Matineh Rahmatbakhsh
| Snapshot Date: 2025-01-30 13:00 -0500 (Thu, 30 Jan 2025) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_20 |
| git_last_commit: ce9e305 |
| git_last_commit_date: 2024-10-29 11:04:11 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-02-03 12:06 -0500 (Mon, 03 Feb 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4746 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4494 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4517 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4469 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4400 |
| 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 979/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.12.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.12.0 |
| Command: F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.12.0.tar.gz |
| StartedAt: 2025-01-31 02:57:52 -0500 (Fri, 31 Jan 2025) |
| EndedAt: 2025-01-31 03:03:24 -0500 (Fri, 31 Jan 2025) |
| EllapsedTime: 332.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck'
* using R version 4.4.2 (2024-10-31 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 13.3.0
GNU Fortran (GCC) 13.3.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.12.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
FSmethod 34.08 2.30 36.55
var_imp 34.11 1.72 35.83
corr_plot 33.56 1.72 35.29
pred_ensembel 12.74 0.48 12.21
enrichfindP 0.61 0.10 13.35
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 3 NOTEs
See
'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.20-bioc/R/library' * installing *source* package 'HPiP' ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 100.451458
final value 93.904720
converged
Fitting Repeat 2
# weights: 103
initial value 95.153471
final value 93.455030
converged
Fitting Repeat 3
# weights: 103
initial value 96.892118
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.680009
iter 10 value 93.582419
final value 93.582418
converged
Fitting Repeat 5
# weights: 103
initial value 94.464131
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 103.267873
final value 93.582418
converged
Fitting Repeat 2
# weights: 305
initial value 95.128159
final value 93.869755
converged
Fitting Repeat 3
# weights: 305
initial value 125.751870
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 125.389600
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 93.923007
final value 93.582418
converged
Fitting Repeat 1
# weights: 507
initial value 111.293872
final value 93.366019
converged
Fitting Repeat 2
# weights: 507
initial value 97.446634
final value 93.582418
converged
Fitting Repeat 3
# weights: 507
initial value 106.242239
iter 10 value 91.720357
iter 20 value 89.957614
iter 30 value 88.822822
final value 88.770405
converged
Fitting Repeat 4
# weights: 507
initial value 95.563639
iter 10 value 93.582418
iter 10 value 93.582418
iter 10 value 93.582418
final value 93.582418
converged
Fitting Repeat 5
# weights: 507
initial value 102.911366
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 105.095404
iter 10 value 93.789793
iter 20 value 92.273536
iter 30 value 92.049241
iter 40 value 92.045650
iter 50 value 92.045347
iter 60 value 92.045205
iter 70 value 92.044651
iter 80 value 92.044469
iter 90 value 87.644947
iter 100 value 86.085677
final value 86.085677
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 100.379651
iter 10 value 93.675406
iter 20 value 93.444187
iter 30 value 93.411254
iter 40 value 90.623202
iter 50 value 88.807600
iter 60 value 88.725133
iter 70 value 84.924137
iter 80 value 83.239588
iter 90 value 82.840454
iter 100 value 82.287373
final value 82.287373
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.104777
iter 10 value 94.006383
iter 20 value 93.543226
iter 30 value 93.417167
iter 40 value 89.988971
iter 50 value 86.674766
iter 60 value 86.357410
iter 70 value 85.890010
iter 80 value 85.456450
iter 90 value 85.236770
iter 100 value 85.233305
final value 85.233305
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.166604
iter 10 value 94.137451
iter 20 value 93.825693
iter 30 value 88.722368
iter 40 value 86.781651
iter 50 value 86.350077
iter 60 value 85.182020
iter 70 value 83.190371
iter 80 value 82.436924
iter 90 value 82.236078
iter 100 value 82.222584
final value 82.222584
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.331036
iter 10 value 93.890018
iter 20 value 93.468455
iter 30 value 93.417826
iter 40 value 93.413712
iter 50 value 92.988224
iter 60 value 88.948160
iter 70 value 87.296548
iter 80 value 85.660262
iter 90 value 85.272965
iter 100 value 85.236921
final value 85.236921
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 102.848684
iter 10 value 94.074832
iter 20 value 92.765823
iter 30 value 89.011842
iter 40 value 87.520319
iter 50 value 86.287444
iter 60 value 86.001124
iter 70 value 85.060154
iter 80 value 83.029517
iter 90 value 82.194188
iter 100 value 81.820098
final value 81.820098
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.462265
iter 10 value 94.328190
iter 20 value 90.603478
iter 30 value 88.373807
iter 40 value 87.071557
iter 50 value 85.634221
iter 60 value 84.650894
iter 70 value 84.306002
iter 80 value 83.418846
iter 90 value 83.078235
iter 100 value 82.405196
final value 82.405196
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 98.317230
iter 10 value 92.757332
iter 20 value 92.185708
iter 30 value 86.072033
iter 40 value 84.995708
iter 50 value 83.925666
iter 60 value 81.947654
iter 70 value 81.322602
iter 80 value 81.020989
iter 90 value 80.796320
iter 100 value 80.748391
final value 80.748391
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 111.587713
iter 10 value 93.722305
iter 20 value 93.490093
iter 30 value 92.361204
iter 40 value 85.980949
iter 50 value 85.315182
iter 60 value 85.041869
iter 70 value 82.988435
iter 80 value 82.025428
iter 90 value 81.401518
iter 100 value 80.835558
final value 80.835558
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 120.801637
iter 10 value 93.996641
iter 20 value 91.259559
iter 30 value 86.762633
iter 40 value 85.108350
iter 50 value 83.676112
iter 60 value 83.306910
iter 70 value 82.485921
iter 80 value 81.853442
iter 90 value 81.392213
iter 100 value 81.353349
final value 81.353349
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.571158
iter 10 value 93.825886
iter 20 value 92.224104
iter 30 value 88.230611
iter 40 value 85.249914
iter 50 value 83.723357
iter 60 value 81.818914
iter 70 value 81.529439
iter 80 value 81.376750
iter 90 value 81.313507
iter 100 value 81.225985
final value 81.225985
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.935165
iter 10 value 93.817380
iter 20 value 87.963672
iter 30 value 84.877303
iter 40 value 83.859424
iter 50 value 83.544984
iter 60 value 83.104240
iter 70 value 82.794183
iter 80 value 81.833930
iter 90 value 81.158090
iter 100 value 81.004354
final value 81.004354
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.687968
iter 10 value 97.343298
iter 20 value 93.460788
iter 30 value 89.596154
iter 40 value 88.146776
iter 50 value 86.756551
iter 60 value 84.764916
iter 70 value 83.590552
iter 80 value 82.847058
iter 90 value 82.064892
iter 100 value 81.993907
final value 81.993907
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.585415
iter 10 value 94.413292
iter 20 value 90.301062
iter 30 value 87.330945
iter 40 value 86.770856
iter 50 value 85.937622
iter 60 value 85.607003
iter 70 value 84.873521
iter 80 value 83.954652
iter 90 value 83.055178
iter 100 value 82.677612
final value 82.677612
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.283791
iter 10 value 93.673069
iter 20 value 93.339658
iter 30 value 87.574946
iter 40 value 84.359649
iter 50 value 83.820169
iter 60 value 82.889447
iter 70 value 81.345173
iter 80 value 80.756305
iter 90 value 80.507591
iter 100 value 80.440054
final value 80.440054
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.398100
final value 94.053400
converged
Fitting Repeat 2
# weights: 103
initial value 100.743434
final value 94.054326
converged
Fitting Repeat 3
# weights: 103
initial value 97.683728
iter 10 value 93.871335
iter 20 value 93.871092
final value 93.455139
converged
Fitting Repeat 4
# weights: 103
initial value 94.444096
final value 94.054711
converged
Fitting Repeat 5
# weights: 103
initial value 100.318251
final value 94.054491
converged
Fitting Repeat 1
# weights: 305
initial value 101.617302
iter 10 value 94.057938
iter 20 value 93.518624
iter 30 value 91.699265
final value 91.699025
converged
Fitting Repeat 2
# weights: 305
initial value 99.467972
iter 10 value 93.587600
iter 20 value 93.582931
iter 30 value 93.053070
iter 40 value 89.951014
iter 50 value 88.136073
iter 60 value 86.684369
iter 70 value 86.477785
iter 80 value 85.557815
iter 90 value 82.088114
iter 100 value 81.629971
final value 81.629971
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 97.679316
iter 10 value 94.057801
iter 20 value 94.030931
iter 30 value 93.410450
iter 30 value 93.410450
iter 30 value 93.410450
final value 93.410450
converged
Fitting Repeat 4
# weights: 305
initial value 99.383001
iter 10 value 93.587535
iter 20 value 93.584249
iter 30 value 93.376222
iter 40 value 90.514625
iter 50 value 89.124324
iter 60 value 85.512329
iter 70 value 85.208354
iter 80 value 85.207412
iter 90 value 83.512680
iter 100 value 83.309112
final value 83.309112
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 115.324715
iter 10 value 94.056969
iter 20 value 93.688578
iter 30 value 93.391231
iter 40 value 93.390648
final value 93.390638
converged
Fitting Repeat 1
# weights: 507
initial value 111.005696
iter 10 value 93.591866
iter 20 value 93.258189
iter 30 value 93.195445
iter 40 value 93.194680
iter 50 value 93.193978
iter 60 value 93.084423
iter 70 value 85.693072
iter 80 value 83.751298
iter 90 value 83.685014
iter 100 value 83.557175
final value 83.557175
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 95.985512
iter 10 value 93.727893
iter 20 value 93.602334
iter 30 value 93.601594
iter 40 value 93.115266
iter 50 value 92.506678
iter 60 value 92.460669
iter 70 value 92.096129
iter 80 value 85.567359
iter 90 value 84.616120
iter 100 value 84.168918
final value 84.168918
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 123.767829
iter 10 value 93.878132
iter 20 value 93.871078
iter 30 value 91.306242
iter 40 value 90.666305
iter 50 value 90.664284
final value 90.664274
converged
Fitting Repeat 4
# weights: 507
initial value 102.234404
iter 10 value 90.177091
iter 20 value 88.006434
iter 30 value 87.826302
final value 87.825110
converged
Fitting Repeat 5
# weights: 507
initial value 105.501650
iter 10 value 88.440351
iter 20 value 87.250252
iter 30 value 87.246539
iter 40 value 87.191345
iter 50 value 86.928654
iter 60 value 85.666881
iter 70 value 85.643951
iter 80 value 84.185750
iter 90 value 84.123938
iter 100 value 83.900252
final value 83.900252
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.502368
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 97.048657
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 98.802439
final value 93.915746
converged
Fitting Repeat 4
# weights: 103
initial value 95.919216
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 97.808883
final value 93.915746
converged
Fitting Repeat 1
# weights: 305
initial value 101.681888
iter 10 value 93.915746
iter 10 value 93.915746
iter 10 value 93.915746
final value 93.915746
converged
Fitting Repeat 2
# weights: 305
initial value 99.349944
final value 94.052911
converged
Fitting Repeat 3
# weights: 305
initial value 115.684536
iter 10 value 93.915671
iter 20 value 85.321649
final value 85.321374
converged
Fitting Repeat 4
# weights: 305
initial value 130.332053
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 99.279160
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 101.117791
iter 10 value 93.141616
final value 93.141612
converged
Fitting Repeat 2
# weights: 507
initial value 122.506262
iter 10 value 87.064554
iter 20 value 84.435195
iter 30 value 84.434059
iter 40 value 84.013795
iter 50 value 83.999088
final value 83.999053
converged
Fitting Repeat 3
# weights: 507
initial value 106.039775
iter 10 value 89.175750
iter 20 value 87.861766
iter 30 value 87.668510
iter 40 value 85.040148
iter 50 value 83.579415
iter 60 value 83.204596
iter 70 value 83.184905
iter 80 value 83.161528
iter 90 value 83.158991
final value 83.158908
converged
Fitting Repeat 4
# weights: 507
initial value 97.853376
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 103.766808
iter 10 value 86.569026
iter 20 value 85.243353
final value 85.239269
converged
Fitting Repeat 1
# weights: 103
initial value 102.381545
iter 10 value 93.798904
iter 20 value 83.908844
iter 30 value 83.399820
iter 40 value 83.203014
iter 50 value 83.154292
final value 83.132665
converged
Fitting Repeat 2
# weights: 103
initial value 113.659026
iter 10 value 93.987405
iter 20 value 92.758284
iter 30 value 86.055506
iter 40 value 84.670386
iter 50 value 84.112939
iter 60 value 83.261004
iter 70 value 83.147832
iter 80 value 83.133137
final value 83.132665
converged
Fitting Repeat 3
# weights: 103
initial value 98.573692
iter 10 value 94.032836
iter 20 value 93.939386
iter 30 value 93.866488
iter 40 value 93.856627
iter 50 value 93.124794
iter 60 value 85.688734
iter 70 value 83.719467
iter 80 value 83.026587
iter 90 value 82.700749
iter 100 value 82.318434
final value 82.318434
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 107.430684
iter 10 value 94.054870
iter 20 value 87.137795
iter 30 value 84.894215
iter 40 value 84.192987
iter 50 value 83.689881
iter 60 value 83.578414
iter 70 value 83.568263
iter 70 value 83.568263
iter 70 value 83.568263
final value 83.568263
converged
Fitting Repeat 5
# weights: 103
initial value 102.437108
iter 10 value 94.030575
iter 20 value 86.136402
iter 30 value 83.837359
iter 40 value 83.562756
iter 50 value 83.243132
iter 60 value 83.132704
final value 83.132665
converged
Fitting Repeat 1
# weights: 305
initial value 104.554837
iter 10 value 94.281442
iter 20 value 94.155581
iter 30 value 92.655788
iter 40 value 92.154365
iter 50 value 91.973065
iter 60 value 85.840643
iter 70 value 84.857413
iter 80 value 83.501092
iter 90 value 83.019520
iter 100 value 82.654668
final value 82.654668
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.447058
iter 10 value 93.575423
iter 20 value 88.937680
iter 30 value 87.092694
iter 40 value 85.898535
iter 50 value 85.824497
iter 60 value 85.436299
iter 70 value 82.869534
iter 80 value 82.165426
iter 90 value 81.567829
iter 100 value 81.314871
final value 81.314871
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.388251
iter 10 value 89.524913
iter 20 value 86.043954
iter 30 value 85.673828
iter 40 value 84.081224
iter 50 value 82.662035
iter 60 value 81.444043
iter 70 value 80.653376
iter 80 value 80.608176
iter 90 value 80.604874
iter 100 value 80.592094
final value 80.592094
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.747151
iter 10 value 94.030875
iter 20 value 86.925729
iter 30 value 85.575649
iter 40 value 83.823973
iter 50 value 82.032222
iter 60 value 81.520166
iter 70 value 81.351462
iter 80 value 81.249445
iter 90 value 81.233683
iter 90 value 81.233683
iter 90 value 81.233683
final value 81.233683
converged
Fitting Repeat 5
# weights: 305
initial value 106.408658
iter 10 value 94.085343
iter 20 value 94.006596
iter 30 value 85.269212
iter 40 value 84.465245
iter 50 value 83.972362
iter 60 value 83.820661
iter 70 value 83.373257
iter 80 value 82.116972
iter 90 value 81.806494
iter 100 value 81.475681
final value 81.475681
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 115.748332
iter 10 value 93.789984
iter 20 value 83.879227
iter 30 value 83.550212
iter 40 value 82.931510
iter 50 value 82.218501
iter 60 value 81.451954
iter 70 value 81.242843
iter 80 value 80.892833
iter 90 value 80.685395
iter 100 value 80.605967
final value 80.605967
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.094711
iter 10 value 94.179842
iter 20 value 86.276620
iter 30 value 85.731988
iter 40 value 84.312808
iter 50 value 83.730580
iter 60 value 83.654959
iter 70 value 83.509321
iter 80 value 82.710473
iter 90 value 82.110091
iter 100 value 80.924130
final value 80.924130
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 127.276506
iter 10 value 95.555185
iter 20 value 92.975355
iter 30 value 92.323928
iter 40 value 86.891578
iter 50 value 84.000638
iter 60 value 83.196458
iter 70 value 82.902371
iter 80 value 82.796412
iter 90 value 82.573993
iter 100 value 82.067206
final value 82.067206
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.563728
iter 10 value 93.785230
iter 20 value 86.188112
iter 30 value 85.412256
iter 40 value 83.991909
iter 50 value 83.637885
iter 60 value 83.541563
iter 70 value 83.096518
iter 80 value 82.505987
iter 90 value 81.122771
iter 100 value 80.648734
final value 80.648734
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.738491
iter 10 value 93.734904
iter 20 value 91.020461
iter 30 value 84.384720
iter 40 value 83.111783
iter 50 value 82.176060
iter 60 value 81.482601
iter 70 value 81.139126
iter 80 value 81.093556
iter 90 value 81.030478
iter 100 value 80.669488
final value 80.669488
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.000561
final value 94.054570
converged
Fitting Repeat 2
# weights: 103
initial value 100.086680
iter 10 value 94.054333
final value 94.053110
converged
Fitting Repeat 3
# weights: 103
initial value 97.494979
final value 94.054684
converged
Fitting Repeat 4
# weights: 103
initial value 95.576282
final value 94.055021
converged
Fitting Repeat 5
# weights: 103
initial value 117.839263
iter 10 value 94.054698
iter 20 value 94.053006
iter 30 value 93.964256
iter 40 value 93.813712
final value 93.813550
converged
Fitting Repeat 1
# weights: 305
initial value 96.325528
iter 10 value 93.611395
iter 20 value 93.491403
iter 30 value 93.454680
iter 40 value 93.453831
iter 50 value 93.452935
iter 60 value 93.452663
iter 70 value 92.201127
iter 80 value 90.586499
iter 90 value 86.793229
iter 100 value 86.545339
final value 86.545339
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.885784
iter 10 value 94.057808
iter 20 value 94.052968
iter 30 value 87.254024
iter 40 value 85.281478
iter 50 value 85.270212
iter 60 value 84.901580
iter 70 value 84.901140
iter 80 value 83.581898
iter 90 value 82.837553
iter 100 value 82.744014
final value 82.744014
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 114.405326
iter 10 value 93.905772
iter 20 value 93.903245
iter 30 value 93.553236
iter 40 value 93.544492
iter 50 value 93.544237
final value 93.544218
converged
Fitting Repeat 4
# weights: 305
initial value 100.367487
iter 10 value 94.057686
final value 94.052926
converged
Fitting Repeat 5
# weights: 305
initial value 96.919056
iter 10 value 94.057208
iter 20 value 93.977049
iter 30 value 93.588330
iter 40 value 88.100198
iter 50 value 84.425003
iter 60 value 84.226210
iter 70 value 84.077914
iter 80 value 84.047317
iter 90 value 83.661425
final value 83.658811
converged
Fitting Repeat 1
# weights: 507
initial value 104.037202
final value 94.061529
converged
Fitting Repeat 2
# weights: 507
initial value 101.679401
iter 10 value 92.227817
iter 20 value 84.455177
iter 30 value 83.963370
iter 40 value 83.672257
final value 83.666109
converged
Fitting Repeat 3
# weights: 507
initial value 106.175618
iter 10 value 94.060577
iter 20 value 94.015474
iter 30 value 85.738275
iter 40 value 84.903116
iter 50 value 84.837265
iter 60 value 83.799077
iter 70 value 83.796836
iter 80 value 83.694959
iter 90 value 83.449102
iter 100 value 81.455006
final value 81.455006
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.417015
iter 10 value 93.923928
iter 20 value 93.914041
iter 30 value 93.839691
iter 40 value 93.777138
iter 50 value 85.765740
iter 60 value 85.139475
iter 70 value 84.295560
iter 80 value 82.628996
iter 90 value 82.028302
iter 100 value 81.065937
final value 81.065937
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 97.154945
iter 10 value 94.057290
iter 20 value 93.967474
iter 30 value 86.504671
iter 40 value 84.714921
iter 50 value 84.085016
iter 60 value 83.899724
iter 70 value 83.888474
iter 80 value 83.875388
iter 90 value 83.595123
iter 100 value 81.341982
final value 81.341982
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.679366
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.097888
iter 10 value 93.596024
iter 20 value 92.794474
iter 30 value 92.639973
iter 40 value 92.621366
iter 50 value 92.618258
iter 60 value 92.618217
final value 92.618182
converged
Fitting Repeat 3
# weights: 103
initial value 96.162917
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 119.544013
iter 10 value 92.747201
iter 20 value 92.731197
final value 92.731184
converged
Fitting Repeat 5
# weights: 103
initial value 96.972081
final value 94.443243
converged
Fitting Repeat 1
# weights: 305
initial value 110.614339
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 110.121281
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 97.526269
iter 10 value 93.387365
final value 93.387354
converged
Fitting Repeat 4
# weights: 305
initial value 94.945114
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 101.895317
final value 94.443243
converged
Fitting Repeat 1
# weights: 507
initial value 105.610462
final value 94.443243
converged
Fitting Repeat 2
# weights: 507
initial value 99.736486
iter 10 value 94.443262
final value 94.443243
converged
Fitting Repeat 3
# weights: 507
initial value 115.529942
iter 10 value 88.287852
iter 20 value 84.415808
iter 30 value 82.958451
iter 40 value 82.308759
final value 82.308758
converged
Fitting Repeat 4
# weights: 507
initial value 123.431995
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 100.750567
final value 94.325945
converged
Fitting Repeat 1
# weights: 103
initial value 99.856671
iter 10 value 94.490940
iter 20 value 93.736850
iter 30 value 86.403682
iter 40 value 84.508343
iter 50 value 84.050820
iter 60 value 83.007128
iter 70 value 82.615202
iter 80 value 82.542779
iter 90 value 80.946993
iter 100 value 79.715984
final value 79.715984
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 98.818886
iter 10 value 94.417924
iter 20 value 93.763429
iter 30 value 87.436273
iter 40 value 85.575400
iter 50 value 83.671675
iter 60 value 82.248926
iter 70 value 81.382408
final value 81.377997
converged
Fitting Repeat 3
# weights: 103
initial value 103.327256
iter 10 value 94.491322
iter 20 value 94.019763
iter 30 value 93.771402
iter 40 value 92.388496
iter 50 value 85.479092
iter 60 value 83.144811
iter 70 value 82.733209
iter 80 value 82.610001
final value 82.605435
converged
Fitting Repeat 4
# weights: 103
initial value 108.142863
iter 10 value 94.486630
iter 20 value 92.885427
iter 30 value 89.465047
iter 40 value 85.129467
iter 50 value 84.151737
iter 60 value 82.812586
iter 70 value 82.485496
iter 80 value 81.102260
iter 90 value 79.818969
iter 100 value 79.450769
final value 79.450769
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 105.096048
iter 10 value 94.434278
iter 20 value 88.985571
iter 30 value 87.692749
iter 40 value 86.190741
iter 50 value 83.563987
iter 60 value 81.387020
iter 70 value 80.679037
iter 80 value 79.502789
iter 90 value 79.442637
final value 79.441280
converged
Fitting Repeat 1
# weights: 305
initial value 105.828933
iter 10 value 94.586013
iter 20 value 92.289766
iter 30 value 91.819895
iter 40 value 90.749754
iter 50 value 85.981763
iter 60 value 81.167250
iter 70 value 79.221661
iter 80 value 78.614670
iter 90 value 78.206856
iter 100 value 77.791448
final value 77.791448
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 111.748479
iter 10 value 94.320347
iter 20 value 88.386382
iter 30 value 86.605152
iter 40 value 84.379477
iter 50 value 82.504727
iter 60 value 81.258302
iter 70 value 80.280510
iter 80 value 79.504858
iter 90 value 79.454258
iter 100 value 79.322967
final value 79.322967
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 112.617752
iter 10 value 94.448415
iter 20 value 91.521409
iter 30 value 90.063232
iter 40 value 89.556324
iter 50 value 89.245974
iter 60 value 88.049479
iter 70 value 84.678998
iter 80 value 79.607009
iter 90 value 78.556916
iter 100 value 78.245142
final value 78.245142
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 110.126474
iter 10 value 94.574766
iter 20 value 89.201121
iter 30 value 84.964499
iter 40 value 84.633145
iter 50 value 84.094987
iter 60 value 83.952554
iter 70 value 83.652700
iter 80 value 81.489394
iter 90 value 79.387080
iter 100 value 79.221956
final value 79.221956
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 113.408241
iter 10 value 94.171528
iter 20 value 91.885702
iter 30 value 87.191446
iter 40 value 86.344316
iter 50 value 83.956333
iter 60 value 83.322116
iter 70 value 82.289649
iter 80 value 81.030756
iter 90 value 80.020871
iter 100 value 79.464146
final value 79.464146
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.019628
iter 10 value 94.279429
iter 20 value 87.863827
iter 30 value 86.378532
iter 40 value 84.747352
iter 50 value 83.847395
iter 60 value 83.382537
iter 70 value 83.164982
iter 80 value 82.305552
iter 90 value 80.213700
iter 100 value 78.554465
final value 78.554465
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 129.423486
iter 10 value 95.404881
iter 20 value 93.867694
iter 30 value 90.822837
iter 40 value 86.000145
iter 50 value 83.946132
iter 60 value 83.097058
iter 70 value 82.847973
iter 80 value 82.287704
iter 90 value 80.063062
iter 100 value 79.256150
final value 79.256150
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.761391
iter 10 value 94.168231
iter 20 value 84.626747
iter 30 value 83.736776
iter 40 value 82.829555
iter 50 value 79.488394
iter 60 value 78.299017
iter 70 value 78.112915
iter 80 value 78.032421
iter 90 value 77.985527
iter 100 value 77.744617
final value 77.744617
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.666307
iter 10 value 94.473039
iter 20 value 92.289758
iter 30 value 88.860017
iter 40 value 83.861163
iter 50 value 82.528369
iter 60 value 80.309898
iter 70 value 78.121099
iter 80 value 77.989384
iter 90 value 77.891103
iter 100 value 77.755309
final value 77.755309
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.048736
iter 10 value 95.629459
iter 20 value 87.433330
iter 30 value 84.904845
iter 40 value 81.517641
iter 50 value 79.315021
iter 60 value 78.298976
iter 70 value 78.184244
iter 80 value 77.917301
iter 90 value 77.881216
iter 100 value 77.694587
final value 77.694587
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 105.939028
iter 10 value 94.485978
iter 20 value 94.484185
iter 30 value 94.214086
final value 94.214050
converged
Fitting Repeat 2
# weights: 103
initial value 100.256180
final value 94.485926
converged
Fitting Repeat 3
# weights: 103
initial value 99.173915
final value 94.485724
converged
Fitting Repeat 4
# weights: 103
initial value 99.730999
final value 94.486035
converged
Fitting Repeat 5
# weights: 103
initial value 102.867164
iter 10 value 94.485891
final value 94.484244
converged
Fitting Repeat 1
# weights: 305
initial value 99.919402
iter 10 value 94.490609
iter 20 value 94.321909
iter 30 value 93.390088
iter 40 value 93.389246
iter 50 value 93.388372
iter 60 value 92.752187
final value 92.736078
converged
Fitting Repeat 2
# weights: 305
initial value 115.521027
iter 10 value 88.385996
iter 20 value 88.217844
iter 30 value 87.946164
iter 40 value 86.796566
iter 50 value 85.343166
iter 60 value 84.981957
iter 70 value 83.961096
iter 80 value 82.188275
iter 90 value 80.283671
iter 100 value 77.514958
final value 77.514958
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.025047
iter 10 value 94.489062
iter 20 value 94.484382
iter 30 value 94.375578
iter 40 value 93.341461
iter 50 value 93.337511
iter 60 value 93.337306
final value 93.337234
converged
Fitting Repeat 4
# weights: 305
initial value 95.233300
iter 10 value 94.482869
iter 20 value 93.075855
iter 30 value 92.500994
iter 40 value 92.496763
iter 50 value 92.496652
final value 92.496447
converged
Fitting Repeat 5
# weights: 305
initial value 110.091344
iter 10 value 94.449609
iter 20 value 94.439374
iter 30 value 85.623522
iter 40 value 83.948530
iter 50 value 83.608183
iter 60 value 83.594703
iter 70 value 83.593686
iter 80 value 83.095019
iter 90 value 83.079258
iter 100 value 83.079192
final value 83.079192
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.841575
iter 10 value 93.957055
iter 20 value 93.954507
iter 30 value 92.947157
iter 40 value 92.941754
iter 50 value 92.695633
iter 60 value 92.692949
iter 70 value 92.650100
iter 80 value 92.078207
iter 90 value 90.516054
iter 100 value 89.579305
final value 89.579305
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.992489
iter 10 value 94.492281
iter 20 value 94.377835
iter 30 value 86.961950
iter 40 value 86.260461
iter 50 value 85.585244
iter 60 value 82.824253
iter 70 value 81.130296
iter 80 value 77.070991
iter 90 value 76.807410
iter 100 value 76.803598
final value 76.803598
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 125.352120
iter 10 value 94.451497
iter 20 value 93.217949
iter 30 value 93.212135
iter 40 value 91.312205
iter 50 value 83.886786
iter 60 value 81.355917
iter 70 value 81.262087
iter 80 value 81.256285
iter 90 value 80.867626
iter 100 value 80.804511
final value 80.804511
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.636728
iter 10 value 94.492906
iter 20 value 94.471253
iter 30 value 85.243627
iter 40 value 83.227101
iter 50 value 82.870696
iter 60 value 79.746437
iter 70 value 79.363778
iter 80 value 79.273821
iter 90 value 79.271377
iter 100 value 79.166403
final value 79.166403
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.308278
iter 10 value 94.491922
iter 20 value 93.404519
iter 30 value 91.936084
iter 40 value 91.506444
iter 50 value 91.505054
iter 60 value 91.502621
iter 70 value 91.438405
iter 80 value 91.226859
iter 90 value 91.054620
iter 100 value 90.368942
final value 90.368942
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.930194
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.960536
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.363718
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.512220
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 100.113222
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 102.226905
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 98.983230
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 103.309333
final value 94.466823
converged
Fitting Repeat 4
# weights: 305
initial value 98.349859
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 95.107781
final value 94.484214
converged
Fitting Repeat 1
# weights: 507
initial value 102.779870
iter 10 value 94.112570
iter 10 value 94.112570
iter 10 value 94.112570
final value 94.112570
converged
Fitting Repeat 2
# weights: 507
initial value 106.708796
final value 94.466823
converged
Fitting Repeat 3
# weights: 507
initial value 96.549229
final value 94.466823
converged
Fitting Repeat 4
# weights: 507
initial value 117.132207
iter 10 value 94.431169
iter 20 value 94.428843
final value 94.428840
converged
Fitting Repeat 5
# weights: 507
initial value 114.739772
final value 94.466823
converged
Fitting Repeat 1
# weights: 103
initial value 107.541517
iter 10 value 92.732265
iter 20 value 91.103992
iter 30 value 90.992674
iter 40 value 90.089499
iter 50 value 90.064445
final value 90.063989
converged
Fitting Repeat 2
# weights: 103
initial value 97.877201
iter 10 value 94.425601
iter 20 value 94.182174
iter 30 value 91.427817
iter 40 value 85.554010
iter 50 value 85.117993
iter 60 value 84.380625
iter 70 value 84.224340
final value 84.224289
converged
Fitting Repeat 3
# weights: 103
initial value 106.222816
iter 10 value 94.393761
iter 20 value 89.509989
iter 30 value 87.860348
iter 40 value 87.200242
iter 50 value 82.590819
iter 60 value 82.066441
iter 70 value 81.679699
iter 80 value 81.484383
iter 90 value 81.465405
iter 100 value 81.462544
final value 81.462544
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 112.724626
iter 10 value 94.912703
iter 20 value 94.419813
iter 30 value 88.995678
iter 40 value 84.586620
iter 50 value 83.539566
iter 60 value 83.387465
iter 70 value 82.411340
iter 80 value 81.903600
iter 90 value 81.690449
iter 100 value 81.625194
final value 81.625194
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 114.043212
iter 10 value 94.437212
iter 20 value 91.142928
iter 30 value 87.220967
iter 40 value 86.185713
iter 50 value 85.663242
iter 60 value 85.453443
iter 70 value 85.405116
iter 80 value 85.235239
final value 85.231629
converged
Fitting Repeat 1
# weights: 305
initial value 105.842092
iter 10 value 93.958913
iter 20 value 91.071433
iter 30 value 89.281628
iter 40 value 86.771289
iter 50 value 85.912132
iter 60 value 81.184978
iter 70 value 80.372473
iter 80 value 80.308558
iter 90 value 80.227757
iter 100 value 80.153436
final value 80.153436
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 120.297353
iter 10 value 96.376463
iter 20 value 93.780823
iter 30 value 90.780785
iter 40 value 85.904671
iter 50 value 83.593856
iter 60 value 83.039802
iter 70 value 81.428827
iter 80 value 81.073544
iter 90 value 80.970408
iter 100 value 80.874341
final value 80.874341
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.748364
iter 10 value 94.573640
iter 20 value 91.765891
iter 30 value 90.735377
iter 40 value 85.691490
iter 50 value 83.959316
iter 60 value 83.332663
iter 70 value 82.513668
iter 80 value 81.297652
iter 90 value 80.810377
iter 100 value 80.613338
final value 80.613338
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.003769
iter 10 value 94.748724
iter 20 value 94.386692
iter 30 value 89.943794
iter 40 value 88.528357
iter 50 value 88.354019
iter 60 value 85.725067
iter 70 value 84.817569
iter 80 value 84.122418
iter 90 value 83.356555
iter 100 value 82.464521
final value 82.464521
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.525880
iter 10 value 94.500414
iter 20 value 89.049457
iter 30 value 88.697260
iter 40 value 87.966460
iter 50 value 85.260727
iter 60 value 80.987090
iter 70 value 80.573507
iter 80 value 80.515288
iter 90 value 80.420438
iter 100 value 80.229259
final value 80.229259
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.605726
iter 10 value 96.212107
iter 20 value 93.658172
iter 30 value 89.363178
iter 40 value 84.810407
iter 50 value 84.382278
iter 60 value 82.761654
iter 70 value 82.514554
iter 80 value 82.315432
iter 90 value 81.585611
iter 100 value 80.734157
final value 80.734157
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.712578
iter 10 value 94.046208
iter 20 value 87.664198
iter 30 value 85.465564
iter 40 value 84.917556
iter 50 value 84.481302
iter 60 value 84.255440
iter 70 value 83.962491
iter 80 value 82.892710
iter 90 value 82.009592
iter 100 value 81.678999
final value 81.678999
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.810778
iter 10 value 91.148138
iter 20 value 88.200423
iter 30 value 83.720450
iter 40 value 81.367390
iter 50 value 80.494832
iter 60 value 80.263513
iter 70 value 80.023566
iter 80 value 79.978160
iter 90 value 79.970812
iter 100 value 79.937567
final value 79.937567
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.313303
iter 10 value 94.772436
iter 20 value 92.227060
iter 30 value 88.136791
iter 40 value 86.871188
iter 50 value 83.560836
iter 60 value 81.938800
iter 70 value 81.514279
iter 80 value 81.223061
iter 90 value 80.871553
iter 100 value 80.362061
final value 80.362061
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.201115
iter 10 value 94.361523
iter 20 value 92.813342
iter 30 value 87.175939
iter 40 value 85.432046
iter 50 value 84.453551
iter 60 value 84.348961
iter 70 value 82.549812
iter 80 value 81.415963
iter 90 value 81.225240
iter 100 value 80.931727
final value 80.931727
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.956366
final value 94.468413
converged
Fitting Repeat 2
# weights: 103
initial value 96.278287
final value 94.090807
converged
Fitting Repeat 3
# weights: 103
initial value 98.800366
final value 94.485545
converged
Fitting Repeat 4
# weights: 103
initial value 99.669763
final value 94.485982
converged
Fitting Repeat 5
# weights: 103
initial value 97.864176
final value 94.486082
converged
Fitting Repeat 1
# weights: 305
initial value 98.176264
iter 10 value 94.471729
iter 20 value 94.345467
iter 30 value 86.180017
iter 40 value 85.927006
iter 50 value 85.893713
iter 60 value 83.661685
iter 70 value 81.107858
iter 80 value 81.099220
iter 90 value 81.095981
iter 100 value 80.731593
final value 80.731593
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.383038
iter 10 value 94.488874
iter 20 value 94.394220
iter 30 value 85.403204
iter 40 value 84.760918
iter 50 value 83.366496
iter 60 value 82.518855
iter 70 value 82.012976
iter 80 value 82.012269
iter 90 value 81.997771
iter 100 value 81.995546
final value 81.995546
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 136.303582
iter 10 value 94.471527
iter 20 value 94.426649
iter 30 value 90.712843
iter 40 value 82.957524
iter 50 value 81.441633
iter 60 value 81.293004
iter 70 value 81.291740
iter 80 value 81.276646
iter 90 value 81.252930
iter 100 value 80.989638
final value 80.989638
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 96.388085
iter 10 value 94.170693
iter 20 value 94.166605
iter 30 value 94.121708
iter 40 value 94.063426
iter 50 value 91.316276
iter 60 value 88.700202
iter 70 value 83.005131
iter 80 value 82.985669
iter 90 value 82.681427
iter 100 value 82.679027
final value 82.679027
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.584602
iter 10 value 94.110574
iter 20 value 94.104009
iter 30 value 94.076851
iter 40 value 94.076463
iter 40 value 94.076463
final value 94.076463
converged
Fitting Repeat 1
# weights: 507
initial value 100.666910
iter 10 value 85.203346
iter 20 value 84.490373
iter 30 value 83.635485
iter 40 value 83.508877
iter 50 value 83.421563
iter 60 value 83.418727
iter 70 value 83.418185
iter 80 value 83.247929
iter 90 value 82.979843
iter 100 value 82.963123
final value 82.963123
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 100.688512
iter 10 value 94.173529
iter 20 value 94.167425
iter 30 value 94.113967
iter 40 value 94.113483
iter 50 value 94.110417
iter 60 value 94.110299
final value 94.110290
converged
Fitting Repeat 3
# weights: 507
initial value 111.791961
iter 10 value 94.097457
iter 20 value 94.091381
iter 30 value 94.091010
iter 40 value 93.884035
iter 50 value 90.226302
iter 60 value 89.011252
iter 70 value 88.804609
iter 80 value 84.491540
iter 90 value 82.795043
iter 100 value 82.791443
final value 82.791443
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 97.995515
iter 10 value 94.474450
iter 20 value 94.094199
iter 30 value 94.082323
iter 40 value 94.067447
iter 50 value 94.062830
final value 94.062205
converged
Fitting Repeat 5
# weights: 507
initial value 115.279168
iter 10 value 94.493227
iter 20 value 92.900683
iter 30 value 86.591875
iter 40 value 84.388040
iter 50 value 83.644988
iter 60 value 82.256639
iter 70 value 82.240519
iter 80 value 82.230906
iter 90 value 82.225559
iter 100 value 81.430216
final value 81.430216
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.671577
final value 94.484210
converged
Fitting Repeat 2
# weights: 103
initial value 97.543059
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 94.627924
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.497543
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 103.613942
final value 94.484210
converged
Fitting Repeat 1
# weights: 305
initial value 96.569450
final value 94.443182
converged
Fitting Repeat 2
# weights: 305
initial value 103.622623
final value 94.443243
converged
Fitting Repeat 3
# weights: 305
initial value 110.270542
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 130.045471
final value 94.443243
converged
Fitting Repeat 5
# weights: 305
initial value 104.852838
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 101.009939
iter 10 value 94.400026
final value 94.400000
converged
Fitting Repeat 2
# weights: 507
initial value 101.836939
final value 94.443243
converged
Fitting Repeat 3
# weights: 507
initial value 105.395984
final value 94.443243
converged
Fitting Repeat 4
# weights: 507
initial value 98.348232
final value 93.634731
converged
Fitting Repeat 5
# weights: 507
initial value 98.265923
iter 10 value 94.129891
final value 94.129874
converged
Fitting Repeat 1
# weights: 103
initial value 106.839109
iter 10 value 94.289961
iter 20 value 88.268873
iter 30 value 87.374777
iter 40 value 87.308365
iter 50 value 85.159789
iter 60 value 84.046675
iter 70 value 83.971169
iter 80 value 83.948010
iter 80 value 83.948010
final value 83.948010
converged
Fitting Repeat 2
# weights: 103
initial value 108.590887
iter 10 value 94.546013
iter 20 value 94.486872
iter 30 value 92.572583
iter 40 value 91.791084
iter 50 value 91.687662
iter 60 value 90.960897
iter 70 value 88.356801
iter 80 value 84.765049
iter 90 value 84.268956
iter 100 value 84.048584
final value 84.048584
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 102.446821
iter 10 value 94.405548
iter 20 value 93.891065
iter 30 value 91.638111
iter 40 value 86.167665
iter 50 value 85.413994
iter 60 value 84.513274
iter 70 value 84.096725
iter 80 value 83.955564
iter 90 value 83.941204
final value 83.941192
converged
Fitting Repeat 4
# weights: 103
initial value 98.544834
iter 10 value 94.723776
iter 20 value 91.780344
iter 30 value 88.561550
iter 40 value 85.082519
iter 50 value 84.790838
iter 60 value 83.674943
iter 70 value 83.500173
iter 80 value 83.355074
iter 90 value 83.336980
iter 100 value 83.334183
final value 83.334183
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 102.029078
iter 10 value 94.489650
iter 20 value 93.834066
iter 30 value 86.207749
iter 40 value 84.803473
iter 50 value 84.153564
iter 60 value 83.957973
final value 83.941192
converged
Fitting Repeat 1
# weights: 305
initial value 105.598816
iter 10 value 94.481344
iter 20 value 93.504200
iter 30 value 89.646797
iter 40 value 87.430587
iter 50 value 85.292636
iter 60 value 82.994602
iter 70 value 82.703026
iter 80 value 82.107958
iter 90 value 81.884152
iter 100 value 81.807226
final value 81.807226
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.012260
iter 10 value 94.176230
iter 20 value 85.515925
iter 30 value 84.640631
iter 40 value 84.458634
iter 50 value 84.302502
iter 60 value 83.451484
iter 70 value 82.868618
iter 80 value 82.655463
iter 90 value 82.468680
iter 100 value 82.398922
final value 82.398922
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.674171
iter 10 value 93.011739
iter 20 value 92.508994
iter 30 value 91.337057
iter 40 value 91.055115
iter 50 value 84.082345
iter 60 value 83.019139
iter 70 value 82.181372
iter 80 value 81.786747
iter 90 value 81.551383
iter 100 value 81.207335
final value 81.207335
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.706582
iter 10 value 94.505030
iter 20 value 85.451129
iter 30 value 84.646947
iter 40 value 82.921827
iter 50 value 82.688758
iter 60 value 82.376491
iter 70 value 81.614715
iter 80 value 81.448323
iter 90 value 81.370211
iter 100 value 81.348002
final value 81.348002
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.885500
iter 10 value 92.637625
iter 20 value 91.754057
iter 30 value 90.128689
iter 40 value 87.779053
iter 50 value 86.382340
iter 60 value 85.026782
iter 70 value 83.931070
iter 80 value 83.554915
iter 90 value 83.444696
iter 100 value 82.894025
final value 82.894025
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 113.997633
iter 10 value 95.435622
iter 20 value 93.876324
iter 30 value 85.262900
iter 40 value 84.706311
iter 50 value 84.570644
iter 60 value 83.987452
iter 70 value 83.470871
iter 80 value 82.744537
iter 90 value 82.560576
iter 100 value 82.467800
final value 82.467800
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.826227
iter 10 value 94.528054
iter 20 value 91.128682
iter 30 value 89.428919
iter 40 value 84.170993
iter 50 value 82.885753
iter 60 value 81.984331
iter 70 value 81.161070
iter 80 value 81.038643
iter 90 value 80.984397
iter 100 value 80.855046
final value 80.855046
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.125121
iter 10 value 95.233797
iter 20 value 90.573354
iter 30 value 85.707263
iter 40 value 85.311566
iter 50 value 85.090866
iter 60 value 83.405337
iter 70 value 82.815695
iter 80 value 82.790096
iter 90 value 82.751831
iter 100 value 82.363085
final value 82.363085
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 124.071441
iter 10 value 93.934674
iter 20 value 85.524057
iter 30 value 84.376419
iter 40 value 84.148300
iter 50 value 83.235833
iter 60 value 82.722552
iter 70 value 82.579079
iter 80 value 82.517176
iter 90 value 82.440275
iter 100 value 82.312671
final value 82.312671
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.164396
iter 10 value 94.378205
iter 20 value 88.675562
iter 30 value 88.047329
iter 40 value 87.718425
iter 50 value 83.113655
iter 60 value 82.338682
iter 70 value 81.748184
iter 80 value 81.433779
iter 90 value 81.284174
iter 100 value 81.222758
final value 81.222758
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.654673
iter 10 value 94.486045
iter 20 value 94.480781
iter 30 value 92.338932
iter 40 value 92.295652
iter 50 value 92.295282
final value 92.295123
converged
Fitting Repeat 2
# weights: 103
initial value 94.660774
iter 10 value 94.486032
final value 94.484218
converged
Fitting Repeat 3
# weights: 103
initial value 104.512032
final value 94.485789
converged
Fitting Repeat 4
# weights: 103
initial value 106.722170
final value 94.485957
converged
Fitting Repeat 5
# weights: 103
initial value 98.095880
final value 94.485883
converged
Fitting Repeat 1
# weights: 305
initial value 102.145732
iter 10 value 94.447896
iter 20 value 94.391586
iter 30 value 89.188760
iter 40 value 84.224381
iter 50 value 80.768780
iter 60 value 80.323482
iter 70 value 80.312907
iter 80 value 80.309305
iter 90 value 80.308124
iter 100 value 80.307936
final value 80.307936
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.507561
iter 10 value 94.489274
iter 20 value 94.484188
iter 30 value 90.125385
iter 40 value 89.844300
iter 50 value 89.122841
iter 60 value 88.922050
iter 70 value 87.063598
iter 80 value 86.506684
iter 90 value 85.361379
iter 100 value 85.331671
final value 85.331671
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 95.462200
iter 10 value 89.677712
iter 20 value 86.510775
iter 30 value 86.506679
iter 40 value 86.504693
iter 50 value 85.821801
iter 60 value 85.316642
iter 70 value 84.843803
iter 80 value 82.068048
iter 90 value 81.359241
iter 100 value 80.726680
final value 80.726680
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 97.760581
iter 10 value 94.488965
iter 20 value 94.325088
iter 30 value 84.957997
iter 40 value 84.942021
final value 84.941741
converged
Fitting Repeat 5
# weights: 305
initial value 99.272263
iter 10 value 94.488892
iter 20 value 94.319065
iter 30 value 91.514793
iter 40 value 91.504978
iter 50 value 91.504760
iter 60 value 91.456644
iter 70 value 91.453568
iter 80 value 88.731691
iter 90 value 84.940088
iter 100 value 84.053504
final value 84.053504
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 124.921193
iter 10 value 94.492975
iter 20 value 94.027040
iter 30 value 85.485483
iter 40 value 84.005200
iter 50 value 83.542755
iter 60 value 83.318809
iter 70 value 81.435818
iter 80 value 80.463377
iter 90 value 80.326376
iter 100 value 80.305121
final value 80.305121
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 101.342382
iter 10 value 94.451692
iter 20 value 94.418582
iter 30 value 93.266725
iter 40 value 87.582612
iter 50 value 87.205249
iter 60 value 87.202253
iter 70 value 85.744607
iter 80 value 85.387247
iter 90 value 85.386413
iter 100 value 84.665490
final value 84.665490
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 99.672975
iter 10 value 94.451854
iter 20 value 94.444859
iter 30 value 89.264051
iter 40 value 86.815077
iter 50 value 85.946030
iter 60 value 84.502819
iter 70 value 84.492512
iter 80 value 83.495424
iter 90 value 83.011390
iter 100 value 82.962460
final value 82.962460
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 101.557375
iter 10 value 90.938474
iter 20 value 89.715030
iter 30 value 89.244178
iter 40 value 89.237917
iter 50 value 89.155937
iter 60 value 89.151635
iter 70 value 89.149471
iter 80 value 88.027390
iter 90 value 87.856076
iter 100 value 87.601560
final value 87.601560
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 96.931267
iter 10 value 94.490427
iter 20 value 94.326150
iter 30 value 84.340307
final value 84.331917
converged
Fitting Repeat 1
# weights: 305
initial value 117.946462
iter 10 value 117.892827
iter 20 value 115.038993
iter 30 value 114.406463
iter 40 value 113.951023
iter 50 value 112.954365
iter 60 value 103.122311
iter 70 value 100.844715
iter 80 value 100.009138
iter 90 value 99.858416
iter 100 value 99.755419
final value 99.755419
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 123.052085
iter 10 value 117.763515
iter 20 value 117.758914
final value 117.758836
converged
Fitting Repeat 3
# weights: 305
initial value 137.375419
iter 10 value 117.033735
iter 20 value 116.908126
iter 30 value 108.805010
iter 40 value 104.348263
iter 50 value 104.280618
final value 104.279952
converged
Fitting Repeat 4
# weights: 305
initial value 123.829085
iter 10 value 117.894226
iter 20 value 117.416317
iter 30 value 108.636440
iter 40 value 105.143341
iter 50 value 101.896244
iter 60 value 101.510804
iter 70 value 100.056843
iter 80 value 99.744896
iter 90 value 99.499499
iter 100 value 99.472342
final value 99.472342
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 120.355801
iter 10 value 117.210893
iter 20 value 116.931132
iter 30 value 113.736172
iter 40 value 108.492704
final value 108.424964
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Fri Jan 31 03:03:09 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
39.43 1.39 75.29
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 34.08 | 2.30 | 36.55 | |
| FreqInteractors | 0.22 | 0.05 | 0.28 | |
| calculateAAC | 0.07 | 0.00 | 0.07 | |
| calculateAutocor | 0.42 | 0.09 | 0.51 | |
| calculateCTDC | 0.08 | 0.01 | 0.10 | |
| calculateCTDD | 0.89 | 0.04 | 0.92 | |
| calculateCTDT | 0.32 | 0.01 | 0.34 | |
| calculateCTriad | 0.44 | 0.00 | 0.44 | |
| calculateDC | 0.16 | 0.00 | 0.15 | |
| calculateF | 0.45 | 0.00 | 0.46 | |
| calculateKSAAP | 0.11 | 0.00 | 0.11 | |
| calculateQD_Sm | 2.52 | 0.28 | 2.79 | |
| calculateTC | 1.86 | 0.24 | 2.10 | |
| calculateTC_Sm | 0.31 | 0.04 | 0.36 | |
| corr_plot | 33.56 | 1.72 | 35.29 | |
| enrichfindP | 0.61 | 0.10 | 13.35 | |
| enrichfind_hp | 0.08 | 0.01 | 1.15 | |
| enrichplot | 0.45 | 0.02 | 0.47 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.00 | 0.03 | 2.31 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0.01 | 0.00 | 0.02 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.11 | 0.00 | 0.11 | |
| pred_ensembel | 12.74 | 0.48 | 12.21 | |
| var_imp | 34.11 | 1.72 | 35.83 | |