Matineh Rahmatbakhsh
| Snapshot Date: 2025-03-23 13:40 -0400 (Sun, 23 Mar 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 -0400 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-03-24 11:42 -0400 (Mon, 24 Mar 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2025-03-13 r87965) -- "Unsuffered Consequences" | 4779 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2025-03-01 r87860 ucrt) -- "Unsuffered Consequences" | 4550 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4578 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4530 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4461 |
| 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 989/2313 | 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 | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.13.0 |
| 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: 2025-03-24 02:23:44 -0400 (Mon, 24 Mar 2025) |
| EndedAt: 2025-03-24 02:30:18 -0400 (Mon, 24 Mar 2025) |
| EllapsedTime: 394.4 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) (2025-03-01 r87860 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 35.12 1.70 37.06
var_imp 35.41 1.09 36.51
corr_plot 33.13 1.66 34.81
pred_ensembel 13.42 0.30 12.41
enrichfindP 0.55 0.20 14.60
* 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) (2025-03-01 r87860 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 95.121130
final value 93.922222
converged
Fitting Repeat 2
# weights: 103
initial value 96.760952
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.320456
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 108.584083
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 97.408799
final value 94.275362
converged
Fitting Repeat 1
# weights: 305
initial value 102.926767
iter 10 value 94.371902
iter 20 value 87.842785
iter 30 value 84.901741
iter 40 value 84.845436
final value 84.842568
converged
Fitting Repeat 2
# weights: 305
initial value 102.695309
iter 10 value 94.458391
final value 94.457914
converged
Fitting Repeat 3
# weights: 305
initial value 98.188675
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 108.559687
iter 10 value 90.384232
iter 20 value 89.271983
iter 30 value 88.419121
iter 40 value 88.419075
iter 50 value 87.313169
final value 87.308431
converged
Fitting Repeat 5
# weights: 305
initial value 95.882369
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 108.944728
iter 10 value 94.483183
final value 94.448053
converged
Fitting Repeat 2
# weights: 507
initial value 108.398440
iter 10 value 94.484221
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 103.849650
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 101.040314
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 101.355692
iter 10 value 94.285114
final value 94.275362
converged
Fitting Repeat 1
# weights: 103
initial value 105.791166
iter 10 value 94.488473
iter 20 value 93.520197
iter 30 value 87.973094
iter 40 value 84.088241
iter 50 value 83.313237
iter 60 value 82.478741
iter 70 value 82.116197
iter 80 value 82.016901
iter 90 value 81.992166
iter 100 value 81.990337
final value 81.990337
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 99.485766
iter 10 value 94.489301
iter 20 value 93.408443
iter 30 value 86.026997
iter 40 value 85.395480
iter 50 value 85.217855
iter 60 value 84.829478
iter 70 value 84.553858
iter 80 value 82.950722
iter 90 value 82.439025
iter 100 value 82.315786
final value 82.315786
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.445627
iter 10 value 88.549680
iter 20 value 84.371567
iter 30 value 83.625818
iter 40 value 83.375286
iter 50 value 82.795194
iter 60 value 82.401685
iter 70 value 82.290430
iter 80 value 82.237642
final value 82.235217
converged
Fitting Repeat 4
# weights: 103
initial value 106.086033
iter 10 value 94.455435
iter 20 value 94.095308
iter 30 value 93.963591
iter 40 value 86.835488
iter 50 value 84.186142
iter 60 value 83.452255
iter 70 value 83.355294
iter 80 value 82.328222
iter 90 value 82.237389
final value 82.235217
converged
Fitting Repeat 5
# weights: 103
initial value 103.888803
iter 10 value 94.488526
iter 20 value 94.378184
iter 30 value 94.333748
iter 40 value 94.329406
iter 50 value 94.066200
iter 60 value 94.017705
iter 70 value 90.845299
iter 80 value 88.662941
iter 90 value 86.525374
iter 100 value 83.383594
final value 83.383594
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.481135
iter 10 value 94.129264
iter 20 value 93.974777
iter 30 value 87.556863
iter 40 value 86.589425
iter 50 value 84.933413
iter 60 value 84.557470
iter 70 value 84.269891
iter 80 value 82.946316
iter 90 value 82.334932
iter 100 value 81.758516
final value 81.758516
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.809940
iter 10 value 94.522087
iter 20 value 93.274336
iter 30 value 86.532797
iter 40 value 84.844625
iter 50 value 84.300647
iter 60 value 84.260256
iter 70 value 83.984058
iter 80 value 83.024151
iter 90 value 82.776241
iter 100 value 82.631018
final value 82.631018
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 118.561786
iter 10 value 95.959742
iter 20 value 94.491359
iter 30 value 94.232898
iter 40 value 84.780648
iter 50 value 83.974837
iter 60 value 83.357541
iter 70 value 83.037914
iter 80 value 82.603607
iter 90 value 82.456735
iter 100 value 82.191462
final value 82.191462
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 114.533332
iter 10 value 90.558400
iter 20 value 87.298723
iter 30 value 86.154228
iter 40 value 83.564226
iter 50 value 82.848754
iter 60 value 82.531194
iter 70 value 82.060919
iter 80 value 81.735929
iter 90 value 81.436200
iter 100 value 81.342537
final value 81.342537
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.646632
iter 10 value 94.570106
iter 20 value 90.029685
iter 30 value 85.570899
iter 40 value 85.153156
iter 50 value 85.045503
iter 60 value 84.928469
iter 70 value 83.222361
iter 80 value 81.777341
iter 90 value 81.475439
iter 100 value 81.210769
final value 81.210769
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.224120
iter 10 value 94.361237
iter 20 value 91.809608
iter 30 value 83.559705
iter 40 value 83.075938
iter 50 value 82.942808
iter 60 value 82.479662
iter 70 value 82.116144
iter 80 value 81.817768
iter 90 value 81.729305
iter 100 value 81.559630
final value 81.559630
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 112.721094
iter 10 value 92.670902
iter 20 value 87.598739
iter 30 value 85.544876
iter 40 value 83.737859
iter 50 value 81.989372
iter 60 value 81.808624
iter 70 value 81.690103
iter 80 value 81.577803
iter 90 value 81.410824
iter 100 value 81.130329
final value 81.130329
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.923528
iter 10 value 94.632648
iter 20 value 94.355428
iter 30 value 92.812096
iter 40 value 89.890191
iter 50 value 86.443630
iter 60 value 86.130599
iter 70 value 85.370558
iter 80 value 84.036024
iter 90 value 83.271572
iter 100 value 81.682537
final value 81.682537
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.324100
iter 10 value 94.730061
iter 20 value 86.442092
iter 30 value 84.030139
iter 40 value 83.210149
iter 50 value 82.901581
iter 60 value 82.656543
iter 70 value 82.471400
iter 80 value 82.389521
iter 90 value 82.282585
iter 100 value 81.894683
final value 81.894683
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.643477
iter 10 value 94.540516
iter 20 value 93.737590
iter 30 value 91.797458
iter 40 value 86.197646
iter 50 value 83.656590
iter 60 value 82.985557
iter 70 value 82.538847
iter 80 value 82.471494
iter 90 value 82.427155
iter 100 value 82.337420
final value 82.337420
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.231665
iter 10 value 92.106447
iter 20 value 91.726825
iter 30 value 91.724263
iter 40 value 91.724094
iter 50 value 91.723356
iter 60 value 91.721027
iter 70 value 91.400423
final value 91.383374
converged
Fitting Repeat 2
# weights: 103
initial value 96.919984
iter 10 value 94.479799
iter 20 value 94.452628
final value 94.276850
converged
Fitting Repeat 3
# weights: 103
initial value 99.507396
iter 10 value 94.485713
iter 20 value 94.484217
final value 94.484215
converged
Fitting Repeat 4
# weights: 103
initial value 96.544601
final value 94.485922
converged
Fitting Repeat 5
# weights: 103
initial value 105.457567
iter 10 value 94.485901
iter 20 value 92.856345
iter 30 value 85.672381
iter 40 value 85.216067
iter 50 value 85.211244
iter 60 value 85.210745
final value 85.209951
converged
Fitting Repeat 1
# weights: 305
initial value 112.164490
iter 10 value 94.489766
iter 20 value 94.485060
iter 20 value 94.485059
iter 20 value 94.485059
final value 94.485059
converged
Fitting Repeat 2
# weights: 305
initial value 94.996447
iter 10 value 93.893645
iter 20 value 93.892743
iter 30 value 93.834245
iter 40 value 93.831418
final value 93.831416
converged
Fitting Repeat 3
# weights: 305
initial value 101.230909
iter 10 value 94.489511
iter 20 value 94.484632
iter 30 value 93.466820
iter 40 value 93.427204
iter 50 value 92.334636
iter 60 value 90.660454
iter 70 value 89.022783
iter 80 value 85.016044
iter 90 value 85.014394
iter 100 value 83.256846
final value 83.256846
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 118.342363
iter 10 value 92.707749
iter 20 value 91.017479
iter 30 value 90.602675
iter 40 value 90.598253
iter 50 value 90.566803
iter 60 value 90.537625
iter 70 value 90.535206
iter 80 value 86.883082
iter 90 value 85.861984
iter 100 value 85.790020
final value 85.790020
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.515235
iter 10 value 94.489379
iter 20 value 94.484249
iter 30 value 94.280724
iter 40 value 89.033956
iter 50 value 87.884283
iter 60 value 86.810730
iter 70 value 84.535335
iter 80 value 84.365169
final value 84.347719
converged
Fitting Repeat 1
# weights: 507
initial value 120.103801
iter 10 value 94.211354
iter 20 value 94.121569
iter 30 value 94.116953
iter 40 value 93.925921
iter 50 value 93.866855
iter 60 value 93.865915
iter 70 value 86.801817
iter 80 value 83.811809
iter 90 value 82.969047
iter 100 value 82.851411
final value 82.851411
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 101.008219
iter 10 value 94.042471
iter 20 value 94.040543
iter 30 value 94.034359
final value 94.034310
converged
Fitting Repeat 3
# weights: 507
initial value 102.798230
iter 10 value 94.495828
iter 20 value 94.462468
iter 30 value 86.002812
iter 40 value 85.686926
iter 50 value 84.165873
iter 60 value 83.671866
iter 70 value 83.671399
iter 80 value 83.668816
final value 83.668141
converged
Fitting Repeat 4
# weights: 507
initial value 103.339437
iter 10 value 94.121725
iter 20 value 94.106699
iter 30 value 93.885931
iter 40 value 93.867479
iter 50 value 93.708059
iter 60 value 84.632411
iter 70 value 83.847257
iter 80 value 83.621777
iter 90 value 81.880345
iter 100 value 80.564566
final value 80.564566
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 98.855153
iter 10 value 91.347301
iter 20 value 84.805076
iter 30 value 84.783902
iter 40 value 84.780640
iter 50 value 84.776176
iter 60 value 83.106391
iter 70 value 80.968554
iter 80 value 80.897189
iter 90 value 80.792498
iter 100 value 80.789441
final value 80.789441
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 111.503506
final value 94.026542
converged
Fitting Repeat 2
# weights: 103
initial value 101.246971
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 99.443145
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 99.498237
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 100.682575
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 95.275337
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 95.665010
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 103.813462
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 110.588250
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 98.770229
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 105.206350
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 105.888412
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 97.604464
iter 10 value 86.054862
iter 20 value 82.833801
final value 82.824676
converged
Fitting Repeat 4
# weights: 507
initial value 105.102485
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 100.858628
iter 10 value 94.026543
iter 10 value 94.026542
iter 10 value 94.026542
final value 94.026542
converged
Fitting Repeat 1
# weights: 103
initial value 97.840588
iter 10 value 94.493304
iter 20 value 92.931351
iter 30 value 88.943257
iter 40 value 87.398152
iter 50 value 86.851433
iter 60 value 86.752886
iter 70 value 86.640981
iter 80 value 86.483395
final value 86.483390
converged
Fitting Repeat 2
# weights: 103
initial value 97.268347
iter 10 value 92.699326
iter 20 value 87.678702
iter 30 value 85.585726
iter 40 value 84.420967
iter 50 value 84.111439
iter 60 value 83.981051
iter 70 value 83.973340
final value 83.973337
converged
Fitting Repeat 3
# weights: 103
initial value 118.801185
iter 10 value 94.489654
iter 20 value 93.781923
iter 30 value 92.812961
iter 40 value 92.568385
iter 50 value 84.172308
iter 60 value 84.064198
iter 70 value 84.030295
iter 80 value 83.977577
final value 83.977459
converged
Fitting Repeat 4
# weights: 103
initial value 106.592150
iter 10 value 94.492430
iter 20 value 94.428345
iter 30 value 94.128493
iter 40 value 94.052626
iter 50 value 90.110808
iter 60 value 85.716698
iter 70 value 84.398380
iter 80 value 83.837447
iter 90 value 83.372936
iter 100 value 83.117562
final value 83.117562
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 103.229265
iter 10 value 94.502630
iter 20 value 94.487823
iter 30 value 94.129808
iter 40 value 94.087849
iter 50 value 93.949223
iter 60 value 92.302738
iter 70 value 89.982121
iter 80 value 89.803896
iter 90 value 89.739104
iter 100 value 86.663944
final value 86.663944
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 111.201512
iter 10 value 94.545066
iter 20 value 93.317650
iter 30 value 92.242475
iter 40 value 92.063252
iter 50 value 90.348148
iter 60 value 84.458900
iter 70 value 82.542563
iter 80 value 81.916832
iter 90 value 81.548365
iter 100 value 81.445202
final value 81.445202
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.792115
iter 10 value 89.738568
iter 20 value 84.707133
iter 30 value 83.605640
iter 40 value 81.950550
iter 50 value 81.134937
iter 60 value 80.957399
iter 70 value 80.909819
iter 80 value 80.907589
iter 90 value 80.906330
iter 100 value 80.905898
final value 80.905898
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.441206
iter 10 value 94.513950
iter 20 value 85.604417
iter 30 value 85.251884
iter 40 value 84.917290
iter 50 value 84.235049
iter 60 value 84.051428
iter 70 value 83.814035
iter 80 value 83.742475
iter 90 value 83.708214
iter 100 value 83.678300
final value 83.678300
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.578073
iter 10 value 93.773133
iter 20 value 86.647629
iter 30 value 84.541440
iter 40 value 83.826370
iter 50 value 83.204278
iter 60 value 82.793858
iter 70 value 82.749655
iter 80 value 82.718740
iter 90 value 82.389427
iter 100 value 81.705557
final value 81.705557
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.838878
iter 10 value 94.903629
iter 20 value 94.250333
iter 30 value 86.934980
iter 40 value 85.534987
iter 50 value 85.461109
iter 60 value 84.804105
iter 70 value 83.371872
iter 80 value 81.546305
iter 90 value 81.333082
iter 100 value 81.243184
final value 81.243184
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 126.096516
iter 10 value 94.149509
iter 20 value 93.743687
iter 30 value 91.800675
iter 40 value 89.765176
iter 50 value 87.157233
iter 60 value 84.198965
iter 70 value 83.325369
iter 80 value 82.091427
iter 90 value 81.629912
iter 100 value 81.564342
final value 81.564342
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.423476
iter 10 value 94.588151
iter 20 value 90.686747
iter 30 value 86.903118
iter 40 value 86.279856
iter 50 value 83.886439
iter 60 value 81.755802
iter 70 value 81.387630
iter 80 value 81.312940
iter 90 value 81.208642
iter 100 value 81.142458
final value 81.142458
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 122.018553
iter 10 value 91.039951
iter 20 value 85.100808
iter 30 value 84.021708
iter 40 value 83.790852
iter 50 value 83.076649
iter 60 value 81.665907
iter 70 value 81.242626
iter 80 value 81.083180
iter 90 value 80.942322
iter 100 value 80.893106
final value 80.893106
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 115.519284
iter 10 value 93.607541
iter 20 value 88.344298
iter 30 value 85.584295
iter 40 value 85.405079
iter 50 value 85.040779
iter 60 value 84.702206
iter 70 value 84.502979
iter 80 value 84.133231
iter 90 value 83.327486
iter 100 value 81.390971
final value 81.390971
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 133.135939
iter 10 value 95.063372
iter 20 value 94.307073
iter 30 value 92.199445
iter 40 value 90.046547
iter 50 value 85.302590
iter 60 value 83.782167
iter 70 value 83.484985
iter 80 value 83.260158
iter 90 value 83.217050
iter 100 value 82.920509
final value 82.920509
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.051779
final value 94.485993
converged
Fitting Repeat 2
# weights: 103
initial value 95.322955
final value 94.485635
converged
Fitting Repeat 3
# weights: 103
initial value 97.754495
final value 94.493104
converged
Fitting Repeat 4
# weights: 103
initial value 94.950653
final value 94.485989
converged
Fitting Repeat 5
# weights: 103
initial value 95.320849
final value 94.485883
converged
Fitting Repeat 1
# weights: 305
initial value 94.621748
iter 10 value 94.478026
iter 20 value 94.475440
iter 30 value 94.473790
final value 94.473744
converged
Fitting Repeat 2
# weights: 305
initial value 102.645767
iter 10 value 94.488815
iter 20 value 94.482427
iter 30 value 94.027218
final value 94.027143
converged
Fitting Repeat 3
# weights: 305
initial value 100.370164
iter 10 value 94.416870
iter 20 value 94.303583
iter 30 value 94.298926
iter 40 value 94.297713
iter 50 value 94.294797
iter 60 value 94.283120
final value 94.262739
converged
Fitting Repeat 4
# weights: 305
initial value 105.999303
iter 10 value 94.488973
iter 20 value 94.484378
iter 30 value 89.272295
iter 40 value 89.261784
iter 50 value 89.259284
iter 60 value 89.258445
final value 89.258062
converged
Fitting Repeat 5
# weights: 305
initial value 96.965709
iter 10 value 94.031742
iter 20 value 93.838235
iter 30 value 87.117329
iter 40 value 86.698500
final value 86.697215
converged
Fitting Repeat 1
# weights: 507
initial value 120.576629
iter 10 value 94.470005
iter 20 value 93.655347
iter 30 value 91.896389
iter 40 value 91.856316
final value 91.856219
converged
Fitting Repeat 2
# weights: 507
initial value 105.542227
iter 10 value 94.491974
iter 20 value 94.440596
iter 30 value 92.428160
iter 40 value 88.279155
iter 50 value 88.144010
final value 88.140742
converged
Fitting Repeat 3
# weights: 507
initial value 106.863737
iter 10 value 94.330615
iter 20 value 94.329525
iter 30 value 94.324167
iter 40 value 93.961044
iter 50 value 93.858161
iter 60 value 93.844423
iter 70 value 87.740499
iter 80 value 87.736350
iter 90 value 87.725120
iter 100 value 86.785810
final value 86.785810
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 94.939395
iter 10 value 94.492563
iter 20 value 94.478376
final value 94.253142
converged
Fitting Repeat 5
# weights: 507
initial value 95.761172
iter 10 value 94.489304
iter 20 value 94.484242
final value 94.484234
converged
Fitting Repeat 1
# weights: 103
initial value 103.365608
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 101.796709
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 111.834495
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 97.395269
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 105.552471
final value 94.032967
converged
Fitting Repeat 1
# weights: 305
initial value 95.705695
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 97.456813
final value 94.032967
converged
Fitting Repeat 3
# weights: 305
initial value 116.396541
iter 10 value 93.455031
final value 93.455030
converged
Fitting Repeat 4
# weights: 305
initial value 103.476013
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 102.430724
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 104.209395
final value 94.032967
converged
Fitting Repeat 2
# weights: 507
initial value 99.290532
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 102.082379
final value 94.032967
converged
Fitting Repeat 4
# weights: 507
initial value 95.908277
final value 94.032967
converged
Fitting Repeat 5
# weights: 507
initial value 111.948707
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 98.918650
iter 10 value 94.057571
iter 20 value 93.910330
iter 30 value 93.322434
iter 40 value 93.220094
iter 50 value 93.130495
iter 60 value 89.314259
iter 70 value 85.286899
iter 80 value 83.270292
iter 90 value 82.489149
iter 100 value 82.451562
final value 82.451562
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 99.250478
iter 10 value 94.053453
iter 20 value 91.432533
iter 30 value 85.283076
iter 40 value 83.433214
iter 50 value 81.310004
iter 60 value 81.042604
iter 70 value 80.783977
final value 80.782446
converged
Fitting Repeat 3
# weights: 103
initial value 101.681900
iter 10 value 94.054242
iter 20 value 93.642279
iter 30 value 93.531963
iter 40 value 93.214868
iter 50 value 83.927468
iter 60 value 82.740688
iter 70 value 81.314131
iter 80 value 80.702747
iter 90 value 80.695731
final value 80.693330
converged
Fitting Repeat 4
# weights: 103
initial value 102.357571
iter 10 value 94.056468
iter 20 value 94.055238
iter 30 value 87.962647
iter 40 value 85.697854
iter 50 value 84.257503
iter 60 value 81.868346
iter 70 value 80.585929
iter 80 value 80.204563
iter 90 value 80.193486
final value 80.193446
converged
Fitting Repeat 5
# weights: 103
initial value 96.526846
iter 10 value 94.073650
iter 20 value 94.050774
iter 30 value 93.540570
iter 40 value 93.491482
iter 50 value 89.154464
iter 60 value 86.071614
iter 70 value 85.962452
iter 80 value 85.766881
iter 90 value 85.352955
iter 100 value 84.729582
final value 84.729582
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.597554
iter 10 value 94.190170
iter 20 value 93.536344
iter 30 value 89.999363
iter 40 value 86.328077
iter 50 value 84.131445
iter 60 value 82.235883
iter 70 value 80.979434
iter 80 value 80.738789
iter 90 value 80.642342
iter 100 value 80.608238
final value 80.608238
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.534554
iter 10 value 94.200570
iter 20 value 94.018850
iter 30 value 93.507083
iter 40 value 89.054080
iter 50 value 82.498908
iter 60 value 80.653049
iter 70 value 79.945996
iter 80 value 79.712956
iter 90 value 79.463184
iter 100 value 79.314397
final value 79.314397
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 118.524392
iter 10 value 94.055267
iter 20 value 93.270400
iter 30 value 83.684064
iter 40 value 82.914930
iter 50 value 82.143267
iter 60 value 82.085136
iter 70 value 81.939675
iter 80 value 81.852545
iter 90 value 80.984740
iter 100 value 80.191481
final value 80.191481
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 118.587775
iter 10 value 103.606785
iter 20 value 94.094417
iter 30 value 94.037676
iter 40 value 88.269203
iter 50 value 86.099578
iter 60 value 83.543224
iter 70 value 83.080043
iter 80 value 82.767807
iter 90 value 82.700595
iter 100 value 82.604815
final value 82.604815
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 111.942889
iter 10 value 95.005074
iter 20 value 88.166488
iter 30 value 84.221030
iter 40 value 82.933964
iter 50 value 82.741099
iter 60 value 82.530485
iter 70 value 81.144609
iter 80 value 80.718747
iter 90 value 80.374644
iter 100 value 80.214382
final value 80.214382
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 118.568169
iter 10 value 94.184623
iter 20 value 93.605289
iter 30 value 93.293495
iter 40 value 86.856766
iter 50 value 85.261782
iter 60 value 82.976965
iter 70 value 81.933582
iter 80 value 81.647168
iter 90 value 81.374055
iter 100 value 79.592752
final value 79.592752
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.562833
iter 10 value 94.276178
iter 20 value 91.879072
iter 30 value 89.950465
iter 40 value 86.610702
iter 50 value 83.289869
iter 60 value 81.606008
iter 70 value 80.251317
iter 80 value 79.794526
iter 90 value 79.388111
iter 100 value 79.213939
final value 79.213939
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.177063
iter 10 value 97.390098
iter 20 value 89.504805
iter 30 value 84.591271
iter 40 value 83.923116
iter 50 value 82.787837
iter 60 value 82.722878
iter 70 value 82.299546
iter 80 value 81.452724
iter 90 value 79.493772
iter 100 value 79.251393
final value 79.251393
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.006171
iter 10 value 94.857339
iter 20 value 94.130837
iter 30 value 93.708000
iter 40 value 88.639152
iter 50 value 83.657332
iter 60 value 83.012221
iter 70 value 81.596832
iter 80 value 80.223343
iter 90 value 79.841383
iter 100 value 79.517139
final value 79.517139
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.715636
iter 10 value 92.991656
iter 20 value 87.228097
iter 30 value 86.738512
iter 40 value 85.541577
iter 50 value 84.197756
iter 60 value 82.534497
iter 70 value 80.662112
iter 80 value 79.051764
iter 90 value 78.619688
iter 100 value 78.452344
final value 78.452344
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.046697
final value 94.054639
converged
Fitting Repeat 2
# weights: 103
initial value 97.498962
iter 10 value 94.035943
iter 20 value 94.034607
iter 30 value 94.001300
iter 40 value 83.786063
iter 50 value 83.750139
final value 83.631999
converged
Fitting Repeat 3
# weights: 103
initial value 97.756404
final value 94.054592
converged
Fitting Repeat 4
# weights: 103
initial value 96.441459
final value 93.698931
converged
Fitting Repeat 5
# weights: 103
initial value 103.422519
final value 94.054982
converged
Fitting Repeat 1
# weights: 305
initial value 110.941183
iter 10 value 94.037763
iter 20 value 94.033423
iter 30 value 93.829379
iter 40 value 90.261141
iter 50 value 84.414506
iter 60 value 84.266660
final value 84.265996
converged
Fitting Repeat 2
# weights: 305
initial value 98.566359
iter 10 value 94.057592
iter 20 value 94.045715
iter 30 value 93.155863
iter 40 value 86.827820
iter 50 value 84.944719
iter 60 value 84.448196
iter 70 value 84.059909
iter 80 value 83.212741
iter 90 value 80.148053
iter 100 value 79.744678
final value 79.744678
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 97.837904
iter 10 value 94.059194
iter 20 value 94.052200
iter 30 value 93.653444
iter 40 value 86.390489
iter 50 value 86.385794
iter 60 value 86.261012
iter 70 value 86.256578
iter 80 value 83.198327
iter 90 value 82.027675
iter 100 value 82.024235
final value 82.024235
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 94.243961
iter 10 value 94.037554
iter 20 value 92.858310
iter 30 value 89.378712
iter 40 value 88.084543
iter 50 value 88.049172
iter 60 value 88.048060
iter 70 value 88.047124
iter 80 value 88.046722
iter 90 value 86.577320
iter 100 value 85.637488
final value 85.637488
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.882896
iter 10 value 88.331355
iter 20 value 85.625751
iter 30 value 82.165840
iter 40 value 81.621569
final value 81.610640
converged
Fitting Repeat 1
# weights: 507
initial value 98.455537
iter 10 value 94.060801
iter 20 value 93.186205
iter 30 value 93.101295
iter 40 value 91.507204
iter 50 value 90.372659
iter 60 value 90.367199
iter 70 value 90.364013
final value 90.363509
converged
Fitting Repeat 2
# weights: 507
initial value 95.250626
iter 10 value 94.061380
iter 20 value 93.128513
iter 30 value 85.715571
iter 40 value 85.695700
iter 50 value 85.689993
iter 60 value 85.465171
iter 70 value 85.442128
final value 85.441740
converged
Fitting Repeat 3
# weights: 507
initial value 99.251918
iter 10 value 94.060328
iter 20 value 93.619643
iter 30 value 90.268789
iter 40 value 80.126455
iter 50 value 79.487870
iter 60 value 79.342197
iter 70 value 79.340866
final value 79.340307
converged
Fitting Repeat 4
# weights: 507
initial value 104.167481
iter 10 value 94.041676
iter 20 value 94.033892
final value 94.033314
converged
Fitting Repeat 5
# weights: 507
initial value 95.366120
iter 10 value 94.041355
iter 20 value 94.034211
iter 30 value 85.684441
iter 40 value 83.784080
iter 50 value 82.208250
iter 60 value 80.868332
iter 70 value 80.824154
iter 80 value 80.821114
final value 80.820300
converged
Fitting Repeat 1
# weights: 103
initial value 94.593596
final value 94.038251
converged
Fitting Repeat 2
# weights: 103
initial value 98.678505
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.744552
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.565559
final value 94.038251
converged
Fitting Repeat 5
# weights: 103
initial value 98.906188
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 99.847066
iter 10 value 90.107956
iter 20 value 83.277574
iter 30 value 83.233966
final value 83.233856
converged
Fitting Repeat 2
# weights: 305
initial value 111.226480
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 96.011095
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 99.137905
iter 10 value 93.662297
final value 93.662011
converged
Fitting Repeat 5
# weights: 305
initial value 100.946330
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 107.116228
iter 10 value 94.038251
iter 10 value 94.038251
iter 10 value 94.038251
final value 94.038251
converged
Fitting Repeat 2
# weights: 507
initial value 127.601526
iter 10 value 95.235301
iter 20 value 88.469220
iter 30 value 87.939980
iter 40 value 84.649890
iter 50 value 83.247683
iter 60 value 83.064853
iter 70 value 83.052810
iter 80 value 83.048483
final value 83.048473
converged
Fitting Repeat 3
# weights: 507
initial value 102.052867
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 96.123270
final value 94.052874
converged
Fitting Repeat 5
# weights: 507
initial value 114.309915
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 97.388918
iter 10 value 94.020839
iter 20 value 85.643945
iter 30 value 84.735486
iter 40 value 82.658275
iter 50 value 81.531576
iter 60 value 81.475076
iter 70 value 81.002433
iter 80 value 80.948136
iter 90 value 80.928630
iter 100 value 80.925508
final value 80.925508
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 103.508526
iter 10 value 94.042688
iter 20 value 91.187716
iter 30 value 86.399171
iter 40 value 85.165421
iter 50 value 83.038348
iter 60 value 82.499137
iter 70 value 82.457058
iter 80 value 82.340370
iter 90 value 82.285977
final value 82.283144
converged
Fitting Repeat 3
# weights: 103
initial value 98.239808
iter 10 value 93.979136
iter 20 value 91.284316
iter 30 value 91.036279
iter 40 value 89.966091
iter 50 value 89.838783
iter 60 value 89.833473
final value 89.833469
converged
Fitting Repeat 4
# weights: 103
initial value 104.723008
iter 10 value 94.061000
iter 20 value 93.529703
iter 30 value 88.403805
iter 40 value 87.461883
iter 50 value 87.172700
iter 60 value 85.988445
iter 70 value 84.636705
iter 80 value 83.714474
iter 90 value 82.536568
iter 100 value 82.294797
final value 82.294797
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 100.488349
iter 10 value 94.056968
iter 20 value 89.413737
iter 30 value 88.071592
iter 40 value 83.352190
iter 50 value 82.354471
iter 60 value 81.155807
iter 70 value 81.008428
iter 80 value 80.161284
iter 90 value 79.192091
iter 100 value 79.176387
final value 79.176387
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 123.927300
iter 10 value 94.067333
iter 20 value 87.500449
iter 30 value 83.741968
iter 40 value 82.894438
iter 50 value 82.597663
iter 60 value 82.124722
iter 70 value 81.626914
iter 80 value 81.251469
iter 90 value 80.381805
iter 100 value 78.919310
final value 78.919310
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.307560
iter 10 value 93.358600
iter 20 value 87.440553
iter 30 value 84.625362
iter 40 value 82.472075
iter 50 value 81.812532
iter 60 value 79.822282
iter 70 value 78.476972
iter 80 value 78.099199
iter 90 value 77.968205
iter 100 value 77.853751
final value 77.853751
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.557212
iter 10 value 93.355046
iter 20 value 83.094415
iter 30 value 81.873998
iter 40 value 80.928333
iter 50 value 79.781982
iter 60 value 79.656827
iter 70 value 79.509714
iter 80 value 79.469666
iter 90 value 79.398113
iter 100 value 79.233372
final value 79.233372
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.414980
iter 10 value 94.020699
iter 20 value 87.389980
iter 30 value 84.973701
iter 40 value 81.924665
iter 50 value 80.476128
iter 60 value 80.228912
iter 70 value 79.874929
iter 80 value 79.712110
iter 90 value 79.158495
iter 100 value 78.994223
final value 78.994223
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.862287
iter 10 value 90.579685
iter 20 value 86.140593
iter 30 value 83.013420
iter 40 value 81.491076
iter 50 value 80.701377
iter 60 value 80.247587
iter 70 value 79.937336
iter 80 value 79.691979
iter 90 value 79.221303
iter 100 value 78.515303
final value 78.515303
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.420674
iter 10 value 94.226276
iter 20 value 94.042657
iter 30 value 85.250549
iter 40 value 81.582069
iter 50 value 80.044290
iter 60 value 79.148509
iter 70 value 78.185450
iter 80 value 77.942187
iter 90 value 77.799006
iter 100 value 77.656396
final value 77.656396
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 120.093561
iter 10 value 94.111764
iter 20 value 89.631139
iter 30 value 84.428464
iter 40 value 80.552492
iter 50 value 79.132481
iter 60 value 78.904332
iter 70 value 78.768848
iter 80 value 78.604420
iter 90 value 78.494931
iter 100 value 78.366944
final value 78.366944
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 112.853269
iter 10 value 95.723669
iter 20 value 85.445136
iter 30 value 83.915961
iter 40 value 81.780426
iter 50 value 80.463648
iter 60 value 80.047845
iter 70 value 79.471023
iter 80 value 79.057612
iter 90 value 78.573232
iter 100 value 78.244479
final value 78.244479
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.954414
iter 10 value 94.088840
iter 20 value 88.544330
iter 30 value 85.509294
iter 40 value 81.949128
iter 50 value 80.816651
iter 60 value 78.604698
iter 70 value 78.182883
iter 80 value 77.796720
iter 90 value 77.598242
iter 100 value 77.452624
final value 77.452624
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.893191
iter 10 value 94.727986
iter 20 value 92.840539
iter 30 value 83.984327
iter 40 value 82.365733
iter 50 value 81.671068
iter 60 value 81.383063
iter 70 value 80.940440
iter 80 value 80.650348
iter 90 value 80.336274
iter 100 value 80.168965
final value 80.168965
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.565025
final value 94.054493
converged
Fitting Repeat 2
# weights: 103
initial value 98.676956
final value 94.054634
converged
Fitting Repeat 3
# weights: 103
initial value 94.510870
final value 94.054544
converged
Fitting Repeat 4
# weights: 103
initial value 110.034877
final value 94.054424
converged
Fitting Repeat 5
# weights: 103
initial value 94.605146
iter 10 value 84.209122
iter 20 value 83.867257
iter 30 value 83.859714
final value 83.859595
converged
Fitting Repeat 1
# weights: 305
initial value 104.802658
iter 10 value 94.059131
iter 20 value 92.801168
iter 30 value 84.514582
iter 40 value 83.081645
iter 50 value 83.061533
iter 60 value 80.675769
iter 70 value 78.346880
iter 80 value 77.196137
iter 90 value 77.014831
iter 100 value 76.765570
final value 76.765570
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 95.523338
iter 10 value 94.058504
iter 20 value 93.553707
iter 30 value 89.712033
iter 40 value 89.457250
iter 50 value 89.421352
iter 60 value 89.362190
iter 70 value 89.342848
iter 80 value 89.335186
iter 90 value 89.334046
iter 100 value 89.316263
final value 89.316263
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.601397
iter 10 value 94.042996
iter 20 value 94.014683
iter 30 value 91.916474
iter 40 value 82.197744
iter 50 value 81.157971
iter 60 value 81.085071
final value 81.084924
converged
Fitting Repeat 4
# weights: 305
initial value 98.970707
iter 10 value 94.057698
iter 20 value 94.044634
iter 30 value 81.723457
iter 40 value 81.425125
iter 50 value 81.320456
iter 60 value 80.560318
iter 70 value 80.040468
iter 80 value 80.016798
final value 80.016687
converged
Fitting Repeat 5
# weights: 305
initial value 99.424336
iter 10 value 94.057995
iter 20 value 94.052921
iter 20 value 94.052921
final value 94.052921
converged
Fitting Repeat 1
# weights: 507
initial value 102.288850
iter 10 value 94.046756
iter 20 value 93.304756
iter 30 value 87.830186
iter 40 value 86.295803
iter 50 value 86.293902
iter 60 value 86.292612
final value 86.292415
converged
Fitting Repeat 2
# weights: 507
initial value 102.033081
iter 10 value 93.093417
iter 20 value 92.190384
iter 30 value 92.141232
iter 40 value 90.847950
iter 50 value 90.762408
iter 60 value 90.762065
iter 70 value 90.760466
iter 70 value 90.760465
iter 70 value 90.760465
final value 90.760465
converged
Fitting Repeat 3
# weights: 507
initial value 95.954100
iter 10 value 87.039724
iter 20 value 83.754081
iter 30 value 82.936784
iter 40 value 82.924116
iter 50 value 82.072069
iter 60 value 81.409494
iter 70 value 81.391103
iter 80 value 81.389641
iter 90 value 81.387906
iter 100 value 81.363322
final value 81.363322
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.517570
iter 10 value 85.649288
iter 20 value 81.972072
iter 30 value 81.884165
iter 40 value 81.751425
iter 50 value 81.720738
iter 60 value 81.720119
iter 70 value 81.719055
iter 80 value 81.718288
iter 90 value 81.717598
final value 81.717049
converged
Fitting Repeat 5
# weights: 507
initial value 103.940788
iter 10 value 94.046599
iter 20 value 94.038959
iter 30 value 93.102292
iter 40 value 81.173044
iter 50 value 80.637587
iter 60 value 79.975924
iter 70 value 79.750842
iter 80 value 79.749296
iter 90 value 78.661926
iter 100 value 77.725010
final value 77.725010
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.521110
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 103.525853
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.482119
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 94.427901
iter 10 value 89.915592
iter 20 value 89.069068
iter 20 value 89.069068
iter 20 value 89.069068
final value 89.069068
converged
Fitting Repeat 5
# weights: 103
initial value 113.170685
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 97.698889
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 98.033846
iter 10 value 88.969431
iter 20 value 88.810615
iter 30 value 88.804664
final value 88.804661
converged
Fitting Repeat 3
# weights: 305
initial value 106.603830
iter 10 value 94.052435
iter 10 value 94.052434
iter 10 value 94.052434
final value 94.052434
converged
Fitting Repeat 4
# weights: 305
initial value 101.146257
iter 10 value 94.055937
iter 20 value 94.052437
final value 94.052435
converged
Fitting Repeat 5
# weights: 305
initial value 101.872016
final value 94.275362
converged
Fitting Repeat 1
# weights: 507
initial value 108.359103
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 109.691336
iter 10 value 93.030766
iter 20 value 89.854505
iter 30 value 87.052669
iter 40 value 86.923320
iter 50 value 86.269119
iter 60 value 85.692001
final value 85.691980
converged
Fitting Repeat 3
# weights: 507
initial value 122.222666
final value 94.483810
converged
Fitting Repeat 4
# weights: 507
initial value 97.140803
final value 94.483810
converged
Fitting Repeat 5
# weights: 507
initial value 114.685960
iter 10 value 94.276113
final value 94.275345
converged
Fitting Repeat 1
# weights: 103
initial value 114.085850
iter 10 value 94.422813
iter 20 value 88.676319
iter 30 value 88.372174
iter 40 value 86.393920
iter 50 value 85.989557
iter 60 value 85.000784
iter 70 value 84.325756
iter 80 value 83.441459
iter 90 value 83.374017
iter 100 value 83.291935
final value 83.291935
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 98.783242
iter 10 value 94.487770
iter 20 value 94.369869
iter 30 value 94.322662
iter 40 value 90.869563
iter 50 value 87.128618
iter 60 value 85.949676
iter 70 value 85.504203
iter 80 value 85.282306
iter 90 value 85.208150
final value 85.208017
converged
Fitting Repeat 3
# weights: 103
initial value 101.875068
iter 10 value 94.498434
iter 20 value 94.349754
iter 30 value 92.733812
iter 40 value 91.475322
iter 50 value 87.185664
iter 60 value 86.115809
iter 70 value 86.091916
iter 80 value 84.722320
iter 90 value 83.472695
iter 100 value 83.393406
final value 83.393406
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 111.572436
iter 10 value 94.547401
iter 20 value 94.392465
iter 30 value 92.794732
iter 40 value 88.744208
iter 50 value 88.119058
iter 60 value 87.474896
iter 70 value 86.310782
iter 80 value 85.999879
iter 90 value 85.895177
iter 100 value 85.260513
final value 85.260513
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 100.023041
iter 10 value 94.237627
iter 20 value 87.845044
iter 30 value 86.002016
iter 40 value 85.567764
iter 50 value 84.627319
iter 60 value 83.890141
iter 70 value 83.424961
iter 80 value 83.407255
iter 90 value 83.384466
iter 100 value 83.272952
final value 83.272952
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 102.182511
iter 10 value 94.456785
iter 20 value 91.787127
iter 30 value 89.737505
iter 40 value 87.950066
iter 50 value 86.782570
iter 60 value 85.749000
iter 70 value 83.578638
iter 80 value 82.818004
iter 90 value 82.690345
iter 100 value 82.400252
final value 82.400252
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 114.975819
iter 10 value 95.882939
iter 20 value 94.482345
iter 30 value 90.299015
iter 40 value 89.065565
iter 50 value 88.088109
iter 60 value 83.826055
iter 70 value 83.348663
iter 80 value 82.975779
iter 90 value 82.435598
iter 100 value 82.085931
final value 82.085931
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 111.859592
iter 10 value 94.214721
iter 20 value 93.946852
iter 30 value 89.956070
iter 40 value 88.240090
iter 50 value 87.366799
iter 60 value 86.376014
iter 70 value 86.232835
iter 80 value 85.722097
iter 90 value 85.452666
iter 100 value 84.775609
final value 84.775609
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.960897
iter 10 value 94.841612
iter 20 value 94.629924
iter 30 value 88.607073
iter 40 value 86.010522
iter 50 value 84.960221
iter 60 value 84.067176
iter 70 value 83.340801
iter 80 value 82.667604
iter 90 value 82.309020
iter 100 value 82.233801
final value 82.233801
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.068482
iter 10 value 93.191647
iter 20 value 89.886820
iter 30 value 86.624076
iter 40 value 86.337704
iter 50 value 86.257874
iter 60 value 85.728179
iter 70 value 83.144079
iter 80 value 82.585799
iter 90 value 82.412744
iter 100 value 82.329777
final value 82.329777
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 111.624360
iter 10 value 94.620750
iter 20 value 94.470760
iter 30 value 89.439568
iter 40 value 87.179445
iter 50 value 86.302166
iter 60 value 84.618915
iter 70 value 83.015189
iter 80 value 82.225195
iter 90 value 82.097115
iter 100 value 82.012053
final value 82.012053
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 147.905695
iter 10 value 95.367517
iter 20 value 94.987540
iter 30 value 94.519470
iter 40 value 87.646918
iter 50 value 86.986144
iter 60 value 86.638125
iter 70 value 86.383657
iter 80 value 85.632570
iter 90 value 83.767269
iter 100 value 83.174653
final value 83.174653
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 133.912692
iter 10 value 94.984467
iter 20 value 92.385236
iter 30 value 87.658585
iter 40 value 86.835338
iter 50 value 85.425852
iter 60 value 83.563930
iter 70 value 83.037628
iter 80 value 82.880507
iter 90 value 82.725120
iter 100 value 82.633037
final value 82.633037
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.415502
iter 10 value 95.824973
iter 20 value 93.842152
iter 30 value 91.612533
iter 40 value 88.788821
iter 50 value 87.150807
iter 60 value 83.974565
iter 70 value 82.951056
iter 80 value 82.045368
iter 90 value 81.635251
iter 100 value 81.479574
final value 81.479574
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.075682
iter 10 value 94.378343
iter 20 value 88.085679
iter 30 value 86.317730
iter 40 value 85.781040
iter 50 value 85.384199
iter 60 value 85.152591
iter 70 value 84.056477
iter 80 value 82.531637
iter 90 value 81.991076
iter 100 value 81.742820
final value 81.742820
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.513844
iter 10 value 94.485521
final value 94.484266
converged
Fitting Repeat 2
# weights: 103
initial value 100.479748
final value 94.485872
converged
Fitting Repeat 3
# weights: 103
initial value 99.677334
final value 94.486099
converged
Fitting Repeat 4
# weights: 103
initial value 96.821034
iter 10 value 90.945885
iter 20 value 90.884191
iter 30 value 90.708143
iter 40 value 90.522969
iter 50 value 90.521857
final value 90.521842
converged
Fitting Repeat 5
# weights: 103
initial value 95.017175
final value 94.485849
converged
Fitting Repeat 1
# weights: 305
initial value 102.945190
iter 10 value 94.488384
iter 20 value 94.276494
iter 20 value 94.276493
iter 20 value 94.276493
final value 94.276493
converged
Fitting Repeat 2
# weights: 305
initial value 110.373904
iter 10 value 94.489229
iter 20 value 94.484343
iter 30 value 94.325253
iter 40 value 92.344183
iter 50 value 89.144841
iter 60 value 87.864736
iter 70 value 87.022110
iter 80 value 86.907541
iter 90 value 86.657321
iter 100 value 86.586395
final value 86.586395
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.032338
iter 10 value 94.489302
iter 20 value 94.483876
iter 30 value 93.747173
iter 40 value 88.390979
iter 50 value 88.390384
iter 60 value 88.333604
iter 70 value 88.314243
iter 80 value 88.307768
iter 90 value 87.424959
iter 100 value 86.929096
final value 86.929096
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 110.182662
iter 10 value 94.488893
iter 20 value 94.483582
iter 30 value 91.520188
iter 40 value 86.558861
iter 50 value 83.869008
iter 60 value 83.665769
final value 83.662436
converged
Fitting Repeat 5
# weights: 305
initial value 106.637107
iter 10 value 94.280599
iter 20 value 94.276004
final value 94.275679
converged
Fitting Repeat 1
# weights: 507
initial value 103.306285
iter 10 value 86.665685
iter 20 value 86.661499
iter 30 value 85.708024
iter 40 value 85.658765
iter 50 value 85.482816
iter 60 value 85.481332
iter 70 value 85.449068
iter 80 value 85.348290
iter 90 value 85.116774
iter 100 value 85.114650
final value 85.114650
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 100.274756
iter 10 value 94.492835
iter 20 value 93.610824
iter 30 value 88.806333
final value 88.805964
converged
Fitting Repeat 3
# weights: 507
initial value 108.052294
iter 10 value 93.912077
iter 20 value 92.221365
iter 30 value 86.657981
iter 40 value 86.349771
iter 50 value 85.438157
iter 60 value 85.030817
iter 70 value 85.029044
final value 85.029008
converged
Fitting Repeat 4
# weights: 507
initial value 103.202679
iter 10 value 94.296772
iter 20 value 94.291212
iter 30 value 87.198152
iter 40 value 83.636549
iter 50 value 81.578866
iter 60 value 81.357742
iter 70 value 81.279322
iter 80 value 81.262929
iter 90 value 81.261179
iter 100 value 81.246379
final value 81.246379
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 122.896732
iter 10 value 94.283615
iter 20 value 94.276025
iter 30 value 93.443377
iter 40 value 92.051163
iter 50 value 91.632995
iter 60 value 86.379618
iter 70 value 85.582981
iter 80 value 85.161951
iter 90 value 84.018874
iter 100 value 83.778156
final value 83.778156
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 119.697242
iter 10 value 117.895790
iter 20 value 117.884436
iter 30 value 117.555753
final value 117.550892
converged
Fitting Repeat 2
# weights: 305
initial value 132.460022
iter 10 value 117.923235
iter 20 value 117.902035
iter 30 value 111.612734
iter 40 value 107.029359
iter 50 value 106.918178
iter 60 value 106.734884
iter 70 value 106.670187
iter 80 value 106.667102
iter 90 value 105.150796
iter 100 value 105.067854
final value 105.067854
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 122.337886
iter 10 value 117.895350
iter 20 value 117.890423
iter 30 value 117.611502
final value 117.607897
converged
Fitting Repeat 4
# weights: 305
initial value 123.119745
iter 10 value 117.764306
iter 20 value 117.759758
final value 117.758942
converged
Fitting Repeat 5
# weights: 305
initial value 133.448158
iter 10 value 117.893581
iter 20 value 117.761234
iter 30 value 117.759994
iter 40 value 117.729683
iter 40 value 117.729682
iter 40 value 117.729682
final value 117.729682
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 -- Mon Mar 24 02:30:09 2025
***********************************************
Number of test functions: 7
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7
Number of errors: 0
Number of failures: 0
Warning messages:
1: `repeats` has no meaning for this resampling method.
2: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
43.03 1.34 132.12
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 35.12 | 1.70 | 37.06 | |
| FreqInteractors | 0.33 | 0.01 | 0.43 | |
| calculateAAC | 0.06 | 0.00 | 0.08 | |
| calculateAutocor | 0.42 | 0.10 | 0.56 | |
| calculateCTDC | 0.11 | 0.00 | 0.11 | |
| calculateCTDD | 0.91 | 0.04 | 1.00 | |
| calculateCTDT | 0.39 | 0.02 | 0.40 | |
| calculateCTriad | 0.5 | 0.0 | 0.5 | |
| calculateDC | 0.09 | 0.03 | 0.13 | |
| calculateF | 0.39 | 0.02 | 0.44 | |
| calculateKSAAP | 0.14 | 0.00 | 0.14 | |
| calculateQD_Sm | 2.45 | 0.12 | 2.58 | |
| calculateTC | 2.10 | 0.06 | 2.15 | |
| calculateTC_Sm | 0.29 | 0.00 | 0.30 | |
| corr_plot | 33.13 | 1.66 | 34.81 | |
| enrichfindP | 0.55 | 0.20 | 14.60 | |
| enrichfind_hp | 0.04 | 0.03 | 1.07 | |
| enrichplot | 0.49 | 0.00 | 0.49 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.03 | 0.00 | 2.06 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.08 | 0.00 | 0.07 | |
| pred_ensembel | 13.42 | 0.30 | 12.41 | |
| var_imp | 35.41 | 1.09 | 36.51 | |