Matineh Rahmatbakhsh
| Snapshot Date: 2024-10-16 14:00 -0400 (Wed, 16 Oct 2024) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_19 |
| git_last_commit: 09dc3c1 |
| git_last_commit_date: 2024-04-30 11:37:16 -0400 (Tue, 30 Apr 2024) |
| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-10-18 20:39 -0400 (Fri, 18 Oct 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4763 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4500 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4530 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4480 |
| 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 987/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.10.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
|
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: 1.10.0 |
| Command: E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz |
| StartedAt: 2024-10-17 02:23:57 -0400 (Thu, 17 Oct 2024) |
| EndedAt: 2024-10-17 02:28:57 -0400 (Thu, 17 Oct 2024) |
| EllapsedTime: 300.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'E:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck'
* using R version 4.4.1 (2024-06-14 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 13.2.0
GNU Fortran (GCC) 13.2.0
* 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 '1.10.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
FSmethod 33.97 1.98 36.15
corr_plot 33.21 1.68 34.92
var_imp 32.94 1.32 34.25
pred_ensembel 15.21 0.46 11.67
enrichfindP 0.59 0.14 13.94
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 3 NOTEs
See
'E:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'E:/biocbuild/bbs-3.19-bioc/R/library' * installing *source* package 'HPiP' ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 98.556749
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 98.343401
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.209083
iter 10 value 94.439858
iter 20 value 86.614283
iter 30 value 83.661313
iter 40 value 83.564520
iter 50 value 83.563671
final value 83.563640
converged
Fitting Repeat 4
# weights: 103
initial value 105.053982
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.524554
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.687721
final value 94.443243
converged
Fitting Repeat 2
# weights: 305
initial value 96.162642
iter 10 value 94.476471
iter 10 value 94.476471
iter 10 value 94.476471
final value 94.476471
converged
Fitting Repeat 3
# weights: 305
initial value 101.364461
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 117.280308
final value 94.443243
converged
Fitting Repeat 5
# weights: 305
initial value 97.291988
iter 10 value 93.487638
iter 20 value 93.395985
iter 30 value 93.196112
final value 93.196015
converged
Fitting Repeat 1
# weights: 507
initial value 96.283686
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 104.873619
final value 94.443243
converged
Fitting Repeat 3
# weights: 507
initial value 107.095772
final value 94.443243
converged
Fitting Repeat 4
# weights: 507
initial value 102.257822
iter 10 value 94.413881
final value 94.400000
converged
Fitting Repeat 5
# weights: 507
initial value 106.629320
final value 94.443243
converged
Fitting Repeat 1
# weights: 103
initial value 118.867070
iter 10 value 94.463909
iter 20 value 92.820601
iter 30 value 91.795272
iter 40 value 91.377547
iter 50 value 91.101129
iter 60 value 91.048610
iter 70 value 90.953127
final value 90.950849
converged
Fitting Repeat 2
# weights: 103
initial value 98.350381
iter 10 value 94.444481
iter 20 value 94.419757
iter 30 value 92.985708
iter 40 value 89.525928
iter 50 value 85.925181
iter 60 value 85.589648
iter 70 value 85.196229
iter 80 value 84.837526
iter 90 value 84.625727
final value 84.625447
converged
Fitting Repeat 3
# weights: 103
initial value 96.584213
iter 10 value 94.481782
iter 20 value 93.222134
iter 30 value 88.923327
iter 40 value 86.130242
iter 50 value 84.995538
iter 60 value 84.640726
iter 70 value 84.638211
final value 84.637945
converged
Fitting Repeat 4
# weights: 103
initial value 106.286581
iter 10 value 90.696785
iter 20 value 82.400936
iter 30 value 81.611931
iter 40 value 81.341136
iter 50 value 81.047079
iter 60 value 81.029191
final value 81.017477
converged
Fitting Repeat 5
# weights: 103
initial value 98.705284
iter 10 value 89.809173
iter 20 value 84.281384
iter 30 value 83.992059
iter 40 value 83.202762
iter 50 value 82.604280
iter 60 value 81.987195
iter 70 value 81.776608
iter 80 value 81.371661
iter 90 value 81.345588
final value 81.345309
converged
Fitting Repeat 1
# weights: 305
initial value 99.945858
iter 10 value 94.526170
iter 20 value 94.495216
iter 30 value 93.932113
iter 40 value 91.914759
iter 50 value 91.409560
iter 60 value 90.816401
iter 70 value 90.759819
iter 80 value 89.214703
iter 90 value 85.504499
iter 100 value 83.717807
final value 83.717807
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 107.702956
iter 10 value 94.475126
iter 20 value 94.213880
iter 30 value 87.571119
iter 40 value 86.885457
iter 50 value 86.408191
iter 60 value 85.808578
iter 70 value 81.605372
iter 80 value 80.637078
iter 90 value 80.031153
iter 100 value 79.916417
final value 79.916417
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 110.336950
iter 10 value 94.463632
iter 20 value 85.723853
iter 30 value 82.906129
iter 40 value 82.032431
iter 50 value 81.945353
iter 60 value 81.724894
iter 70 value 81.161922
iter 80 value 80.116120
iter 90 value 79.838136
iter 100 value 79.804443
final value 79.804443
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.859152
iter 10 value 93.220564
iter 20 value 86.903122
iter 30 value 85.761111
iter 40 value 85.459550
iter 50 value 85.243800
iter 60 value 83.839176
iter 70 value 82.568139
iter 80 value 82.213618
iter 90 value 81.430869
iter 100 value 81.369260
final value 81.369260
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.054237
iter 10 value 93.358451
iter 20 value 88.510657
iter 30 value 87.201408
iter 40 value 84.909022
iter 50 value 82.828697
iter 60 value 82.581145
iter 70 value 82.516050
iter 80 value 82.418227
iter 90 value 81.625640
iter 100 value 80.674863
final value 80.674863
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.995822
iter 10 value 88.909434
iter 20 value 85.328313
iter 30 value 84.468774
iter 40 value 84.387244
iter 50 value 83.527909
iter 60 value 82.611108
iter 70 value 82.146762
iter 80 value 81.790578
iter 90 value 80.893893
iter 100 value 80.728907
final value 80.728907
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.034434
iter 10 value 95.535743
iter 20 value 94.498633
iter 30 value 94.310032
iter 40 value 89.963011
iter 50 value 86.867006
iter 60 value 84.719795
iter 70 value 83.435219
iter 80 value 82.617751
iter 90 value 82.355456
iter 100 value 81.523138
final value 81.523138
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 118.726153
iter 10 value 93.847308
iter 20 value 90.873204
iter 30 value 88.190001
iter 40 value 86.749777
iter 50 value 83.170362
iter 60 value 81.228562
iter 70 value 79.945364
iter 80 value 79.845373
iter 90 value 79.829622
iter 100 value 79.807868
final value 79.807868
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 116.452346
iter 10 value 94.946428
iter 20 value 89.265873
iter 30 value 86.266035
iter 40 value 85.547680
iter 50 value 85.106684
iter 60 value 83.745197
iter 70 value 81.896341
iter 80 value 80.499003
iter 90 value 80.167354
iter 100 value 79.926428
final value 79.926428
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.383853
iter 10 value 93.813564
iter 20 value 86.454742
iter 30 value 85.855592
iter 40 value 82.942527
iter 50 value 80.674920
iter 60 value 79.731129
iter 70 value 79.561900
iter 80 value 79.514856
iter 90 value 79.260013
iter 100 value 79.177583
final value 79.177583
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.237703
final value 94.479813
converged
Fitting Repeat 2
# weights: 103
initial value 97.094592
final value 94.485579
converged
Fitting Repeat 3
# weights: 103
initial value 103.741689
final value 94.485841
converged
Fitting Repeat 4
# weights: 103
initial value 108.545940
final value 94.485867
converged
Fitting Repeat 5
# weights: 103
initial value 98.563767
final value 94.488168
converged
Fitting Repeat 1
# weights: 305
initial value 101.220465
iter 10 value 92.643005
iter 20 value 92.628987
iter 30 value 92.576428
iter 40 value 92.529195
iter 50 value 92.528162
iter 60 value 92.527607
final value 92.527361
converged
Fitting Repeat 2
# weights: 305
initial value 101.455916
iter 10 value 94.448310
iter 20 value 94.381122
iter 30 value 94.379491
final value 94.379475
converged
Fitting Repeat 3
# weights: 305
initial value 96.813156
iter 10 value 94.359395
iter 20 value 84.714659
iter 30 value 83.862386
iter 40 value 83.749723
iter 50 value 83.500260
iter 60 value 83.489944
iter 70 value 83.485745
iter 80 value 83.456750
iter 90 value 83.455808
final value 83.454908
converged
Fitting Repeat 4
# weights: 305
initial value 118.721693
iter 10 value 94.489173
iter 20 value 94.478288
iter 30 value 92.573235
iter 40 value 92.520391
iter 50 value 92.461139
iter 60 value 91.584854
iter 70 value 86.263872
iter 80 value 84.308571
iter 90 value 83.582654
iter 100 value 82.957015
final value 82.957015
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 97.414994
iter 10 value 94.448224
iter 20 value 94.443886
final value 94.443603
converged
Fitting Repeat 1
# weights: 507
initial value 133.948773
iter 10 value 94.460778
iter 20 value 94.450597
iter 30 value 93.634152
iter 40 value 88.216097
iter 50 value 88.120369
iter 60 value 88.095665
iter 70 value 88.089041
iter 80 value 87.768006
iter 90 value 83.268469
iter 100 value 82.004638
final value 82.004638
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.846910
iter 10 value 94.484523
iter 20 value 94.458656
iter 30 value 88.231389
iter 40 value 88.146534
iter 50 value 87.739409
iter 60 value 87.586915
final value 87.579766
converged
Fitting Repeat 3
# weights: 507
initial value 122.824704
iter 10 value 94.451298
iter 20 value 94.439104
iter 30 value 93.851974
iter 40 value 85.401795
iter 50 value 84.542820
iter 60 value 81.561330
iter 70 value 77.940896
iter 80 value 77.697029
iter 90 value 77.682334
iter 100 value 77.678480
final value 77.678480
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.280599
iter 10 value 94.492039
iter 20 value 88.765695
iter 30 value 88.216356
iter 40 value 88.208880
iter 50 value 88.208633
final value 88.207468
converged
Fitting Repeat 5
# weights: 507
initial value 106.347344
iter 10 value 91.616031
iter 20 value 85.768238
iter 30 value 85.746072
iter 40 value 85.719671
iter 50 value 85.600889
final value 85.599245
converged
Fitting Repeat 1
# weights: 103
initial value 109.526050
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.400455
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.663763
iter 10 value 90.372455
iter 20 value 90.292985
iter 30 value 88.503808
iter 40 value 86.469962
iter 50 value 86.433671
final value 86.431987
converged
Fitting Repeat 4
# weights: 103
initial value 95.856028
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.523285
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.660031
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 112.635957
final value 93.809648
converged
Fitting Repeat 3
# weights: 305
initial value 97.532650
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 124.751922
final value 94.484205
converged
Fitting Repeat 5
# weights: 305
initial value 114.647574
final value 93.809648
converged
Fitting Repeat 1
# weights: 507
initial value 100.350427
final value 94.484137
converged
Fitting Repeat 2
# weights: 507
initial value 95.430806
final value 94.354396
converged
Fitting Repeat 3
# weights: 507
initial value 107.447751
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 111.220695
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 96.471691
iter 10 value 93.576815
iter 20 value 92.270782
iter 30 value 92.270366
final value 92.270352
converged
Fitting Repeat 1
# weights: 103
initial value 104.452061
iter 10 value 94.489018
iter 20 value 94.428000
iter 30 value 93.898208
iter 40 value 93.870064
iter 50 value 89.949906
iter 60 value 85.047388
iter 70 value 82.464523
iter 80 value 81.984306
iter 90 value 81.875054
iter 100 value 81.626584
final value 81.626584
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 98.600463
iter 10 value 94.500824
iter 20 value 93.913599
iter 30 value 87.654317
iter 40 value 85.270668
iter 50 value 84.783577
iter 60 value 83.076253
iter 70 value 82.454013
iter 80 value 82.327048
iter 90 value 82.301065
iter 100 value 82.277861
final value 82.277861
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 103.922912
iter 10 value 91.836625
iter 20 value 86.151424
iter 30 value 85.732176
iter 40 value 84.060667
iter 50 value 82.948811
iter 60 value 82.346835
iter 70 value 82.299570
iter 80 value 82.277863
final value 82.277856
converged
Fitting Repeat 4
# weights: 103
initial value 97.396475
iter 10 value 94.509984
iter 20 value 86.852858
iter 30 value 85.061331
iter 40 value 84.706611
iter 50 value 83.789850
iter 60 value 83.252314
iter 70 value 83.112146
iter 80 value 82.592151
iter 90 value 82.276328
iter 100 value 81.764088
final value 81.764088
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 102.260592
iter 10 value 94.448938
iter 20 value 92.854634
iter 30 value 92.386161
iter 40 value 83.491076
iter 50 value 82.751893
iter 60 value 82.265719
iter 70 value 81.562032
iter 80 value 81.468512
final value 81.468233
converged
Fitting Repeat 1
# weights: 305
initial value 101.777953
iter 10 value 94.465309
iter 20 value 84.616190
iter 30 value 84.234219
iter 40 value 83.942832
iter 50 value 83.721013
iter 60 value 83.184495
iter 70 value 82.286224
iter 80 value 82.112006
iter 90 value 82.036182
iter 100 value 82.001436
final value 82.001436
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.630910
iter 10 value 97.042817
iter 20 value 86.178306
iter 30 value 83.869369
iter 40 value 83.387383
iter 50 value 82.655236
iter 60 value 82.170704
iter 70 value 81.968183
iter 80 value 81.143412
iter 90 value 80.776448
iter 100 value 80.764181
final value 80.764181
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.006003
iter 10 value 94.438862
iter 20 value 93.951357
iter 30 value 93.843070
iter 40 value 87.131299
iter 50 value 84.695125
iter 60 value 84.097290
iter 70 value 82.678484
iter 80 value 81.616029
iter 90 value 80.896022
iter 100 value 80.841043
final value 80.841043
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 121.030922
iter 10 value 94.464739
iter 20 value 92.947481
iter 30 value 88.393382
iter 40 value 84.377117
iter 50 value 83.875504
iter 60 value 83.682808
iter 70 value 83.470329
iter 80 value 83.011044
iter 90 value 81.974107
iter 100 value 81.258667
final value 81.258667
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.188664
iter 10 value 94.224389
iter 20 value 84.791329
iter 30 value 84.366680
iter 40 value 83.182524
iter 50 value 82.023950
iter 60 value 81.227179
iter 70 value 81.050941
iter 80 value 80.870695
iter 90 value 80.629324
iter 100 value 80.519456
final value 80.519456
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.614862
iter 10 value 94.653280
iter 20 value 86.932976
iter 30 value 85.428825
iter 40 value 82.357320
iter 50 value 81.438511
iter 60 value 80.139011
iter 70 value 80.095612
iter 80 value 79.925851
iter 90 value 79.860084
iter 100 value 79.782090
final value 79.782090
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.706529
iter 10 value 93.798216
iter 20 value 87.828185
iter 30 value 84.252556
iter 40 value 82.363148
iter 50 value 81.768917
iter 60 value 81.181684
iter 70 value 80.610937
iter 80 value 80.541916
iter 90 value 80.481551
iter 100 value 80.388596
final value 80.388596
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.077088
iter 10 value 95.846375
iter 20 value 95.260592
iter 30 value 87.265074
iter 40 value 84.819702
iter 50 value 82.529664
iter 60 value 82.303836
iter 70 value 82.274786
iter 80 value 81.789270
iter 90 value 80.861979
iter 100 value 80.323288
final value 80.323288
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.814175
iter 10 value 90.511341
iter 20 value 84.244425
iter 30 value 83.644318
iter 40 value 83.027294
iter 50 value 82.790122
iter 60 value 82.281789
iter 70 value 82.255487
iter 80 value 82.074630
iter 90 value 81.505486
iter 100 value 81.097131
final value 81.097131
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 119.308988
iter 10 value 94.762745
iter 20 value 94.408502
iter 30 value 86.166536
iter 40 value 85.286221
iter 50 value 85.157106
iter 60 value 84.816180
iter 70 value 84.004080
iter 80 value 82.022487
iter 90 value 81.362116
iter 100 value 80.816412
final value 80.816412
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.748296
final value 94.485789
converged
Fitting Repeat 2
# weights: 103
initial value 96.877273
final value 94.486012
converged
Fitting Repeat 3
# weights: 103
initial value 96.836913
final value 94.485972
converged
Fitting Repeat 4
# weights: 103
initial value 104.214847
iter 10 value 94.485941
final value 94.484218
converged
Fitting Repeat 5
# weights: 103
initial value 96.963778
final value 94.485744
converged
Fitting Repeat 1
# weights: 305
initial value 99.437822
iter 10 value 94.489416
iter 20 value 94.484006
final value 93.810448
converged
Fitting Repeat 2
# weights: 305
initial value 98.954837
iter 10 value 88.966350
iter 20 value 88.249920
iter 30 value 86.949924
iter 40 value 86.938236
iter 50 value 86.935846
iter 60 value 84.866332
iter 70 value 84.825442
iter 80 value 84.823214
iter 80 value 84.823214
final value 84.823214
converged
Fitting Repeat 3
# weights: 305
initial value 96.073459
iter 10 value 94.392548
iter 20 value 94.340006
iter 30 value 94.321063
iter 40 value 90.253702
iter 50 value 88.799752
iter 60 value 87.534357
iter 70 value 84.377780
iter 80 value 84.044904
iter 90 value 83.779007
iter 100 value 82.700590
final value 82.700590
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.666069
iter 10 value 94.383507
iter 20 value 94.359271
iter 30 value 94.356730
iter 40 value 94.315360
iter 50 value 85.402353
iter 60 value 82.515896
iter 70 value 82.085606
iter 80 value 81.441647
iter 90 value 80.655011
iter 100 value 80.480845
final value 80.480845
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.123453
iter 10 value 94.489800
iter 20 value 94.484288
iter 30 value 91.923993
iter 40 value 90.722603
iter 50 value 82.294270
iter 60 value 81.575580
iter 70 value 81.342149
iter 80 value 81.279352
iter 90 value 80.753066
iter 100 value 80.444944
final value 80.444944
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 101.753248
iter 10 value 94.362877
iter 20 value 94.357565
iter 30 value 93.050577
iter 40 value 86.957431
iter 50 value 86.943379
iter 60 value 86.939908
iter 70 value 85.742376
iter 80 value 83.154701
iter 90 value 82.166125
iter 100 value 81.913823
final value 81.913823
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 128.489614
iter 10 value 94.361161
iter 20 value 94.328158
iter 30 value 90.458382
iter 40 value 86.315544
iter 50 value 86.313300
iter 60 value 85.466357
final value 85.465999
converged
Fitting Repeat 3
# weights: 507
initial value 97.342308
iter 10 value 94.362337
iter 20 value 94.354540
iter 30 value 92.606383
iter 40 value 86.345931
iter 50 value 84.299453
iter 60 value 83.849550
iter 70 value 82.875199
iter 80 value 81.692592
iter 90 value 81.692190
final value 81.691930
converged
Fitting Repeat 4
# weights: 507
initial value 101.603215
iter 10 value 92.249323
iter 20 value 91.899525
iter 30 value 91.898740
iter 40 value 91.893792
iter 50 value 91.561361
iter 60 value 90.910043
iter 70 value 83.883734
iter 80 value 81.932379
iter 90 value 80.370089
iter 100 value 79.654499
final value 79.654499
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.822547
iter 10 value 94.364678
iter 20 value 94.358698
iter 30 value 93.930725
iter 40 value 88.106674
iter 50 value 84.848207
iter 60 value 84.823475
iter 70 value 84.798377
iter 80 value 84.798147
iter 90 value 84.797364
iter 100 value 83.833638
final value 83.833638
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 115.122782
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 102.414498
final value 93.836066
converged
Fitting Repeat 3
# weights: 103
initial value 102.009720
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 100.649514
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 96.230663
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 101.893237
iter 10 value 93.901766
iter 20 value 85.323632
iter 30 value 85.321488
iter 40 value 85.321378
iter 40 value 85.321378
iter 40 value 85.321378
final value 85.321378
converged
Fitting Repeat 2
# weights: 305
initial value 108.074364
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 95.963820
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 104.146725
final value 93.836066
converged
Fitting Repeat 5
# weights: 305
initial value 104.704921
iter 10 value 85.976292
iter 20 value 84.734963
iter 30 value 84.734144
iter 30 value 84.734144
iter 30 value 84.734144
final value 84.734144
converged
Fitting Repeat 1
# weights: 507
initial value 100.289975
iter 10 value 93.836067
final value 93.836066
converged
Fitting Repeat 2
# weights: 507
initial value 107.241171
iter 10 value 93.836166
final value 93.836066
converged
Fitting Repeat 3
# weights: 507
initial value 96.081111
final value 94.052447
converged
Fitting Repeat 4
# weights: 507
initial value 101.832754
iter 10 value 88.065838
iter 20 value 85.746854
iter 30 value 85.652946
iter 40 value 85.651313
final value 85.651282
converged
Fitting Repeat 5
# weights: 507
initial value 96.184194
final value 93.836066
converged
Fitting Repeat 1
# weights: 103
initial value 99.032911
iter 10 value 93.898025
iter 20 value 93.423615
iter 30 value 92.702047
iter 40 value 82.694996
iter 50 value 82.276368
iter 60 value 82.117655
iter 70 value 81.365422
iter 80 value 81.324922
iter 90 value 80.540993
iter 100 value 80.538893
final value 80.538893
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 95.707825
iter 10 value 92.130961
iter 20 value 86.994686
iter 30 value 86.299374
iter 40 value 84.132390
iter 50 value 83.539683
iter 60 value 82.435052
iter 70 value 81.586881
iter 80 value 80.815268
iter 90 value 80.723728
iter 100 value 80.599454
final value 80.599454
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.656427
iter 10 value 94.057323
iter 20 value 94.028433
iter 30 value 93.941886
iter 40 value 93.936336
iter 50 value 93.935612
iter 60 value 93.935094
iter 70 value 93.717662
iter 80 value 88.777539
iter 90 value 83.460039
iter 100 value 82.472619
final value 82.472619
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.654769
iter 10 value 93.978763
iter 20 value 87.861415
iter 30 value 85.479754
iter 40 value 82.216766
iter 50 value 81.323438
iter 60 value 80.841976
iter 70 value 80.839463
final value 80.839355
converged
Fitting Repeat 5
# weights: 103
initial value 100.536063
iter 10 value 93.887887
iter 20 value 89.039161
iter 30 value 87.372673
iter 40 value 85.895743
iter 50 value 81.789181
iter 60 value 81.009145
iter 70 value 80.998883
final value 80.998875
converged
Fitting Repeat 1
# weights: 305
initial value 123.833673
iter 10 value 94.255270
iter 20 value 93.172773
iter 30 value 87.874841
iter 40 value 86.007702
iter 50 value 82.584147
iter 60 value 80.037288
iter 70 value 77.908562
iter 80 value 77.148861
iter 90 value 77.089007
iter 100 value 76.770059
final value 76.770059
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.713030
iter 10 value 94.651693
iter 20 value 94.016640
iter 30 value 90.526552
iter 40 value 88.853356
iter 50 value 82.148336
iter 60 value 81.738742
iter 70 value 81.644631
iter 80 value 80.949003
iter 90 value 79.039200
iter 100 value 77.739286
final value 77.739286
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 116.083270
iter 10 value 90.334969
iter 20 value 84.180927
iter 30 value 82.612437
iter 40 value 81.974363
iter 50 value 80.027790
iter 60 value 78.781629
iter 70 value 78.737143
iter 80 value 78.714333
iter 90 value 78.316271
iter 100 value 77.509620
final value 77.509620
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.492491
iter 10 value 93.905672
iter 20 value 89.212941
iter 30 value 88.217740
iter 40 value 87.616991
iter 50 value 84.207065
iter 60 value 81.950166
iter 70 value 81.748830
iter 80 value 81.323098
iter 90 value 81.039155
iter 100 value 79.682923
final value 79.682923
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.107728
iter 10 value 94.733671
iter 20 value 93.993643
iter 30 value 89.794816
iter 40 value 84.615854
iter 50 value 83.551080
iter 60 value 81.647222
iter 70 value 80.466817
iter 80 value 79.270026
iter 90 value 78.330012
iter 100 value 77.969443
final value 77.969443
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.163211
iter 10 value 94.044512
iter 20 value 86.611110
iter 30 value 79.927152
iter 40 value 78.534945
iter 50 value 77.544784
iter 60 value 77.255497
iter 70 value 77.145716
iter 80 value 76.980199
iter 90 value 76.858686
iter 100 value 76.779341
final value 76.779341
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.478394
iter 10 value 91.112850
iter 20 value 82.348693
iter 30 value 81.565700
iter 40 value 79.266124
iter 50 value 78.533896
iter 60 value 77.948758
iter 70 value 77.178768
iter 80 value 76.904582
iter 90 value 76.440859
iter 100 value 76.339485
final value 76.339485
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.147552
iter 10 value 90.900880
iter 20 value 84.976890
iter 30 value 80.634955
iter 40 value 79.147269
iter 50 value 78.146873
iter 60 value 77.956356
iter 70 value 77.484002
iter 80 value 76.995978
iter 90 value 76.913914
iter 100 value 76.733604
final value 76.733604
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 124.149290
iter 10 value 94.343616
iter 20 value 89.531149
iter 30 value 83.980555
iter 40 value 78.819426
iter 50 value 78.111947
iter 60 value 77.736776
iter 70 value 77.583567
iter 80 value 77.159277
iter 90 value 76.906618
iter 100 value 76.802369
final value 76.802369
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 120.821903
iter 10 value 90.482540
iter 20 value 85.838819
iter 30 value 79.850292
iter 40 value 78.757247
iter 50 value 78.420891
iter 60 value 77.644893
iter 70 value 76.904018
iter 80 value 76.571673
iter 90 value 76.445219
iter 100 value 76.283113
final value 76.283113
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 111.136740
final value 94.054532
converged
Fitting Repeat 2
# weights: 103
initial value 95.494652
final value 94.054449
converged
Fitting Repeat 3
# weights: 103
initial value 107.364144
final value 94.054474
converged
Fitting Repeat 4
# weights: 103
initial value 94.369193
final value 94.054363
converged
Fitting Repeat 5
# weights: 103
initial value 96.060323
iter 10 value 94.054427
final value 94.052924
converged
Fitting Repeat 1
# weights: 305
initial value 103.104132
iter 10 value 94.058122
iter 20 value 94.045268
iter 30 value 84.981868
final value 83.651293
converged
Fitting Repeat 2
# weights: 305
initial value 104.225060
iter 10 value 90.578742
iter 20 value 89.926505
iter 30 value 89.924768
iter 30 value 89.924767
iter 30 value 89.924767
final value 89.924767
converged
Fitting Repeat 3
# weights: 305
initial value 102.177751
iter 10 value 94.057695
iter 20 value 94.054389
iter 30 value 94.052634
iter 40 value 89.657158
iter 50 value 81.837822
iter 60 value 81.756084
iter 70 value 81.750206
iter 80 value 81.749912
iter 90 value 81.749152
iter 100 value 81.533356
final value 81.533356
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.285835
iter 10 value 94.057422
iter 20 value 94.056966
iter 30 value 94.054531
iter 40 value 93.990988
iter 50 value 93.838458
iter 60 value 93.837168
iter 70 value 93.398370
iter 80 value 84.233507
iter 90 value 84.063074
iter 100 value 82.640109
final value 82.640109
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 97.789352
iter 10 value 93.729320
iter 20 value 89.034874
iter 30 value 83.042441
iter 40 value 78.939588
iter 50 value 78.508989
iter 60 value 77.762772
iter 70 value 77.567836
iter 80 value 77.567703
final value 77.567333
converged
Fitting Repeat 1
# weights: 507
initial value 132.403958
iter 10 value 94.020918
iter 20 value 94.012676
iter 30 value 91.401230
iter 40 value 81.248139
iter 50 value 77.800585
iter 60 value 76.387053
iter 70 value 75.984133
iter 80 value 75.979842
iter 90 value 75.978281
final value 75.978155
converged
Fitting Repeat 2
# weights: 507
initial value 101.824480
iter 10 value 93.844131
iter 20 value 92.620093
iter 30 value 81.871217
iter 40 value 81.827048
iter 50 value 81.826881
iter 60 value 81.826225
iter 70 value 81.742894
iter 80 value 80.740855
iter 90 value 79.585457
iter 100 value 78.103783
final value 78.103783
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 92.940053
iter 10 value 91.058138
iter 20 value 91.014475
iter 30 value 90.978496
final value 90.972559
converged
Fitting Repeat 4
# weights: 507
initial value 101.983234
iter 10 value 93.844049
iter 20 value 93.838433
iter 30 value 93.836133
iter 40 value 92.860030
iter 50 value 82.236883
iter 60 value 80.679658
iter 70 value 77.908094
iter 80 value 77.158535
iter 90 value 75.811229
iter 100 value 75.565560
final value 75.565560
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 100.988789
iter 10 value 94.059960
iter 20 value 93.964301
iter 30 value 83.656783
final value 83.651588
converged
Fitting Repeat 1
# weights: 103
initial value 97.102719
final value 94.252920
converged
Fitting Repeat 2
# weights: 103
initial value 96.405241
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 107.670622
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 103.483547
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 97.648653
iter 10 value 90.755543
iter 20 value 87.395633
iter 30 value 85.116479
iter 40 value 85.077370
iter 50 value 85.060968
iter 60 value 85.059554
final value 85.059491
converged
Fitting Repeat 1
# weights: 305
initial value 103.456669
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 101.987095
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 113.683873
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 104.658741
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 115.752835
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 95.808797
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 101.854875
final value 94.466823
converged
Fitting Repeat 3
# weights: 507
initial value 110.180717
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 102.701609
final value 94.466823
converged
Fitting Repeat 5
# weights: 507
initial value 95.971748
iter 10 value 90.052453
iter 20 value 85.888450
iter 30 value 85.172935
iter 40 value 84.879999
final value 84.878678
converged
Fitting Repeat 1
# weights: 103
initial value 100.800672
iter 10 value 94.025134
iter 20 value 93.498681
iter 30 value 91.541189
iter 40 value 88.962702
iter 50 value 88.644304
iter 60 value 88.571570
iter 70 value 88.557991
iter 80 value 88.006452
iter 90 value 84.236252
iter 100 value 82.940097
final value 82.940097
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 99.834264
iter 10 value 94.486965
iter 20 value 93.613654
iter 30 value 88.946525
iter 40 value 87.442430
iter 50 value 87.120728
iter 60 value 86.836549
iter 70 value 84.136147
iter 80 value 83.897758
iter 90 value 83.883254
iter 100 value 83.875939
final value 83.875939
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.555707
iter 10 value 94.491331
iter 20 value 94.334835
iter 30 value 94.033536
iter 40 value 93.984968
iter 50 value 93.948221
iter 60 value 85.759250
iter 70 value 84.269694
iter 80 value 84.041923
iter 90 value 83.963932
iter 100 value 83.936500
final value 83.936500
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.150496
iter 10 value 94.447699
iter 20 value 94.035954
iter 30 value 93.993842
iter 40 value 92.062214
iter 50 value 84.679873
iter 60 value 83.124428
iter 70 value 81.641224
iter 80 value 81.114583
final value 81.102143
converged
Fitting Repeat 5
# weights: 103
initial value 100.417542
iter 10 value 94.023762
iter 20 value 93.980211
iter 30 value 93.955924
iter 40 value 89.532657
iter 50 value 85.195744
iter 60 value 84.742926
iter 70 value 84.021191
iter 80 value 83.925331
iter 90 value 83.876137
final value 83.874865
converged
Fitting Repeat 1
# weights: 305
initial value 104.427699
iter 10 value 94.260464
iter 20 value 87.997508
iter 30 value 84.832423
iter 40 value 84.628964
iter 50 value 84.108758
iter 60 value 84.033258
iter 70 value 83.713217
iter 80 value 81.226524
iter 90 value 80.645140
iter 100 value 80.479766
final value 80.479766
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.869454
iter 10 value 94.524240
iter 20 value 93.773061
iter 30 value 89.651713
iter 40 value 88.839032
iter 50 value 88.347004
iter 60 value 86.171443
iter 70 value 84.726562
iter 80 value 83.706617
iter 90 value 82.103086
iter 100 value 80.460189
final value 80.460189
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.844392
iter 10 value 94.498030
iter 20 value 94.103729
iter 30 value 93.314195
iter 40 value 88.369564
iter 50 value 85.946057
iter 60 value 85.519073
iter 70 value 85.179625
iter 80 value 83.265466
iter 90 value 80.859714
iter 100 value 80.305724
final value 80.305724
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 114.647394
iter 10 value 94.458850
iter 20 value 93.591489
iter 30 value 88.965653
iter 40 value 86.660548
iter 50 value 84.388442
iter 60 value 82.834685
iter 70 value 81.764930
iter 80 value 81.492421
iter 90 value 80.922837
iter 100 value 80.741650
final value 80.741650
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.423442
iter 10 value 94.873595
iter 20 value 89.346334
iter 30 value 88.708341
iter 40 value 87.511499
iter 50 value 83.280829
iter 60 value 81.914616
iter 70 value 81.728888
iter 80 value 81.073483
iter 90 value 80.015894
iter 100 value 79.897787
final value 79.897787
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 114.243546
iter 10 value 94.561900
iter 20 value 92.740765
iter 30 value 88.585147
iter 40 value 85.079457
iter 50 value 82.514276
iter 60 value 81.977765
iter 70 value 81.773806
iter 80 value 81.488092
iter 90 value 81.238501
iter 100 value 80.565913
final value 80.565913
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 114.244703
iter 10 value 94.467672
iter 20 value 90.158221
iter 30 value 86.840886
iter 40 value 83.236722
iter 50 value 82.608225
iter 60 value 81.768717
iter 70 value 80.865532
iter 80 value 80.394768
iter 90 value 80.242341
iter 100 value 79.934485
final value 79.934485
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.667795
iter 10 value 86.710852
iter 20 value 84.349199
iter 30 value 81.973956
iter 40 value 81.471605
iter 50 value 81.010872
iter 60 value 80.494191
iter 70 value 79.898873
iter 80 value 79.741219
iter 90 value 79.692127
iter 100 value 79.622118
final value 79.622118
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 115.005981
iter 10 value 94.603972
iter 20 value 94.438304
iter 30 value 94.025712
iter 40 value 90.690051
iter 50 value 83.292363
iter 60 value 82.515635
iter 70 value 81.630212
iter 80 value 80.622215
iter 90 value 80.233064
iter 100 value 80.161080
final value 80.161080
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.337423
iter 10 value 94.444569
iter 20 value 90.587879
iter 30 value 86.222318
iter 40 value 84.908326
iter 50 value 83.624708
iter 60 value 83.328864
iter 70 value 82.680480
iter 80 value 81.575747
iter 90 value 81.115033
iter 100 value 80.218590
final value 80.218590
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.783420
final value 94.485790
converged
Fitting Repeat 2
# weights: 103
initial value 99.514460
final value 94.485706
converged
Fitting Repeat 3
# weights: 103
initial value 100.764046
iter 10 value 94.485846
iter 20 value 94.484250
iter 30 value 85.850504
final value 85.747542
converged
Fitting Repeat 4
# weights: 103
initial value 104.293862
final value 94.485895
converged
Fitting Repeat 5
# weights: 103
initial value 98.501067
final value 94.486147
converged
Fitting Repeat 1
# weights: 305
initial value 96.713284
iter 10 value 94.485988
iter 20 value 89.501032
iter 30 value 87.091213
iter 40 value 86.580995
iter 50 value 86.479191
iter 60 value 86.476206
iter 70 value 86.475694
iter 80 value 86.472365
iter 90 value 86.469387
iter 100 value 86.467765
final value 86.467765
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.390614
iter 10 value 94.488445
iter 20 value 94.346115
iter 30 value 90.969750
iter 40 value 85.227173
iter 50 value 82.932145
iter 60 value 81.662280
iter 70 value 81.646422
iter 80 value 81.645526
final value 81.644121
converged
Fitting Repeat 3
# weights: 305
initial value 100.277780
iter 10 value 94.489044
iter 20 value 94.462123
iter 30 value 93.991513
iter 30 value 93.991512
final value 93.991501
converged
Fitting Repeat 4
# weights: 305
initial value 103.947483
iter 10 value 94.489120
iter 20 value 94.484447
final value 94.484224
converged
Fitting Repeat 5
# weights: 305
initial value 95.884394
iter 10 value 94.488167
iter 20 value 94.209606
iter 30 value 86.002378
iter 40 value 83.765627
final value 83.756405
converged
Fitting Repeat 1
# weights: 507
initial value 118.669842
iter 10 value 94.494960
iter 20 value 93.716500
iter 30 value 93.005078
iter 40 value 92.154812
iter 50 value 92.130892
iter 60 value 91.211211
iter 70 value 91.181965
iter 80 value 91.084801
iter 90 value 90.993916
iter 100 value 90.991570
final value 90.991570
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.578726
iter 10 value 94.474713
iter 20 value 94.467605
final value 94.466905
converged
Fitting Repeat 3
# weights: 507
initial value 110.483507
iter 10 value 86.111256
iter 20 value 85.449609
iter 30 value 85.442564
iter 40 value 84.112642
iter 50 value 84.077969
iter 60 value 83.951793
iter 70 value 83.908849
iter 80 value 83.370083
iter 90 value 83.077941
iter 100 value 81.895646
final value 81.895646
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.873063
iter 10 value 94.491893
iter 20 value 94.443829
iter 30 value 92.280238
final value 92.279738
converged
Fitting Repeat 5
# weights: 507
initial value 101.308201
iter 10 value 94.491751
iter 20 value 94.484302
iter 30 value 92.204697
iter 40 value 86.251199
iter 50 value 85.557834
iter 60 value 81.738680
iter 70 value 79.348693
iter 80 value 79.306618
iter 90 value 79.299333
iter 100 value 79.286002
final value 79.286002
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.146145
final value 94.052911
converged
Fitting Repeat 2
# weights: 103
initial value 98.400992
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 99.894729
final value 93.836066
converged
Fitting Repeat 4
# weights: 103
initial value 96.643252
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 95.453768
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 112.762370
iter 10 value 93.593528
iter 20 value 93.573797
final value 93.573739
converged
Fitting Repeat 2
# weights: 305
initial value 97.940106
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 105.613263
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 97.157751
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 100.195361
iter 10 value 93.841263
final value 93.518236
converged
Fitting Repeat 1
# weights: 507
initial value 99.728928
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 104.753110
iter 10 value 93.549199
iter 20 value 93.544799
iter 30 value 93.480142
final value 93.479964
converged
Fitting Repeat 3
# weights: 507
initial value 94.500953
final value 94.052908
converged
Fitting Repeat 4
# weights: 507
initial value 101.726234
iter 10 value 93.694307
iter 20 value 93.687934
final value 93.687903
converged
Fitting Repeat 5
# weights: 507
initial value 94.554701
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 99.388869
iter 10 value 93.607441
iter 20 value 93.120921
iter 30 value 90.688775
iter 40 value 87.809107
iter 50 value 87.159039
iter 60 value 86.960845
iter 70 value 86.578653
iter 80 value 85.481848
iter 90 value 84.912194
iter 100 value 84.714867
final value 84.714867
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.572965
iter 10 value 94.011200
iter 20 value 93.621923
iter 30 value 89.940693
iter 40 value 86.839152
iter 50 value 86.518261
iter 60 value 86.451485
final value 86.438677
converged
Fitting Repeat 3
# weights: 103
initial value 95.730907
iter 10 value 94.044790
iter 20 value 93.816491
iter 30 value 93.027074
iter 40 value 90.280158
iter 50 value 89.364464
iter 60 value 88.889783
iter 70 value 88.154718
iter 80 value 87.905292
final value 87.872463
converged
Fitting Repeat 4
# weights: 103
initial value 100.555721
iter 10 value 94.056515
iter 20 value 93.912495
iter 30 value 93.740854
iter 40 value 91.554858
iter 50 value 89.780391
iter 60 value 85.792149
iter 70 value 85.235353
iter 80 value 84.926866
iter 90 value 84.765668
iter 100 value 84.714010
final value 84.714010
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 98.653384
iter 10 value 94.106776
iter 20 value 93.691686
iter 30 value 93.597078
iter 40 value 92.272443
iter 50 value 90.015550
iter 60 value 88.464218
iter 70 value 88.136382
iter 80 value 87.662860
iter 90 value 87.302874
iter 100 value 87.021174
final value 87.021174
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 113.648890
iter 10 value 94.056361
iter 20 value 93.616686
iter 30 value 93.586340
iter 40 value 92.912846
iter 50 value 87.022992
iter 60 value 86.633298
iter 70 value 85.332337
iter 80 value 84.705319
iter 90 value 84.149526
iter 100 value 83.963347
final value 83.963347
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 112.164874
iter 10 value 93.640739
iter 20 value 91.229381
iter 30 value 87.908065
iter 40 value 87.511777
iter 50 value 86.203261
iter 60 value 85.797408
iter 70 value 85.217773
iter 80 value 84.811053
iter 90 value 84.457383
iter 100 value 83.958867
final value 83.958867
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.183138
iter 10 value 94.057397
iter 20 value 93.361217
iter 30 value 91.679268
iter 40 value 88.729314
iter 50 value 86.740238
iter 60 value 86.106709
iter 70 value 85.498571
iter 80 value 84.292099
iter 90 value 83.761573
iter 100 value 83.377232
final value 83.377232
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.338297
iter 10 value 94.159209
iter 20 value 88.052420
iter 30 value 87.661030
iter 40 value 87.610625
iter 50 value 87.403090
iter 60 value 86.402561
iter 70 value 85.521935
iter 80 value 84.164910
iter 90 value 83.767465
iter 100 value 83.690299
final value 83.690299
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.565934
iter 10 value 96.981644
iter 20 value 91.434773
iter 30 value 87.244915
iter 40 value 86.933898
iter 50 value 86.656292
iter 60 value 86.378096
iter 70 value 86.222248
iter 80 value 86.049356
iter 90 value 86.036360
iter 100 value 85.940878
final value 85.940878
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 116.357600
iter 10 value 94.091241
iter 20 value 90.266591
iter 30 value 87.664206
iter 40 value 86.752796
iter 50 value 86.156893
iter 60 value 85.882358
iter 70 value 84.474829
iter 80 value 84.261534
iter 90 value 83.976299
iter 100 value 83.576090
final value 83.576090
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 124.380413
iter 10 value 94.148661
iter 20 value 91.162017
iter 30 value 87.360254
iter 40 value 86.456143
iter 50 value 85.407093
iter 60 value 84.428253
iter 70 value 83.892406
iter 80 value 83.578727
iter 90 value 83.300819
iter 100 value 83.155080
final value 83.155080
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.333932
iter 10 value 93.930801
iter 20 value 91.405826
iter 30 value 89.540728
iter 40 value 89.336989
iter 50 value 87.487733
iter 60 value 87.015091
iter 70 value 85.802528
iter 80 value 84.531408
iter 90 value 83.922170
iter 100 value 83.716939
final value 83.716939
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 121.024078
iter 10 value 94.021537
iter 20 value 91.489361
iter 30 value 89.038863
iter 40 value 88.270027
iter 50 value 87.395086
iter 60 value 85.153474
iter 70 value 84.850590
iter 80 value 84.584986
iter 90 value 83.910258
iter 100 value 83.562386
final value 83.562386
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.518212
iter 10 value 93.958316
iter 20 value 93.606989
iter 30 value 88.014709
iter 40 value 87.001758
iter 50 value 86.335316
iter 60 value 85.242482
iter 70 value 84.007127
iter 80 value 83.756220
iter 90 value 83.722621
iter 100 value 83.620817
final value 83.620817
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.047766
final value 93.838034
converged
Fitting Repeat 2
# weights: 103
initial value 96.995565
iter 10 value 94.054448
iter 20 value 94.052921
iter 30 value 90.426467
iter 40 value 90.324499
iter 50 value 87.387915
final value 87.377201
converged
Fitting Repeat 3
# weights: 103
initial value 103.162409
iter 10 value 94.032429
iter 20 value 93.837864
final value 93.837772
converged
Fitting Repeat 4
# weights: 103
initial value 97.523784
iter 10 value 93.837715
iter 20 value 93.837623
iter 30 value 93.606111
iter 40 value 93.605535
final value 93.604888
converged
Fitting Repeat 5
# weights: 103
initial value 108.642538
final value 94.054395
converged
Fitting Repeat 1
# weights: 305
initial value 105.858284
iter 10 value 93.846117
iter 20 value 93.613499
iter 30 value 93.608823
final value 93.607236
converged
Fitting Repeat 2
# weights: 305
initial value 97.837015
iter 10 value 88.412460
iter 20 value 88.134379
iter 30 value 87.958153
iter 40 value 87.813063
iter 50 value 87.812399
iter 60 value 87.810651
final value 87.810447
converged
Fitting Repeat 3
# weights: 305
initial value 94.907669
iter 10 value 94.057329
iter 20 value 94.048656
iter 30 value 92.784181
iter 40 value 92.497394
iter 50 value 92.496863
iter 60 value 90.149823
iter 70 value 89.976183
iter 80 value 87.112896
iter 90 value 86.209881
iter 100 value 84.196967
final value 84.196967
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.175206
iter 10 value 94.057703
iter 20 value 94.012026
iter 30 value 92.949458
iter 40 value 92.933850
iter 50 value 92.933310
iter 60 value 92.735872
iter 70 value 87.365989
final value 87.365983
converged
Fitting Repeat 5
# weights: 305
initial value 106.419402
iter 10 value 94.058099
iter 20 value 93.994490
final value 93.836280
converged
Fitting Repeat 1
# weights: 507
initial value 109.107795
iter 10 value 93.297300
iter 20 value 93.286554
iter 30 value 89.814889
iter 40 value 87.038740
iter 50 value 84.880985
iter 60 value 84.333825
iter 70 value 83.991086
iter 80 value 83.977053
iter 90 value 83.380989
iter 100 value 83.106857
final value 83.106857
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.831908
iter 10 value 94.061353
iter 20 value 93.958398
iter 30 value 87.423267
iter 40 value 87.366260
iter 50 value 87.334407
iter 60 value 87.333492
iter 60 value 87.333491
iter 60 value 87.333491
final value 87.333491
converged
Fitting Repeat 3
# weights: 507
initial value 123.805963
iter 10 value 94.061109
iter 20 value 94.039948
iter 30 value 90.281118
iter 40 value 89.096321
iter 50 value 89.065213
iter 60 value 89.064220
iter 60 value 89.064220
iter 60 value 89.064220
final value 89.064220
converged
Fitting Repeat 4
# weights: 507
initial value 104.421687
iter 10 value 93.670228
iter 20 value 93.581948
iter 30 value 93.579933
iter 40 value 93.574127
iter 50 value 93.565413
iter 60 value 88.574883
iter 70 value 87.941647
iter 80 value 87.153987
iter 90 value 87.137896
iter 100 value 86.929938
final value 86.929938
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 98.196570
iter 10 value 92.009801
iter 20 value 88.209912
iter 30 value 86.160638
iter 40 value 86.051904
iter 50 value 85.999504
iter 60 value 85.995009
iter 70 value 84.727221
iter 80 value 84.483896
iter 90 value 83.886189
iter 100 value 83.743878
final value 83.743878
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 174.362197
iter 10 value 124.163988
iter 20 value 112.583673
iter 30 value 110.050567
iter 40 value 109.539256
iter 50 value 109.381319
iter 60 value 105.873744
iter 70 value 103.314772
iter 80 value 102.743046
iter 90 value 102.526741
iter 100 value 102.350160
final value 102.350160
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 124.415333
iter 10 value 116.807906
iter 20 value 108.059833
iter 30 value 105.826537
iter 40 value 102.725754
iter 50 value 102.250525
iter 60 value 101.394333
iter 70 value 101.082950
iter 80 value 100.994933
iter 90 value 100.845609
iter 100 value 100.811919
final value 100.811919
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 126.165270
iter 10 value 121.043781
iter 20 value 115.252380
iter 30 value 114.339045
iter 40 value 113.859630
iter 50 value 111.968962
iter 60 value 107.720173
iter 70 value 103.857819
iter 80 value 102.914992
iter 90 value 102.562159
iter 100 value 102.235604
final value 102.235604
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 127.492728
iter 10 value 117.104704
iter 20 value 108.771068
iter 30 value 107.426567
iter 40 value 106.632513
iter 50 value 105.012727
iter 60 value 103.624889
iter 70 value 103.002500
iter 80 value 102.767192
iter 90 value 102.593155
iter 100 value 101.900270
final value 101.900270
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 123.727015
iter 10 value 117.765401
iter 20 value 117.565306
iter 30 value 111.702901
iter 40 value 109.228728
iter 50 value 107.436670
iter 60 value 104.306352
iter 70 value 103.112573
iter 80 value 102.845194
iter 90 value 102.777313
iter 100 value 102.228195
final value 102.228195
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Thu Oct 17 02:28:46 2024
***********************************************
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
45.28 1.60 48.40
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.97 | 1.98 | 36.15 | |
| FreqInteractors | 0.25 | 0.00 | 0.26 | |
| calculateAAC | 0.04 | 0.00 | 0.04 | |
| calculateAutocor | 0.44 | 0.13 | 0.57 | |
| calculateCTDC | 0.09 | 0.00 | 0.09 | |
| calculateCTDD | 0.67 | 0.05 | 0.72 | |
| calculateCTDT | 0.31 | 0.01 | 0.32 | |
| calculateCTriad | 0.35 | 0.06 | 0.41 | |
| calculateDC | 0.09 | 0.00 | 0.09 | |
| calculateF | 0.38 | 0.00 | 0.37 | |
| calculateKSAAP | 0.15 | 0.02 | 0.18 | |
| calculateQD_Sm | 2.08 | 0.14 | 2.21 | |
| calculateTC | 1.92 | 0.11 | 2.04 | |
| calculateTC_Sm | 0.28 | 0.00 | 0.28 | |
| corr_plot | 33.21 | 1.68 | 34.92 | |
| enrichfindP | 0.59 | 0.14 | 13.94 | |
| enrichfind_hp | 0.11 | 0.02 | 1.04 | |
| enrichplot | 0.41 | 0.01 | 0.44 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.02 | 0.02 | 2.29 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.00 | 0.02 | 0.02 | |
| plotPPI | 0.08 | 0.00 | 0.08 | |
| pred_ensembel | 15.21 | 0.46 | 11.67 | |
| var_imp | 32.94 | 1.32 | 34.25 | |