.316354
iter 60 value 83.342418
iter 70 value 82.349559
iter 80 value 82.080114
iter 90 value 81.665315
iter 100 value 81.536681
final value 81.536681
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.816010
iter 10 value 90.000714
iter 20 value 88.160525
iter 30 value 85.977856
iter 40 value 84.408278
iter 50 value 83.775861
iter 60 value 83.052572
iter 70 value 82.662632
iter 80 value 82.044017
iter 90 value 81.480691
iter 100 value 81.418760
final value 81.418760
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.449115
iter 10 value 94.387455
iter 20 value 93.618642
iter 30 value 92.321766
iter 40 value 86.707278
iter 50 value 84.812481
iter 60 value 84.373168
iter 70 value 83.945090
iter 80 value 81.865224
iter 90 value 80.918506
iter 100 value 80.529216
final value 80.529216
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 115.961094
iter 10 value 94.654845
iter 20 value 94.130823
iter 30 value 84.802687
iter 40 value 83.846591
iter 50 value 82.740251
iter 60 value 82.104753
iter 70 value 81.991724
iter 80 value 81.795742
iter 90 value 80.882821
iter 100 value 80.411229
final value 80.411229
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.294998
iter 10 value 94.245938
iter 20 value 89.309029
iter 30 value 88.839596
iter 40 value 88.701835
iter 50 value 87.128813
iter 60 value 85.035219
iter 70 value 84.087497
iter 80 value 83.600439
iter 90 value 83.488726
iter 100 value 82.534164
final value 82.534164
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.900473
iter 10 value 94.490110
iter 20 value 87.432891
iter 30 value 86.354628
iter 40 value 86.273870
iter 50 value 86.028838
iter 60 value 84.159941
iter 70 value 83.339934
iter 80 value 81.747161
iter 90 value 80.745532
iter 100 value 80.620218
final value 80.620218
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.733476
iter 10 value 88.955849
iter 20 value 85.902796
iter 30 value 84.918032
iter 40 value 82.559686
iter 50 value 81.883419
iter 60 value 81.597014
iter 70 value 81.462975
iter 80 value 81.393690
iter 90 value 80.644752
iter 100 value 80.496070
final value 80.496070
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 116.149028
iter 10 value 94.042560
iter 20 value 91.680112
iter 30 value 90.745963
iter 40 value 90.607151
iter 50 value 84.624464
iter 60 value 83.645411
iter 70 value 82.761917
iter 80 value 82.311283
iter 90 value 81.772025
iter 100 value 81.562908
final value 81.562908
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.338994
iter 10 value 94.435310
iter 20 value 93.331906
iter 30 value 91.648009
iter 40 value 89.852344
iter 50 value 84.662415
iter 60 value 83.795736
iter 70 value 83.557655
iter 80 value 82.738531
iter 90 value 82.555805
iter 100 value 82.224351
final value 82.224351
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.400150
iter 10 value 91.725124
iter 20 value 88.994205
iter 30 value 88.344130
iter 40 value 87.155605
iter 50 value 85.571016
iter 60 value 84.978825
iter 70 value 84.275151
iter 80 value 82.859018
iter 90 value 82.319527
iter 100 value 81.541276
final value 81.541276
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 122.604756
iter 10 value 94.834653
iter 20 value 91.603831
iter 30 value 88.639364
iter 40 value 88.391107
iter 50 value 86.685618
iter 60 value 85.282732
iter 70 value 84.599167
iter 80 value 83.679825
iter 90 value 82.819273
iter 100 value 82.570547
final value 82.570547
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.457753
final value 94.485817
converged
Fitting Repeat 2
# weights: 103
initial value 99.517443
final value 94.485835
converged
Fitting Repeat 3
# weights: 103
initial value 94.507980
final value 94.485649
converged
Fitting Repeat 4
# weights: 103
initial value 97.588057
final value 94.485820
converged
Fitting Repeat 5
# weights: 103
initial value 102.868966
final value 94.486107
converged
Fitting Repeat 1
# weights: 305
initial value 102.325443
iter 10 value 94.489702
iter 20 value 94.433188
iter 30 value 93.558402
final value 93.558397
converged
Fitting Repeat 2
# weights: 305
initial value 101.620039
iter 10 value 94.471539
iter 20 value 93.896565
iter 30 value 93.165579
iter 40 value 92.679148
iter 50 value 86.516412
iter 60 value 85.406759
iter 70 value 81.836763
iter 80 value 80.530818
iter 90 value 80.385454
iter 100 value 80.381592
final value 80.381592
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 116.465091
iter 10 value 94.489969
iter 20 value 94.484874
iter 30 value 88.034869
iter 40 value 86.723862
iter 50 value 86.639635
iter 60 value 83.757980
iter 70 value 83.547647
iter 80 value 83.500998
iter 90 value 83.500717
iter 100 value 83.500286
final value 83.500286
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 117.754657
iter 10 value 94.471989
iter 20 value 94.468266
iter 30 value 91.836251
iter 40 value 88.766746
iter 50 value 88.757351
final value 88.756868
converged
Fitting Repeat 5
# weights: 305
initial value 96.057817
iter 10 value 94.488441
iter 20 value 94.330538
iter 30 value 85.102999
iter 40 value 85.097081
iter 50 value 84.904890
iter 60 value 84.592381
iter 70 value 84.587485
iter 80 value 84.269052
iter 90 value 83.232813
iter 100 value 83.224613
final value 83.224613
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 120.520943
iter 10 value 94.493451
iter 20 value 94.485888
iter 30 value 88.809358
iter 40 value 85.753293
iter 50 value 85.674869
iter 60 value 85.672946
iter 70 value 85.669645
iter 80 value 85.669490
iter 90 value 85.669093
iter 100 value 85.567395
final value 85.567395
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 125.775926
iter 10 value 94.494271
iter 20 value 94.484576
iter 30 value 93.558797
iter 40 value 93.558630
iter 40 value 93.558629
final value 93.558627
converged
Fitting Repeat 3
# weights: 507
initial value 104.646664
iter 10 value 94.491396
iter 20 value 93.851882
iter 30 value 90.560399
iter 40 value 90.260202
iter 50 value 89.802048
iter 60 value 89.456850
iter 70 value 89.456088
iter 80 value 89.455203
iter 90 value 87.189031
iter 100 value 85.621573
final value 85.621573
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.639382
iter 10 value 94.492321
iter 20 value 94.484149
iter 30 value 93.201547
iter 40 value 90.103614
iter 50 value 85.729499
iter 60 value 85.703558
iter 70 value 84.079115
iter 80 value 81.865073
iter 90 value 81.856373
iter 100 value 81.841512
final value 81.841512
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 126.391980
iter 10 value 94.541556
iter 20 value 94.097578
iter 30 value 87.684275
iter 40 value 84.544204
iter 50 value 84.493827
iter 60 value 84.459515
iter 70 value 84.404876
iter 80 value 83.910454
iter 90 value 83.152595
iter 100 value 83.104998
final value 83.104998
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.881546
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.827372
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 100.027181
iter 10 value 94.026543
iter 10 value 94.026542
iter 10 value 94.026542
final value 94.026542
converged
Fitting Repeat 4
# weights: 103
initial value 96.111030
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.461052
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 126.128283
iter 10 value 93.715479
final value 93.714942
converged
Fitting Repeat 2
# weights: 305
initial value 103.109841
final value 94.484137
converged
Fitting Repeat 3
# weights: 305
initial value 95.837647
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 110.488384
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 105.270649
iter 10 value 92.863250
iter 20 value 79.639935
iter 30 value 79.227006
iter 40 value 79.179434
iter 50 value 79.050791
iter 60 value 78.787216
iter 70 value 78.758692
iter 80 value 78.736161
iter 90 value 78.659972
final value 78.653671
converged
Fitting Repeat 1
# weights: 507
initial value 113.331731
iter 10 value 89.237971
iter 20 value 80.054988
iter 30 value 79.601286
iter 40 value 79.511654
iter 50 value 79.511404
final value 79.511388
converged
Fitting Repeat 2
# weights: 507
initial value 95.237245
iter 10 value 89.930187
iter 20 value 89.713136
iter 30 value 89.542452
final value 89.542428
converged
Fitting Repeat 3
# weights: 507
initial value 100.830599
final value 94.026542
converged
Fitting Repeat 4
# weights: 507
initial value 102.891711
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 100.536548
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 99.650293
iter 10 value 94.375366
iter 20 value 90.812379
iter 30 value 90.756095
iter 40 value 90.632675
iter 50 value 89.125761
iter 60 value 89.041698
iter 70 value 89.027813
iter 80 value 89.023356
final value 89.023314
converged
Fitting Repeat 2
# weights: 103
initial value 101.673670
iter 10 value 94.274369
iter 20 value 84.184740
iter 30 value 80.917905
iter 40 value 80.678491
iter 50 value 78.402156
iter 60 value 78.124888
final value 78.124686
converged
Fitting Repeat 3
# weights: 103
initial value 96.636410
iter 10 value 94.458209
iter 20 value 88.881104
iter 30 value 81.658002
iter 40 value 81.537767
iter 50 value 81.424116
iter 60 value 81.201227
iter 70 value 80.997237
iter 80 value 80.952776
iter 80 value 80.952776
iter 80 value 80.952776
final value 80.952776
converged
Fitting Repeat 4
# weights: 103
initial value 99.154258
final value 94.488535
converged
Fitting Repeat 5
# weights: 103
initial value 103.634733
iter 10 value 93.724184
iter 20 value 85.180992
iter 30 value 84.932928
iter 40 value 81.607442
iter 50 value 80.987387
iter 60 value 80.953290
iter 70 value 80.952791
final value 80.952776
converged
Fitting Repeat 1
# weights: 305
initial value 119.656826
iter 10 value 94.239261
iter 20 value 85.507248
iter 30 value 83.949206
iter 40 value 81.371333
iter 50 value 80.336869
iter 60 value 79.028963
iter 70 value 78.295649
iter 80 value 77.276308
iter 90 value 77.151631
iter 100 value 77.049643
final value 77.049643
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.485319
iter 10 value 93.988354
iter 20 value 84.665583
iter 30 value 83.112892
iter 40 value 79.855740
iter 50 value 79.053219
iter 60 value 78.570546
iter 70 value 78.442887
iter 80 value 78.277860
iter 90 value 78.182046
iter 100 value 78.149610
final value 78.149610
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.662028
iter 10 value 94.496526
iter 20 value 94.153401
iter 30 value 93.547378
iter 40 value 91.173584
iter 50 value 90.450594
iter 60 value 88.382235
iter 70 value 81.959873
iter 80 value 81.344149
iter 90 value 81.201655
iter 100 value 80.010829
final value 80.010829
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.221809
iter 10 value 94.496288
iter 20 value 94.132285
iter 30 value 93.984179
iter 40 value 89.933417
iter 50 value 81.775601
iter 60 value 79.507684
iter 70 value 79.257176
iter 80 value 78.440868
iter 90 value 77.803253
iter 100 value 77.295995
final value 77.295995
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 121.203008
iter 10 value 94.399848
iter 20 value 91.414073
iter 30 value 86.628565
iter 40 value 86.227646
iter 50 value 85.166148
iter 60 value 83.678067
iter 70 value 80.106953
iter 80 value 79.467824
iter 90 value 79.069582
iter 100 value 78.802416
final value 78.802416
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 117.342882
iter 10 value 94.596038
iter 20 value 86.610809
iter 30 value 83.183052
iter 40 value 82.347919
iter 50 value 79.884980
iter 60 value 79.184533
iter 70 value 78.393950
iter 80 value 77.464911
iter 90 value 77.272515
iter 100 value 77.085368
final value 77.085368
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.049719
iter 10 value 95.411428
iter 20 value 94.499070
iter 30 value 90.710020
iter 40 value 85.512676
iter 50 value 80.793470
iter 60 value 78.444915
iter 70 value 77.711625
iter 80 value 76.945019
iter 90 value 76.697355
iter 100 value 76.514107
final value 76.514107
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.444541
iter 10 value 94.175451
iter 20 value 87.059238
iter 30 value 81.671313
iter 40 value 79.430016
iter 50 value 78.842054
iter 60 value 78.520598
iter 70 value 78.300296
iter 80 value 77.985886
iter 90 value 77.943556
iter 100 value 77.890082
final value 77.890082
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 120.385638
iter 10 value 94.585299
iter 20 value 90.848563
iter 30 value 83.701760
iter 40 value 83.382877
iter 50 value 81.816362
iter 60 value 79.717919
iter 70 value 78.114431
iter 80 value 77.941102
iter 90 value 77.466644
iter 100 value 77.255383
final value 77.255383
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.732607
iter 10 value 94.780298
iter 20 value 88.991208
iter 30 value 82.281969
iter 40 value 79.955228
iter 50 value 78.756629
iter 60 value 76.835584
iter 70 value 76.657817
iter 80 value 76.545974
iter 90 value 76.233802
iter 100 value 76.053638
final value 76.053638
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 107.704985
iter 10 value 94.808234
iter 20 value 94.705273
iter 30 value 94.510444
final value 94.484222
converged
Fitting Repeat 2
# weights: 103
initial value 103.225800
iter 10 value 94.029108
iter 20 value 94.027640
final value 94.026694
converged
Fitting Repeat 3
# weights: 103
initial value 95.457710
final value 94.485926
converged
Fitting Repeat 4
# weights: 103
initial value 95.016174
final value 94.485775
converged
Fitting Repeat 5
# weights: 103
initial value 108.019338
final value 94.485871
converged
Fitting Repeat 1
# weights: 305
initial value 112.394395
iter 10 value 94.489066
iter 20 value 94.484242
iter 30 value 93.866535
iter 40 value 93.551567
iter 50 value 86.818669
iter 60 value 85.118500
iter 70 value 85.115647
iter 80 value 85.105637
iter 90 value 83.381422
iter 100 value 83.213995
final value 83.213995
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 110.830167
iter 10 value 94.489391
iter 20 value 94.403836
iter 30 value 83.677600
iter 40 value 82.837467
iter 50 value 79.184888
iter 60 value 79.089086
iter 70 value 79.074812
iter 80 value 79.062557
iter 90 value 79.059394
iter 100 value 79.042195
final value 79.042195
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 92.609993
iter 10 value 85.790198
iter 20 value 84.723628
iter 30 value 84.708968
iter 40 value 82.131271
iter 50 value 78.604183
iter 60 value 78.248896
iter 70 value 78.237171
iter 80 value 77.545287
iter 90 value 75.949736
iter 100 value 75.700848
final value 75.700848
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.082382
iter 10 value 94.031620
iter 20 value 93.964508
iter 30 value 88.624544
iter 40 value 79.089995
iter 50 value 78.513025
iter 60 value 77.974117
iter 70 value 77.935295
final value 77.935153
converged
Fitting Repeat 5
# weights: 305
initial value 98.156121
iter 10 value 94.031305
iter 20 value 94.026412
iter 30 value 92.197651
iter 40 value 86.056035
iter 50 value 85.630531
iter 60 value 85.416678
iter 70 value 80.783307
iter 80 value 80.712981
iter 90 value 80.108184
final value 80.107267
converged
Fitting Repeat 1
# weights: 507
initial value 97.663253
iter 10 value 94.035313
iter 20 value 93.937197
iter 30 value 93.794987
final value 93.790881
converged
Fitting Repeat 2
# weights: 507
initial value 105.564743
iter 10 value 94.492333
iter 20 value 94.484261
final value 94.484217
converged
Fitting Repeat 3
# weights: 507
initial value 95.827231
iter 10 value 86.168552
iter 20 value 84.972136
iter 30 value 84.960598
iter 40 value 84.958248
iter 50 value 84.952927
iter 60 value 84.952013
iter 70 value 82.819052
iter 80 value 79.802379
iter 90 value 79.713599
iter 100 value 79.532619
final value 79.532619
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.101081
iter 10 value 92.996040
iter 20 value 83.321030
iter 30 value 83.287036
iter 40 value 83.079561
iter 50 value 82.972984
iter 60 value 82.961116
iter 70 value 82.959304
iter 80 value 82.863308
iter 90 value 82.120667
iter 100 value 79.138737
final value 79.138737
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 96.307442
iter 10 value 94.492339
iter 20 value 94.484411
iter 30 value 88.406989
iter 40 value 87.178244
iter 50 value 87.177706
iter 60 value 87.175039
iter 70 value 85.091532
iter 80 value 83.802446
iter 90 value 81.971046
iter 100 value 81.890592
final value 81.890592
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 136.824183
iter 10 value 117.524685
iter 20 value 112.180964
iter 30 value 108.429825
iter 40 value 104.890335
iter 50 value 103.076526
iter 60 value 101.988316
iter 70 value 101.585142
iter 80 value 101.380991
final value 101.341156
converged
Fitting Repeat 2
# weights: 507
initial value 147.929429
iter 10 value 117.497251
iter 20 value 107.752937
iter 30 value 107.397435
iter 40 value 105.407701
iter 50 value 105.006441
iter 60 value 104.041818
iter 70 value 103.153668
iter 80 value 102.372958
iter 90 value 101.913027
iter 100 value 101.416285
final value 101.416285
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 143.511874
iter 10 value 111.679588
iter 20 value 106.282742
iter 30 value 104.987757
iter 40 value 103.104153
iter 50 value 102.173651
iter 60 value 101.342658
iter 70 value 100.915589
iter 80 value 100.643747
iter 90 value 100.273717
iter 100 value 100.155504
final value 100.155504
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 148.152376
iter 10 value 117.902613
iter 20 value 115.280164
iter 30 value 109.276624
iter 40 value 106.614814
iter 50 value 104.535414
iter 60 value 103.068297
iter 70 value 102.466213
iter 80 value 101.745097
iter 90 value 101.654195
iter 100 value 101.563876
final value 101.563876
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 127.788104
iter 10 value 118.330675
iter 20 value 117.484120
iter 30 value 110.951569
iter 40 value 109.319646
iter 50 value 107.402493
iter 60 value 103.142848
iter 70 value 102.479226
iter 80 value 102.211734
iter 90 value 102.047472
iter 100 value 101.801256
final value 101.801256
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 -- Thu Dec 4 02:35:20 2025
***********************************************
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
41.453 1.162 95.002
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 32.587 | 0.586 | 33.175 | |
| FreqInteractors | 0.422 | 0.036 | 0.457 | |
| calculateAAC | 0.029 | 0.003 | 0.033 | |
| calculateAutocor | 0.270 | 0.018 | 0.289 | |
| calculateCTDC | 0.071 | 0.000 | 0.071 | |
| calculateCTDD | 0.444 | 0.003 | 0.447 | |
| calculateCTDT | 0.135 | 0.001 | 0.137 | |
| calculateCTriad | 0.345 | 0.008 | 0.353 | |
| calculateDC | 0.082 | 0.008 | 0.090 | |
| calculateF | 0.286 | 0.001 | 0.287 | |
| calculateKSAAP | 0.097 | 0.004 | 0.100 | |
| calculateQD_Sm | 1.609 | 0.034 | 1.643 | |
| calculateTC | 1.516 | 0.134 | 1.650 | |
| calculateTC_Sm | 0.249 | 0.005 | 0.254 | |
| corr_plot | 33.427 | 0.508 | 33.937 | |
| enrichfindP | 0.517 | 0.044 | 15.689 | |
| enrichfind_hp | 0.044 | 0.003 | 1.173 | |
| enrichplot | 0.475 | 0.002 | 0.477 | |
| filter_missing_values | 0.000 | 0.000 | 0.001 | |
| getFASTA | 0.337 | 0.007 | 6.877 | |
| getHPI | 0.001 | 0.001 | 0.001 | |
| get_negativePPI | 0.001 | 0.001 | 0.001 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.000 | 0.001 | 0.001 | |
| plotPPI | 0.082 | 0.000 | 0.082 | |
| pred_ensembel | 12.769 | 0.119 | 11.519 | |
| var_imp | 32.800 | 0.423 | 33.226 | |