Matineh Rahmatbakhsh
| Snapshot Date: 2024-07-15 14:00 -0400 (Mon, 15 Jul 2024) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: 74e36f0 |
| git_last_commit_date: 2024-04-30 11:37:16 -0400 (Tue, 30 Apr 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2024-07-16 11:40 -0400 (Tue, 16 Jul 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4677 |
| palomino6 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4416 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4444 |
| kjohnson3 | macOS 13.6.5 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4393 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4373 |
| 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 963/2243 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.11.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino6 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.6.5 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | 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: 1.11.0 |
| Command: C:\Users\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=C:\Users\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.11.0.tar.gz |
| StartedAt: 2024-07-16 00:52:58 -0400 (Tue, 16 Jul 2024) |
| EndedAt: 2024-07-16 00:58:07 -0400 (Tue, 16 Jul 2024) |
| EllapsedTime: 309.2 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### C:\Users\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=C:\Users\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.11.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'C:/Users/biocbuild/bbs-3.20-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 '1.11.0'
* 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
var_imp 35.76 1.29 37.24
FSmethod 34.83 1.59 33.95
corr_plot 34.41 1.88 33.15
pred_ensembel 18.63 1.99 16.79
enrichfindP 2.19 0.12 18.00
* 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
'C:/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### C:\Users\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'C:/Users/biocbuild/bbs-3.20-bioc/R/library' * installing *source* package 'HPiP' ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.4.1 (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 98.602318
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 101.203963
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 94.122661
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 99.671502
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 102.066908
iter 10 value 94.052976
final value 94.052911
converged
Fitting Repeat 1
# weights: 305
initial value 114.854202
final value 94.011429
converged
Fitting Repeat 2
# weights: 305
initial value 105.078913
iter 10 value 93.478227
iter 10 value 93.478227
iter 10 value 93.478227
final value 93.478227
converged
Fitting Repeat 3
# weights: 305
initial value 100.811806
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 107.804326
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 103.423782
iter 10 value 85.636026
iter 20 value 83.472835
iter 30 value 83.233874
final value 83.233861
converged
Fitting Repeat 1
# weights: 507
initial value 95.803174
final value 93.836066
converged
Fitting Repeat 2
# weights: 507
initial value 100.965909
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 100.495251
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 106.050990
iter 10 value 93.839852
final value 93.836066
converged
Fitting Repeat 5
# weights: 507
initial value 103.340091
final value 93.743590
converged
Fitting Repeat 1
# weights: 103
initial value 107.992147
iter 10 value 93.656501
iter 20 value 91.830907
iter 30 value 91.061209
iter 40 value 91.001742
iter 50 value 89.340176
iter 60 value 88.616675
iter 70 value 85.077787
iter 80 value 84.121773
iter 90 value 81.521044
iter 100 value 80.274958
final value 80.274958
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.534263
iter 10 value 94.054880
iter 20 value 93.731976
iter 30 value 93.441184
iter 40 value 93.346579
iter 50 value 91.666387
iter 60 value 83.843286
iter 70 value 80.724423
iter 80 value 80.160133
iter 90 value 79.699216
iter 100 value 79.553038
final value 79.553038
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 100.052787
iter 10 value 94.059332
iter 20 value 93.552111
iter 30 value 93.324504
iter 40 value 93.269013
iter 50 value 87.420942
iter 60 value 86.032844
iter 70 value 84.025236
iter 80 value 82.512253
iter 90 value 82.252734
iter 100 value 82.251952
final value 82.251952
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.356212
iter 10 value 93.970693
iter 20 value 93.408461
iter 30 value 93.379726
iter 40 value 92.911608
iter 50 value 86.987640
iter 60 value 86.879613
iter 70 value 86.823129
iter 80 value 86.822990
iter 90 value 86.766947
iter 100 value 84.424161
final value 84.424161
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.053447
iter 10 value 93.764290
iter 20 value 90.745415
iter 30 value 90.623979
iter 40 value 90.608214
final value 90.608175
converged
Fitting Repeat 1
# weights: 305
initial value 107.086326
iter 10 value 94.416291
iter 20 value 92.695165
iter 30 value 87.464271
iter 40 value 83.567384
iter 50 value 82.223955
iter 60 value 82.009747
iter 70 value 81.581761
iter 80 value 80.605114
iter 90 value 79.885987
iter 100 value 79.722637
final value 79.722637
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.117220
iter 10 value 93.922008
iter 20 value 93.450248
iter 30 value 93.307408
iter 40 value 84.921416
iter 50 value 83.568729
iter 60 value 81.176021
iter 70 value 80.359076
iter 80 value 79.899033
iter 90 value 79.811102
iter 100 value 79.388959
final value 79.388959
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 110.756926
iter 10 value 93.160261
iter 20 value 84.611817
iter 30 value 81.818330
iter 40 value 80.763934
iter 50 value 80.071884
iter 60 value 79.308194
iter 70 value 78.393197
iter 80 value 78.259433
iter 90 value 78.224470
iter 100 value 78.205330
final value 78.205330
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 114.687837
iter 10 value 94.051376
iter 20 value 92.425271
iter 30 value 91.205629
iter 40 value 90.650365
iter 50 value 89.927612
iter 60 value 86.858898
iter 70 value 84.361424
iter 80 value 79.736083
iter 90 value 78.833609
iter 100 value 78.621956
final value 78.621956
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.164781
iter 10 value 93.397450
iter 20 value 84.107031
iter 30 value 83.632862
iter 40 value 81.832883
iter 50 value 81.304138
iter 60 value 81.146093
iter 70 value 80.151447
iter 80 value 79.014104
iter 90 value 78.637640
iter 100 value 78.348729
final value 78.348729
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.338033
iter 10 value 94.362791
iter 20 value 91.552901
iter 30 value 91.240797
iter 40 value 87.859990
iter 50 value 84.324024
iter 60 value 81.035267
iter 70 value 80.246102
iter 80 value 79.976191
iter 90 value 79.674801
iter 100 value 79.598841
final value 79.598841
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 131.942923
iter 10 value 97.946695
iter 20 value 94.304627
iter 30 value 93.889783
iter 40 value 82.089087
iter 50 value 81.125209
iter 60 value 80.880961
iter 70 value 80.703057
iter 80 value 79.936588
iter 90 value 79.467089
iter 100 value 79.355471
final value 79.355471
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.416088
iter 10 value 94.350971
iter 20 value 92.689975
iter 30 value 83.155036
iter 40 value 82.037214
iter 50 value 81.081915
iter 60 value 80.584898
iter 70 value 79.535086
iter 80 value 78.718034
iter 90 value 78.638171
iter 100 value 78.570212
final value 78.570212
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.117890
iter 10 value 95.356127
iter 20 value 86.602789
iter 30 value 85.921211
iter 40 value 83.280768
iter 50 value 83.117869
iter 60 value 83.012716
iter 70 value 82.906140
iter 80 value 82.620330
iter 90 value 82.245988
iter 100 value 81.057607
final value 81.057607
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.531631
iter 10 value 93.733446
iter 20 value 86.957017
iter 30 value 81.127689
iter 40 value 80.259908
iter 50 value 78.604400
iter 60 value 78.236615
iter 70 value 78.158536
iter 80 value 78.097966
iter 90 value 78.036771
iter 100 value 78.007722
final value 78.007722
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.530403
final value 94.054818
converged
Fitting Repeat 2
# weights: 103
initial value 101.154455
final value 94.054697
converged
Fitting Repeat 3
# weights: 103
initial value 114.518289
iter 10 value 94.054548
iter 20 value 94.009746
final value 93.836197
converged
Fitting Repeat 4
# weights: 103
initial value 98.362916
final value 94.054603
converged
Fitting Repeat 5
# weights: 103
initial value 106.918556
final value 94.054493
converged
Fitting Repeat 1
# weights: 305
initial value 94.641566
iter 10 value 94.056358
iter 20 value 94.033422
iter 30 value 84.198090
iter 40 value 82.168774
final value 82.168758
converged
Fitting Repeat 2
# weights: 305
initial value 95.899346
iter 10 value 93.865282
iter 20 value 93.863201
iter 30 value 93.806458
iter 40 value 93.788930
iter 50 value 93.784962
iter 60 value 82.741491
iter 70 value 82.737889
iter 80 value 82.168416
iter 80 value 82.168415
iter 80 value 82.168415
final value 82.168415
converged
Fitting Repeat 3
# weights: 305
initial value 101.765527
iter 10 value 93.880660
iter 20 value 93.795376
iter 30 value 93.788861
iter 40 value 93.786272
iter 50 value 93.448982
iter 60 value 84.308494
iter 70 value 83.354390
iter 80 value 83.344761
iter 90 value 83.344544
iter 90 value 83.344544
iter 90 value 83.344544
final value 83.344544
converged
Fitting Repeat 4
# weights: 305
initial value 99.930605
iter 10 value 94.053094
iter 20 value 86.861041
final value 85.954488
converged
Fitting Repeat 5
# weights: 305
initial value 105.506344
iter 10 value 94.058135
iter 20 value 93.307220
final value 93.111255
converged
Fitting Repeat 1
# weights: 507
initial value 106.093447
iter 10 value 94.061107
iter 20 value 94.002673
iter 30 value 84.838163
iter 40 value 82.235588
iter 50 value 81.732709
iter 60 value 81.546381
iter 70 value 81.495789
iter 80 value 81.322130
iter 90 value 81.320249
iter 90 value 81.320249
final value 81.320249
converged
Fitting Repeat 2
# weights: 507
initial value 110.779963
iter 10 value 93.407815
iter 20 value 93.394218
iter 30 value 93.151432
iter 40 value 93.111470
iter 40 value 93.111470
iter 40 value 93.111470
final value 93.111470
converged
Fitting Repeat 3
# weights: 507
initial value 96.004962
iter 10 value 93.844334
iter 20 value 88.086943
iter 30 value 83.998348
iter 40 value 83.997188
iter 50 value 82.129089
iter 60 value 82.126647
iter 70 value 82.126416
final value 82.126336
converged
Fitting Repeat 4
# weights: 507
initial value 102.030965
iter 10 value 93.844495
iter 20 value 93.837602
iter 30 value 93.797427
iter 40 value 88.393177
iter 50 value 88.280597
iter 60 value 88.273710
iter 70 value 88.235744
iter 80 value 87.993934
iter 90 value 87.543795
iter 100 value 84.595315
final value 84.595315
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 108.356468
iter 10 value 93.844148
iter 20 value 93.837623
iter 30 value 88.560230
iter 40 value 84.063075
iter 50 value 82.269442
iter 60 value 80.803134
iter 70 value 80.744734
iter 80 value 80.680652
iter 90 value 80.596212
iter 100 value 80.594455
final value 80.594455
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.781181
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.218383
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.012346
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 99.011429
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 105.533214
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 135.503693
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 94.806066
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 94.831281
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 121.061288
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 112.602623
final value 94.038251
converged
Fitting Repeat 1
# weights: 507
initial value 104.474010
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 98.769096
final value 94.027933
converged
Fitting Repeat 3
# weights: 507
initial value 98.391040
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 105.858472
iter 10 value 94.050978
iter 20 value 90.711246
iter 30 value 89.603160
final value 89.518522
converged
Fitting Repeat 5
# weights: 507
initial value 127.415032
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 96.441843
iter 10 value 94.064860
iter 20 value 92.842548
iter 30 value 90.373196
iter 40 value 88.947475
iter 50 value 88.448255
iter 60 value 87.972895
iter 70 value 87.237744
iter 80 value 87.147042
final value 87.141230
converged
Fitting Repeat 2
# weights: 103
initial value 96.274185
iter 10 value 89.721843
iter 20 value 89.059997
iter 30 value 88.620976
iter 40 value 88.482288
iter 50 value 88.479248
final value 88.479009
converged
Fitting Repeat 3
# weights: 103
initial value 108.938077
iter 10 value 94.056771
iter 20 value 90.701884
iter 30 value 87.917767
iter 40 value 87.841132
iter 50 value 87.740187
iter 60 value 87.704995
final value 87.704898
converged
Fitting Repeat 4
# weights: 103
initial value 103.796335
iter 10 value 93.595746
iter 20 value 87.392423
iter 30 value 86.700110
iter 40 value 86.538322
iter 50 value 86.411017
iter 60 value 86.334316
iter 70 value 86.314688
iter 80 value 86.204098
iter 90 value 85.322935
iter 100 value 85.111869
final value 85.111869
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 109.481557
iter 10 value 94.051584
iter 20 value 90.798266
iter 30 value 88.990020
iter 40 value 88.647466
iter 50 value 88.640009
iter 60 value 88.635247
final value 88.635243
converged
Fitting Repeat 1
# weights: 305
initial value 110.132762
iter 10 value 94.093356
iter 20 value 93.916845
iter 30 value 90.876708
iter 40 value 88.302413
iter 50 value 86.495002
iter 60 value 85.817332
iter 70 value 85.561185
iter 80 value 85.360787
iter 90 value 85.205033
iter 100 value 85.173974
final value 85.173974
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 109.451424
iter 10 value 94.070645
iter 20 value 92.161821
iter 30 value 87.849394
iter 40 value 86.745693
iter 50 value 86.053981
iter 60 value 85.700952
iter 70 value 85.103835
iter 80 value 84.573031
iter 90 value 84.393047
iter 100 value 84.389401
final value 84.389401
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.139198
iter 10 value 94.043221
iter 20 value 91.661052
iter 30 value 89.202326
iter 40 value 88.324352
iter 50 value 87.695581
iter 60 value 85.133855
iter 70 value 83.901191
iter 80 value 83.674337
iter 90 value 83.436717
iter 100 value 83.409261
final value 83.409261
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.902695
iter 10 value 94.164512
iter 20 value 90.241057
iter 30 value 88.659796
iter 40 value 87.816106
iter 50 value 87.117578
iter 60 value 86.839351
iter 70 value 84.961212
iter 80 value 84.400458
iter 90 value 83.937063
iter 100 value 83.402651
final value 83.402651
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.171651
iter 10 value 94.288638
iter 20 value 94.021804
iter 30 value 91.818325
iter 40 value 90.089636
iter 50 value 88.654874
iter 60 value 88.445672
iter 70 value 88.348906
iter 80 value 87.869472
iter 90 value 86.406233
iter 100 value 85.968601
final value 85.968601
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.588474
iter 10 value 94.068094
iter 20 value 90.053498
iter 30 value 89.193781
iter 40 value 88.689764
iter 50 value 88.543885
iter 60 value 87.449940
iter 70 value 86.098857
iter 80 value 85.117887
iter 90 value 84.201426
iter 100 value 83.956087
final value 83.956087
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 128.108993
iter 10 value 94.142255
iter 20 value 94.030150
iter 30 value 91.882508
iter 40 value 89.862935
iter 50 value 88.718966
iter 60 value 85.644167
iter 70 value 84.974201
iter 80 value 83.337770
iter 90 value 83.150908
iter 100 value 83.064132
final value 83.064132
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 130.650795
iter 10 value 94.653455
iter 20 value 94.124804
iter 30 value 90.651555
iter 40 value 89.183898
iter 50 value 88.295815
iter 60 value 87.641505
iter 70 value 87.068975
iter 80 value 85.591822
iter 90 value 85.202531
iter 100 value 84.697747
final value 84.697747
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.122540
iter 10 value 94.365367
iter 20 value 89.345257
iter 30 value 88.940712
iter 40 value 88.778147
iter 50 value 87.775051
iter 60 value 86.434271
iter 70 value 85.885690
iter 80 value 85.353454
iter 90 value 84.459895
iter 100 value 84.230044
final value 84.230044
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.757543
iter 10 value 94.447451
iter 20 value 89.450480
iter 30 value 88.676810
iter 40 value 88.506897
iter 50 value 88.350493
iter 60 value 87.042687
iter 70 value 85.636192
iter 80 value 84.542737
iter 90 value 84.328181
iter 100 value 84.262542
final value 84.262542
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.635776
final value 94.054833
converged
Fitting Repeat 2
# weights: 103
initial value 107.334591
final value 94.054581
converged
Fitting Repeat 3
# weights: 103
initial value 95.672136
final value 94.054544
converged
Fitting Repeat 4
# weights: 103
initial value 97.979807
iter 10 value 93.887917
iter 20 value 93.886951
iter 30 value 93.886206
final value 93.886091
converged
Fitting Repeat 5
# weights: 103
initial value 100.915602
final value 94.054520
converged
Fitting Repeat 1
# weights: 305
initial value 98.959857
iter 10 value 92.879814
iter 20 value 89.292465
iter 30 value 88.820462
iter 40 value 87.925772
final value 87.921401
converged
Fitting Repeat 2
# weights: 305
initial value 94.860169
iter 10 value 88.047448
iter 20 value 88.044175
final value 88.040823
converged
Fitting Repeat 3
# weights: 305
initial value 109.549521
iter 10 value 94.056829
iter 20 value 93.831029
iter 30 value 91.208189
iter 40 value 91.207974
iter 40 value 91.207974
final value 91.207972
converged
Fitting Repeat 4
# weights: 305
initial value 94.061146
iter 10 value 94.053326
final value 94.052920
converged
Fitting Repeat 5
# weights: 305
initial value 96.432315
iter 10 value 94.057654
iter 20 value 93.981206
iter 30 value 89.863054
iter 40 value 87.167646
iter 50 value 87.086080
iter 60 value 87.074809
final value 87.074623
converged
Fitting Repeat 1
# weights: 507
initial value 127.930642
iter 10 value 94.046656
iter 20 value 93.671607
iter 30 value 92.044625
iter 40 value 90.067423
iter 50 value 88.276553
final value 88.270136
converged
Fitting Repeat 2
# weights: 507
initial value 100.989573
iter 10 value 94.028254
iter 20 value 94.023016
iter 30 value 93.788544
iter 40 value 93.787347
iter 50 value 93.781757
iter 60 value 93.532314
iter 70 value 93.340996
iter 80 value 93.333151
iter 90 value 93.328096
iter 100 value 93.058905
final value 93.058905
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 96.943888
iter 10 value 94.054325
iter 20 value 91.344254
iter 30 value 88.753663
iter 40 value 88.739087
iter 50 value 88.736433
iter 60 value 88.214086
iter 70 value 88.067982
iter 80 value 88.034226
final value 88.034225
converged
Fitting Repeat 4
# weights: 507
initial value 99.437187
iter 10 value 93.946006
iter 20 value 93.903150
iter 30 value 93.885346
iter 40 value 93.878759
iter 50 value 93.877818
iter 60 value 93.046448
iter 70 value 89.365577
iter 80 value 88.812076
iter 90 value 88.011108
iter 100 value 86.920044
final value 86.920044
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.648431
iter 10 value 93.432839
iter 20 value 88.321176
iter 30 value 85.220308
iter 40 value 84.517613
iter 50 value 84.515070
iter 60 value 84.502997
iter 70 value 84.159143
iter 80 value 84.156974
final value 84.155905
converged
Fitting Repeat 1
# weights: 103
initial value 103.389940
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 102.871682
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.563354
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 99.368660
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 100.208784
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 110.000173
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 104.063937
final value 94.354396
converged
Fitting Repeat 3
# weights: 305
initial value 109.209780
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 102.455899
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 115.839041
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 95.028961
iter 10 value 84.709858
iter 20 value 84.588757
final value 84.588745
converged
Fitting Repeat 2
# weights: 507
initial value 97.986285
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 108.018715
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 104.157185
iter 10 value 93.109891
iter 10 value 93.109890
iter 10 value 93.109890
final value 93.109890
converged
Fitting Repeat 5
# weights: 507
initial value 121.783074
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 99.700668
iter 10 value 94.480826
iter 20 value 84.708634
iter 30 value 84.451201
iter 40 value 82.787784
iter 50 value 82.646647
final value 82.646451
converged
Fitting Repeat 2
# weights: 103
initial value 106.497734
iter 10 value 94.420518
iter 20 value 90.687595
iter 30 value 88.133877
iter 40 value 84.068632
iter 50 value 82.896074
iter 60 value 82.662332
iter 70 value 82.646500
final value 82.646451
converged
Fitting Repeat 3
# weights: 103
initial value 103.656201
iter 10 value 94.523404
iter 20 value 94.477357
iter 30 value 93.521802
iter 40 value 93.488912
iter 50 value 93.481573
iter 60 value 85.176797
iter 70 value 83.740239
iter 80 value 83.059507
iter 90 value 82.994652
iter 100 value 82.834323
final value 82.834323
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.569177
iter 10 value 94.437805
iter 20 value 87.838998
iter 30 value 86.468195
iter 40 value 86.246766
iter 50 value 85.097525
iter 60 value 84.599806
iter 70 value 82.843222
iter 80 value 82.152750
iter 90 value 81.781393
iter 100 value 81.635534
final value 81.635534
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 103.914246
iter 10 value 94.349127
iter 20 value 84.349564
iter 30 value 84.240058
iter 40 value 82.708454
iter 50 value 82.290105
iter 60 value 82.100664
iter 70 value 82.095643
iter 80 value 82.095047
iter 90 value 82.090045
iter 100 value 82.084896
final value 82.084896
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 102.518658
iter 10 value 94.255411
iter 20 value 85.357212
iter 30 value 84.241962
iter 40 value 82.163788
iter 50 value 80.455264
iter 60 value 79.902750
iter 70 value 79.659514
iter 80 value 79.630297
iter 90 value 79.623257
iter 100 value 79.620009
final value 79.620009
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 119.158239
iter 10 value 94.675643
iter 20 value 87.442377
iter 30 value 84.763479
iter 40 value 82.972762
iter 50 value 82.808735
iter 60 value 82.697083
iter 70 value 81.370571
iter 80 value 80.859914
iter 90 value 80.400954
iter 100 value 80.030677
final value 80.030677
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 113.520777
iter 10 value 94.545251
iter 20 value 94.491143
iter 30 value 91.732103
iter 40 value 86.546002
iter 50 value 86.054833
iter 60 value 85.542907
iter 70 value 85.280281
iter 80 value 82.475759
iter 90 value 81.813507
iter 100 value 81.098126
final value 81.098126
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.028092
iter 10 value 94.709867
iter 20 value 90.230691
iter 30 value 84.718835
iter 40 value 81.584026
iter 50 value 80.886422
iter 60 value 80.528676
iter 70 value 79.849817
iter 80 value 79.685566
iter 90 value 79.675422
iter 100 value 79.654691
final value 79.654691
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.755851
iter 10 value 94.506252
iter 20 value 91.565949
iter 30 value 85.991581
iter 40 value 84.031572
iter 50 value 82.363921
iter 60 value 82.212346
iter 70 value 81.926996
iter 80 value 81.642937
iter 90 value 81.553758
iter 100 value 81.281928
final value 81.281928
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 133.568536
iter 10 value 94.719577
iter 20 value 93.798596
iter 30 value 90.280023
iter 40 value 87.706267
iter 50 value 84.365659
iter 60 value 80.659453
iter 70 value 80.201415
iter 80 value 79.629300
iter 90 value 79.166987
iter 100 value 79.064709
final value 79.064709
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.949364
iter 10 value 90.769536
iter 20 value 86.778705
iter 30 value 85.877368
iter 40 value 84.355140
iter 50 value 82.615399
iter 60 value 82.117420
iter 70 value 80.744977
iter 80 value 80.221220
iter 90 value 80.113512
iter 100 value 79.989631
final value 79.989631
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.655082
iter 10 value 94.346539
iter 20 value 92.727672
iter 30 value 86.085657
iter 40 value 83.563521
iter 50 value 82.379547
iter 60 value 82.044956
iter 70 value 81.345766
iter 80 value 80.984139
iter 90 value 80.582544
iter 100 value 80.420738
final value 80.420738
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.066678
iter 10 value 93.994172
iter 20 value 90.980761
iter 30 value 87.634329
iter 40 value 84.099700
iter 50 value 81.846206
iter 60 value 80.853405
iter 70 value 80.601462
iter 80 value 80.391702
iter 90 value 80.129465
iter 100 value 79.789188
final value 79.789188
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 116.104695
iter 10 value 92.355113
iter 20 value 83.989618
iter 30 value 83.242335
iter 40 value 82.670372
iter 50 value 82.098509
iter 60 value 81.580846
iter 70 value 81.266525
iter 80 value 81.172604
iter 90 value 81.135198
iter 100 value 80.938626
final value 80.938626
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.449729
final value 94.485793
converged
Fitting Repeat 2
# weights: 103
initial value 97.692167
final value 94.485891
converged
Fitting Repeat 3
# weights: 103
initial value 97.616668
final value 94.485909
converged
Fitting Repeat 4
# weights: 103
initial value 96.197308
final value 94.356039
converged
Fitting Repeat 5
# weights: 103
initial value 104.736593
final value 94.356185
converged
Fitting Repeat 1
# weights: 305
initial value 96.436038
iter 10 value 94.359367
iter 20 value 92.229612
iter 30 value 84.443618
iter 40 value 83.914902
final value 83.912867
converged
Fitting Repeat 2
# weights: 305
initial value 130.146792
iter 10 value 94.489070
iter 20 value 94.484594
iter 30 value 94.372709
iter 40 value 94.154974
iter 50 value 94.152571
final value 94.152568
converged
Fitting Repeat 3
# weights: 305
initial value 97.781940
iter 10 value 94.487505
iter 20 value 94.262902
iter 30 value 94.159571
iter 40 value 94.159284
final value 94.159167
converged
Fitting Repeat 4
# weights: 305
initial value 100.214094
iter 10 value 94.487393
iter 20 value 94.114522
iter 30 value 84.179749
iter 40 value 84.093788
iter 50 value 83.594125
final value 83.594033
converged
Fitting Repeat 5
# weights: 305
initial value 102.521749
iter 10 value 94.269947
iter 20 value 94.265467
iter 30 value 91.101750
final value 91.089639
converged
Fitting Repeat 1
# weights: 507
initial value 97.230677
iter 10 value 84.767316
iter 20 value 83.299092
iter 30 value 83.284888
iter 40 value 83.282933
iter 50 value 83.280232
iter 60 value 83.279944
final value 83.279507
converged
Fitting Repeat 2
# weights: 507
initial value 95.489264
iter 10 value 94.320026
iter 20 value 92.290464
iter 30 value 82.327389
iter 40 value 81.458610
iter 50 value 80.925468
iter 60 value 80.568620
iter 70 value 80.492788
iter 80 value 80.426302
iter 90 value 80.144606
iter 100 value 78.214182
final value 78.214182
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 100.171361
iter 10 value 94.492998
iter 20 value 89.785942
iter 30 value 85.676633
iter 40 value 85.163488
iter 50 value 85.158539
final value 85.158518
converged
Fitting Repeat 4
# weights: 507
initial value 99.340396
iter 10 value 94.362249
iter 20 value 94.253904
iter 30 value 93.018551
iter 40 value 92.783657
iter 50 value 85.647055
iter 60 value 83.623281
iter 70 value 83.616736
final value 83.616733
converged
Fitting Repeat 5
# weights: 507
initial value 104.086049
iter 10 value 90.935843
iter 20 value 88.905949
final value 88.896210
converged
Fitting Repeat 1
# weights: 103
initial value 99.343520
final value 94.443243
converged
Fitting Repeat 2
# weights: 103
initial value 106.367743
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.674427
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.622015
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.689692
iter 10 value 94.457505
final value 94.449438
converged
Fitting Repeat 1
# weights: 305
initial value 96.414565
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 106.861986
iter 10 value 94.385017
iter 20 value 88.620273
iter 30 value 81.927243
iter 40 value 80.499329
iter 50 value 80.432190
final value 80.432030
converged
Fitting Repeat 3
# weights: 305
initial value 96.103162
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 96.159117
iter 10 value 84.476199
iter 20 value 81.973235
iter 30 value 81.897727
final value 81.897581
converged
Fitting Repeat 5
# weights: 305
initial value 114.330332
final value 94.046703
converged
Fitting Repeat 1
# weights: 507
initial value 110.177552
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 107.143515
iter 10 value 94.306258
final value 94.291327
converged
Fitting Repeat 3
# weights: 507
initial value 104.500672
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 97.114614
iter 10 value 94.129410
iter 20 value 93.783602
iter 30 value 86.483412
iter 40 value 82.590701
iter 50 value 82.286808
iter 60 value 82.095305
iter 70 value 79.302600
iter 80 value 79.162535
iter 90 value 79.160116
iter 100 value 79.160063
final value 79.160063
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 96.082880
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 98.049901
iter 10 value 94.500647
iter 20 value 94.328978
iter 30 value 88.388971
iter 40 value 81.710031
iter 50 value 80.863254
iter 60 value 80.770967
iter 70 value 80.724498
iter 80 value 80.703223
iter 90 value 79.755887
iter 100 value 79.147954
final value 79.147954
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.866422
iter 10 value 94.430135
iter 20 value 88.183455
iter 30 value 83.652782
iter 40 value 82.841064
iter 50 value 81.299710
iter 60 value 80.861743
iter 70 value 80.668892
iter 80 value 80.519872
final value 80.493357
converged
Fitting Repeat 3
# weights: 103
initial value 97.581814
iter 10 value 94.512482
iter 20 value 94.488579
iter 30 value 85.486091
iter 40 value 82.199982
iter 50 value 81.655296
iter 60 value 81.084590
iter 70 value 80.772510
iter 80 value 80.670290
iter 90 value 80.630531
iter 100 value 80.520121
final value 80.520121
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 102.588537
iter 10 value 93.767509
iter 20 value 83.369662
iter 30 value 81.221490
iter 40 value 80.839629
iter 50 value 80.630795
iter 60 value 79.908762
iter 70 value 79.458683
iter 80 value 79.352720
iter 90 value 79.227541
iter 100 value 79.001980
final value 79.001980
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 101.053946
iter 10 value 94.487844
iter 20 value 94.425250
iter 30 value 90.652809
iter 40 value 85.792975
iter 50 value 82.869566
iter 60 value 82.572953
iter 70 value 81.579273
iter 80 value 80.849291
iter 90 value 80.656942
final value 80.649355
converged
Fitting Repeat 1
# weights: 305
initial value 120.745465
iter 10 value 93.082600
iter 20 value 84.338699
iter 30 value 82.964898
iter 40 value 81.033390
iter 50 value 80.605046
iter 60 value 79.676040
iter 70 value 78.217333
iter 80 value 77.824782
iter 90 value 77.358816
iter 100 value 77.219414
final value 77.219414
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 111.163921
iter 10 value 94.532574
iter 20 value 94.059660
iter 30 value 84.900199
iter 40 value 84.038795
iter 50 value 82.572484
iter 60 value 80.084655
iter 70 value 78.512895
iter 80 value 78.272718
iter 90 value 78.057033
iter 100 value 77.980558
final value 77.980558
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 118.459589
iter 10 value 98.665500
iter 20 value 87.834333
iter 30 value 81.738232
iter 40 value 81.524578
iter 50 value 80.166378
iter 60 value 78.746262
iter 70 value 78.344068
iter 80 value 78.169382
iter 90 value 77.845521
iter 100 value 77.768625
final value 77.768625
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 125.561130
iter 10 value 94.385209
iter 20 value 90.045270
iter 30 value 88.497057
iter 40 value 84.386155
iter 50 value 82.836701
iter 60 value 81.630529
iter 70 value 80.106070
iter 80 value 79.541563
iter 90 value 78.789707
iter 100 value 78.221069
final value 78.221069
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.599145
iter 10 value 94.448689
iter 20 value 88.234889
iter 30 value 83.681866
iter 40 value 81.881702
iter 50 value 81.731763
iter 60 value 81.077241
iter 70 value 79.761064
iter 80 value 78.481697
iter 90 value 77.732800
iter 100 value 77.526357
final value 77.526357
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 121.604971
iter 10 value 96.377798
iter 20 value 90.057073
iter 30 value 81.594934
iter 40 value 79.772181
iter 50 value 79.581690
iter 60 value 78.858031
iter 70 value 78.641091
iter 80 value 78.494144
iter 90 value 78.383088
iter 100 value 78.228795
final value 78.228795
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.104450
iter 10 value 89.793853
iter 20 value 86.721729
iter 30 value 84.678481
iter 40 value 84.118524
iter 50 value 83.774449
iter 60 value 82.907586
iter 70 value 82.534238
iter 80 value 82.410397
iter 90 value 82.284538
iter 100 value 79.454412
final value 79.454412
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 134.084538
iter 10 value 94.609099
iter 20 value 93.356710
iter 30 value 91.809070
iter 40 value 86.575204
iter 50 value 83.454546
iter 60 value 82.602181
iter 70 value 80.496388
iter 80 value 78.921803
iter 90 value 78.380248
iter 100 value 78.130285
final value 78.130285
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.363977
iter 10 value 95.417347
iter 20 value 84.220925
iter 30 value 82.293882
iter 40 value 82.114947
iter 50 value 81.063303
iter 60 value 80.126033
iter 70 value 79.386863
iter 80 value 79.178864
iter 90 value 78.710136
iter 100 value 78.224198
final value 78.224198
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.865100
iter 10 value 94.409514
iter 20 value 91.873066
iter 30 value 91.373498
iter 40 value 90.669153
iter 50 value 88.959518
iter 60 value 81.133123
iter 70 value 80.041718
iter 80 value 79.406456
iter 90 value 78.604660
iter 100 value 78.121873
final value 78.121873
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.845718
iter 10 value 94.485694
iter 20 value 94.484259
final value 94.484215
converged
Fitting Repeat 2
# weights: 103
initial value 97.314778
final value 94.485760
converged
Fitting Repeat 3
# weights: 103
initial value 96.754054
final value 94.486050
converged
Fitting Repeat 4
# weights: 103
initial value 99.132257
final value 94.485795
converged
Fitting Repeat 5
# weights: 103
initial value 98.176170
final value 94.485944
converged
Fitting Repeat 1
# weights: 305
initial value 95.505784
iter 10 value 94.489025
iter 20 value 94.484083
iter 30 value 92.980055
iter 40 value 84.430755
iter 50 value 84.403703
final value 84.402858
converged
Fitting Repeat 2
# weights: 305
initial value 104.373201
iter 10 value 94.488805
iter 20 value 84.439928
iter 30 value 81.317467
final value 81.307308
converged
Fitting Repeat 3
# weights: 305
initial value 102.431006
iter 10 value 94.488667
iter 20 value 83.686378
iter 30 value 83.474357
iter 40 value 82.697894
iter 50 value 82.030332
iter 60 value 82.029282
iter 70 value 81.469936
iter 80 value 79.623040
iter 90 value 78.101837
iter 100 value 77.089925
final value 77.089925
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 95.868076
iter 10 value 94.447985
iter 20 value 94.445854
final value 94.445826
converged
Fitting Repeat 5
# weights: 305
initial value 97.436182
iter 10 value 94.489462
iter 20 value 94.433891
iter 30 value 92.690437
iter 40 value 85.290016
iter 50 value 84.944408
iter 60 value 84.038574
iter 70 value 84.031540
final value 84.031068
converged
Fitting Repeat 1
# weights: 507
initial value 97.830226
iter 10 value 94.501132
iter 20 value 94.458202
iter 30 value 94.454045
iter 40 value 94.422272
iter 50 value 83.770771
iter 60 value 83.743059
iter 70 value 83.733276
iter 80 value 83.697900
iter 90 value 81.406083
iter 100 value 80.202673
final value 80.202673
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 95.408121
iter 10 value 94.450703
iter 20 value 94.236716
iter 30 value 94.231731
iter 40 value 86.345034
iter 50 value 86.003389
iter 60 value 84.484183
iter 70 value 80.359141
iter 80 value 80.358976
iter 90 value 79.998206
iter 100 value 79.609337
final value 79.609337
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 97.553344
iter 10 value 94.492396
iter 20 value 94.425053
iter 30 value 85.509204
iter 40 value 84.521300
final value 84.520569
converged
Fitting Repeat 4
# weights: 507
initial value 97.026505
iter 10 value 84.704999
iter 20 value 83.884055
final value 83.883993
converged
Fitting Repeat 5
# weights: 507
initial value 122.265781
iter 10 value 94.429379
iter 20 value 93.555694
iter 30 value 85.520083
iter 40 value 84.976278
iter 50 value 84.971675
iter 60 value 84.970603
final value 84.970135
converged
Fitting Repeat 1
# weights: 103
initial value 98.555825
final value 94.477594
converged
Fitting Repeat 2
# weights: 103
initial value 99.568833
iter 10 value 91.271455
iter 20 value 91.266260
final value 91.265072
converged
Fitting Repeat 3
# weights: 103
initial value 110.051450
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 94.392842
final value 93.637383
converged
Fitting Repeat 5
# weights: 103
initial value 102.012532
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 94.529690
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 137.438634
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 103.638039
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 96.220498
iter 10 value 93.630936
final value 93.630886
converged
Fitting Repeat 5
# weights: 305
initial value 111.551866
final value 94.026542
converged
Fitting Repeat 1
# weights: 507
initial value 112.916611
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 101.735755
iter 10 value 94.484137
iter 10 value 94.484137
iter 10 value 94.484137
final value 94.484137
converged
Fitting Repeat 3
# weights: 507
initial value 124.882842
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 98.337868
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 105.207332
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 97.659548
iter 10 value 94.490319
iter 20 value 92.440847
iter 30 value 91.645811
iter 40 value 91.498034
iter 50 value 91.375424
iter 60 value 90.769140
iter 70 value 86.188078
iter 80 value 86.001142
iter 90 value 85.498466
iter 100 value 83.998442
final value 83.998442
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.851459
iter 10 value 94.130793
iter 20 value 90.786949
iter 30 value 85.766717
iter 40 value 84.944724
iter 50 value 84.689851
iter 60 value 84.619246
iter 70 value 82.760962
iter 80 value 82.566013
iter 90 value 82.465033
final value 82.465032
converged
Fitting Repeat 3
# weights: 103
initial value 98.326116
iter 10 value 94.530149
iter 20 value 94.373163
iter 30 value 91.523617
iter 40 value 90.187908
iter 50 value 86.483971
iter 60 value 85.339315
iter 70 value 84.010945
iter 80 value 83.210170
iter 90 value 82.823924
iter 100 value 82.515491
final value 82.515491
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.190361
iter 10 value 94.489213
iter 20 value 94.472654
iter 30 value 92.484659
iter 40 value 85.608185
iter 50 value 85.183205
iter 60 value 85.046929
iter 70 value 84.896994
iter 80 value 84.341104
iter 90 value 84.324862
final value 84.324848
converged
Fitting Repeat 5
# weights: 103
initial value 100.906889
iter 10 value 94.496346
iter 20 value 90.546623
iter 30 value 87.605437
iter 40 value 86.785005
iter 50 value 86.348287
iter 60 value 85.976964
iter 70 value 84.979432
iter 80 value 84.751428
iter 90 value 84.654781
iter 100 value 84.613341
final value 84.613341
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 100.348281
iter 10 value 94.317538
iter 20 value 93.765278
iter 30 value 91.603698
iter 40 value 86.668200
iter 50 value 85.739086
iter 60 value 83.483420
iter 70 value 82.073831
iter 80 value 81.527451
iter 90 value 81.429976
iter 100 value 81.398205
final value 81.398205
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.074819
iter 10 value 93.581417
iter 20 value 86.694346
iter 30 value 86.346729
iter 40 value 84.243081
iter 50 value 82.948468
iter 60 value 81.890416
iter 70 value 81.642114
iter 80 value 81.140013
iter 90 value 81.006669
iter 100 value 80.842337
final value 80.842337
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.143559
iter 10 value 94.411945
iter 20 value 93.032480
iter 30 value 87.342136
iter 40 value 86.332849
iter 50 value 84.984134
iter 60 value 81.664223
iter 70 value 81.295681
iter 80 value 81.118572
iter 90 value 81.005037
iter 100 value 80.942512
final value 80.942512
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.990542
iter 10 value 94.421655
iter 20 value 87.511518
iter 30 value 85.084809
iter 40 value 84.136512
iter 50 value 83.514114
iter 60 value 83.174294
iter 70 value 82.936272
iter 80 value 82.670433
iter 90 value 82.317133
iter 100 value 82.001590
final value 82.001590
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.684745
iter 10 value 94.552655
iter 20 value 89.108377
iter 30 value 85.015052
iter 40 value 84.298618
iter 50 value 83.950886
iter 60 value 83.722956
iter 70 value 82.695888
iter 80 value 81.751741
iter 90 value 81.146104
iter 100 value 80.968460
final value 80.968460
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.782081
iter 10 value 92.669229
iter 20 value 91.343264
iter 30 value 89.106211
iter 40 value 85.830587
iter 50 value 84.696525
iter 60 value 84.280519
iter 70 value 83.820661
iter 80 value 83.488367
iter 90 value 82.965654
iter 100 value 82.355861
final value 82.355861
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.090768
iter 10 value 94.435662
iter 20 value 87.626115
iter 30 value 86.913303
iter 40 value 86.016389
iter 50 value 85.165225
iter 60 value 82.957811
iter 70 value 81.871660
iter 80 value 81.686422
iter 90 value 81.509942
iter 100 value 81.423698
final value 81.423698
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 130.436909
iter 10 value 94.491874
iter 20 value 87.502520
iter 30 value 85.746360
iter 40 value 84.670436
iter 50 value 84.189209
iter 60 value 82.359240
iter 70 value 81.818587
iter 80 value 81.568094
iter 90 value 81.346324
iter 100 value 81.191234
final value 81.191234
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.606954
iter 10 value 95.309511
iter 20 value 87.778505
iter 30 value 84.864002
iter 40 value 84.469132
iter 50 value 84.068382
iter 60 value 83.806903
iter 70 value 83.785811
iter 80 value 83.693811
iter 90 value 83.135648
iter 100 value 81.867719
final value 81.867719
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 110.514043
iter 10 value 94.734063
iter 20 value 94.237985
iter 30 value 90.730202
iter 40 value 86.837146
iter 50 value 84.640040
iter 60 value 83.404477
iter 70 value 82.940903
iter 80 value 82.500061
iter 90 value 82.376566
iter 100 value 82.357154
final value 82.357154
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.052825
final value 94.485726
converged
Fitting Repeat 2
# weights: 103
initial value 101.312347
final value 94.485669
converged
Fitting Repeat 3
# weights: 103
initial value 106.399158
final value 94.485875
converged
Fitting Repeat 4
# weights: 103
initial value 101.420217
final value 94.485718
converged
Fitting Repeat 5
# weights: 103
initial value 99.670440
final value 94.058950
converged
Fitting Repeat 1
# weights: 305
initial value 98.617636
iter 10 value 94.489550
iter 20 value 94.423571
iter 30 value 93.554904
iter 40 value 92.212741
iter 50 value 90.465572
iter 60 value 87.940036
final value 87.938788
converged
Fitting Repeat 2
# weights: 305
initial value 96.056271
iter 10 value 93.642983
iter 20 value 93.634644
final value 93.633383
converged
Fitting Repeat 3
# weights: 305
initial value 103.560858
iter 10 value 94.489154
iter 20 value 94.443988
iter 30 value 91.047018
iter 40 value 90.813819
iter 50 value 88.464733
iter 60 value 87.676136
iter 70 value 87.664473
iter 80 value 87.654422
iter 90 value 87.644076
iter 100 value 87.524121
final value 87.524121
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 95.278929
iter 10 value 94.031425
iter 20 value 94.024713
iter 30 value 93.988170
iter 40 value 93.617749
iter 50 value 93.614866
final value 93.614851
converged
Fitting Repeat 5
# weights: 305
initial value 97.976049
iter 10 value 88.141933
iter 20 value 87.742346
iter 30 value 87.733008
iter 40 value 87.731432
iter 50 value 86.363073
iter 60 value 86.289638
iter 70 value 85.962707
iter 80 value 85.955665
iter 90 value 84.688910
iter 100 value 84.594860
final value 84.594860
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 113.809829
iter 10 value 94.492098
iter 20 value 94.472765
iter 30 value 87.374718
iter 40 value 85.846480
iter 50 value 85.764394
iter 60 value 84.863937
iter 70 value 84.614927
iter 80 value 84.571538
iter 90 value 82.758969
iter 100 value 82.707136
final value 82.707136
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.492834
iter 10 value 94.034707
iter 20 value 92.255602
iter 30 value 87.556934
iter 40 value 87.355222
final value 87.355190
converged
Fitting Repeat 3
# weights: 507
initial value 120.154028
iter 10 value 94.490876
iter 20 value 94.054302
iter 30 value 87.255804
iter 40 value 86.250700
iter 50 value 85.659340
iter 60 value 84.701585
iter 70 value 83.023300
iter 80 value 80.629864
iter 90 value 79.778107
iter 100 value 79.741780
final value 79.741780
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.232800
iter 10 value 93.892937
iter 20 value 93.888589
iter 30 value 93.884101
iter 30 value 93.884101
final value 93.884084
converged
Fitting Repeat 5
# weights: 507
initial value 100.187996
iter 10 value 94.491650
iter 20 value 94.484314
iter 30 value 92.756908
iter 40 value 84.465587
iter 50 value 83.394996
iter 60 value 82.830355
iter 70 value 82.619110
iter 80 value 82.616406
iter 90 value 82.609829
iter 100 value 82.609089
final value 82.609089
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 124.416055
iter 10 value 117.895085
iter 20 value 113.041912
final value 110.229649
converged
Fitting Repeat 2
# weights: 305
initial value 121.784401
iter 10 value 110.880406
iter 20 value 110.844680
iter 30 value 108.467926
iter 40 value 108.398406
final value 108.397662
converged
Fitting Repeat 3
# weights: 305
initial value 119.525087
iter 10 value 117.893745
iter 20 value 117.890349
final value 117.890340
converged
Fitting Repeat 4
# weights: 305
initial value 129.847355
iter 10 value 116.813749
iter 20 value 116.404353
iter 30 value 110.001549
iter 40 value 108.913805
iter 50 value 104.285407
final value 104.284283
converged
Fitting Repeat 5
# weights: 305
initial value 120.879280
iter 10 value 117.763963
iter 20 value 117.762445
iter 30 value 117.753178
iter 40 value 114.268788
iter 50 value 111.064900
iter 60 value 111.040322
iter 70 value 111.010863
iter 80 value 108.563154
iter 90 value 108.545780
iter 100 value 108.515463
final value 108.515463
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 -- Tue Jul 16 00:57:54 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
45.57 6.03 56.34
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 34.83 | 1.59 | 33.95 | |
| FreqInteractors | 0.19 | 0.04 | 0.21 | |
| calculateAAC | 0.05 | 0.00 | 0.05 | |
| calculateAutocor | 0.33 | 0.06 | 0.39 | |
| calculateCTDC | 0.06 | 0.01 | 0.08 | |
| calculateCTDD | 0.47 | 0.03 | 0.50 | |
| calculateCTDT | 0.19 | 0.02 | 0.20 | |
| calculateCTriad | 0.26 | 0.02 | 0.28 | |
| calculateDC | 0.08 | 0.00 | 0.08 | |
| calculateF | 0.25 | 0.03 | 0.28 | |
| calculateKSAAP | 0.1 | 0.0 | 0.1 | |
| calculateQD_Sm | 1.32 | 0.33 | 1.65 | |
| calculateTC | 1.36 | 0.18 | 1.55 | |
| calculateTC_Sm | 0.25 | 0.00 | 0.25 | |
| corr_plot | 34.41 | 1.88 | 33.15 | |
| enrichfindP | 2.19 | 0.12 | 18.00 | |
| enrichfind_hp | 0.08 | 0.02 | 1.52 | |
| enrichplot | 0.28 | 0.03 | 0.31 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.03 | 0.03 | 2.90 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.06 | 0.00 | 0.07 | |
| pred_ensembel | 18.63 | 1.99 | 16.79 | |
| var_imp | 35.76 | 1.29 | 37.24 | |