Comments (9)
pat-s
commented on May 24, 2024
Hi Jürgen,
thanks for posting your issue here.
Please provide a reproducible example, preferably using the reprex package.
I cannot reproduce your issue - see my reprex below.
library("mlr3verse")
#> Loading required package: mlr3
#> Loading required package: mlr3filters
#> Loading required package: mlr3learners
#> Loading required package: mlr3pipelines
#> Loading required package: mlr3tuning
#> Loading required package: mlr3viz
#> Loading required package: paradox
library("mlr3spatiotempcv")
learner <- lrn("classif.rpart")
tune_ps <- ParamSet$new(list(
ParamDbl$new("cp", lower = 0.001, upper = 0.1),
ParamInt$new("minsplit", lower = 1, upper = 10)
))
terminator <- trm("evals", n_evals = 2)
tuner <- tnr("random_search")
logger <- lgr::get_logger("bbotk")
logger$set_threshold("warn")
logger_mlr3 <- lgr::get_logger("mlr3")
logger_mlr3$set_threshold("warn")
at <- AutoTuner$new(
learner = learner,
resampling = rsmp("spcv_coords", folds = 3),
measure = msr("classif.ce"),
search_space = tune_ps,
terminator = terminator,
tuner = tuner
)
grid <- benchmark_grid(
task = tsk("ecuador"),
learner = list(at),
resampling = rsmp("spcv_coords", folds = 3)
)
bmr <- benchmark(grid)
bmr$resamplings
#> resampling_hash resampling_id resampling
#> 1: 1ed7490ce716cb8b spcv_coords <ResamplingSpCVCoords[19]>Created on 2021-01-06 by the reprex package (v0.3.0)
Session info
devtools::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.0.3 Patched (2020-12-21 r79675)
#> os macOS Big Sur 10.16
#> system x86_64, darwin17.0
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Europe/Zurich
#> date 2021-01-06
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date lib
#> assertthat 0.2.1 2019-03-21 [1]
#> backports 1.2.1 2020-12-09 [1]
#> bbotk 0.2.2 2020-10-08 [1]
#> callr 3.5.1 2020-10-13 [1]
#> checkmate 2.0.0 2020-02-06 [1]
#> cli 2.2.0 2020-11-20 [1]
#> codetools 0.2-18 2020-11-04 [2]
#> colorspace 2.0-0 2020-11-11 [1]
#> crayon 1.3.4 2017-09-16 [1]
#> data.table 1.13.6 2020-12-30 [1]
#> desc 1.2.0 2018-05-01 [1]
#> devtools 2.3.2 2020-09-18 [1]
#> digest 0.6.27 2020-10-24 [1]
#> dplyr 1.0.2 2020-08-18 [1]
#> ellipsis 0.3.1 2020-05-15 [1]
#> evaluate 0.14 2019-05-28 [1]
#> fansi 0.4.1 2020-01-08 [1]
#> fs 1.5.0 2020-07-31 [1]
#> future 1.21.0 2020-12-10 [1]
#> future.apply 1.7.0 2021-01-04 [1]
#> generics 0.1.0 2020-10-31 [1]
#> ggplot2 3.3.3 2020-12-30 [1]
#> globals 0.14.0 2020-11-22 [1]
#> glue 1.4.2 2020-08-27 [1]
#> gtable 0.3.0 2019-03-25 [1]
#> highr 0.8 2019-03-20 [1]
#> htmltools 0.5.0.9003 2020-12-26 [1]
#> knitr 1.30 2020-09-22 [1]
#> lgr 0.4.1 2020-10-20 [1]
#> lifecycle 0.2.0 2020-03-06 [1]
#> listenv 0.8.0 2019-12-05 [1]
#> magrittr 2.0.1 2020-11-17 [1]
#> memoise 1.1.0 2017-04-21 [1]
#> mlr3 * 0.9.0 2020-12-06 [1]
#> mlr3filters * 0.4.0 2020-11-10 [1]
#> mlr3learners * 0.4.3 2020-12-08 [1]
#> mlr3measures 0.3.0 2020-10-05 [1]
#> mlr3misc 0.6.0 2020-11-17 [1]
#> mlr3pipelines * 0.3.2 2020-12-17 [1]
#> mlr3spatiotempcv * 0.1.0.9000 2020-12-26 [1]
#> mlr3tuning * 0.5.0 2020-12-07 [1]
#> mlr3verse * 0.1.3 2020-07-06 [1]
#> mlr3viz * 0.5.0 2020-11-02 [1]
#> munsell 0.5.0 2018-06-12 [1]
#> paradox * 0.6.0 2020-12-04 [1]
#> parallelly 1.23.0 2021-01-04 [1]
#> pillar 1.4.7 2020-11-20 [1]
#> pkgbuild 1.2.0 2020-12-15 [1]
#> pkgconfig 2.0.3 2019-09-22 [1]
#> pkgload 1.1.0 2020-05-29 [1]
#> prettyunits 1.1.1 2020-01-24 [1]
#> processx 3.4.5 2020-11-30 [1]
#> ps 1.5.0 2020-12-05 [1]
#> purrr 0.3.4 2020-04-17 [1]
#> R6 2.5.0 2020-10-28 [1]
#> remotes 2.2.0 2020-07-21 [1]
#> rlang 0.4.10 2020-12-30 [1]
#> rmarkdown 2.6.4 2021-01-05 [1]
#> rpart 4.1-15 2019-04-12 [2]
#> rprojroot 2.0.2 2020-11-15 [1]
#> scales 1.1.1 2020-05-11 [1]
#> sessioninfo 1.1.1 2018-11-05 [1]
#> stringi 1.5.3 2020-09-09 [1]
#> stringr 1.4.0 2019-02-10 [1]
#> testthat 3.0.1 2021-01-05 [1]
#> tibble 3.0.4 2020-10-12 [1]
#> tidyselect 1.1.0 2020-05-11 [1]
#> usethis 2.0.0.9000 2020-12-24 [1]
#> uuid 0.1-4 2020-02-26 [1]
#> vctrs 0.3.6 2020-12-17 [1]
#> withr 2.3.0 2020-09-22 [1]
#> xfun 0.19 2020-10-30 [1]
#> yaml 2.2.1 2020-02-01 [1]
#> source
#> CRAN (R 4.0.3)
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#> Github (rstudio/htmltools@d18bd8e)
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#> Github (mlr-org/mlr3spatiotempcv@59cbc9f)
#> CRAN (R 4.0.3)
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#> CRAN (R 4.0.3)
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#>
#> [1] /Users/pjs/Library/R/4.0/library
#> [2] /Library/Frameworks/R.framework/Versions/4.0/Resources/libraryfrom mlr3spatiotempcv.
jue-d
commented on May 24, 2024
Hi Patrick,
thanks for the swift response!
It seems to be working now after reloading and rerunning the session again. I was trying to identify the issue now, but I can't reproduce it myself anymore. Must have been have been a little hickup on my end. Anyways, thanks again and sorry for the inconvenience caused!
Have a nice day!
Jürgen
from mlr3spatiotempcv.
pat-s
commented on May 24, 2024
Sounds good! 👍
from mlr3spatiotempcv.
fitzLab-AL
commented on May 24, 2024
I am trying to run the reproducible example above and get an error:
library("mlr3verse")
library("mlr3spatiotempcv")
learner <- lrn("classif.rpart")
tune_ps <- ParamSet$new(list(
ParamDbl$new("cp", lower = 0.001, upper = 0.1),
ParamInt$new("minsplit", lower = 1, upper = 10)
))
#> Error in eval(expr, envir, enclos): object 'ParamSet' not found
Any idea why this isn't reproducible for me?
from mlr3spatiotempcv.
pat-s
commented on May 24, 2024
Most likely your package versions differ.
from mlr3spatiotempcv.
fitzLab-AL
commented on May 24, 2024
Thanks for your reply.
I am using mlr3spatiotempcv 0.2.0 and mlr3verse 0.2.1. The code works for me if I load the paradox package.
library(mlr3verse)
library(mlr3spatiotempcv)
library(paradox)
learner <- lrn("classif.rpart")
tune_ps <- ParamSet$new(list(
ParamDbl$new("cp", lower = 0.001, upper = 0.1),
ParamInt$new("minsplit", lower = 1, upper = 10)
))
Here is my session info after loading mlr3spatiotempcv and mlr3verse.
library("mlr3verse")
library("mlr3spatiotempcv")
sessionInfo()
#> R version 4.0.4 (2021-02-15)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Big Sur 10.16
#>
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
#>
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] mlr3spatiotempcv_0.2.0 mlr3verse_0.2.1
#>
#> loaded via a namespace (and not attached):
#> [1] Rcpp_1.0.6 paradox_0.7.1 lattice_0.20-41
#> [4] palmerpenguins_0.1.0 assertthat_0.2.1 digest_0.6.27
#> [7] utf8_1.1.4 parallelly_1.23.0 R6_2.5.0
#> [10] backports_1.2.1 reprex_1.0.0 evaluate_0.14
#> [13] ggplot2_3.3.3 highr_0.8 pillar_1.5.0
#> [16] rlang_0.4.10 mlr3fselect_0.5.0 uuid_0.1-4
#> [19] rstudioapi_0.13 data.table_1.14.0 distr6_1.5.0
#> [22] Matrix_1.3-2 checkmate_2.0.0 rmarkdown_2.7
#> [25] splines_4.0.4 stringr_1.4.0 mlr3pipelines_0.3.4
#> [28] munsell_0.5.0 compiler_4.0.4 set6_0.2.1
#> [31] xfun_0.21 pkgconfig_2.0.3 mlr3tuning_0.7.0
#> [34] htmltools_0.5.1.1 tidyselect_1.1.0 mlr3data_0.3.0
#> [37] tibble_3.1.0 lgr_0.4.2 mlr3cluster_0.1.1
#> [40] mlr3misc_0.7.0 clusterCrit_1.2.8 fansi_0.4.2
#> [43] crayon_1.4.1 dplyr_1.0.4 withr_2.4.1
#> [46] grid_4.0.4 gtable_0.3.0 lifecycle_1.0.0
#> [49] DBI_1.1.1 magrittr_2.0.1 mlr3learners_0.4.3
#> [52] scales_1.1.1 mlr3proba_0.3.1 cli_2.3.1
#> [55] stringi_1.5.3 mlr3viz_0.5.2 fs_1.5.0
#> [58] mlr3filters_0.4.1 ellipsis_0.3.1 bbotk_0.3.0
#> [61] vctrs_0.3.6 generics_0.1.0 tools_4.0.4
#> [64] mlr3_0.11.0 glue_1.4.2 purrr_0.3.4
#> [67] parallel_4.0.4 survival_3.2-7 yaml_2.2.1
#> [70] clue_0.3-58 colorspace_2.0-0 cluster_2.1.0
#> [73] R62S3_1.4.1 knitr_1.31
Thanks for your help with this.
from mlr3spatiotempcv.
pat-s
commented on May 24, 2024
Thanks. Maybe like we're missing some imports from paradox in the latest mlr3verse?
from mlr3spatiotempcv.
mllg
commented on May 24, 2024
paradox (and mlr3verse) now offer a more concise way to create parameter sets:
tune_ps <- ps(
cp = p_dbl(lower = 0.001, upper = 0.1),
minsplit = p_int(lower = 1, upper = 10)
)We are currently in the process of updating all examples, sorry for the confusion.
If you prefer the old syntax, you can still attach paradox.
from mlr3spatiotempcv.
fitzLab-AL
commented on May 24, 2024
OK - that makes sense. I have actually been using ps to create parameter sets in my code, but I'm new at this and didn't recognize the connection with ParamSet. Thanks for your help!
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