Matineh Rahmatbakhsh
| Snapshot Date: 2025-02-05 13:48 -0500 (Wed, 05 Feb 2025) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: 65e718f |
| git_last_commit_date: 2024-10-29 11:04:11 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-02-06 11:41 -0500 (Thu, 06 Feb 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences" | 4719 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2025-01-21 r87610 ucrt) -- "Unsuffered Consequences" | 4480 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2025-01-22 r87618) -- "Unsuffered Consequences" | 4491 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences" | 4444 |
| 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 981/2295 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.13.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | 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: 1.13.0 |
| Command: E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.21-bioc\R\library --no-vignettes --timings HPiP_1.13.0.tar.gz |
| StartedAt: 2025-02-06 02:30:30 -0500 (Thu, 06 Feb 2025) |
| EndedAt: 2025-02-06 02:37:04 -0500 (Thu, 06 Feb 2025) |
| EllapsedTime: 393.5 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.21-bioc\R\library --no-vignettes --timings HPiP_1.13.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'E:/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck'
* using R Under development (unstable) (2025-01-21 r87610 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 '1.13.0'
* 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 ... INFO
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
FSmethod 35.16 1.89 37.07
corr_plot 34.47 1.53 36.04
var_imp 33.94 0.98 34.93
pred_ensembel 13.24 0.33 12.07
enrichfindP 0.78 0.09 12.74
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
'E:/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'E:/biocbuild/bbs-3.21-bioc/R/library' * installing *source* package 'HPiP' ... ** this is package 'HPiP' version '1.13.0' ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R Under development (unstable) (2025-01-21 r87610 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2025 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 103.194928
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 102.200898
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.562231
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.192370
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 98.051009
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 136.717717
iter 10 value 94.466876
final value 94.466823
converged
Fitting Repeat 2
# weights: 305
initial value 116.980847
final value 94.484210
converged
Fitting Repeat 3
# weights: 305
initial value 110.694242
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 99.689658
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 99.037355
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 95.961660
final value 94.480513
converged
Fitting Repeat 2
# weights: 507
initial value 97.376068
final value 94.466823
converged
Fitting Repeat 3
# weights: 507
initial value 105.099013
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 126.280532
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 111.816849
final value 94.466823
converged
Fitting Repeat 1
# weights: 103
initial value 114.028602
iter 10 value 94.412789
iter 20 value 90.180446
iter 30 value 87.534060
iter 40 value 87.023871
iter 50 value 86.772693
iter 60 value 85.464560
iter 70 value 85.075757
iter 80 value 84.936165
iter 90 value 84.829850
iter 100 value 84.775660
final value 84.775660
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.357537
iter 10 value 94.441460
iter 20 value 94.197132
iter 30 value 93.552851
iter 40 value 86.355258
iter 50 value 85.210534
iter 60 value 84.898071
iter 70 value 84.667442
iter 80 value 84.545894
iter 90 value 84.467295
iter 100 value 84.265263
final value 84.265263
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 106.722140
iter 10 value 94.487874
iter 20 value 94.346918
iter 30 value 90.769991
iter 40 value 89.861594
iter 50 value 86.774962
iter 60 value 85.733729
iter 70 value 85.634553
iter 80 value 85.619304
iter 90 value 85.581416
iter 100 value 85.156905
final value 85.156905
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.876608
iter 10 value 94.488512
iter 20 value 92.307368
iter 30 value 91.090540
iter 40 value 90.454123
iter 50 value 85.982003
iter 60 value 85.449786
iter 70 value 84.989857
iter 80 value 84.828996
iter 90 value 84.776439
final value 84.774199
converged
Fitting Repeat 5
# weights: 103
initial value 100.674479
iter 10 value 94.145654
iter 20 value 87.024463
iter 30 value 86.219543
iter 40 value 86.047717
iter 50 value 85.868524
iter 60 value 85.207080
iter 70 value 84.797157
iter 80 value 84.774201
final value 84.774199
converged
Fitting Repeat 1
# weights: 305
initial value 100.289716
iter 10 value 89.158685
iter 20 value 86.518623
iter 30 value 86.022324
iter 40 value 85.471379
iter 50 value 84.919165
iter 60 value 84.364429
iter 70 value 83.727036
iter 80 value 83.218670
iter 90 value 83.094962
iter 100 value 83.092769
final value 83.092769
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.947865
iter 10 value 94.409009
iter 20 value 87.914856
iter 30 value 87.302152
iter 40 value 85.635186
iter 50 value 85.006897
iter 60 value 84.349759
iter 70 value 83.654594
iter 80 value 83.461837
iter 90 value 83.225433
iter 100 value 83.101758
final value 83.101758
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.371733
iter 10 value 94.489785
iter 20 value 93.389984
iter 30 value 86.177859
iter 40 value 85.299134
iter 50 value 84.354970
iter 60 value 83.906332
iter 70 value 82.852600
iter 80 value 82.529128
iter 90 value 82.486434
iter 100 value 82.460915
final value 82.460915
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.152259
iter 10 value 94.415594
iter 20 value 93.326743
iter 30 value 90.092961
iter 40 value 88.156708
iter 50 value 86.734275
iter 60 value 84.822961
iter 70 value 84.174192
iter 80 value 83.611169
iter 90 value 83.026944
iter 100 value 82.845283
final value 82.845283
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.166712
iter 10 value 94.493419
iter 20 value 92.656680
iter 30 value 90.666613
iter 40 value 84.905537
iter 50 value 84.287450
iter 60 value 83.365719
iter 70 value 83.134421
iter 80 value 82.798737
iter 90 value 82.657551
iter 100 value 82.463027
final value 82.463027
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.515312
iter 10 value 94.673263
iter 20 value 88.486071
iter 30 value 86.441039
iter 40 value 85.426162
iter 50 value 84.804010
iter 60 value 84.425762
iter 70 value 84.314215
iter 80 value 84.167124
iter 90 value 84.035762
iter 100 value 83.147130
final value 83.147130
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 119.814482
iter 10 value 94.567126
iter 20 value 93.256707
iter 30 value 88.283806
iter 40 value 85.822825
iter 50 value 85.002731
iter 60 value 83.888693
iter 70 value 83.278688
iter 80 value 82.760194
iter 90 value 82.540363
iter 100 value 82.441456
final value 82.441456
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.897717
iter 10 value 94.582888
iter 20 value 93.322961
iter 30 value 90.314649
iter 40 value 88.368404
iter 50 value 87.472263
iter 60 value 86.712387
iter 70 value 85.530027
iter 80 value 84.185390
iter 90 value 83.706223
iter 100 value 83.476549
final value 83.476549
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.366742
iter 10 value 87.862324
iter 20 value 86.058495
iter 30 value 85.153631
iter 40 value 84.050399
iter 50 value 82.961252
iter 60 value 82.357710
iter 70 value 82.256234
iter 80 value 82.216806
iter 90 value 82.121718
iter 100 value 82.075698
final value 82.075698
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 116.508220
iter 10 value 94.340743
iter 20 value 88.256497
iter 30 value 86.917169
iter 40 value 86.081414
iter 50 value 84.464846
iter 60 value 83.091780
iter 70 value 82.722499
iter 80 value 82.594684
iter 90 value 82.421950
iter 100 value 82.374480
final value 82.374480
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.795704
iter 10 value 94.468364
final value 94.466844
converged
Fitting Repeat 2
# weights: 103
initial value 108.287543
final value 94.485776
converged
Fitting Repeat 3
# weights: 103
initial value 111.399516
final value 94.486064
converged
Fitting Repeat 4
# weights: 103
initial value 101.495826
final value 94.485721
converged
Fitting Repeat 5
# weights: 103
initial value 98.669898
final value 94.485651
converged
Fitting Repeat 1
# weights: 305
initial value 103.101472
iter 10 value 94.489377
iter 20 value 94.374949
iter 30 value 89.420749
iter 40 value 87.445289
iter 50 value 87.156218
iter 60 value 87.072296
iter 70 value 87.037968
final value 87.034164
converged
Fitting Repeat 2
# weights: 305
initial value 105.807038
iter 10 value 94.488461
iter 20 value 94.484179
iter 30 value 88.158198
iter 40 value 86.452716
iter 50 value 84.826831
iter 60 value 84.730395
iter 70 value 84.712207
final value 84.712203
converged
Fitting Repeat 3
# weights: 305
initial value 125.079079
iter 10 value 94.489593
iter 20 value 94.429892
iter 30 value 94.038621
iter 40 value 92.464102
iter 50 value 92.402522
iter 60 value 92.378831
iter 70 value 92.374569
iter 80 value 91.287356
iter 90 value 91.285825
final value 91.285823
converged
Fitting Repeat 4
# weights: 305
initial value 96.706796
iter 10 value 94.489033
iter 20 value 94.471191
iter 30 value 92.678341
iter 40 value 88.228248
iter 50 value 88.223000
iter 60 value 88.218109
iter 70 value 88.030326
iter 80 value 85.224669
iter 90 value 84.616689
iter 100 value 83.874768
final value 83.874768
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 95.951532
iter 10 value 94.487428
iter 20 value 93.142371
iter 30 value 93.136643
iter 40 value 89.009091
iter 50 value 88.349846
iter 60 value 88.338705
iter 70 value 88.293284
iter 80 value 88.291669
iter 90 value 88.251454
iter 100 value 87.905853
final value 87.905853
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.558580
iter 10 value 87.403356
iter 20 value 85.697575
iter 30 value 85.661842
final value 85.660817
converged
Fitting Repeat 2
# weights: 507
initial value 98.241448
iter 10 value 89.245957
iter 20 value 88.027389
iter 30 value 87.858658
iter 40 value 87.813172
final value 87.812321
converged
Fitting Repeat 3
# weights: 507
initial value 120.071580
iter 10 value 95.110317
iter 20 value 88.945883
iter 30 value 88.927779
iter 40 value 87.780834
iter 50 value 86.607096
iter 60 value 86.429772
iter 70 value 86.402459
iter 80 value 86.370017
iter 90 value 86.361152
iter 100 value 86.358608
final value 86.358608
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 124.976423
iter 10 value 89.782472
iter 20 value 87.786292
iter 30 value 87.779899
iter 40 value 87.711478
iter 50 value 87.710743
iter 60 value 85.915105
iter 70 value 85.504745
iter 80 value 85.502808
iter 90 value 84.982693
iter 100 value 84.969607
final value 84.969607
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.071139
iter 10 value 94.475454
iter 20 value 94.342186
iter 30 value 85.657631
iter 40 value 85.651154
iter 50 value 85.650594
iter 60 value 85.276875
iter 70 value 84.619239
iter 80 value 84.561323
iter 90 value 84.183922
iter 100 value 83.778705
final value 83.778705
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.633342
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 103.679719
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 99.897802
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 101.489924
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 102.477852
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 102.258548
iter 10 value 94.466985
final value 94.466823
converged
Fitting Repeat 2
# weights: 305
initial value 101.111214
final value 94.466823
converged
Fitting Repeat 3
# weights: 305
initial value 98.638343
final value 94.461538
converged
Fitting Repeat 4
# weights: 305
initial value 94.941694
final value 94.466823
converged
Fitting Repeat 5
# weights: 305
initial value 106.043561
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 106.804544
iter 10 value 94.195523
iter 20 value 92.980755
iter 30 value 91.651177
final value 91.651099
converged
Fitting Repeat 2
# weights: 507
initial value 102.709116
final value 94.484210
converged
Fitting Repeat 3
# weights: 507
initial value 109.893605
iter 10 value 94.487218
iter 20 value 94.484217
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 138.656673
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 101.175720
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 96.999051
iter 10 value 94.449684
iter 20 value 90.344025
iter 30 value 84.805850
iter 40 value 83.530959
iter 50 value 82.019665
iter 60 value 81.544667
iter 70 value 81.436366
final value 81.433048
converged
Fitting Repeat 2
# weights: 103
initial value 98.680174
iter 10 value 94.430659
iter 20 value 91.570058
iter 30 value 90.487593
iter 40 value 86.851575
iter 50 value 85.734962
iter 60 value 85.460368
iter 70 value 85.328125
iter 80 value 85.306929
final value 85.303008
converged
Fitting Repeat 3
# weights: 103
initial value 98.759980
iter 10 value 93.790313
iter 20 value 87.671006
iter 30 value 86.738373
iter 40 value 83.861768
iter 50 value 83.492378
iter 60 value 82.865351
iter 70 value 82.861063
final value 82.861044
converged
Fitting Repeat 4
# weights: 103
initial value 97.878456
iter 10 value 94.408614
iter 20 value 90.485910
iter 30 value 86.620890
iter 40 value 86.493417
iter 50 value 85.672734
iter 60 value 85.330504
final value 85.330428
converged
Fitting Repeat 5
# weights: 103
initial value 98.406671
iter 10 value 92.871728
iter 20 value 88.429599
iter 30 value 84.281492
iter 40 value 83.944531
iter 50 value 83.016561
iter 60 value 82.861701
final value 82.860834
converged
Fitting Repeat 1
# weights: 305
initial value 106.939864
iter 10 value 95.350709
iter 20 value 92.019524
iter 30 value 87.121674
iter 40 value 83.194695
iter 50 value 81.317425
iter 60 value 80.453726
iter 70 value 79.943930
iter 80 value 79.821293
iter 90 value 79.509897
iter 100 value 79.382603
final value 79.382603
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.113972
iter 10 value 93.688552
iter 20 value 93.184392
iter 30 value 91.302227
iter 40 value 90.113660
iter 50 value 90.011751
iter 60 value 89.872725
iter 70 value 82.654599
iter 80 value 82.142970
iter 90 value 80.804649
iter 100 value 80.720953
final value 80.720953
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 125.775872
iter 10 value 94.507205
iter 20 value 86.752280
iter 30 value 86.004837
iter 40 value 84.875779
iter 50 value 84.443403
iter 60 value 84.193229
iter 70 value 83.300290
iter 80 value 81.273621
iter 90 value 80.534059
iter 100 value 79.779653
final value 79.779653
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.948293
iter 10 value 94.457108
iter 20 value 90.351636
iter 30 value 85.729539
iter 40 value 84.579758
iter 50 value 83.164768
iter 60 value 82.214058
iter 70 value 81.667940
iter 80 value 81.300704
iter 90 value 80.398660
iter 100 value 79.983930
final value 79.983930
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.826211
iter 10 value 94.478131
iter 20 value 94.248689
iter 30 value 92.111248
iter 40 value 90.024943
iter 50 value 89.569017
iter 60 value 84.283437
iter 70 value 83.856662
iter 80 value 83.292493
iter 90 value 82.946384
iter 100 value 82.495612
final value 82.495612
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.032359
iter 10 value 94.562698
iter 20 value 86.849451
iter 30 value 82.478078
iter 40 value 80.580923
iter 50 value 79.727107
iter 60 value 79.450636
iter 70 value 79.267862
iter 80 value 79.201654
iter 90 value 79.116751
iter 100 value 79.057981
final value 79.057981
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 116.047125
iter 10 value 94.235576
iter 20 value 89.811095
iter 30 value 87.230201
iter 40 value 86.696342
iter 50 value 86.123987
iter 60 value 85.594543
iter 70 value 83.241241
iter 80 value 82.153201
iter 90 value 81.717558
iter 100 value 80.667918
final value 80.667918
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.389412
iter 10 value 94.854515
iter 20 value 92.597479
iter 30 value 85.621532
iter 40 value 83.285551
iter 50 value 82.762047
iter 60 value 82.198356
iter 70 value 81.908425
iter 80 value 81.141291
iter 90 value 80.982250
iter 100 value 80.893776
final value 80.893776
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.647886
iter 10 value 95.185143
iter 20 value 94.610872
iter 30 value 87.516496
iter 40 value 87.328263
iter 50 value 86.890826
iter 60 value 84.792872
iter 70 value 83.490901
iter 80 value 81.782515
iter 90 value 80.544374
iter 100 value 80.170507
final value 80.170507
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 152.400106
iter 10 value 99.932767
iter 20 value 87.001237
iter 30 value 83.300947
iter 40 value 82.705644
iter 50 value 82.294746
iter 60 value 81.611182
iter 70 value 81.214324
iter 80 value 81.130428
iter 90 value 80.403277
iter 100 value 80.076277
final value 80.076277
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.826117
iter 10 value 94.485744
iter 20 value 94.481034
iter 30 value 86.857595
iter 40 value 84.291717
final value 84.283883
converged
Fitting Repeat 2
# weights: 103
initial value 96.253778
final value 94.485718
converged
Fitting Repeat 3
# weights: 103
initial value 97.113834
final value 94.485892
converged
Fitting Repeat 4
# weights: 103
initial value 115.600884
final value 94.485755
converged
Fitting Repeat 5
# weights: 103
initial value 101.897189
final value 94.485924
converged
Fitting Repeat 1
# weights: 305
initial value 97.473221
iter 10 value 94.488841
iter 20 value 94.481030
iter 30 value 94.250098
iter 40 value 90.536878
iter 50 value 89.992226
iter 60 value 89.985799
iter 70 value 82.753777
iter 80 value 82.145229
iter 90 value 81.965346
iter 100 value 81.930824
final value 81.930824
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 126.944913
iter 10 value 94.493455
iter 20 value 94.488126
iter 30 value 94.395807
iter 40 value 90.933004
iter 50 value 90.777327
iter 60 value 90.752447
iter 70 value 90.749349
final value 90.748431
converged
Fitting Repeat 3
# weights: 305
initial value 96.751830
iter 10 value 94.483359
iter 20 value 84.964676
iter 30 value 84.292492
iter 40 value 84.182848
iter 50 value 84.181252
iter 60 value 84.179142
iter 70 value 84.179011
iter 80 value 84.176284
iter 90 value 83.737200
iter 100 value 83.735719
final value 83.735719
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.941869
iter 10 value 94.471959
iter 20 value 94.308861
iter 30 value 88.702989
iter 40 value 87.542921
iter 50 value 87.539471
iter 60 value 86.921590
iter 70 value 86.872695
final value 86.872528
converged
Fitting Repeat 5
# weights: 305
initial value 109.637934
iter 10 value 94.488936
iter 20 value 94.483500
iter 30 value 93.059692
iter 40 value 85.822782
iter 50 value 85.813372
iter 60 value 85.789512
iter 70 value 82.082680
iter 80 value 80.426251
iter 90 value 80.401224
iter 100 value 80.397024
final value 80.397024
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 114.401855
iter 10 value 89.683742
iter 20 value 85.220083
iter 30 value 81.346322
iter 40 value 80.932075
iter 50 value 80.843002
iter 60 value 80.593460
iter 70 value 80.541129
iter 80 value 80.483542
iter 90 value 80.459053
iter 100 value 80.455312
final value 80.455312
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.362209
iter 10 value 94.494443
iter 20 value 94.479491
iter 30 value 87.828224
iter 40 value 85.122364
iter 50 value 84.205791
iter 60 value 82.836997
iter 70 value 81.825047
iter 80 value 81.617299
iter 90 value 81.594763
iter 100 value 81.561080
final value 81.561080
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 97.413083
iter 10 value 90.099783
iter 20 value 89.864369
iter 30 value 89.863362
iter 40 value 88.917932
iter 50 value 88.909798
iter 60 value 88.908370
iter 70 value 88.908308
iter 80 value 88.745145
iter 90 value 85.090337
iter 100 value 81.774515
final value 81.774515
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.643280
iter 10 value 91.381353
iter 20 value 86.294589
iter 30 value 85.497630
iter 40 value 84.544810
iter 50 value 84.481631
iter 60 value 84.481228
iter 70 value 84.343209
iter 80 value 83.083670
iter 90 value 82.885589
iter 100 value 82.764273
final value 82.764273
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 96.843827
iter 10 value 94.487458
iter 20 value 94.157227
iter 30 value 86.728567
iter 40 value 84.524953
final value 84.522619
converged
Fitting Repeat 1
# weights: 103
initial value 101.340717
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 101.267883
iter 10 value 93.915938
final value 93.915746
converged
Fitting Repeat 3
# weights: 103
initial value 99.162857
final value 93.915746
converged
Fitting Repeat 4
# weights: 103
initial value 94.096489
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 110.322328
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 109.467397
final value 93.915746
converged
Fitting Repeat 2
# weights: 305
initial value 98.451391
iter 10 value 92.343311
iter 20 value 91.986319
iter 30 value 91.986053
final value 91.986050
converged
Fitting Repeat 3
# weights: 305
initial value 94.454507
iter 10 value 93.672973
iter 10 value 93.672973
iter 10 value 93.672973
final value 93.672973
converged
Fitting Repeat 4
# weights: 305
initial value 109.962209
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 95.870671
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 111.795758
iter 10 value 90.878640
iter 20 value 90.820582
final value 90.820513
converged
Fitting Repeat 2
# weights: 507
initial value 94.936393
final value 93.915746
converged
Fitting Repeat 3
# weights: 507
initial value 96.330650
iter 10 value 94.053756
final value 94.052909
converged
Fitting Repeat 4
# weights: 507
initial value 96.689350
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 99.439896
final value 93.915746
converged
Fitting Repeat 1
# weights: 103
initial value 109.450160
iter 10 value 93.979796
iter 20 value 93.614934
iter 30 value 91.583441
iter 40 value 91.210325
iter 50 value 91.098134
iter 60 value 85.664270
iter 70 value 85.077392
iter 80 value 82.797259
iter 90 value 82.612580
iter 100 value 82.224608
final value 82.224608
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 104.117236
iter 10 value 94.056957
iter 20 value 94.039388
iter 30 value 92.793338
iter 40 value 85.212240
iter 50 value 82.844095
iter 60 value 82.417507
iter 70 value 81.689100
iter 80 value 80.425205
iter 90 value 79.966892
iter 100 value 79.751177
final value 79.751177
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 101.912984
iter 10 value 94.052029
iter 20 value 93.846312
iter 30 value 93.726161
iter 40 value 85.203338
iter 50 value 82.427002
iter 60 value 82.382345
iter 70 value 82.228116
iter 80 value 81.748311
iter 90 value 80.797926
iter 100 value 80.271299
final value 80.271299
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 99.210720
iter 10 value 93.024583
iter 20 value 88.742890
iter 30 value 83.887276
iter 40 value 82.541990
iter 50 value 81.802798
iter 60 value 80.720330
iter 70 value 80.340302
final value 80.339175
converged
Fitting Repeat 5
# weights: 103
initial value 103.712546
iter 10 value 93.950288
iter 20 value 86.943170
iter 30 value 85.314853
iter 40 value 84.603691
iter 50 value 83.652106
iter 60 value 83.587023
iter 70 value 83.578445
final value 83.578264
converged
Fitting Repeat 1
# weights: 305
initial value 106.768891
iter 10 value 93.891339
iter 20 value 91.471859
iter 30 value 84.108144
iter 40 value 82.622368
iter 50 value 80.938826
iter 60 value 79.889862
iter 70 value 78.956030
iter 80 value 78.730408
iter 90 value 78.690896
iter 100 value 78.660097
final value 78.660097
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.256803
iter 10 value 93.899428
iter 20 value 85.306396
iter 30 value 84.264822
iter 40 value 82.721415
iter 50 value 82.329778
iter 60 value 81.561418
iter 70 value 81.291751
iter 80 value 81.073558
iter 90 value 81.048959
iter 100 value 80.945990
final value 80.945990
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 111.814050
iter 10 value 93.973004
iter 20 value 87.527936
iter 30 value 83.928474
iter 40 value 83.349642
iter 50 value 82.301583
iter 60 value 81.976275
iter 70 value 79.685014
iter 80 value 78.920292
iter 90 value 78.414554
iter 100 value 78.241588
final value 78.241588
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.906793
iter 10 value 93.960660
iter 20 value 88.311712
iter 30 value 83.267461
iter 40 value 82.366703
iter 50 value 81.998943
iter 60 value 80.657304
iter 70 value 80.039648
iter 80 value 79.535608
iter 90 value 79.400155
iter 100 value 78.939692
final value 78.939692
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.586620
iter 10 value 94.257571
iter 20 value 90.540770
iter 30 value 89.016364
iter 40 value 88.604503
iter 50 value 88.324184
iter 60 value 83.370646
iter 70 value 81.610899
iter 80 value 81.082557
iter 90 value 80.866652
iter 100 value 80.755780
final value 80.755780
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 141.176829
iter 10 value 97.003693
iter 20 value 86.087185
iter 30 value 82.922650
iter 40 value 82.535935
iter 50 value 80.636382
iter 60 value 79.181096
iter 70 value 78.690044
iter 80 value 78.667991
iter 90 value 78.661919
iter 100 value 78.624246
final value 78.624246
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 121.202259
iter 10 value 93.974911
iter 20 value 89.299621
iter 30 value 88.801924
iter 40 value 88.687874
iter 50 value 86.286131
iter 60 value 82.669747
iter 70 value 81.640501
iter 80 value 80.825635
iter 90 value 80.605901
iter 100 value 80.306238
final value 80.306238
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.525317
iter 10 value 87.288648
iter 20 value 84.939146
iter 30 value 81.682385
iter 40 value 81.054372
iter 50 value 80.599176
iter 60 value 80.293763
iter 70 value 80.129273
iter 80 value 79.980474
iter 90 value 79.744849
iter 100 value 79.428177
final value 79.428177
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 129.613882
iter 10 value 95.316727
iter 20 value 91.485409
iter 30 value 87.930252
iter 40 value 84.814320
iter 50 value 84.155589
iter 60 value 83.427054
iter 70 value 82.342780
iter 80 value 81.513183
iter 90 value 81.241899
iter 100 value 81.097807
final value 81.097807
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 116.128372
iter 10 value 94.101868
iter 20 value 86.458559
iter 30 value 85.783066
iter 40 value 85.128292
iter 50 value 82.674499
iter 60 value 79.881659
iter 70 value 79.334311
iter 80 value 79.198187
iter 90 value 78.845554
iter 100 value 78.676485
final value 78.676485
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.998179
final value 94.054501
converged
Fitting Repeat 2
# weights: 103
initial value 103.895490
final value 93.917377
converged
Fitting Repeat 3
# weights: 103
initial value 97.553259
final value 93.917169
converged
Fitting Repeat 4
# weights: 103
initial value 98.533063
final value 94.054277
converged
Fitting Repeat 5
# weights: 103
initial value 103.035541
final value 94.054421
converged
Fitting Repeat 1
# weights: 305
initial value 96.331341
iter 10 value 94.076678
iter 20 value 89.650271
iter 30 value 86.198549
iter 40 value 86.183398
iter 50 value 85.896620
iter 60 value 84.527516
iter 70 value 84.510920
iter 80 value 84.493766
iter 90 value 81.126089
iter 100 value 78.726012
final value 78.726012
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 133.343579
iter 10 value 94.057316
iter 20 value 94.052961
iter 30 value 86.915836
iter 40 value 86.180070
iter 50 value 86.179647
iter 60 value 84.789133
iter 70 value 84.777671
iter 80 value 84.772571
final value 84.772244
converged
Fitting Repeat 3
# weights: 305
initial value 97.422230
iter 10 value 89.178714
iter 20 value 83.566937
iter 30 value 83.547003
iter 40 value 83.545824
iter 50 value 83.422069
iter 60 value 81.423391
iter 70 value 81.413364
final value 81.413280
converged
Fitting Repeat 4
# weights: 305
initial value 104.770361
iter 10 value 94.057615
iter 20 value 93.855184
iter 30 value 93.492165
iter 40 value 93.464474
final value 93.464369
converged
Fitting Repeat 5
# weights: 305
initial value 104.852900
iter 10 value 94.057754
iter 20 value 94.053182
final value 94.052930
converged
Fitting Repeat 1
# weights: 507
initial value 97.209823
iter 10 value 94.058784
iter 20 value 94.040897
iter 30 value 93.858976
iter 40 value 91.762765
iter 50 value 90.780583
iter 60 value 88.148530
iter 70 value 87.998595
iter 80 value 87.950360
iter 90 value 87.228391
iter 100 value 81.980294
final value 81.980294
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 117.154214
iter 10 value 93.380604
iter 20 value 93.375606
iter 30 value 93.093675
iter 40 value 89.083961
iter 50 value 88.275067
iter 60 value 87.957280
final value 87.724509
converged
Fitting Repeat 3
# weights: 507
initial value 100.035187
iter 10 value 94.060915
iter 20 value 85.855938
final value 83.432819
converged
Fitting Repeat 4
# weights: 507
initial value 128.491541
iter 10 value 94.061234
iter 20 value 94.052600
iter 30 value 90.183268
iter 40 value 84.814044
iter 50 value 84.564354
iter 60 value 83.348448
iter 70 value 81.983097
iter 80 value 81.888340
iter 90 value 81.887889
iter 100 value 81.762952
final value 81.762952
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 108.832444
iter 10 value 94.061632
iter 20 value 94.056721
iter 30 value 93.988724
iter 40 value 93.922282
iter 50 value 93.918314
iter 60 value 93.826170
iter 70 value 93.495290
iter 80 value 91.311907
iter 90 value 87.203816
iter 100 value 87.186644
final value 87.186644
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.080552
iter 10 value 91.145880
iter 20 value 91.145741
final value 91.145730
converged
Fitting Repeat 2
# weights: 103
initial value 95.163641
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.374206
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.593590
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 97.097837
iter 10 value 92.732051
iter 20 value 92.731184
iter 20 value 92.731183
iter 20 value 92.731183
final value 92.731183
converged
Fitting Repeat 1
# weights: 305
initial value 109.968006
final value 94.483810
converged
Fitting Repeat 2
# weights: 305
initial value 103.867683
final value 93.300000
converged
Fitting Repeat 3
# weights: 305
initial value 104.595037
final value 93.299996
converged
Fitting Repeat 4
# weights: 305
initial value 102.638857
final value 94.484210
converged
Fitting Repeat 5
# weights: 305
initial value 95.702330
iter 10 value 92.747588
iter 20 value 92.731198
final value 92.731184
converged
Fitting Repeat 1
# weights: 507
initial value 131.869886
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 124.976693
iter 10 value 92.752750
iter 20 value 92.731202
final value 92.731183
converged
Fitting Repeat 3
# weights: 507
initial value 105.580127
iter 10 value 93.105535
iter 20 value 90.159135
iter 30 value 90.070607
iter 40 value 90.068048
final value 90.068030
converged
Fitting Repeat 4
# weights: 507
initial value 108.881092
iter 10 value 89.856641
iter 20 value 87.872797
final value 87.853335
converged
Fitting Repeat 5
# weights: 507
initial value 108.361820
iter 10 value 92.755414
iter 20 value 92.731204
final value 92.731183
converged
Fitting Repeat 1
# weights: 103
initial value 98.954197
iter 10 value 94.488546
iter 20 value 94.190393
iter 30 value 93.729812
iter 40 value 93.684383
iter 50 value 93.678059
iter 60 value 93.674558
iter 70 value 93.668382
iter 80 value 93.199872
iter 90 value 86.977753
iter 100 value 85.095606
final value 85.095606
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 102.889943
iter 10 value 94.468903
iter 20 value 93.873420
iter 30 value 93.517498
iter 40 value 93.230106
iter 50 value 87.684230
iter 60 value 83.449234
iter 70 value 82.920706
iter 80 value 82.565278
iter 90 value 82.534371
final value 82.533437
converged
Fitting Repeat 3
# weights: 103
initial value 104.801726
iter 10 value 94.408780
iter 20 value 92.725722
iter 30 value 88.294148
iter 40 value 84.921168
iter 50 value 84.704949
iter 60 value 83.430312
iter 70 value 82.462516
iter 80 value 82.285661
iter 90 value 82.269931
final value 82.269598
converged
Fitting Repeat 4
# weights: 103
initial value 96.794398
iter 10 value 94.479242
iter 20 value 85.543395
iter 30 value 84.114018
iter 40 value 83.607567
iter 50 value 83.380601
iter 60 value 82.626964
iter 70 value 82.293663
iter 80 value 82.269598
iter 80 value 82.269597
iter 80 value 82.269597
final value 82.269597
converged
Fitting Repeat 5
# weights: 103
initial value 97.513414
iter 10 value 94.446596
iter 20 value 84.978202
iter 30 value 82.300783
iter 40 value 82.190308
iter 50 value 81.528251
iter 60 value 80.782821
iter 70 value 80.365687
iter 80 value 80.033869
iter 90 value 79.937582
final value 79.937531
converged
Fitting Repeat 1
# weights: 305
initial value 114.576503
iter 10 value 94.439239
iter 20 value 87.796202
iter 30 value 86.382545
iter 40 value 82.209570
iter 50 value 81.499808
iter 60 value 80.371242
iter 70 value 79.149824
iter 80 value 78.929315
iter 90 value 78.530232
iter 100 value 78.376786
final value 78.376786
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.723722
iter 10 value 94.485699
iter 20 value 92.630924
iter 30 value 85.700462
iter 40 value 81.616466
iter 50 value 80.826786
iter 60 value 79.486944
iter 70 value 79.078636
iter 80 value 78.923179
iter 90 value 78.898669
iter 100 value 78.694990
final value 78.694990
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.000344
iter 10 value 93.266590
iter 20 value 93.082060
iter 30 value 89.459825
iter 40 value 85.897708
iter 50 value 85.051916
iter 60 value 83.655118
iter 70 value 82.592482
iter 80 value 82.388704
iter 90 value 82.327239
iter 100 value 81.205215
final value 81.205215
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 112.788548
iter 10 value 93.816519
iter 20 value 93.158124
iter 30 value 91.862775
iter 40 value 84.038026
iter 50 value 82.512030
iter 60 value 80.900439
iter 70 value 79.896069
iter 80 value 79.669309
iter 90 value 79.624774
iter 100 value 79.518104
final value 79.518104
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.112488
iter 10 value 93.242975
iter 20 value 92.051167
iter 30 value 84.191743
iter 40 value 81.483114
iter 50 value 80.968507
iter 60 value 80.139746
iter 70 value 79.727661
iter 80 value 79.486163
iter 90 value 79.282280
iter 100 value 79.144386
final value 79.144386
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.950839
iter 10 value 94.500675
iter 20 value 84.546124
iter 30 value 82.461186
iter 40 value 81.116056
iter 50 value 80.641460
iter 60 value 79.757533
iter 70 value 79.497870
iter 80 value 78.975280
iter 90 value 78.451764
iter 100 value 78.288851
final value 78.288851
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.015738
iter 10 value 94.871047
iter 20 value 93.092982
iter 30 value 86.058753
iter 40 value 84.929468
iter 50 value 81.260916
iter 60 value 79.769347
iter 70 value 79.089473
iter 80 value 78.699734
iter 90 value 78.591062
iter 100 value 78.563500
final value 78.563500
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.760186
iter 10 value 96.024350
iter 20 value 93.579515
iter 30 value 93.277311
iter 40 value 91.837310
iter 50 value 87.905805
iter 60 value 82.982841
iter 70 value 80.397818
iter 80 value 79.510310
iter 90 value 78.991637
iter 100 value 78.544177
final value 78.544177
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 136.560342
iter 10 value 100.318769
iter 20 value 94.605144
iter 30 value 91.200368
iter 40 value 85.176438
iter 50 value 83.219771
iter 60 value 81.368896
iter 70 value 80.846926
iter 80 value 80.605842
iter 90 value 80.349665
iter 100 value 80.043598
final value 80.043598
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 119.985689
iter 10 value 95.395189
iter 20 value 94.204578
iter 30 value 85.514812
iter 40 value 84.762999
iter 50 value 83.109961
iter 60 value 80.866359
iter 70 value 79.903175
iter 80 value 79.130736
iter 90 value 78.335263
iter 100 value 78.056836
final value 78.056836
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.447799
final value 94.486040
converged
Fitting Repeat 2
# weights: 103
initial value 97.214083
iter 10 value 92.687899
iter 20 value 92.495454
iter 30 value 92.495297
final value 92.493835
converged
Fitting Repeat 3
# weights: 103
initial value 94.672054
final value 94.486038
converged
Fitting Repeat 4
# weights: 103
initial value 97.462849
iter 10 value 94.485868
iter 20 value 94.484216
final value 94.484212
converged
Fitting Repeat 5
# weights: 103
initial value 95.313736
final value 94.485492
converged
Fitting Repeat 1
# weights: 305
initial value 100.514719
iter 10 value 93.880424
iter 20 value 93.876568
iter 30 value 92.861334
iter 40 value 92.739634
iter 50 value 92.716930
iter 60 value 83.341405
iter 70 value 83.043693
iter 80 value 83.042368
final value 83.042364
converged
Fitting Repeat 2
# weights: 305
initial value 106.519671
iter 10 value 94.489159
iter 20 value 94.412923
iter 30 value 92.742405
iter 40 value 92.739567
final value 92.739502
converged
Fitting Repeat 3
# weights: 305
initial value 115.883186
iter 10 value 92.771127
iter 20 value 92.743257
iter 30 value 92.738519
iter 40 value 92.325269
iter 50 value 90.310400
iter 60 value 82.001675
iter 70 value 80.984753
iter 80 value 80.967162
iter 90 value 80.946185
final value 80.945995
converged
Fitting Repeat 4
# weights: 305
initial value 105.269528
iter 10 value 92.748712
iter 20 value 92.742516
iter 30 value 83.631092
iter 40 value 82.147891
iter 50 value 82.104812
iter 60 value 82.101906
iter 70 value 81.406502
iter 80 value 81.400990
iter 90 value 81.294694
iter 100 value 81.212831
final value 81.212831
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.921122
iter 10 value 94.488941
iter 20 value 94.463720
iter 30 value 93.300629
final value 93.300593
converged
Fitting Repeat 1
# weights: 507
initial value 125.885689
iter 10 value 83.379555
iter 20 value 81.705996
iter 30 value 81.705049
iter 40 value 81.367152
iter 50 value 81.059196
iter 60 value 81.051369
iter 70 value 81.051122
iter 80 value 81.050536
iter 90 value 81.049593
iter 100 value 81.049336
final value 81.049336
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.839097
iter 10 value 94.113381
iter 10 value 94.113381
final value 94.113381
converged
Fitting Repeat 3
# weights: 507
initial value 107.744263
iter 10 value 94.492264
iter 20 value 94.325285
iter 30 value 84.870093
iter 40 value 82.566789
iter 50 value 78.048220
iter 60 value 77.552093
iter 70 value 77.528316
iter 80 value 77.470402
iter 90 value 77.207012
iter 100 value 77.054751
final value 77.054751
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.067461
iter 10 value 92.703821
iter 20 value 92.503468
iter 30 value 92.502289
iter 40 value 91.892510
iter 50 value 85.384260
iter 60 value 82.173112
iter 70 value 77.723981
iter 80 value 76.453587
iter 90 value 76.399879
iter 100 value 76.394853
final value 76.394853
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 138.779993
iter 10 value 92.768500
iter 20 value 92.651489
iter 30 value 92.484723
iter 40 value 92.214088
iter 50 value 92.211697
iter 60 value 92.208728
iter 70 value 92.208154
iter 80 value 90.421884
iter 90 value 84.922258
iter 100 value 77.893783
final value 77.893783
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 106.424939
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 95.831224
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 99.643104
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 94.322691
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 99.724029
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 115.127293
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 104.881595
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 112.918964
final value 93.962011
converged
Fitting Repeat 4
# weights: 305
initial value 95.999739
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 113.402378
iter 10 value 93.870537
final value 93.672973
converged
Fitting Repeat 1
# weights: 507
initial value 97.993767
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 98.620217
final value 94.038251
converged
Fitting Repeat 3
# weights: 507
initial value 97.814331
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 110.094099
final value 93.688926
converged
Fitting Repeat 5
# weights: 507
initial value 107.079393
final value 94.038251
converged
Fitting Repeat 1
# weights: 103
initial value 102.413279
iter 10 value 93.627466
iter 20 value 91.070386
iter 30 value 88.727167
iter 40 value 86.528070
iter 50 value 84.885812
iter 60 value 84.192716
iter 70 value 84.147893
iter 80 value 84.143433
final value 84.143426
converged
Fitting Repeat 2
# weights: 103
initial value 97.319013
iter 10 value 94.056666
iter 20 value 93.811185
iter 30 value 93.506296
iter 40 value 93.502197
iter 50 value 93.500515
iter 60 value 88.132969
iter 70 value 85.397044
iter 80 value 85.161499
iter 90 value 85.138328
iter 100 value 84.745006
final value 84.745006
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 99.377924
iter 10 value 94.056842
iter 20 value 94.042435
iter 30 value 89.945293
iter 40 value 87.800176
iter 50 value 86.791992
iter 60 value 84.047036
iter 70 value 82.865561
iter 80 value 82.609542
iter 90 value 82.311655
iter 100 value 82.108524
final value 82.108524
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 99.046680
iter 10 value 94.051051
iter 20 value 94.042806
iter 30 value 94.042095
iter 40 value 93.667140
iter 50 value 88.492331
iter 60 value 87.579264
iter 70 value 87.068634
iter 80 value 85.510913
iter 90 value 84.399103
iter 100 value 84.324204
final value 84.324204
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 97.193150
iter 10 value 94.057018
iter 20 value 93.934607
iter 30 value 89.203557
iter 40 value 87.027236
iter 50 value 84.077019
iter 60 value 83.476813
iter 70 value 82.874398
iter 80 value 82.493072
iter 90 value 82.184850
iter 100 value 82.115101
final value 82.115101
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.362455
iter 10 value 94.264346
iter 20 value 94.073402
iter 30 value 94.032021
iter 40 value 93.385169
iter 50 value 88.386276
iter 60 value 87.456082
iter 70 value 84.927234
iter 80 value 83.051093
iter 90 value 82.236219
iter 100 value 82.138759
final value 82.138759
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 112.615942
iter 10 value 93.471825
iter 20 value 87.119300
iter 30 value 86.403256
iter 40 value 85.074017
iter 50 value 84.532977
iter 60 value 84.056002
iter 70 value 83.836609
iter 80 value 83.705240
iter 90 value 83.613226
iter 100 value 83.369906
final value 83.369906
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.621754
iter 10 value 94.382035
iter 20 value 93.940274
iter 30 value 88.575910
iter 40 value 87.790319
iter 50 value 87.504291
iter 60 value 86.903390
iter 70 value 86.859064
iter 80 value 86.414597
iter 90 value 82.412075
iter 100 value 81.768722
final value 81.768722
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.597272
iter 10 value 93.949387
iter 20 value 86.882585
iter 30 value 84.764365
iter 40 value 83.911950
iter 50 value 83.368634
iter 60 value 82.255138
iter 70 value 81.914689
iter 80 value 81.791317
iter 90 value 81.504123
iter 100 value 81.125069
final value 81.125069
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.527790
iter 10 value 92.860749
iter 20 value 91.514579
iter 30 value 90.156376
iter 40 value 88.298449
iter 50 value 87.496165
iter 60 value 87.253363
iter 70 value 84.633871
iter 80 value 83.207012
iter 90 value 82.481218
iter 100 value 82.221833
final value 82.221833
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 119.670684
iter 10 value 94.168237
iter 20 value 93.673577
iter 30 value 92.431703
iter 40 value 87.167602
iter 50 value 86.703317
iter 60 value 86.137236
iter 70 value 83.708786
iter 80 value 82.701282
iter 90 value 81.883718
iter 100 value 81.156463
final value 81.156463
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.921919
iter 10 value 95.185347
iter 20 value 94.104972
iter 30 value 88.763955
iter 40 value 88.058680
iter 50 value 87.431725
iter 60 value 84.609816
iter 70 value 83.293409
iter 80 value 82.700459
iter 90 value 82.362329
iter 100 value 82.252369
final value 82.252369
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 134.964397
iter 10 value 94.115818
iter 20 value 88.675667
iter 30 value 87.036037
iter 40 value 86.816906
iter 50 value 85.803709
iter 60 value 84.106135
iter 70 value 83.609912
iter 80 value 83.446591
iter 90 value 82.896507
iter 100 value 82.334849
final value 82.334849
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.028887
iter 10 value 93.923620
iter 20 value 86.628615
iter 30 value 85.430087
iter 40 value 83.201428
iter 50 value 82.755659
iter 60 value 82.362738
iter 70 value 81.694603
iter 80 value 80.888211
iter 90 value 80.752386
iter 100 value 80.619059
final value 80.619059
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.432557
iter 10 value 94.222135
iter 20 value 92.735110
iter 30 value 85.550735
iter 40 value 85.165961
iter 50 value 83.318607
iter 60 value 82.026516
iter 70 value 81.541273
iter 80 value 81.271118
iter 90 value 80.730642
iter 100 value 80.591975
final value 80.591975
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.423502
iter 10 value 94.104161
iter 20 value 94.096988
iter 30 value 94.057269
final value 94.052914
converged
Fitting Repeat 2
# weights: 103
initial value 99.677242
final value 94.039941
converged
Fitting Repeat 3
# weights: 103
initial value 97.580789
iter 10 value 94.091144
iter 20 value 94.087728
iter 30 value 94.054289
final value 94.052917
converged
Fitting Repeat 4
# weights: 103
initial value 119.726968
final value 94.039729
converged
Fitting Repeat 5
# weights: 103
initial value 94.266154
final value 94.054456
converged
Fitting Repeat 1
# weights: 305
initial value 97.384309
iter 10 value 94.057748
iter 20 value 94.005543
iter 30 value 93.603056
iter 40 value 85.993066
iter 50 value 83.340112
iter 60 value 83.337241
final value 83.337239
converged
Fitting Repeat 2
# weights: 305
initial value 107.609629
iter 10 value 94.042532
iter 20 value 94.038589
final value 94.038583
converged
Fitting Repeat 3
# weights: 305
initial value 95.133833
iter 10 value 90.888808
iter 20 value 85.639968
iter 30 value 85.552946
iter 40 value 85.552581
iter 50 value 85.549705
iter 60 value 85.512401
iter 70 value 85.149663
iter 80 value 85.104742
iter 90 value 85.104480
iter 100 value 85.104362
final value 85.104362
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 121.687287
iter 10 value 94.055655
iter 20 value 93.882427
final value 93.542931
converged
Fitting Repeat 5
# weights: 305
initial value 100.801347
iter 10 value 85.587664
iter 20 value 82.953947
iter 30 value 82.349906
iter 40 value 82.149599
iter 50 value 82.147729
iter 60 value 82.082775
iter 70 value 81.640603
iter 80 value 81.524120
iter 90 value 81.516851
iter 100 value 81.468497
final value 81.468497
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.068368
iter 10 value 94.046343
iter 20 value 93.909000
iter 30 value 85.498403
iter 40 value 83.789589
iter 50 value 83.499886
iter 60 value 83.497311
final value 83.497200
converged
Fitting Repeat 2
# weights: 507
initial value 101.061028
iter 10 value 94.046536
iter 20 value 94.038302
iter 30 value 92.127260
iter 40 value 84.877700
iter 50 value 84.341769
iter 60 value 84.330934
final value 84.330865
converged
Fitting Repeat 3
# weights: 507
initial value 102.037381
iter 10 value 93.531154
iter 20 value 91.926100
iter 30 value 91.672039
iter 40 value 82.647970
iter 50 value 82.218711
iter 60 value 82.213970
iter 70 value 82.086171
iter 80 value 81.015248
iter 90 value 80.444838
iter 100 value 80.399074
final value 80.399074
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 97.021983
iter 10 value 93.710480
iter 20 value 93.697052
iter 30 value 93.690237
iter 40 value 93.588762
iter 50 value 85.556907
iter 60 value 85.055203
iter 70 value 84.613689
iter 80 value 84.517909
iter 90 value 81.731510
iter 100 value 80.642917
final value 80.642917
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.253661
iter 10 value 94.060617
iter 20 value 92.479204
iter 30 value 89.550040
iter 40 value 86.230968
iter 50 value 85.857069
iter 60 value 84.513934
iter 70 value 84.484924
iter 80 value 82.879486
iter 90 value 82.467563
iter 100 value 81.551569
final value 81.551569
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 119.910590
iter 10 value 117.767359
iter 20 value 117.732829
final value 117.728758
converged
Fitting Repeat 2
# weights: 507
initial value 131.373200
iter 10 value 117.898357
iter 20 value 117.778966
iter 30 value 117.735952
final value 117.729881
converged
Fitting Repeat 3
# weights: 507
initial value 121.001325
iter 10 value 117.525669
iter 20 value 117.506452
iter 30 value 117.503966
iter 40 value 117.463199
iter 50 value 117.460032
iter 60 value 115.928555
iter 70 value 109.546454
iter 80 value 106.782382
iter 90 value 106.761268
iter 100 value 106.756083
final value 106.756083
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 126.155095
final value 117.898615
converged
Fitting Repeat 5
# weights: 507
initial value 145.235250
iter 10 value 117.903892
iter 20 value 117.891477
iter 30 value 116.169314
iter 40 value 107.414732
iter 50 value 105.755534
iter 60 value 104.127518
iter 70 value 103.337852
iter 80 value 103.331324
iter 90 value 103.327955
final value 103.326219
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 -- Thu Feb 6 02:36:53 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
43.85 1.45 141.35
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 35.16 | 1.89 | 37.07 | |
| FreqInteractors | 0.31 | 0.00 | 0.34 | |
| calculateAAC | 0.05 | 0.02 | 0.06 | |
| calculateAutocor | 0.50 | 0.10 | 0.61 | |
| calculateCTDC | 0.09 | 0.02 | 0.11 | |
| calculateCTDD | 0.80 | 0.08 | 0.89 | |
| calculateCTDT | 0.33 | 0.01 | 0.34 | |
| calculateCTriad | 0.40 | 0.00 | 0.41 | |
| calculateDC | 0.13 | 0.02 | 0.14 | |
| calculateF | 0.36 | 0.06 | 0.42 | |
| calculateKSAAP | 0.15 | 0.00 | 0.16 | |
| calculateQD_Sm | 2.44 | 0.24 | 2.67 | |
| calculateTC | 1.75 | 0.12 | 1.89 | |
| calculateTC_Sm | 0.28 | 0.02 | 0.30 | |
| corr_plot | 34.47 | 1.53 | 36.04 | |
| enrichfindP | 0.78 | 0.09 | 12.74 | |
| enrichfind_hp | 0.08 | 0.02 | 1.11 | |
| enrichplot | 0.36 | 0.01 | 0.37 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.03 | 0.00 | 2.35 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.09 | 0.02 | 0.10 | |
| pred_ensembel | 13.24 | 0.33 | 12.07 | |
| var_imp | 33.94 | 0.98 | 34.93 | |