| Back to Build/check report for BioC 3.17 |
|
This page was generated on 2023-01-02 09:00:33 -0500 (Mon, 02 Jan 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| palomino5 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2022-12-25 r83502 ucrt) -- "Unsuffered Consequences" | 4165 |
| 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 | ||||
|
To the developers/maintainers of the HPiP package: Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 912/2158 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.5.0 (landing page) Matineh Rahmatbakhsh
| palomino5 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ||||||||
| Package: HPiP |
| Version: 1.5.0 |
| Command: F:\biocbuild\bbs-3.17-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.17-bioc\R\library --no-vignettes --timings HPiP_1.5.0.tar.gz |
| StartedAt: 2022-12-29 00:32:58 -0500 (Thu, 29 Dec 2022) |
| EndedAt: 2022-12-29 00:36:51 -0500 (Thu, 29 Dec 2022) |
| EllapsedTime: 232.7 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.17-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.17-bioc\R\library --no-vignettes --timings HPiP_1.5.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.17-bioc-rtools43/meat/HPiP.Rcheck'
* using R Under development (unstable) (2022-12-25 r83502 ucrt)
* using platform: x86_64-w64-mingw32 (64-bit)
* R was compiled by
gcc.exe (GCC) 10.4.0
GNU Fortran (GCC) 10.4.0
* running under: Windows Server 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 '1.5.0'
* 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 ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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 ... OK
* 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 26.88 0.82 27.72
FSmethod 25.22 1.40 26.81
corr_plot 25.67 0.75 26.42
pred_ensembel 11.61 0.40 8.56
enrichfindP 0.37 0.05 7.53
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in 'inst/doc' ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
'F:/biocbuild/bbs-3.17-bioc-rtools43/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.17-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.17-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 Under development (unstable) (2022-12-25 r83502 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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 97.899732
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 103.741587
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 107.428120
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 100.166035
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 107.934203
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 112.177079
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 107.420928
iter 10 value 94.377441
final value 94.354396
converged
Fitting Repeat 3
# weights: 305
initial value 99.839953
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 117.068292
final value 94.354396
converged
Fitting Repeat 5
# weights: 305
initial value 96.689935
final value 94.354396
converged
Fitting Repeat 1
# weights: 507
initial value 113.117914
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 102.491784
final value 94.354396
converged
Fitting Repeat 3
# weights: 507
initial value 99.279929
final value 93.943255
converged
Fitting Repeat 4
# weights: 507
initial value 97.936809
iter 10 value 87.368087
iter 20 value 85.400844
iter 30 value 85.285353
iter 30 value 85.285353
iter 30 value 85.285353
final value 85.285353
converged
Fitting Repeat 5
# weights: 507
initial value 93.579349
iter 10 value 92.195776
iter 20 value 92.188098
final value 92.188059
converged
Fitting Repeat 1
# weights: 103
initial value 103.562732
iter 10 value 94.466202
iter 20 value 94.391837
iter 30 value 94.377647
iter 40 value 83.130619
iter 50 value 81.428594
iter 60 value 80.386714
iter 70 value 78.946960
iter 80 value 78.347203
iter 90 value 78.264355
iter 100 value 78.261307
final value 78.261307
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 107.711590
iter 10 value 94.482107
iter 20 value 92.975123
iter 30 value 85.529085
iter 40 value 82.981046
iter 50 value 80.948048
iter 60 value 80.562862
iter 70 value 79.350671
iter 80 value 78.264965
iter 90 value 78.261013
final value 78.260981
converged
Fitting Repeat 3
# weights: 103
initial value 104.081718
iter 10 value 92.917314
iter 20 value 89.700761
iter 30 value 80.530184
iter 40 value 79.307129
iter 50 value 79.034524
iter 60 value 78.944282
iter 70 value 78.919907
iter 80 value 78.164993
iter 90 value 77.940291
iter 100 value 77.908344
final value 77.908344
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 99.668659
iter 10 value 94.488922
iter 20 value 94.425146
iter 30 value 92.339461
iter 40 value 91.594721
iter 50 value 91.101870
iter 60 value 90.380919
iter 70 value 90.366558
iter 80 value 90.363014
iter 90 value 90.325703
iter 100 value 90.318427
final value 90.318427
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 98.423275
iter 10 value 94.447101
iter 20 value 90.797210
iter 30 value 84.535616
iter 40 value 83.802487
iter 50 value 83.497792
iter 60 value 82.595252
iter 70 value 82.084881
iter 80 value 79.529078
iter 90 value 78.410796
iter 100 value 78.262413
final value 78.262413
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 109.267699
iter 10 value 94.220664
iter 20 value 93.135484
iter 30 value 90.943858
iter 40 value 90.618010
iter 50 value 87.617880
iter 60 value 82.365250
iter 70 value 78.473228
iter 80 value 77.176313
iter 90 value 76.808549
iter 100 value 76.684145
final value 76.684145
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.583363
iter 10 value 95.193807
iter 20 value 93.166492
iter 30 value 91.418243
iter 40 value 82.637256
iter 50 value 81.355349
iter 60 value 80.623414
iter 70 value 79.354674
iter 80 value 78.923523
iter 90 value 78.216684
iter 100 value 77.363554
final value 77.363554
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 114.502951
iter 10 value 94.473879
iter 20 value 86.533025
iter 30 value 85.049701
iter 40 value 84.673123
iter 50 value 83.942735
iter 60 value 80.093104
iter 70 value 79.110359
iter 80 value 77.784077
iter 90 value 76.614622
iter 100 value 76.406488
final value 76.406488
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.983384
iter 10 value 94.483985
iter 20 value 87.464482
iter 30 value 85.693499
iter 40 value 82.309485
iter 50 value 79.970016
iter 60 value 79.530175
iter 70 value 77.989957
iter 80 value 76.404161
iter 90 value 76.194687
iter 100 value 76.145401
final value 76.145401
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.923883
iter 10 value 94.492745
iter 20 value 85.317169
iter 30 value 82.942170
iter 40 value 82.490157
iter 50 value 82.102987
iter 60 value 81.682499
iter 70 value 79.105404
iter 80 value 77.509732
iter 90 value 77.341298
iter 100 value 76.844227
final value 76.844227
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.790244
iter 10 value 94.622135
iter 20 value 94.481168
iter 30 value 94.198151
iter 40 value 83.768129
iter 50 value 82.779060
iter 60 value 82.301421
iter 70 value 80.624053
iter 80 value 79.166064
iter 90 value 78.304338
iter 100 value 77.816598
final value 77.816598
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.807074
iter 10 value 92.951885
iter 20 value 83.490303
iter 30 value 81.278540
iter 40 value 79.761992
iter 50 value 79.243597
iter 60 value 77.641749
iter 70 value 77.387400
iter 80 value 77.088734
iter 90 value 76.742857
iter 100 value 76.456643
final value 76.456643
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 121.675918
iter 10 value 94.385380
iter 20 value 88.242222
iter 30 value 83.079086
iter 40 value 82.106844
iter 50 value 80.799351
iter 60 value 78.919921
iter 70 value 78.134182
iter 80 value 77.789574
iter 90 value 77.519940
iter 100 value 77.305426
final value 77.305426
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 124.640347
iter 10 value 94.726118
iter 20 value 94.545086
iter 30 value 83.441866
iter 40 value 82.762761
iter 50 value 80.439478
iter 60 value 78.746980
iter 70 value 77.519824
iter 80 value 77.323061
iter 90 value 77.001014
iter 100 value 76.892256
final value 76.892256
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.860898
iter 10 value 94.562358
iter 20 value 87.011671
iter 30 value 82.285270
iter 40 value 79.172501
iter 50 value 77.500296
iter 60 value 77.119467
iter 70 value 76.728636
iter 80 value 76.673133
iter 90 value 76.441585
iter 100 value 76.203145
final value 76.203145
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.109947
final value 94.485857
converged
Fitting Repeat 2
# weights: 103
initial value 96.281361
iter 10 value 94.485817
iter 20 value 94.454994
iter 30 value 82.514693
iter 40 value 80.864534
iter 50 value 80.836185
iter 60 value 80.834112
iter 70 value 80.633248
iter 80 value 80.619570
final value 80.619272
converged
Fitting Repeat 3
# weights: 103
initial value 95.903033
iter 10 value 94.486138
iter 20 value 94.484244
iter 20 value 94.484244
iter 20 value 94.484244
final value 94.484244
converged
Fitting Repeat 4
# weights: 103
initial value 101.569262
final value 94.485942
converged
Fitting Repeat 5
# weights: 103
initial value 100.767989
final value 94.485998
converged
Fitting Repeat 1
# weights: 305
initial value 92.746701
iter 10 value 89.994619
iter 20 value 89.960830
iter 30 value 89.957415
iter 40 value 89.858300
iter 50 value 89.855459
final value 89.854923
converged
Fitting Repeat 2
# weights: 305
initial value 98.567737
iter 10 value 94.488898
iter 20 value 94.483545
iter 30 value 92.257618
iter 40 value 84.594606
iter 50 value 84.507038
final value 84.352898
converged
Fitting Repeat 3
# weights: 305
initial value 105.312984
iter 10 value 94.433661
iter 20 value 93.607445
final value 85.513842
converged
Fitting Repeat 4
# weights: 305
initial value 111.024960
iter 10 value 94.489139
iter 20 value 94.484352
iter 30 value 94.120158
iter 40 value 84.099825
iter 50 value 82.583528
iter 60 value 82.373599
iter 70 value 80.255925
iter 80 value 80.250041
final value 80.249389
converged
Fitting Repeat 5
# weights: 305
initial value 96.948753
iter 10 value 94.432562
iter 20 value 94.419409
iter 30 value 87.604475
iter 40 value 86.079831
iter 50 value 86.078113
iter 50 value 86.078113
final value 86.078113
converged
Fitting Repeat 1
# weights: 507
initial value 95.668037
iter 10 value 94.487234
iter 20 value 92.562536
iter 30 value 87.133886
iter 40 value 87.026187
iter 50 value 87.002720
iter 60 value 86.983339
iter 70 value 86.966748
iter 80 value 85.994619
iter 90 value 80.681117
iter 100 value 78.693002
final value 78.693002
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 96.862632
iter 10 value 92.221958
iter 20 value 92.146553
iter 30 value 92.140389
iter 40 value 89.541031
iter 50 value 81.654587
iter 60 value 80.433475
iter 70 value 79.985678
iter 80 value 78.171400
iter 90 value 75.660745
iter 100 value 74.713813
final value 74.713813
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 100.832399
iter 10 value 94.391357
iter 20 value 94.381921
iter 30 value 94.273984
iter 40 value 81.835016
iter 50 value 81.629072
iter 60 value 81.460482
iter 70 value 81.455302
iter 80 value 78.154213
iter 90 value 77.539450
iter 100 value 77.345610
final value 77.345610
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.071242
iter 10 value 94.492008
iter 20 value 94.301183
final value 87.540491
converged
Fitting Repeat 5
# weights: 507
initial value 117.917880
iter 10 value 94.491869
iter 20 value 85.863989
iter 30 value 85.342485
iter 40 value 85.334955
iter 50 value 85.334733
final value 85.334458
converged
Fitting Repeat 1
# weights: 103
initial value 100.396279
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 95.234757
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 98.841216
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.462207
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 93.102023
iter 10 value 92.501715
final value 92.501299
converged
Fitting Repeat 1
# weights: 305
initial value 94.364118
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 113.821452
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 105.146405
iter 10 value 89.772877
final value 89.772792
converged
Fitting Repeat 4
# weights: 305
initial value 116.169995
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 111.269346
final value 93.867391
converged
Fitting Repeat 1
# weights: 507
initial value 114.024886
iter 10 value 93.867395
final value 93.867391
converged
Fitting Repeat 2
# weights: 507
initial value 120.716641
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 110.895678
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 126.671145
iter 10 value 93.867391
iter 10 value 93.867391
iter 10 value 93.867391
final value 93.867391
converged
Fitting Repeat 5
# weights: 507
initial value 98.841324
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 96.209877
iter 10 value 94.018243
iter 20 value 90.274551
iter 30 value 87.450795
iter 40 value 82.900235
iter 50 value 81.990996
iter 60 value 81.066338
iter 70 value 80.982699
iter 80 value 80.642864
iter 90 value 80.549616
final value 80.546352
converged
Fitting Repeat 2
# weights: 103
initial value 97.015072
iter 10 value 94.057010
iter 20 value 93.359913
iter 30 value 91.082838
iter 40 value 90.541560
iter 50 value 88.904827
iter 60 value 81.083345
iter 70 value 80.883903
iter 80 value 80.818319
iter 90 value 80.536128
iter 100 value 80.303438
final value 80.303438
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 95.956037
iter 10 value 94.061640
iter 20 value 91.312523
iter 30 value 83.706450
iter 40 value 82.339981
iter 50 value 82.245947
iter 60 value 81.996222
iter 70 value 81.847993
iter 80 value 81.765195
final value 81.765192
converged
Fitting Repeat 4
# weights: 103
initial value 106.873127
iter 10 value 93.301371
iter 20 value 84.540519
iter 30 value 83.137466
iter 40 value 82.531742
iter 50 value 81.957633
iter 60 value 81.907109
iter 70 value 81.823392
iter 80 value 81.765354
final value 81.765192
converged
Fitting Repeat 5
# weights: 103
initial value 102.021043
iter 10 value 94.055174
iter 20 value 84.965206
iter 30 value 83.954743
iter 40 value 83.046933
iter 50 value 82.452902
iter 60 value 82.410656
iter 70 value 82.358876
iter 80 value 82.254516
iter 90 value 82.124629
iter 100 value 82.034019
final value 82.034019
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.587484
iter 10 value 94.061872
iter 20 value 89.404942
iter 30 value 84.166896
iter 40 value 82.712943
iter 50 value 81.616455
iter 60 value 80.388356
iter 70 value 79.956767
iter 80 value 79.675503
iter 90 value 79.271490
iter 100 value 79.022547
final value 79.022547
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 117.182248
iter 10 value 93.933048
iter 20 value 86.887485
iter 30 value 84.900541
iter 40 value 83.109669
iter 50 value 82.046726
iter 60 value 81.823543
iter 70 value 81.437561
iter 80 value 80.672161
iter 90 value 79.771342
iter 100 value 79.607569
final value 79.607569
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.861202
iter 10 value 94.084871
iter 20 value 93.526500
iter 30 value 89.751945
iter 40 value 83.887963
iter 50 value 83.444264
iter 60 value 83.009833
iter 70 value 82.882398
iter 80 value 82.718103
iter 90 value 81.634345
iter 100 value 81.038004
final value 81.038004
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.252071
iter 10 value 93.924276
iter 20 value 90.979779
iter 30 value 87.178695
iter 40 value 82.279797
iter 50 value 81.692295
iter 60 value 81.335550
iter 70 value 81.176478
iter 80 value 81.124186
iter 90 value 80.659071
iter 100 value 80.058966
final value 80.058966
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.507888
iter 10 value 94.084566
iter 20 value 93.975733
iter 30 value 93.289944
iter 40 value 87.518855
iter 50 value 84.752720
iter 60 value 81.978679
iter 70 value 81.337957
iter 80 value 80.985185
iter 90 value 80.450857
iter 100 value 80.069105
final value 80.069105
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.998136
iter 10 value 91.237022
iter 20 value 89.341567
iter 30 value 83.933424
iter 40 value 82.474745
iter 50 value 82.377075
iter 60 value 82.156188
iter 70 value 80.860527
iter 80 value 80.120007
iter 90 value 80.018657
iter 100 value 79.864357
final value 79.864357
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.481563
iter 10 value 94.116585
iter 20 value 92.296803
iter 30 value 87.665005
iter 40 value 85.160613
iter 50 value 81.434595
iter 60 value 80.724422
iter 70 value 80.395094
iter 80 value 80.027571
iter 90 value 79.614383
iter 100 value 79.568049
final value 79.568049
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.792040
iter 10 value 94.285727
iter 20 value 85.518106
iter 30 value 83.495155
iter 40 value 82.378018
iter 50 value 80.716716
iter 60 value 80.142905
iter 70 value 79.932642
iter 80 value 79.560406
iter 90 value 79.367658
iter 100 value 79.233882
final value 79.233882
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 116.037825
iter 10 value 96.754547
iter 20 value 96.264209
iter 30 value 87.265206
iter 40 value 82.014200
iter 50 value 80.787767
iter 60 value 80.325794
iter 70 value 80.281648
iter 80 value 80.087206
iter 90 value 79.766508
iter 100 value 79.195647
final value 79.195647
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.337756
iter 10 value 94.321413
iter 20 value 87.253055
iter 30 value 84.641715
iter 40 value 83.984720
iter 50 value 82.323512
iter 60 value 81.519042
iter 70 value 81.349399
iter 80 value 80.918540
iter 90 value 80.278209
iter 100 value 79.559813
final value 79.559813
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.167887
final value 94.054650
converged
Fitting Repeat 2
# weights: 103
initial value 98.765686
final value 94.054434
converged
Fitting Repeat 3
# weights: 103
initial value 94.922587
final value 94.054494
converged
Fitting Repeat 4
# weights: 103
initial value 113.865515
iter 10 value 93.869368
iter 20 value 93.814672
iter 30 value 90.218587
iter 40 value 89.924950
iter 50 value 89.625347
iter 60 value 89.625055
iter 70 value 89.624943
iter 80 value 88.381740
iter 80 value 88.381740
final value 88.381740
converged
Fitting Repeat 5
# weights: 103
initial value 96.289404
final value 94.054608
converged
Fitting Repeat 1
# weights: 305
initial value 98.729980
iter 10 value 94.057126
iter 20 value 93.599956
iter 30 value 83.275622
iter 40 value 82.563452
iter 50 value 82.558850
iter 60 value 82.558614
final value 82.557105
converged
Fitting Repeat 2
# weights: 305
initial value 98.809494
iter 10 value 93.872280
iter 20 value 93.868298
iter 30 value 92.020868
iter 40 value 91.849886
iter 50 value 90.615857
final value 90.615407
converged
Fitting Repeat 3
# weights: 305
initial value 94.799405
iter 10 value 94.057268
iter 20 value 93.769018
iter 30 value 83.381197
iter 40 value 83.307056
iter 50 value 83.277600
iter 60 value 82.523853
iter 70 value 79.884936
iter 80 value 79.881660
iter 90 value 79.880328
final value 79.879276
converged
Fitting Repeat 4
# weights: 305
initial value 106.494571
iter 10 value 90.978672
iter 20 value 83.388397
iter 30 value 82.469174
iter 40 value 81.211151
iter 50 value 81.028335
iter 60 value 80.889140
iter 70 value 80.769366
iter 80 value 80.767532
iter 90 value 80.765335
iter 100 value 80.697922
final value 80.697922
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.464231
iter 10 value 94.058193
iter 20 value 94.025362
iter 30 value 89.497896
iter 40 value 89.495794
final value 89.495777
converged
Fitting Repeat 1
# weights: 507
initial value 100.387794
iter 10 value 93.568668
iter 20 value 93.236877
iter 30 value 88.315618
iter 40 value 84.970610
iter 50 value 81.212098
iter 60 value 81.165840
iter 70 value 81.162109
final value 81.162066
converged
Fitting Repeat 2
# weights: 507
initial value 119.315281
iter 10 value 93.874833
iter 20 value 93.869548
iter 30 value 93.869212
iter 40 value 93.850056
iter 50 value 84.913868
iter 60 value 82.943624
iter 70 value 82.548913
iter 80 value 82.336929
iter 90 value 80.272670
iter 100 value 80.012881
final value 80.012881
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 100.991516
iter 10 value 93.203952
iter 20 value 92.900825
iter 30 value 92.900062
iter 40 value 92.896305
iter 50 value 92.895368
iter 60 value 92.864686
iter 70 value 83.356495
iter 80 value 82.938721
iter 90 value 82.707278
iter 100 value 82.625745
final value 82.625745
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 95.809736
iter 10 value 94.051499
iter 20 value 87.798056
iter 30 value 82.978662
iter 40 value 81.719127
final value 81.718727
converged
Fitting Repeat 5
# weights: 507
initial value 117.935051
iter 10 value 93.875880
iter 20 value 93.010176
iter 30 value 85.968280
iter 40 value 85.822209
iter 50 value 85.815538
iter 60 value 85.815461
final value 85.815459
converged
Fitting Repeat 1
# weights: 103
initial value 95.271002
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.039690
iter 10 value 93.290807
iter 20 value 93.288893
final value 93.288889
converged
Fitting Repeat 3
# weights: 103
initial value 97.939774
final value 93.836066
converged
Fitting Repeat 4
# weights: 103
initial value 96.687301
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 99.642387
iter 10 value 88.679691
iter 20 value 84.102952
iter 30 value 82.585225
iter 40 value 80.829479
iter 50 value 80.323720
iter 60 value 80.321705
final value 80.321695
converged
Fitting Repeat 1
# weights: 305
initial value 106.785385
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 97.408636
iter 10 value 93.547849
iter 20 value 88.104107
iter 30 value 84.512718
iter 40 value 84.503272
final value 84.503042
converged
Fitting Repeat 3
# weights: 305
initial value 97.504395
final value 93.836066
converged
Fitting Repeat 4
# weights: 305
initial value 101.292950
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 111.149962
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 129.550106
iter 10 value 86.803972
iter 20 value 84.611360
iter 30 value 84.228753
iter 40 value 84.187683
final value 84.187625
converged
Fitting Repeat 2
# weights: 507
initial value 110.924318
iter 10 value 93.836066
iter 10 value 93.836066
iter 10 value 93.836066
final value 93.836066
converged
Fitting Repeat 3
# weights: 507
initial value 106.667034
iter 10 value 94.035088
iter 10 value 94.035088
iter 10 value 94.035088
final value 94.035088
converged
Fitting Repeat 4
# weights: 507
initial value 96.148971
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 102.370554
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 109.155915
iter 10 value 94.082599
iter 20 value 93.787436
iter 30 value 88.280868
iter 40 value 87.348310
iter 50 value 85.637191
iter 60 value 85.167047
iter 70 value 85.154142
iter 80 value 85.153296
final value 85.152603
converged
Fitting Repeat 2
# weights: 103
initial value 114.756319
iter 10 value 94.060186
iter 20 value 93.934576
iter 30 value 87.675731
iter 40 value 86.232409
iter 50 value 85.517076
iter 60 value 85.180229
iter 70 value 85.153000
final value 85.152603
converged
Fitting Repeat 3
# weights: 103
initial value 100.136124
iter 10 value 92.698670
iter 20 value 86.660345
iter 30 value 85.128560
iter 40 value 84.199704
iter 50 value 84.112682
iter 60 value 83.658140
iter 70 value 82.151252
iter 80 value 82.137259
final value 82.137232
converged
Fitting Repeat 4
# weights: 103
initial value 104.828988
iter 10 value 93.885573
iter 20 value 90.987730
iter 30 value 89.807187
iter 40 value 83.619158
iter 50 value 82.996695
iter 60 value 82.682097
iter 70 value 82.591465
iter 80 value 82.490404
iter 90 value 82.365165
iter 100 value 82.294515
final value 82.294515
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 102.246880
iter 10 value 94.129097
iter 20 value 94.036729
iter 30 value 93.809369
iter 40 value 92.125843
iter 50 value 89.030711
iter 60 value 86.847976
iter 70 value 85.553027
iter 80 value 84.950640
iter 90 value 84.946124
final value 84.946118
converged
Fitting Repeat 1
# weights: 305
initial value 111.639288
iter 10 value 94.067510
iter 20 value 92.761158
iter 30 value 86.546631
iter 40 value 84.519454
iter 50 value 83.810156
iter 60 value 83.653329
iter 70 value 83.316687
iter 80 value 83.261356
iter 90 value 82.060314
iter 100 value 81.537002
final value 81.537002
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.459986
iter 10 value 94.088029
iter 20 value 93.723302
iter 30 value 93.661389
iter 40 value 92.633179
iter 50 value 86.954155
iter 60 value 86.055538
iter 70 value 85.272271
iter 80 value 84.693452
iter 90 value 81.732111
iter 100 value 81.299157
final value 81.299157
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.462139
iter 10 value 94.038422
iter 20 value 88.125598
iter 30 value 85.252858
iter 40 value 84.242750
iter 50 value 82.879351
iter 60 value 82.533463
iter 70 value 81.511532
iter 80 value 80.810895
iter 90 value 80.657680
iter 100 value 80.587443
final value 80.587443
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 115.568370
iter 10 value 93.931705
iter 20 value 90.662013
iter 30 value 85.771944
iter 40 value 83.972268
iter 50 value 83.578631
iter 60 value 82.594576
iter 70 value 81.658437
iter 80 value 81.470367
iter 90 value 81.300231
iter 100 value 81.178458
final value 81.178458
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.342750
iter 10 value 93.927196
iter 20 value 91.598075
iter 30 value 90.011143
iter 40 value 87.864296
iter 50 value 85.375668
iter 60 value 83.486135
iter 70 value 82.587562
iter 80 value 82.250482
iter 90 value 81.900676
iter 100 value 81.325281
final value 81.325281
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 128.219545
iter 10 value 94.440096
iter 20 value 86.617890
iter 30 value 85.103058
iter 40 value 84.723934
iter 50 value 84.201727
iter 60 value 84.088412
iter 70 value 83.789347
iter 80 value 82.642467
iter 90 value 82.236447
iter 100 value 82.198599
final value 82.198599
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.547545
iter 10 value 94.074444
iter 20 value 89.273375
iter 30 value 87.445607
iter 40 value 84.240600
iter 50 value 82.687338
iter 60 value 82.191434
iter 70 value 81.805497
iter 80 value 81.572961
iter 90 value 81.254705
iter 100 value 81.052861
final value 81.052861
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.210669
iter 10 value 91.143303
iter 20 value 87.384246
iter 30 value 85.241073
iter 40 value 84.773386
iter 50 value 83.074965
iter 60 value 82.871028
iter 70 value 82.687856
iter 80 value 82.594672
iter 90 value 82.499610
iter 100 value 82.455691
final value 82.455691
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.115762
iter 10 value 95.177732
iter 20 value 91.244168
iter 30 value 85.533862
iter 40 value 84.028596
iter 50 value 83.671907
iter 60 value 83.236257
iter 70 value 83.116484
iter 80 value 83.014287
iter 90 value 82.966245
iter 100 value 82.757705
final value 82.757705
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.337566
iter 10 value 94.239022
iter 20 value 93.706436
iter 30 value 85.225352
iter 40 value 84.167647
iter 50 value 83.729661
iter 60 value 83.586257
iter 70 value 82.548917
iter 80 value 82.093624
iter 90 value 82.063309
iter 100 value 82.046899
final value 82.046899
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.010160
iter 10 value 93.901791
iter 20 value 93.900313
iter 30 value 90.793419
iter 40 value 86.353516
iter 50 value 85.933017
final value 85.933008
converged
Fitting Repeat 2
# weights: 103
initial value 101.284293
iter 10 value 94.054754
final value 94.052912
converged
Fitting Repeat 3
# weights: 103
initial value 106.357315
final value 94.054412
converged
Fitting Repeat 4
# weights: 103
initial value 110.847420
final value 94.054746
converged
Fitting Repeat 5
# weights: 103
initial value 102.262274
iter 10 value 94.054578
iter 20 value 92.443461
iter 30 value 86.273187
iter 40 value 86.273081
iter 50 value 85.933160
final value 85.933056
converged
Fitting Repeat 1
# weights: 305
initial value 102.057221
iter 10 value 94.056954
final value 94.052916
converged
Fitting Repeat 2
# weights: 305
initial value 100.581669
iter 10 value 94.057734
iter 20 value 94.052846
iter 30 value 93.607262
final value 93.604633
converged
Fitting Repeat 3
# weights: 305
initial value 98.567193
iter 10 value 92.296303
iter 20 value 92.294841
iter 30 value 89.583184
iter 40 value 87.132475
iter 50 value 85.605356
iter 60 value 85.385906
iter 70 value 85.382101
iter 80 value 85.014443
iter 90 value 82.519149
iter 100 value 81.649638
final value 81.649638
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.134473
iter 10 value 93.841825
iter 20 value 93.690954
iter 30 value 87.203180
iter 40 value 86.168268
iter 50 value 86.160963
iter 60 value 85.438489
iter 70 value 84.905880
iter 80 value 84.183158
iter 90 value 83.657487
iter 100 value 83.642307
final value 83.642307
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 113.549311
iter 10 value 93.841305
iter 20 value 93.837707
final value 93.836477
converged
Fitting Repeat 1
# weights: 507
initial value 116.010810
iter 10 value 94.060873
iter 20 value 94.053064
iter 20 value 94.053063
iter 30 value 93.065278
iter 40 value 85.112610
iter 50 value 84.648362
iter 60 value 84.610540
iter 70 value 84.609378
iter 80 value 84.602679
iter 90 value 84.601531
iter 100 value 84.600028
final value 84.600028
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 95.412585
iter 10 value 94.059697
iter 20 value 92.285041
iter 30 value 85.418100
iter 40 value 85.415021
iter 50 value 84.457869
iter 60 value 82.006913
iter 70 value 81.604855
iter 80 value 81.073770
iter 90 value 80.888402
iter 100 value 80.888284
final value 80.888284
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 101.775016
final value 94.060890
converged
Fitting Repeat 4
# weights: 507
initial value 99.269414
iter 10 value 94.061556
iter 20 value 94.052975
iter 30 value 87.646158
iter 40 value 84.752894
iter 50 value 81.872905
iter 60 value 80.612158
iter 70 value 79.565546
iter 80 value 79.417880
iter 90 value 79.208815
iter 100 value 79.176457
final value 79.176457
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 98.088755
iter 10 value 91.655677
iter 20 value 87.624808
iter 30 value 87.619357
iter 40 value 85.703450
iter 50 value 84.740046
iter 60 value 84.728799
iter 70 value 82.000216
iter 80 value 81.834434
iter 90 value 81.442286
iter 100 value 81.410499
final value 81.410499
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.086626
iter 10 value 86.309449
iter 20 value 85.952094
final value 85.951717
converged
Fitting Repeat 2
# weights: 103
initial value 100.224695
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 104.903851
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 104.052558
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.667904
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 101.318450
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 97.985168
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 95.918798
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 100.332000
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 94.760569
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 113.937676
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 100.564148
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 108.367925
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 98.188603
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 103.151369
iter 10 value 93.064738
iter 20 value 92.811041
iter 30 value 92.715693
final value 92.715463
converged
Fitting Repeat 1
# weights: 103
initial value 97.862236
iter 10 value 94.502311
iter 20 value 93.989545
iter 30 value 92.379731
iter 40 value 85.237871
iter 50 value 85.133984
iter 60 value 84.444071
iter 70 value 83.942990
iter 80 value 83.876088
iter 90 value 83.835562
final value 83.835454
converged
Fitting Repeat 2
# weights: 103
initial value 100.209213
iter 10 value 93.888341
iter 20 value 89.855131
iter 30 value 87.900565
iter 40 value 85.266138
iter 50 value 84.469645
iter 60 value 84.380427
iter 70 value 84.251129
final value 84.246923
converged
Fitting Repeat 3
# weights: 103
initial value 98.236321
iter 10 value 94.506347
iter 20 value 94.414234
iter 30 value 93.973591
iter 40 value 93.960378
iter 50 value 93.603620
iter 60 value 85.962577
iter 70 value 85.356976
iter 80 value 84.105822
iter 90 value 83.915954
iter 100 value 83.838057
final value 83.838057
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 99.554060
iter 10 value 94.486467
iter 20 value 89.169819
iter 30 value 85.060101
iter 40 value 84.415896
iter 50 value 84.292035
final value 84.288136
converged
Fitting Repeat 5
# weights: 103
initial value 99.401366
iter 10 value 94.220978
iter 20 value 85.726477
iter 30 value 84.661774
iter 40 value 83.658025
iter 50 value 83.517166
iter 60 value 83.491072
final value 83.491067
converged
Fitting Repeat 1
# weights: 305
initial value 101.721042
iter 10 value 94.417276
iter 20 value 85.181173
iter 30 value 84.379795
iter 40 value 84.140171
iter 50 value 84.037803
iter 60 value 83.927373
iter 70 value 83.629316
iter 80 value 82.241311
iter 90 value 81.893955
iter 100 value 81.788171
final value 81.788171
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.780569
iter 10 value 94.386537
iter 20 value 87.544366
iter 30 value 86.845762
iter 40 value 84.612061
iter 50 value 83.734578
iter 60 value 82.472347
iter 70 value 81.799945
iter 80 value 81.726474
iter 90 value 81.501244
iter 100 value 81.368829
final value 81.368829
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.402516
iter 10 value 93.809296
iter 20 value 89.977253
iter 30 value 89.035610
iter 40 value 84.875789
iter 50 value 83.549302
iter 60 value 83.253476
iter 70 value 83.181815
iter 80 value 83.163335
iter 90 value 82.709320
iter 100 value 81.828073
final value 81.828073
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.656747
iter 10 value 94.352837
iter 20 value 91.410123
iter 30 value 88.682359
iter 40 value 85.292861
iter 50 value 83.332626
iter 60 value 82.932213
iter 70 value 82.776345
iter 80 value 82.452192
iter 90 value 82.311831
iter 100 value 82.294649
final value 82.294649
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.803070
iter 10 value 92.612163
iter 20 value 85.290205
iter 30 value 85.143622
iter 40 value 84.197234
iter 50 value 83.864769
iter 60 value 83.743881
iter 70 value 83.518475
iter 80 value 83.285380
iter 90 value 82.945440
iter 100 value 82.336156
final value 82.336156
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 123.311421
iter 10 value 94.619741
iter 20 value 93.791270
iter 30 value 91.974093
iter 40 value 89.566326
iter 50 value 85.831348
iter 60 value 83.609781
iter 70 value 82.585920
iter 80 value 81.939661
iter 90 value 81.561679
iter 100 value 81.362609
final value 81.362609
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 116.034944
iter 10 value 94.494781
iter 20 value 91.208446
iter 30 value 86.913838
iter 40 value 83.654183
iter 50 value 83.229131
iter 60 value 83.043138
iter 70 value 82.743802
iter 80 value 82.722588
iter 90 value 82.634197
iter 100 value 82.174752
final value 82.174752
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.940280
iter 10 value 94.401316
iter 20 value 89.322729
iter 30 value 84.849029
iter 40 value 84.276058
iter 50 value 83.351048
iter 60 value 82.891603
iter 70 value 82.593077
iter 80 value 81.671222
iter 90 value 81.433478
iter 100 value 81.203268
final value 81.203268
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 114.331211
iter 10 value 97.455125
iter 20 value 89.277976
iter 30 value 86.456399
iter 40 value 85.100369
iter 50 value 83.984592
iter 60 value 83.361992
iter 70 value 82.940409
iter 80 value 82.076294
iter 90 value 81.766311
iter 100 value 81.643265
final value 81.643265
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.102307
iter 10 value 97.511559
iter 20 value 93.777490
iter 30 value 88.779151
iter 40 value 85.213448
iter 50 value 83.806633
iter 60 value 82.256332
iter 70 value 81.458814
iter 80 value 81.276060
iter 90 value 81.178919
iter 100 value 81.077369
final value 81.077369
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.226873
final value 94.485788
converged
Fitting Repeat 2
# weights: 103
initial value 104.831383
iter 10 value 93.902531
iter 20 value 84.624604
iter 30 value 82.573041
iter 40 value 82.564207
final value 82.563994
converged
Fitting Repeat 3
# weights: 103
initial value 101.867472
final value 94.486021
converged
Fitting Repeat 4
# weights: 103
initial value 95.995974
final value 94.485756
converged
Fitting Repeat 5
# weights: 103
initial value 97.944548
iter 10 value 94.485868
iter 20 value 94.047382
iter 20 value 94.047381
iter 20 value 94.047381
final value 94.047381
converged
Fitting Repeat 1
# weights: 305
initial value 96.305351
iter 10 value 94.359181
iter 20 value 93.859666
iter 30 value 93.728509
iter 40 value 93.725666
final value 93.724965
converged
Fitting Repeat 2
# weights: 305
initial value 98.532830
iter 10 value 93.793829
iter 20 value 93.793174
iter 30 value 93.773768
iter 40 value 85.649319
iter 50 value 85.226429
iter 60 value 85.154692
final value 85.154279
converged
Fitting Repeat 3
# weights: 305
initial value 98.598728
iter 10 value 94.489340
iter 20 value 94.280969
final value 93.911951
converged
Fitting Repeat 4
# weights: 305
initial value 102.917230
iter 10 value 94.488932
iter 20 value 94.470601
iter 30 value 93.876017
iter 40 value 93.216592
iter 50 value 86.595034
final value 86.589702
converged
Fitting Repeat 5
# weights: 305
initial value 98.400387
iter 10 value 94.359325
iter 20 value 93.690012
iter 30 value 83.992727
iter 40 value 83.727001
iter 50 value 82.077797
iter 60 value 82.010654
iter 70 value 81.992627
iter 80 value 81.924009
iter 90 value 81.919762
iter 100 value 81.917906
final value 81.917906
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 125.306393
iter 10 value 94.363702
iter 20 value 94.095611
iter 30 value 93.718819
iter 40 value 93.656782
iter 50 value 93.656303
iter 60 value 93.655382
iter 70 value 93.649763
iter 80 value 85.673196
iter 90 value 83.949183
iter 100 value 83.936551
final value 83.936551
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 97.284110
iter 10 value 91.394973
iter 20 value 84.041803
iter 30 value 84.038696
iter 40 value 84.036755
iter 50 value 83.446775
iter 60 value 83.007628
iter 70 value 82.999230
iter 80 value 82.996488
iter 90 value 82.996361
final value 82.996343
converged
Fitting Repeat 3
# weights: 507
initial value 97.031482
iter 10 value 92.533250
iter 20 value 90.272129
iter 30 value 90.247663
iter 40 value 88.958637
iter 50 value 88.111766
iter 60 value 87.053195
iter 70 value 87.007388
iter 80 value 87.006049
iter 90 value 87.004717
final value 87.003131
converged
Fitting Repeat 4
# weights: 507
initial value 105.756060
iter 10 value 94.254162
iter 20 value 94.251350
iter 30 value 94.246877
final value 94.246299
converged
Fitting Repeat 5
# weights: 507
initial value 96.478630
iter 10 value 94.232172
final value 94.228149
converged
Fitting Repeat 1
# weights: 103
initial value 95.805390
iter 10 value 93.164282
iter 10 value 93.164282
iter 10 value 93.164282
final value 93.164282
converged
Fitting Repeat 2
# weights: 103
initial value 95.681635
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.571877
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 100.709560
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 103.891484
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 95.925711
iter 10 value 91.294143
iter 20 value 87.988447
iter 30 value 87.755324
iter 40 value 87.576025
iter 50 value 87.559331
iter 60 value 87.525369
iter 70 value 87.280373
iter 80 value 87.154692
iter 80 value 87.154692
iter 80 value 87.154691
final value 87.154691
converged
Fitting Repeat 2
# weights: 305
initial value 99.180156
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 103.973087
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 103.554074
final value 94.312038
converged
Fitting Repeat 5
# weights: 305
initial value 97.944739
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 106.563490
final value 93.813953
converged
Fitting Repeat 2
# weights: 507
initial value 108.901039
iter 10 value 93.772973
iter 10 value 93.772973
iter 10 value 93.772973
final value 93.772973
converged
Fitting Repeat 3
# weights: 507
initial value 114.235366
iter 10 value 93.772982
final value 93.772973
converged
Fitting Repeat 4
# weights: 507
initial value 95.637500
iter 10 value 90.617115
iter 20 value 86.352068
iter 30 value 84.309815
iter 40 value 84.297954
final value 84.297262
converged
Fitting Repeat 5
# weights: 507
initial value 109.416522
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 103.282269
iter 10 value 94.662074
iter 20 value 89.039759
iter 30 value 85.732686
iter 40 value 83.736020
iter 50 value 83.557995
iter 60 value 83.524156
iter 70 value 83.201960
iter 80 value 81.624480
iter 90 value 81.418603
iter 100 value 81.329434
final value 81.329434
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.681083
iter 10 value 94.122054
iter 20 value 91.747985
iter 30 value 85.220958
iter 40 value 84.538669
iter 50 value 83.925262
iter 60 value 82.826967
iter 70 value 81.359078
iter 80 value 81.309081
iter 90 value 81.307446
final value 81.307445
converged
Fitting Repeat 3
# weights: 103
initial value 95.818771
iter 10 value 88.606205
iter 20 value 86.202957
iter 30 value 85.412952
iter 40 value 85.064568
iter 50 value 82.717842
iter 60 value 81.408456
iter 70 value 81.315336
final value 81.314848
converged
Fitting Repeat 4
# weights: 103
initial value 101.248299
iter 10 value 94.483065
iter 20 value 93.422358
iter 30 value 93.065788
iter 40 value 89.908957
iter 50 value 84.351811
iter 60 value 83.743639
iter 70 value 81.450888
iter 80 value 81.315223
iter 90 value 81.312692
final value 81.312647
converged
Fitting Repeat 5
# weights: 103
initial value 105.369564
iter 10 value 94.475539
iter 20 value 92.100694
iter 30 value 88.420583
iter 40 value 88.078489
iter 50 value 84.787190
iter 60 value 84.538975
iter 70 value 84.524817
final value 84.524802
converged
Fitting Repeat 1
# weights: 305
initial value 104.338749
iter 10 value 94.492081
iter 20 value 93.416494
iter 30 value 93.231935
iter 40 value 85.865975
iter 50 value 83.273704
iter 60 value 81.619515
iter 70 value 80.536843
iter 80 value 80.008769
iter 90 value 79.893006
iter 100 value 79.782390
final value 79.782390
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.524682
iter 10 value 94.954618
iter 20 value 93.653982
iter 30 value 88.313275
iter 40 value 85.477767
iter 50 value 84.730678
iter 60 value 84.328892
iter 70 value 84.102025
iter 80 value 83.797994
iter 90 value 81.332656
iter 100 value 80.461762
final value 80.461762
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 116.619785
iter 10 value 94.373514
iter 20 value 86.721945
iter 30 value 85.274481
iter 40 value 84.835571
iter 50 value 84.530413
iter 60 value 84.268964
iter 70 value 82.829434
iter 80 value 81.559920
iter 90 value 81.274240
iter 100 value 80.939524
final value 80.939524
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.745203
iter 10 value 93.424695
iter 20 value 92.771799
iter 30 value 88.835411
iter 40 value 87.412685
iter 50 value 86.666468
iter 60 value 85.248602
iter 70 value 81.791780
iter 80 value 81.073791
iter 90 value 80.626897
iter 100 value 80.376694
final value 80.376694
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.101708
iter 10 value 94.445605
iter 20 value 93.489754
iter 30 value 93.132539
iter 40 value 91.958779
iter 50 value 84.957291
iter 60 value 81.622789
iter 70 value 81.428397
iter 80 value 81.071690
iter 90 value 80.560223
iter 100 value 79.922431
final value 79.922431
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 115.450411
iter 10 value 94.603869
iter 20 value 93.570548
iter 30 value 86.089400
iter 40 value 84.861589
iter 50 value 82.846739
iter 60 value 81.177171
iter 70 value 80.876908
iter 80 value 80.781323
iter 90 value 80.401268
iter 100 value 79.944156
final value 79.944156
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 143.837515
iter 10 value 95.096721
iter 20 value 93.290544
iter 30 value 86.006368
iter 40 value 84.634423
iter 50 value 84.535146
iter 60 value 84.438575
iter 70 value 84.205875
iter 80 value 83.969570
iter 90 value 82.376689
iter 100 value 81.650923
final value 81.650923
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.132809
iter 10 value 94.486217
iter 20 value 88.003552
iter 30 value 86.947515
iter 40 value 85.804149
iter 50 value 84.146266
iter 60 value 83.889308
iter 70 value 83.780119
iter 80 value 82.919529
iter 90 value 82.323082
iter 100 value 81.644822
final value 81.644822
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 125.197481
iter 10 value 94.492146
iter 20 value 93.293725
iter 30 value 91.762673
iter 40 value 88.700914
iter 50 value 85.575867
iter 60 value 83.150298
iter 70 value 81.554287
iter 80 value 81.108010
iter 90 value 80.653866
iter 100 value 80.483217
final value 80.483217
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.434466
iter 10 value 91.783196
iter 20 value 87.427265
iter 30 value 84.503904
iter 40 value 81.372856
iter 50 value 80.342693
iter 60 value 80.291405
iter 70 value 80.151543
iter 80 value 79.992997
iter 90 value 79.859453
iter 100 value 79.833844
final value 79.833844
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.887774
final value 94.485844
converged
Fitting Repeat 2
# weights: 103
initial value 96.294540
final value 94.485916
converged
Fitting Repeat 3
# weights: 103
initial value 93.656771
iter 10 value 92.782038
iter 20 value 92.780773
iter 30 value 92.779357
final value 92.779356
converged
Fitting Repeat 4
# weights: 103
initial value 97.175683
final value 94.485804
converged
Fitting Repeat 5
# weights: 103
initial value 98.574728
final value 94.486168
converged
Fitting Repeat 1
# weights: 305
initial value 97.519540
iter 10 value 93.497393
iter 20 value 93.169545
iter 30 value 92.784309
iter 40 value 92.783010
iter 50 value 92.780615
iter 60 value 92.779979
final value 92.779915
converged
Fitting Repeat 2
# weights: 305
initial value 96.482008
iter 10 value 94.166086
iter 20 value 93.778741
iter 30 value 93.435275
iter 40 value 92.795842
iter 50 value 92.765582
iter 60 value 92.758699
iter 70 value 92.758381
iter 70 value 92.758381
iter 70 value 92.758381
final value 92.758381
converged
Fitting Repeat 3
# weights: 305
initial value 109.083807
iter 10 value 94.487392
iter 20 value 94.474103
iter 30 value 86.245905
iter 40 value 85.889372
iter 50 value 85.879154
final value 85.879132
converged
Fitting Repeat 4
# weights: 305
initial value 106.187889
iter 10 value 93.115437
iter 20 value 89.516586
iter 30 value 86.121612
iter 40 value 86.114476
iter 40 value 86.114476
final value 86.114476
converged
Fitting Repeat 5
# weights: 305
initial value 125.556214
iter 10 value 93.778272
iter 20 value 93.776725
iter 30 value 93.065555
iter 40 value 93.024225
iter 50 value 92.817991
iter 60 value 89.071023
iter 70 value 85.526867
iter 80 value 85.251397
iter 90 value 85.251188
final value 85.251012
converged
Fitting Repeat 1
# weights: 507
initial value 99.933551
iter 10 value 94.491718
iter 20 value 94.484284
final value 94.484241
converged
Fitting Repeat 2
# weights: 507
initial value 101.332266
iter 10 value 94.493046
iter 20 value 94.395170
iter 30 value 85.517800
iter 40 value 84.044214
iter 50 value 83.944839
iter 60 value 83.931700
iter 70 value 83.270673
iter 80 value 83.207132
iter 90 value 83.197415
iter 100 value 83.197152
final value 83.197152
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.381965
iter 10 value 94.490219
iter 20 value 87.476625
final value 86.334605
converged
Fitting Repeat 4
# weights: 507
initial value 100.558588
iter 10 value 93.781258
iter 20 value 93.780280
iter 30 value 92.862690
iter 40 value 92.094946
iter 50 value 87.275189
iter 60 value 86.258303
iter 70 value 86.223312
iter 80 value 86.222524
iter 90 value 85.937898
iter 100 value 85.310350
final value 85.310350
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 95.858293
iter 10 value 93.028412
iter 20 value 91.384222
iter 30 value 91.278293
iter 40 value 91.276275
iter 50 value 90.045905
iter 60 value 89.475456
iter 70 value 83.817612
iter 80 value 81.169680
iter 90 value 81.001632
iter 100 value 80.425994
final value 80.425994
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 123.709895
iter 10 value 117.895370
iter 20 value 117.875745
iter 30 value 117.870400
iter 40 value 117.867151
iter 50 value 117.850632
iter 60 value 115.431481
iter 70 value 115.128916
iter 80 value 110.450088
iter 90 value 109.467182
iter 100 value 108.534094
final value 108.534094
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 154.243380
iter 10 value 117.894812
iter 20 value 117.890325
final value 117.890309
converged
Fitting Repeat 3
# weights: 305
initial value 119.131545
iter 10 value 117.763433
iter 20 value 117.483608
iter 30 value 117.457133
iter 40 value 117.455592
iter 50 value 117.445082
final value 117.445010
converged
Fitting Repeat 4
# weights: 305
initial value 120.818823
iter 10 value 117.894832
iter 20 value 117.346478
iter 30 value 108.531201
iter 40 value 108.506942
iter 50 value 108.432933
iter 60 value 108.432152
iter 70 value 108.175499
iter 80 value 107.087435
iter 90 value 107.085284
iter 100 value 107.084837
final value 107.084837
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 123.837271
iter 10 value 115.992566
iter 20 value 108.546316
iter 30 value 108.338275
iter 40 value 108.336778
iter 50 value 106.530442
iter 60 value 106.018203
iter 70 value 106.015144
final value 106.011542
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Thu Dec 29 00:36:40 2022
***********************************************
Number of test functions: 8
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 8 test functions, 0 errors, 0 failures
Number of test functions: 8
Number of errors: 0
Number of failures: 0
Warning messages:
1: The `.data` argument of `add_column()` must have unique names as of tibble
3.0.0.
ℹ Use `.name_repair = "minimal"`.
ℹ The deprecated feature was likely used in the tibble package.
Please report the issue at <https://github.com/tidyverse/tibble/issues>.
2: `repeats` has no meaning for this resampling method.
3: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
36.43 1.70 38.86
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 25.22 | 1.40 | 26.81 | |
| FreqInteractors | 0.19 | 0.03 | 0.22 | |
| calculateAAC | 0.05 | 0.00 | 0.05 | |
| calculateAutocor | 0.28 | 0.08 | 0.35 | |
| calculateBE | 0.14 | 0.02 | 0.16 | |
| calculateCTDC | 0.08 | 0.00 | 0.08 | |
| calculateCTDD | 0.64 | 0.06 | 0.70 | |
| calculateCTDT | 0.22 | 0.00 | 0.22 | |
| calculateCTriad | 0.22 | 0.08 | 0.30 | |
| calculateDC | 0.07 | 0.00 | 0.08 | |
| calculateF | 0.29 | 0.00 | 0.28 | |
| calculateKSAAP | 0.04 | 0.03 | 0.08 | |
| calculateQD_Sm | 1.16 | 0.08 | 1.23 | |
| calculateTC | 1.26 | 0.08 | 1.34 | |
| calculateTC_Sm | 0.18 | 0.01 | 0.19 | |
| corr_plot | 25.67 | 0.75 | 26.42 | |
| enrichfindP | 0.37 | 0.05 | 7.53 | |
| enrichfind_hp | 0.03 | 0.01 | 0.80 | |
| enrichplot | 0.27 | 0.00 | 0.27 | |
| filter_missing_values | 0.00 | 0.02 | 0.01 | |
| getFASTA | 0.02 | 0.00 | 2.52 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.04 | 0.01 | 0.08 | |
| pred_ensembel | 11.61 | 0.40 | 8.56 | |
| var_imp | 26.88 | 0.82 | 27.72 | |