Matineh Rahmatbakhsh
| Snapshot Date: 2025-01-02 13:00 -0500 (Thu, 02 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 2025-01-09 12:06 -0500 (Thu, 09 Jan 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" | 4744 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4487 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4515 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4467 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4358 |
| 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 | ERROR | skipped | ||||||||||
|
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: 2025-01-03 02:37:23 -0500 (Fri, 03 Jan 2025) |
| EndedAt: 2025-01-03 02:42:41 -0500 (Fri, 03 Jan 2025) |
| EllapsedTime: 317.5 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 34.77 1.87 36.84
var_imp 34.96 1.33 36.29
corr_plot 31.59 1.54 33.22
pred_ensembel 13.75 0.27 13.55
enrichfindP 0.65 0.06 14.96
* 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 96.448696
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.646069
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 99.149338
iter 10 value 94.228678
iter 10 value 94.228678
iter 10 value 94.228678
final value 94.228678
converged
Fitting Repeat 4
# weights: 103
initial value 100.163525
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.650185
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 104.126085
iter 10 value 94.411959
iter 20 value 90.253926
iter 30 value 89.404105
iter 40 value 88.508413
iter 50 value 88.490150
final value 88.489561
converged
Fitting Repeat 2
# weights: 305
initial value 98.002585
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 96.808478
final value 94.252920
converged
Fitting Repeat 4
# weights: 305
initial value 106.202782
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 102.728143
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 102.367117
final value 94.275362
converged
Fitting Repeat 2
# weights: 507
initial value 99.943104
final value 94.275362
converged
Fitting Repeat 3
# weights: 507
initial value 113.555504
iter 10 value 94.058705
final value 94.057229
converged
Fitting Repeat 4
# weights: 507
initial value 99.840217
iter 10 value 91.186453
iter 20 value 86.803431
iter 30 value 84.148769
iter 40 value 82.601496
iter 50 value 82.567532
iter 60 value 82.295102
iter 70 value 81.886139
final value 81.869472
converged
Fitting Repeat 5
# weights: 507
initial value 123.849858
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 98.687840
iter 10 value 94.422626
iter 20 value 91.426700
iter 30 value 87.444390
iter 40 value 87.111904
iter 50 value 86.411865
iter 60 value 85.797287
iter 70 value 85.461182
iter 80 value 85.448715
iter 90 value 85.412043
final value 85.409951
converged
Fitting Repeat 2
# weights: 103
initial value 101.253008
iter 10 value 94.495478
iter 20 value 94.345343
iter 30 value 94.327314
iter 40 value 94.267186
iter 50 value 94.076709
iter 60 value 94.015531
iter 70 value 91.704788
iter 80 value 87.718711
iter 90 value 87.422847
iter 100 value 85.611540
final value 85.611540
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 103.277699
iter 10 value 94.449800
iter 20 value 91.900413
iter 30 value 88.544324
iter 40 value 88.281364
iter 50 value 88.105994
iter 60 value 87.154679
iter 70 value 86.745059
iter 80 value 86.487639
iter 90 value 86.350725
final value 86.349068
converged
Fitting Repeat 4
# weights: 103
initial value 97.746867
iter 10 value 94.474538
iter 20 value 94.242085
iter 30 value 94.127775
iter 40 value 94.118252
iter 50 value 94.117478
iter 60 value 94.116386
iter 70 value 93.660677
iter 80 value 91.122980
iter 90 value 90.405164
iter 100 value 90.345640
final value 90.345640
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 105.722380
iter 10 value 94.474457
iter 20 value 93.042316
iter 30 value 91.498373
iter 40 value 91.349182
iter 50 value 89.898992
iter 60 value 87.840791
iter 70 value 87.501353
iter 80 value 87.137858
iter 90 value 85.548547
iter 100 value 84.925122
final value 84.925122
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 128.121393
iter 10 value 104.691860
iter 20 value 99.921783
iter 30 value 86.696556
iter 40 value 86.111534
iter 50 value 85.437012
iter 60 value 85.376359
iter 70 value 85.160126
iter 80 value 84.531137
iter 90 value 83.515008
iter 100 value 83.319628
final value 83.319628
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.963561
iter 10 value 95.114766
iter 20 value 89.050240
iter 30 value 85.671975
iter 40 value 85.466277
iter 50 value 85.147150
iter 60 value 85.124303
iter 70 value 84.933921
iter 80 value 83.324359
iter 90 value 82.491590
iter 100 value 82.406024
final value 82.406024
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.766559
iter 10 value 93.725460
iter 20 value 87.782560
iter 30 value 87.230140
iter 40 value 85.173996
iter 50 value 84.762359
iter 60 value 84.296732
iter 70 value 83.385233
iter 80 value 82.666641
iter 90 value 82.159268
iter 100 value 82.026089
final value 82.026089
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.867391
iter 10 value 95.247746
iter 20 value 94.665754
iter 30 value 94.320971
iter 40 value 93.377245
iter 50 value 89.041724
iter 60 value 88.063443
iter 70 value 84.615019
iter 80 value 83.803850
iter 90 value 83.227883
iter 100 value 82.948861
final value 82.948861
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.075956
iter 10 value 94.357187
iter 20 value 89.006050
iter 30 value 85.951236
iter 40 value 84.451221
iter 50 value 84.021301
iter 60 value 82.700759
iter 70 value 82.103554
iter 80 value 81.802393
iter 90 value 81.559851
iter 100 value 81.471803
final value 81.471803
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.137148
iter 10 value 94.236962
iter 20 value 91.846435
iter 30 value 86.460093
iter 40 value 86.069122
iter 50 value 85.258348
iter 60 value 84.634010
iter 70 value 83.227784
iter 80 value 82.940841
iter 90 value 82.627895
iter 100 value 82.311868
final value 82.311868
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.303803
iter 10 value 94.813639
iter 20 value 88.682089
iter 30 value 84.668727
iter 40 value 84.599266
iter 50 value 83.839645
iter 60 value 83.160793
iter 70 value 82.763530
iter 80 value 82.488862
iter 90 value 82.117281
iter 100 value 81.838403
final value 81.838403
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.865516
iter 10 value 95.452266
iter 20 value 94.412738
iter 30 value 91.506723
iter 40 value 88.761858
iter 50 value 86.282268
iter 60 value 83.984018
iter 70 value 83.294126
iter 80 value 82.976170
iter 90 value 82.858291
iter 100 value 82.559415
final value 82.559415
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 117.785607
iter 10 value 95.673501
iter 20 value 94.220866
iter 30 value 91.865695
iter 40 value 89.469125
iter 50 value 88.216284
iter 60 value 87.119315
iter 70 value 84.965556
iter 80 value 83.661285
iter 90 value 82.762016
iter 100 value 82.305977
final value 82.305977
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 128.989849
iter 10 value 94.388416
iter 20 value 94.089200
iter 30 value 92.365607
iter 40 value 87.463052
iter 50 value 85.294980
iter 60 value 84.783551
iter 70 value 84.473844
iter 80 value 84.349167
iter 90 value 84.078941
iter 100 value 83.853207
final value 83.853207
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.125026
iter 10 value 94.277310
iter 20 value 94.260547
iter 30 value 94.087174
iter 40 value 94.083938
iter 50 value 94.083904
final value 94.083901
converged
Fitting Repeat 2
# weights: 103
initial value 95.400212
final value 94.485769
converged
Fitting Repeat 3
# weights: 103
initial value 96.228425
iter 10 value 94.277433
iter 20 value 94.248161
iter 30 value 94.229025
final value 94.228879
converged
Fitting Repeat 4
# weights: 103
initial value 97.274329
iter 10 value 94.485960
final value 94.484218
converged
Fitting Repeat 5
# weights: 103
initial value 101.386303
iter 10 value 94.485764
iter 20 value 94.484218
final value 94.484213
converged
Fitting Repeat 1
# weights: 305
initial value 94.814947
iter 10 value 94.486694
iter 20 value 94.112790
final value 94.050234
converged
Fitting Repeat 2
# weights: 305
initial value 112.806153
iter 10 value 94.489369
iter 20 value 94.433487
iter 30 value 92.782857
iter 40 value 91.755178
iter 50 value 91.662264
iter 60 value 91.640252
iter 70 value 88.644419
iter 80 value 87.208308
iter 90 value 87.084498
iter 100 value 87.081872
final value 87.081872
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.048748
iter 10 value 94.489542
iter 20 value 94.481399
iter 30 value 90.210004
final value 87.652549
converged
Fitting Repeat 4
# weights: 305
initial value 101.478608
iter 10 value 94.280432
iter 20 value 94.276104
final value 94.275662
converged
Fitting Repeat 5
# weights: 305
initial value 99.208306
iter 10 value 93.970212
iter 20 value 93.901957
final value 93.873431
converged
Fitting Repeat 1
# weights: 507
initial value 97.412893
iter 10 value 94.093679
iter 20 value 94.062552
iter 30 value 94.057035
final value 94.053769
converged
Fitting Repeat 2
# weights: 507
initial value 169.801965
iter 10 value 92.109394
iter 20 value 87.447112
iter 30 value 87.442068
iter 40 value 87.438694
iter 50 value 86.733960
iter 60 value 84.002759
iter 70 value 81.914710
iter 80 value 80.256373
iter 90 value 80.104919
iter 100 value 80.102621
final value 80.102621
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.710766
iter 10 value 94.485175
iter 20 value 94.192450
iter 30 value 94.100501
final value 94.084339
converged
Fitting Repeat 4
# weights: 507
initial value 97.434203
iter 10 value 94.283464
iter 20 value 94.276321
iter 30 value 93.585549
iter 40 value 90.335805
iter 50 value 85.843375
iter 60 value 85.364003
iter 70 value 85.029272
iter 80 value 83.964812
iter 90 value 83.391100
final value 83.390740
converged
Fitting Repeat 5
# weights: 507
initial value 125.963086
iter 10 value 94.283818
iter 20 value 94.279275
iter 30 value 94.153568
iter 40 value 88.223228
iter 50 value 88.213569
iter 60 value 87.354500
iter 70 value 85.752932
iter 80 value 85.675178
iter 90 value 85.675094
iter 100 value 85.674353
final value 85.674353
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.582769
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 97.113879
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 101.160474
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 116.221375
final value 94.052911
converged
Fitting Repeat 5
# weights: 103
initial value 100.240065
iter 10 value 92.838625
iter 20 value 92.830891
iter 30 value 91.944690
iter 40 value 91.857360
iter 50 value 91.270036
iter 60 value 91.250774
final value 91.250752
converged
Fitting Repeat 1
# weights: 305
initial value 95.643712
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 105.201989
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 93.889071
iter 10 value 92.720275
final value 92.720270
converged
Fitting Repeat 4
# weights: 305
initial value 107.472985
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 105.852032
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 95.907243
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 109.560317
final value 94.038251
converged
Fitting Repeat 3
# weights: 507
initial value 94.853244
iter 10 value 90.960765
iter 20 value 81.255827
iter 30 value 81.158387
final value 81.158121
converged
Fitting Repeat 4
# weights: 507
initial value 107.168397
final value 93.628453
converged
Fitting Repeat 5
# weights: 507
initial value 123.485612
final value 94.038251
converged
Fitting Repeat 1
# weights: 103
initial value 96.397888
iter 10 value 94.063428
iter 20 value 88.861215
iter 30 value 85.404049
iter 40 value 84.679211
iter 50 value 84.428012
iter 60 value 84.221424
iter 70 value 84.081299
iter 80 value 83.791853
final value 83.776320
converged
Fitting Repeat 2
# weights: 103
initial value 99.352829
iter 10 value 93.613245
iter 20 value 85.195535
iter 30 value 84.622601
iter 40 value 84.410299
iter 50 value 84.318872
iter 60 value 83.816846
final value 83.776320
converged
Fitting Repeat 3
# weights: 103
initial value 122.112912
iter 10 value 93.937564
iter 20 value 91.568668
iter 30 value 91.310459
iter 40 value 91.297576
iter 50 value 91.032355
iter 60 value 86.702282
iter 70 value 82.983705
iter 80 value 82.693455
iter 90 value 82.596808
iter 100 value 82.549072
final value 82.549072
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 99.185122
iter 10 value 94.057424
iter 20 value 91.540140
iter 30 value 89.691810
iter 40 value 89.471870
iter 50 value 88.732055
iter 60 value 87.891924
iter 70 value 86.203417
iter 80 value 84.249251
iter 90 value 84.153947
iter 100 value 84.046330
final value 84.046330
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 112.311199
iter 10 value 94.219668
iter 20 value 93.572702
iter 30 value 87.232426
iter 40 value 86.038330
iter 50 value 84.639534
iter 60 value 84.192219
iter 70 value 83.895086
iter 80 value 83.776320
iter 80 value 83.776320
iter 80 value 83.776320
final value 83.776320
converged
Fitting Repeat 1
# weights: 305
initial value 103.934080
iter 10 value 94.439262
iter 20 value 90.984467
iter 30 value 84.006963
iter 40 value 83.329962
iter 50 value 82.679236
iter 60 value 82.399874
iter 70 value 81.643219
iter 80 value 80.792596
iter 90 value 79.791855
iter 100 value 79.413890
final value 79.413890
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.846823
iter 10 value 93.985222
iter 20 value 87.799655
iter 30 value 86.698609
iter 40 value 85.775100
iter 50 value 84.497984
iter 60 value 81.813491
iter 70 value 81.293235
iter 80 value 79.906419
iter 90 value 79.751964
iter 100 value 79.662567
final value 79.662567
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.087614
iter 10 value 92.513511
iter 20 value 85.660382
iter 30 value 83.790620
iter 40 value 82.257678
iter 50 value 80.963350
iter 60 value 80.392610
iter 70 value 80.076966
iter 80 value 79.982247
iter 90 value 79.809577
iter 100 value 79.562490
final value 79.562490
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.841635
iter 10 value 94.080922
iter 20 value 90.135509
iter 30 value 85.417127
iter 40 value 85.193202
iter 50 value 84.184042
iter 60 value 82.026126
iter 70 value 80.860907
iter 80 value 80.241838
iter 90 value 80.142557
iter 100 value 80.090736
final value 80.090736
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 129.990044
iter 10 value 93.868801
iter 20 value 92.798523
iter 30 value 88.484751
iter 40 value 83.746194
iter 50 value 82.285763
iter 60 value 81.242603
iter 70 value 80.527176
iter 80 value 79.869485
iter 90 value 79.513109
iter 100 value 79.336449
final value 79.336449
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 128.276850
iter 10 value 94.233713
iter 20 value 88.112920
iter 30 value 86.365912
iter 40 value 84.840277
iter 50 value 83.948732
iter 60 value 83.740193
iter 70 value 82.129083
iter 80 value 81.314046
iter 90 value 80.620066
iter 100 value 80.206810
final value 80.206810
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 123.489698
iter 10 value 94.153915
iter 20 value 94.061144
iter 30 value 92.165892
iter 40 value 85.139350
iter 50 value 84.215795
iter 60 value 81.149093
iter 70 value 80.375373
iter 80 value 79.869444
iter 90 value 79.719911
iter 100 value 79.502638
final value 79.502638
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.259290
iter 10 value 94.021173
iter 20 value 93.047135
iter 30 value 84.883351
iter 40 value 84.119897
iter 50 value 81.533321
iter 60 value 80.861306
iter 70 value 80.478672
iter 80 value 80.113288
iter 90 value 79.942527
iter 100 value 79.704827
final value 79.704827
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 123.264398
iter 10 value 94.591192
iter 20 value 87.375958
iter 30 value 86.496949
iter 40 value 83.255170
iter 50 value 81.479790
iter 60 value 81.103704
iter 70 value 80.100448
iter 80 value 79.598173
iter 90 value 79.247440
iter 100 value 79.146938
final value 79.146938
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.758657
iter 10 value 94.578750
iter 20 value 94.011600
iter 30 value 93.316680
iter 40 value 88.364880
iter 50 value 84.629110
iter 60 value 82.280940
iter 70 value 81.186952
iter 80 value 80.775247
iter 90 value 80.379298
iter 100 value 80.260455
final value 80.260455
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.648510
final value 94.039847
converged
Fitting Repeat 2
# weights: 103
initial value 102.495400
final value 94.054541
converged
Fitting Repeat 3
# weights: 103
initial value 98.931710
final value 94.054522
converged
Fitting Repeat 4
# weights: 103
initial value 111.956051
iter 10 value 94.054558
iter 20 value 94.052973
final value 94.052916
converged
Fitting Repeat 5
# weights: 103
initial value 96.165085
final value 94.039663
converged
Fitting Repeat 1
# weights: 305
initial value 113.332445
iter 10 value 94.057319
iter 20 value 94.041039
iter 30 value 93.785045
iter 40 value 83.786382
iter 50 value 81.750135
iter 60 value 81.427762
iter 70 value 81.386706
iter 80 value 81.386410
final value 81.386401
converged
Fitting Repeat 2
# weights: 305
initial value 97.054828
iter 10 value 94.058248
iter 20 value 93.932459
iter 30 value 89.605793
iter 40 value 88.650931
iter 50 value 88.529484
iter 60 value 88.390613
iter 70 value 88.189531
iter 80 value 84.894730
iter 90 value 84.839318
iter 100 value 83.535172
final value 83.535172
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 111.250007
iter 10 value 94.057904
iter 20 value 93.481956
iter 30 value 87.137968
iter 40 value 87.062223
iter 50 value 85.330453
iter 60 value 84.311827
iter 70 value 84.294723
iter 80 value 83.279966
iter 90 value 83.067711
iter 100 value 83.067426
final value 83.067426
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.523684
iter 10 value 94.057911
iter 20 value 94.048467
iter 30 value 90.983787
iter 40 value 83.224462
iter 50 value 82.880415
iter 60 value 81.849660
iter 70 value 81.631980
iter 80 value 81.428469
iter 90 value 81.389912
iter 100 value 81.389528
final value 81.389528
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.512667
iter 10 value 91.784813
iter 20 value 84.577117
iter 30 value 84.018586
iter 40 value 83.713098
iter 50 value 83.712395
iter 60 value 83.711758
final value 83.710938
converged
Fitting Repeat 1
# weights: 507
initial value 94.472671
iter 10 value 94.057446
iter 20 value 90.500730
iter 30 value 85.453305
iter 40 value 85.226042
final value 85.129947
converged
Fitting Repeat 2
# weights: 507
initial value 98.311665
iter 10 value 93.966528
iter 20 value 91.077244
iter 30 value 90.802949
iter 40 value 90.798911
iter 50 value 90.255608
iter 60 value 90.100228
iter 70 value 90.098956
iter 80 value 90.068882
iter 90 value 90.008829
iter 100 value 90.006400
final value 90.006400
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 94.506495
iter 10 value 93.270970
iter 20 value 93.266034
iter 30 value 91.206979
iter 40 value 90.846610
iter 50 value 81.687481
final value 81.672892
converged
Fitting Repeat 4
# weights: 507
initial value 117.517568
iter 10 value 94.046653
iter 20 value 94.036355
iter 30 value 94.009287
iter 40 value 87.011579
iter 50 value 86.899631
iter 60 value 80.147060
iter 70 value 79.238468
iter 80 value 78.870883
iter 90 value 78.865995
iter 100 value 78.806286
final value 78.806286
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 121.451572
iter 10 value 89.089480
iter 20 value 85.038665
iter 30 value 82.234636
iter 40 value 80.561291
iter 50 value 80.513030
iter 60 value 80.330403
iter 70 value 80.032205
iter 80 value 79.803286
iter 90 value 79.789357
iter 100 value 79.788951
final value 79.788951
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.492769
iter 10 value 93.320229
final value 93.320225
converged
Fitting Repeat 2
# weights: 103
initial value 96.861887
iter 10 value 91.934041
iter 20 value 91.930427
iter 30 value 91.786273
iter 40 value 91.725299
iter 50 value 89.124206
iter 60 value 88.854635
iter 70 value 88.850853
final value 88.850842
converged
Fitting Repeat 3
# weights: 103
initial value 94.800185
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.300761
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.276791
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 97.078261
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 100.396407
iter 10 value 92.579686
final value 92.579683
converged
Fitting Repeat 3
# weights: 305
initial value 102.737601
final value 94.467391
converged
Fitting Repeat 4
# weights: 305
initial value 95.703825
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 113.860453
final value 94.467391
converged
Fitting Repeat 1
# weights: 507
initial value 100.884083
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 118.514332
iter 10 value 94.467553
final value 94.467391
converged
Fitting Repeat 3
# weights: 507
initial value 111.752195
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 108.884636
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 131.585351
final value 94.467391
converged
Fitting Repeat 1
# weights: 103
initial value 106.596357
iter 10 value 94.848454
iter 20 value 94.471816
iter 30 value 83.843252
iter 40 value 82.808450
iter 50 value 82.495880
iter 60 value 82.258640
iter 70 value 81.884826
iter 80 value 81.873233
final value 81.873104
converged
Fitting Repeat 2
# weights: 103
initial value 110.414111
iter 10 value 94.486456
iter 20 value 94.259865
iter 30 value 93.248813
iter 40 value 92.707508
iter 50 value 83.830334
iter 60 value 82.767150
iter 70 value 82.534571
iter 80 value 82.440267
iter 90 value 82.300777
final value 82.297439
converged
Fitting Repeat 3
# weights: 103
initial value 96.774791
iter 10 value 94.488524
iter 20 value 93.512655
iter 30 value 93.473573
final value 93.472503
converged
Fitting Repeat 4
# weights: 103
initial value 100.606803
iter 10 value 94.648530
iter 20 value 94.459040
iter 30 value 89.172404
iter 40 value 85.636546
iter 50 value 83.710802
iter 60 value 82.760347
iter 70 value 82.542513
iter 80 value 82.508707
final value 82.508685
converged
Fitting Repeat 5
# weights: 103
initial value 99.091166
iter 10 value 94.439349
iter 20 value 93.690073
iter 30 value 93.490562
iter 40 value 93.481565
iter 50 value 83.943925
iter 60 value 82.756836
iter 70 value 81.697363
iter 80 value 79.950515
iter 90 value 79.767976
iter 100 value 79.756196
final value 79.756196
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 100.581243
iter 10 value 92.965386
iter 20 value 92.760600
iter 30 value 87.607250
iter 40 value 82.883811
iter 50 value 82.308606
iter 60 value 81.940823
iter 70 value 80.272219
iter 80 value 79.799699
iter 90 value 79.273474
iter 100 value 78.830163
final value 78.830163
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 128.978238
iter 10 value 94.894558
iter 20 value 94.589110
iter 30 value 88.429955
iter 40 value 87.154448
iter 50 value 86.388813
iter 60 value 86.190463
iter 70 value 86.002699
iter 80 value 85.670320
iter 90 value 85.257156
iter 100 value 85.136661
final value 85.136661
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.166368
iter 10 value 93.907299
iter 20 value 89.715189
iter 30 value 85.828492
iter 40 value 84.493187
iter 50 value 83.333337
iter 60 value 80.739363
iter 70 value 80.291949
iter 80 value 80.166791
iter 90 value 79.666615
iter 100 value 78.992864
final value 78.992864
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.786864
iter 10 value 89.610322
iter 20 value 82.797230
iter 30 value 82.347166
iter 40 value 82.229961
iter 50 value 81.238596
iter 60 value 79.780341
iter 70 value 78.795321
iter 80 value 78.622050
iter 90 value 78.357170
iter 100 value 78.113065
final value 78.113065
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.051629
iter 10 value 94.430318
iter 20 value 93.114499
iter 30 value 93.018134
iter 40 value 91.046813
iter 50 value 89.916388
iter 60 value 84.884245
iter 70 value 83.054496
iter 80 value 81.822903
iter 90 value 80.941635
iter 100 value 80.738338
final value 80.738338
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.505890
iter 10 value 94.231030
iter 20 value 87.743376
iter 30 value 84.692777
iter 40 value 81.333676
iter 50 value 80.052342
iter 60 value 79.252794
iter 70 value 78.895182
iter 80 value 78.402151
iter 90 value 78.214238
iter 100 value 78.188343
final value 78.188343
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.582898
iter 10 value 93.756964
iter 20 value 84.408638
iter 30 value 82.745856
iter 40 value 82.461318
iter 50 value 81.048676
iter 60 value 80.322052
iter 70 value 79.233466
iter 80 value 78.714653
iter 90 value 78.596742
iter 100 value 78.492429
final value 78.492429
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.920642
iter 10 value 94.440501
iter 20 value 91.426520
iter 30 value 86.370386
iter 40 value 84.069444
iter 50 value 80.397495
iter 60 value 78.836893
iter 70 value 78.309426
iter 80 value 78.147233
iter 90 value 77.753474
iter 100 value 77.583714
final value 77.583714
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 115.905747
iter 10 value 93.914136
iter 20 value 83.670376
iter 30 value 82.319346
iter 40 value 81.983103
iter 50 value 81.910906
iter 60 value 81.803997
iter 70 value 81.477066
iter 80 value 80.017347
iter 90 value 79.697516
iter 100 value 79.568879
final value 79.568879
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 111.492402
iter 10 value 94.506456
iter 20 value 93.630896
iter 30 value 83.291601
iter 40 value 82.268638
iter 50 value 81.798793
iter 60 value 81.558745
iter 70 value 80.984352
iter 80 value 80.388546
iter 90 value 80.166431
iter 100 value 79.715219
final value 79.715219
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.062346
iter 10 value 94.468927
iter 20 value 94.301999
iter 30 value 91.381132
iter 40 value 90.474177
iter 50 value 82.681844
iter 60 value 82.580595
iter 70 value 82.453129
iter 80 value 82.431194
final value 82.431158
converged
Fitting Repeat 2
# weights: 103
initial value 95.238616
final value 94.485795
converged
Fitting Repeat 3
# weights: 103
initial value 97.647153
final value 94.485981
converged
Fitting Repeat 4
# weights: 103
initial value 104.261396
iter 10 value 93.322315
iter 20 value 93.320708
iter 30 value 92.982679
iter 40 value 85.175610
final value 85.175434
converged
Fitting Repeat 5
# weights: 103
initial value 102.011834
iter 10 value 94.486004
iter 20 value 94.484274
iter 30 value 94.343889
final value 93.322557
converged
Fitting Repeat 1
# weights: 305
initial value 100.057595
iter 10 value 94.466234
iter 20 value 87.743340
iter 30 value 84.144869
iter 40 value 83.958791
iter 50 value 83.955740
iter 60 value 83.890760
iter 70 value 81.071871
iter 80 value 80.942984
iter 90 value 80.913934
iter 100 value 80.475393
final value 80.475393
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.405636
iter 10 value 94.481860
iter 20 value 94.478090
iter 30 value 94.477862
final value 94.477849
converged
Fitting Repeat 3
# weights: 305
initial value 96.455021
iter 10 value 94.472802
iter 20 value 94.232038
iter 30 value 93.902071
iter 40 value 93.898776
iter 50 value 92.840858
iter 60 value 92.748201
iter 70 value 92.743513
final value 92.743392
converged
Fitting Repeat 4
# weights: 305
initial value 109.782458
iter 10 value 94.489018
iter 20 value 94.484326
iter 30 value 93.321486
iter 40 value 92.937489
iter 50 value 90.134405
iter 60 value 85.774749
iter 70 value 83.283771
iter 80 value 81.891971
iter 90 value 81.602947
iter 100 value 80.958037
final value 80.958037
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.780028
iter 10 value 94.488647
iter 20 value 94.399670
iter 30 value 93.275145
iter 40 value 91.505680
iter 50 value 91.470556
iter 60 value 91.470262
iter 70 value 90.055530
iter 80 value 89.936063
iter 90 value 89.935626
final value 89.935614
converged
Fitting Repeat 1
# weights: 507
initial value 106.362893
iter 10 value 94.469508
iter 20 value 94.395328
iter 30 value 87.399047
iter 40 value 85.170832
iter 50 value 85.167168
iter 60 value 84.499857
iter 70 value 84.468640
iter 80 value 82.024362
iter 90 value 80.833882
iter 100 value 80.778668
final value 80.778668
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.053470
iter 10 value 93.822380
iter 20 value 93.584646
iter 30 value 93.317700
iter 40 value 93.316921
iter 50 value 93.312642
iter 60 value 92.042209
iter 70 value 85.590421
iter 80 value 84.726584
iter 90 value 84.631176
final value 84.630939
converged
Fitting Repeat 3
# weights: 507
initial value 101.451059
iter 10 value 94.492955
iter 20 value 94.484704
iter 30 value 94.484566
final value 94.484522
converged
Fitting Repeat 4
# weights: 507
initial value 94.500958
iter 10 value 94.486155
iter 20 value 86.429478
iter 30 value 83.950460
iter 40 value 83.788787
iter 50 value 83.619167
iter 60 value 83.611588
iter 70 value 81.431650
iter 80 value 81.197658
iter 90 value 81.010291
final value 81.010271
converged
Fitting Repeat 5
# weights: 507
initial value 101.716859
iter 10 value 94.491657
iter 20 value 93.243881
final value 92.614685
converged
Fitting Repeat 1
# weights: 103
initial value 111.820602
iter 10 value 94.047268
final value 94.026542
converged
Fitting Repeat 2
# weights: 103
initial value 100.107347
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.862484
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 108.041678
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.009552
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 95.111255
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 107.018232
final value 94.026542
converged
Fitting Repeat 3
# weights: 305
initial value 112.519313
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 103.638542
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 101.142194
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 116.953788
iter 10 value 93.847480
final value 93.793007
converged
Fitting Repeat 2
# weights: 507
initial value 105.769797
final value 93.300000
converged
Fitting Repeat 3
# weights: 507
initial value 111.549291
iter 10 value 94.052244
iter 20 value 87.999023
iter 30 value 87.943236
iter 30 value 87.943236
iter 30 value 87.943236
final value 87.943236
converged
Fitting Repeat 4
# weights: 507
initial value 98.004005
iter 10 value 94.484624
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 105.272233
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 96.910616
iter 10 value 94.459470
iter 20 value 94.134190
iter 30 value 93.586929
iter 40 value 91.827031
iter 50 value 84.311214
iter 60 value 82.632317
iter 70 value 82.566495
iter 80 value 82.034054
iter 90 value 81.595676
iter 100 value 81.297716
final value 81.297716
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 104.277801
iter 10 value 91.419741
iter 20 value 83.934758
iter 30 value 82.229533
iter 40 value 81.650137
iter 50 value 80.962406
iter 60 value 80.477127
iter 70 value 80.176626
iter 80 value 80.145551
final value 80.142573
converged
Fitting Repeat 3
# weights: 103
initial value 102.807554
iter 10 value 94.879939
iter 20 value 94.467227
iter 30 value 91.583083
iter 40 value 90.880328
iter 50 value 88.401101
iter 60 value 82.370708
iter 70 value 82.217351
iter 80 value 81.989682
iter 90 value 81.968057
iter 100 value 81.954009
final value 81.954009
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 115.047118
iter 10 value 94.461493
iter 20 value 89.490415
iter 30 value 87.900057
iter 40 value 85.307517
iter 50 value 82.701773
iter 60 value 82.028268
iter 70 value 80.771356
iter 80 value 80.241124
iter 90 value 80.154012
iter 100 value 80.145574
final value 80.145574
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 104.415174
iter 10 value 91.066229
iter 20 value 85.992043
iter 30 value 83.738080
iter 40 value 83.057181
iter 50 value 82.883994
iter 60 value 82.496458
iter 70 value 82.336226
final value 82.335144
converged
Fitting Repeat 1
# weights: 305
initial value 105.597472
iter 10 value 94.325339
iter 20 value 85.995091
iter 30 value 82.306452
iter 40 value 81.997651
iter 50 value 80.665867
iter 60 value 79.902452
iter 70 value 79.400825
iter 80 value 79.324031
iter 90 value 79.206328
iter 100 value 78.911045
final value 78.911045
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.624202
iter 10 value 91.223332
iter 20 value 84.301026
iter 30 value 83.811382
iter 40 value 82.059374
iter 50 value 81.820735
iter 60 value 80.742404
iter 70 value 80.505229
iter 80 value 80.331311
iter 90 value 79.692969
iter 100 value 79.334319
final value 79.334319
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.457006
iter 10 value 93.739096
iter 20 value 83.968934
iter 30 value 82.944656
iter 40 value 82.384773
iter 50 value 82.250484
iter 60 value 81.916888
iter 70 value 81.869523
iter 80 value 81.782839
iter 90 value 80.724648
iter 100 value 80.288489
final value 80.288489
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.260256
iter 10 value 93.094876
iter 20 value 83.468334
iter 30 value 83.199318
iter 40 value 82.911652
iter 50 value 82.517853
iter 60 value 82.352182
iter 70 value 82.203133
iter 80 value 82.140027
iter 90 value 82.096138
iter 100 value 82.067026
final value 82.067026
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.656306
iter 10 value 94.514542
iter 20 value 91.199654
iter 30 value 83.894876
iter 40 value 83.403188
iter 50 value 81.239461
iter 60 value 80.757120
iter 70 value 80.648002
iter 80 value 79.822034
iter 90 value 79.443046
iter 100 value 79.041013
final value 79.041013
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.199154
iter 10 value 96.689918
iter 20 value 93.658041
iter 30 value 93.456030
iter 40 value 92.257271
iter 50 value 89.082285
iter 60 value 85.602947
iter 70 value 84.821290
iter 80 value 83.704125
iter 90 value 83.136598
iter 100 value 82.389238
final value 82.389238
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.770608
iter 10 value 94.046747
iter 20 value 92.079953
iter 30 value 84.165762
iter 40 value 82.748833
iter 50 value 81.711683
iter 60 value 79.996901
iter 70 value 79.399178
iter 80 value 79.024773
iter 90 value 78.862283
iter 100 value 78.588033
final value 78.588033
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 107.024623
iter 10 value 93.936182
iter 20 value 88.483156
iter 30 value 84.695171
iter 40 value 84.157139
iter 50 value 81.004548
iter 60 value 80.107397
iter 70 value 79.893387
iter 80 value 79.480590
iter 90 value 79.070590
iter 100 value 79.019339
final value 79.019339
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 126.796525
iter 10 value 94.918953
iter 20 value 94.522202
iter 30 value 93.750966
iter 40 value 88.777685
iter 50 value 87.695066
iter 60 value 87.319815
iter 70 value 86.715236
iter 80 value 83.218897
iter 90 value 80.029635
iter 100 value 79.609960
final value 79.609960
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.983411
iter 10 value 93.543107
iter 20 value 83.266214
iter 30 value 82.729817
iter 40 value 82.589889
iter 50 value 81.912202
iter 60 value 81.435250
iter 70 value 81.031193
iter 80 value 80.398540
iter 90 value 79.553402
iter 100 value 79.296857
final value 79.296857
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 107.512228
iter 10 value 94.485853
iter 20 value 94.484303
final value 94.484219
converged
Fitting Repeat 2
# weights: 103
initial value 105.691361
final value 94.485974
converged
Fitting Repeat 3
# weights: 103
initial value 95.242281
iter 10 value 91.813062
iter 20 value 86.957112
iter 30 value 86.956012
iter 40 value 86.955099
final value 86.955093
converged
Fitting Repeat 4
# weights: 103
initial value 99.259445
final value 94.411169
converged
Fitting Repeat 5
# weights: 103
initial value 115.101671
iter 10 value 90.755938
iter 20 value 90.724496
iter 30 value 90.723704
iter 40 value 90.658793
final value 90.623745
converged
Fitting Repeat 1
# weights: 305
initial value 100.865388
iter 10 value 94.488856
iter 20 value 94.471059
iter 30 value 83.558208
iter 40 value 83.341334
iter 50 value 82.323445
iter 60 value 81.509417
iter 70 value 81.335864
final value 81.333449
converged
Fitting Repeat 2
# weights: 305
initial value 104.431153
iter 10 value 94.034828
iter 20 value 94.030420
final value 94.029894
converged
Fitting Repeat 3
# weights: 305
initial value 112.058383
iter 10 value 94.489351
iter 20 value 94.484767
iter 30 value 94.370391
iter 40 value 94.180671
iter 50 value 86.599903
iter 60 value 85.651693
iter 70 value 85.197594
iter 80 value 80.955315
iter 90 value 80.952145
final value 80.952024
converged
Fitting Repeat 4
# weights: 305
initial value 109.206316
iter 10 value 94.489016
iter 20 value 93.545312
iter 30 value 88.307894
iter 40 value 87.285516
iter 50 value 87.263064
iter 60 value 87.262486
final value 87.262089
converged
Fitting Repeat 5
# weights: 305
initial value 110.460777
iter 10 value 94.489828
iter 20 value 94.076196
final value 94.027281
converged
Fitting Repeat 1
# weights: 507
initial value 95.162552
iter 10 value 94.035441
iter 20 value 91.661730
iter 30 value 87.771716
iter 40 value 84.452892
iter 50 value 83.147317
iter 60 value 83.142367
iter 70 value 82.164260
iter 80 value 81.932276
iter 90 value 81.926132
iter 100 value 81.676594
final value 81.676594
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.844816
iter 10 value 94.035882
iter 20 value 94.032558
iter 30 value 85.208055
iter 40 value 83.097158
iter 50 value 82.686849
iter 60 value 81.834954
iter 70 value 81.336667
iter 80 value 81.335079
iter 90 value 81.326947
iter 100 value 81.319820
final value 81.319820
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 97.484664
iter 10 value 93.303214
iter 20 value 87.614924
iter 30 value 82.359835
iter 40 value 82.122608
iter 50 value 82.002961
iter 60 value 81.602864
iter 70 value 81.025834
iter 80 value 80.619254
iter 90 value 80.530434
iter 100 value 80.529642
final value 80.529642
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.232140
iter 10 value 94.489998
iter 20 value 92.254284
iter 30 value 84.218257
iter 40 value 83.406559
iter 50 value 83.404582
iter 60 value 83.090216
iter 70 value 82.977287
iter 80 value 82.957000
final value 82.942899
converged
Fitting Repeat 5
# weights: 507
initial value 101.925156
iter 10 value 94.035234
iter 20 value 93.842347
final value 93.809822
converged
Fitting Repeat 1
# weights: 103
initial value 94.898995
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 113.399571
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 100.103929
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 94.436532
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 99.832396
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 107.850461
iter 10 value 93.469980
final value 93.460693
converged
Fitting Repeat 2
# weights: 305
initial value 116.946663
iter 10 value 93.582418
iter 10 value 93.582418
iter 10 value 93.582418
final value 93.582418
converged
Fitting Repeat 3
# weights: 305
initial value 95.469979
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 102.277413
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 128.544550
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 100.708004
final value 94.052908
converged
Fitting Repeat 2
# weights: 507
initial value 95.168627
iter 10 value 93.479840
final value 93.460693
converged
Fitting Repeat 3
# weights: 507
initial value 95.871375
iter 10 value 93.582418
iter 10 value 93.582418
iter 10 value 93.582418
final value 93.582418
converged
Fitting Repeat 4
# weights: 507
initial value 133.753354
final value 93.904720
converged
Fitting Repeat 5
# weights: 507
initial value 128.840927
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 106.790676
iter 10 value 94.054988
iter 20 value 93.851392
iter 30 value 93.684525
iter 40 value 93.393385
iter 50 value 88.680944
iter 60 value 88.074055
iter 70 value 87.678067
iter 80 value 86.852701
iter 90 value 83.598233
iter 100 value 82.568649
final value 82.568649
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.867419
iter 10 value 94.054915
iter 20 value 93.211597
iter 30 value 88.439441
iter 40 value 85.024077
iter 50 value 84.731508
iter 60 value 84.228514
iter 70 value 83.651242
iter 80 value 83.517893
final value 83.517611
converged
Fitting Repeat 3
# weights: 103
initial value 102.694042
iter 10 value 93.755901
iter 20 value 92.177697
iter 30 value 91.657139
iter 40 value 91.331452
iter 50 value 91.310609
final value 91.310597
converged
Fitting Repeat 4
# weights: 103
initial value 96.574518
iter 10 value 94.056754
iter 20 value 85.822265
iter 30 value 85.056123
iter 40 value 84.395459
iter 50 value 83.430458
iter 60 value 83.365545
iter 70 value 83.325721
iter 80 value 83.275896
final value 83.275796
converged
Fitting Repeat 5
# weights: 103
initial value 102.586334
iter 10 value 93.764328
iter 20 value 93.686586
iter 30 value 93.685418
iter 40 value 93.482691
iter 50 value 91.070296
iter 60 value 87.910547
iter 70 value 87.872801
iter 80 value 87.817543
iter 90 value 87.289926
iter 100 value 85.510811
final value 85.510811
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.176734
iter 10 value 93.592918
iter 20 value 87.704324
iter 30 value 86.564774
iter 40 value 83.329454
iter 50 value 82.193214
iter 60 value 81.709349
iter 70 value 81.478897
iter 80 value 81.262962
iter 90 value 81.195600
iter 100 value 81.174168
final value 81.174168
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.823723
iter 10 value 92.516358
iter 20 value 86.251207
iter 30 value 85.325033
iter 40 value 82.523816
iter 50 value 81.454440
iter 60 value 81.232384
iter 70 value 81.075181
iter 80 value 80.894726
iter 90 value 80.824056
iter 100 value 80.740958
final value 80.740958
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.177786
iter 10 value 93.625650
iter 20 value 84.668882
iter 30 value 83.235265
iter 40 value 81.851738
iter 50 value 81.640212
iter 60 value 81.083092
iter 70 value 80.675062
iter 80 value 80.621551
iter 90 value 80.572027
iter 100 value 80.522626
final value 80.522626
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.826315
iter 10 value 94.212935
iter 20 value 93.553743
iter 30 value 93.457608
iter 40 value 92.961335
iter 50 value 88.358729
iter 60 value 86.872090
iter 70 value 84.940740
iter 80 value 82.530180
iter 90 value 81.470962
iter 100 value 80.683445
final value 80.683445
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 112.611791
iter 10 value 94.048573
iter 20 value 87.232099
iter 30 value 84.745585
iter 40 value 83.059079
iter 50 value 82.896311
iter 60 value 82.369696
iter 70 value 82.040414
iter 80 value 81.709496
iter 90 value 81.590463
iter 100 value 81.133589
final value 81.133589
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.545490
iter 10 value 93.558590
iter 20 value 88.257611
iter 30 value 85.737160
iter 40 value 84.180802
iter 50 value 83.840433
iter 60 value 83.565411
iter 70 value 83.056579
iter 80 value 82.606789
iter 90 value 82.004227
iter 100 value 81.273587
final value 81.273587
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 116.993431
iter 10 value 94.213694
iter 20 value 88.449228
iter 30 value 85.876049
iter 40 value 82.275977
iter 50 value 81.833838
iter 60 value 81.483562
iter 70 value 80.873764
iter 80 value 80.781208
iter 90 value 80.638419
iter 100 value 80.595070
final value 80.595070
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.341647
iter 10 value 93.821275
iter 20 value 93.315058
iter 30 value 87.322931
iter 40 value 85.494628
iter 50 value 83.973088
iter 60 value 83.742633
iter 70 value 83.716116
iter 80 value 83.396303
iter 90 value 82.026027
iter 100 value 81.025827
final value 81.025827
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.453270
iter 10 value 93.541121
iter 20 value 91.377948
iter 30 value 84.895872
iter 40 value 83.006749
iter 50 value 82.036437
iter 60 value 81.722566
iter 70 value 81.630570
iter 80 value 81.456928
iter 90 value 81.428662
iter 100 value 81.075589
final value 81.075589
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.315190
iter 10 value 94.140053
iter 20 value 89.250369
iter 30 value 85.478411
iter 40 value 84.817905
iter 50 value 83.935994
iter 60 value 83.076529
iter 70 value 83.026724
iter 80 value 82.849023
iter 90 value 82.573979
iter 100 value 82.400227
final value 82.400227
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.494544
final value 93.584263
converged
Fitting Repeat 2
# weights: 103
initial value 104.141988
iter 10 value 94.054714
final value 94.052913
converged
Fitting Repeat 3
# weights: 103
initial value 94.716676
final value 94.054691
converged
Fitting Repeat 4
# weights: 103
initial value 127.768803
final value 94.054377
converged
Fitting Repeat 5
# weights: 103
initial value 95.350322
final value 94.054705
converged
Fitting Repeat 1
# weights: 305
initial value 109.332730
iter 10 value 94.057653
iter 20 value 94.053077
final value 94.053070
converged
Fitting Repeat 2
# weights: 305
initial value 111.141345
iter 10 value 94.057978
iter 20 value 93.801564
final value 93.582648
converged
Fitting Repeat 3
# weights: 305
initial value 118.679303
iter 10 value 94.058453
iter 20 value 94.053887
iter 30 value 93.584329
final value 93.583757
converged
Fitting Repeat 4
# weights: 305
initial value 99.950390
iter 10 value 94.058032
iter 20 value 94.053240
iter 30 value 93.628950
iter 40 value 86.428313
iter 50 value 86.272456
iter 60 value 86.271951
iter 70 value 86.271708
iter 80 value 86.271334
iter 90 value 86.270087
iter 100 value 83.592052
final value 83.592052
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 95.051428
iter 10 value 93.710823
iter 20 value 93.586937
iter 30 value 93.349368
iter 40 value 93.345694
iter 50 value 93.240544
iter 60 value 90.920762
iter 70 value 90.641871
final value 90.615479
converged
Fitting Repeat 1
# weights: 507
initial value 99.602205
iter 10 value 94.059539
iter 20 value 87.670578
iter 30 value 87.489395
iter 40 value 87.488953
iter 40 value 87.488952
iter 40 value 87.488952
final value 87.488952
converged
Fitting Repeat 2
# weights: 507
initial value 105.109954
iter 10 value 93.590526
iter 20 value 93.264767
iter 30 value 89.102344
iter 40 value 88.678339
iter 50 value 87.805178
iter 60 value 87.803505
final value 87.803343
converged
Fitting Repeat 3
# weights: 507
initial value 95.664384
iter 10 value 94.038995
iter 20 value 93.590477
iter 30 value 93.586775
iter 40 value 91.506066
iter 50 value 88.494560
iter 60 value 88.334729
iter 70 value 88.330385
final value 88.330313
converged
Fitting Repeat 4
# weights: 507
initial value 101.331524
iter 10 value 93.590933
iter 20 value 92.554952
iter 30 value 89.509741
iter 40 value 89.349670
iter 50 value 89.138523
iter 60 value 83.933595
iter 70 value 83.551531
iter 80 value 81.865065
iter 90 value 81.819738
iter 90 value 81.819737
final value 81.819737
converged
Fitting Repeat 5
# weights: 507
initial value 100.005646
iter 10 value 94.030747
iter 20 value 91.937867
iter 30 value 91.263590
iter 40 value 86.301740
iter 50 value 86.274795
iter 60 value 86.269915
iter 70 value 85.317125
iter 80 value 83.771193
iter 90 value 83.019616
iter 100 value 83.013106
final value 83.013106
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 121.027430
iter 10 value 116.903799
iter 20 value 116.883546
iter 30 value 116.811405
iter 40 value 116.661412
iter 50 value 116.621647
iter 60 value 116.619191
iter 70 value 116.613018
iter 80 value 116.612355
iter 90 value 116.588987
iter 100 value 107.684335
final value 107.684335
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 118.585479
iter 10 value 110.245736
iter 20 value 107.011928
iter 30 value 106.785716
iter 40 value 106.784145
iter 50 value 105.607336
iter 60 value 104.937340
iter 70 value 104.834164
iter 80 value 104.228826
iter 90 value 103.754571
iter 100 value 103.753792
final value 103.753792
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 125.824808
iter 10 value 117.766749
iter 20 value 117.759629
iter 30 value 110.988636
iter 40 value 106.123857
iter 50 value 102.964051
iter 60 value 100.438159
iter 70 value 100.235332
iter 80 value 99.798012
iter 90 value 99.768122
iter 100 value 99.743547
final value 99.743547
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 159.880799
iter 10 value 117.898512
iter 20 value 117.891222
iter 30 value 108.974663
iter 40 value 107.008524
iter 50 value 107.007173
iter 60 value 105.398145
iter 70 value 103.325799
iter 80 value 100.800821
iter 90 value 100.746898
iter 100 value 100.131963
final value 100.131963
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 123.890509
iter 10 value 117.898394
iter 20 value 117.763951
iter 30 value 117.547920
iter 40 value 117.493398
iter 50 value 107.509663
final value 107.008686
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 3 02:42:25 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
38.29 1.42 54.20
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 34.77 | 1.87 | 36.84 | |
| FreqInteractors | 0.28 | 0.07 | 0.42 | |
| calculateAAC | 0.06 | 0.01 | 0.13 | |
| calculateAutocor | 0.38 | 0.05 | 0.48 | |
| calculateCTDC | 0.07 | 0.01 | 0.10 | |
| calculateCTDD | 0.71 | 0.02 | 0.86 | |
| calculateCTDT | 0.26 | 0.00 | 0.26 | |
| calculateCTriad | 0.5 | 0.0 | 0.5 | |
| calculateDC | 0.16 | 0.00 | 0.16 | |
| calculateF | 0.42 | 0.00 | 0.42 | |
| calculateKSAAP | 0.09 | 0.00 | 0.09 | |
| calculateQD_Sm | 2.32 | 0.24 | 2.55 | |
| calculateTC | 1.48 | 0.11 | 1.59 | |
| calculateTC_Sm | 0.24 | 0.01 | 0.25 | |
| corr_plot | 31.59 | 1.54 | 33.22 | |
| enrichfindP | 0.65 | 0.06 | 14.96 | |
| enrichfind_hp | 0.07 | 0.03 | 1.86 | |
| enrichplot | 0.33 | 0.01 | 0.39 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.00 | 0.07 | 1.95 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.10 | 0.01 | 0.11 | |
| pred_ensembel | 13.75 | 0.27 | 13.55 | |
| var_imp | 34.96 | 1.33 | 36.29 | |