sd() on greta_array does not return a greta_array

[hrlai]

Hi there, with the code below, applying sd() on a greta_array does not return the same class. Just wondering if it's intentional?

library(greta)
x <- normal(0, 1, dim = 10)
sd(x)   # class numeric
mean(x)  # class greta_array

I'm want to generate some calculated quantities by scaling using sd(x) so it'd be nice if it returns a greta_array. I could use var(x) or scale(x) (both return greta_array) but they are clunky in their own ways...

This was using greta_0.4.1.9000 on R version 4.1.3 (2022-03-10)

[njtierney]

Thanks for posting, @hrlai !

Confirming that I get the same result as you:

library(greta)
#> 
#> Attaching package: 'greta'
#> The following objects are masked from 'package:stats':
#> 
#>     binomial, cov2cor, poisson
#> The following objects are masked from 'package:base':
#> 
#>     %*%, apply, backsolve, beta, chol2inv, colMeans, colSums, diag,
#>     eigen, forwardsolve, gamma, identity, rowMeans, rowSums, sweep,
#>     tapply
greta_sitrep()
#> ℹ checking if python available
#> ✓ python (version 3.7) available
#> 
#> ℹ checking if TensorFlow available
#> ✓ TensorFlow (version 1.14.0) available
#> 
#> ℹ checking if TensorFlow Probability available
#> ✓ TensorFlow Probability (version 0.7.0) available
#> 
#> ℹ checking if greta conda environment available
#> ✓ greta conda environment available
#> 
#> ℹ Initialising python and checking dependencies, this may take a moment.
#> ✓ Initialising python and checking dependencies ... done!
#> 
#> ℹ greta is ready to use!
x <- normal(0, 1, dim = 10)
sd(x)
#> [1] NA
mean(x)
#> greta array (operation)
#> 
#>      [,1]
#> [1,]  ?
var(x)
#>      [,1]
#> [1,]   NA
scale(x)
#>       [,1]
#>  [1,]  ?  
#>  [2,]  ?  
#>  [3,]  ?  
#>  [4,]  ?  
#>  [5,]  ?  
#>  [6,]  ?  
#>  [7,]  ?  
#>  [8,]  ?  
#>  [9,]  ?  
#> [10,]  ?  
#> attr(,"scaled:center")
#> [1] NaN
#> attr(,"scaled:scale")
#> [1] 0

^{Created on 2022-03-18 by the reprex package (v2.0.1)}

Session info

``` r sessioninfo::session_info() #> ─ Session info ─────────────────────────────────────────────────────────────── #> setting value #> version R version 4.1.3 (2022-03-10) #> os macOS Big Sur/Monterey 10.16 #> system x86_64, darwin17.0 #> ui X11 #> language (EN) #> collate en_AU.UTF-8 #> ctype en_AU.UTF-8 #> tz Australia/Perth #> date 2022-03-18 #> pandoc 2.17.1.1 @ /Applications/RStudio.app/Contents/MacOS/quarto/bin/ (via rmarkdown) #> #> ─ Packages ─────────────────────────────────────────────────────────────────── #> package * version date (UTC) lib source #> backports 1.4.1 2021-12-13 [1] CRAN (R 4.1.0) #> base64enc 0.1-3 2015-07-28 [1] CRAN (R 4.1.0) #> callr 3.7.0 2021-04-20 [1] CRAN (R 4.1.0) #> cli 3.2.0 2022-02-14 [1] CRAN (R 4.1.2) #> coda 0.19-4 2020-09-30 [1] CRAN (R 4.1.0) #> codetools 0.2-18 2020-11-04 [1] CRAN (R 4.1.3) #> crayon 1.5.0 2022-02-14 [1] CRAN (R 4.1.2) #> digest 0.6.29 2021-12-01 [1] CRAN (R 4.1.0) #> ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.1.0) #> evaluate 0.15 2022-02-18 [1] CRAN (R 4.1.2) #> fansi 1.0.2 2022-01-14 [1] CRAN (R 4.1.2) #> fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.1.0) #> fs 1.5.2 2021-12-08 [1] CRAN (R 4.1.0) #> future 1.24.0 2022-02-19 [1] CRAN (R 4.1.2) #> globals 0.14.0 2020-11-22 [1] CRAN (R 4.1.0) #> glue 1.6.2 2022-02-24 [1] CRAN (R 4.1.2) #> greta * 0.4.1 2022-03-15 [1] CRAN (R 4.1.2) #> here 1.0.1 2020-12-13 [1] CRAN (R 4.1.0) #> highr 0.9 2021-04-16 [1] CRAN (R 4.1.0) #> hms 1.1.1 2021-09-26 [1] CRAN (R 4.1.0) #> htmltools 0.5.2 2021-08-25 [1] CRAN (R 4.1.0) #> jsonlite 1.8.0 2022-02-22 [1] CRAN (R 4.1.2) #> knitr 1.37 2021-12-16 [1] CRAN (R 4.1.0) #> lattice 0.20-45 2021-09-22 [1] CRAN (R 4.1.3) #> lifecycle 1.0.1 2021-09-24 [1] CRAN (R 4.1.0) #> listenv 0.8.0 2019-12-05 [1] CRAN (R 4.1.0) #> magrittr 2.0.2 2022-01-26 [1] CRAN (R 4.1.2) #> Matrix 1.4-0 2021-12-08 [1] CRAN (R 4.1.3) #> parallelly 1.30.0 2021-12-17 [1] CRAN (R 4.1.0) #> pillar 1.7.0 2022-02-01 [1] CRAN (R 4.1.2) #> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.1.0) #> png 0.1-7 2013-12-03 [1] CRAN (R 4.1.0) #> prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.1.0) #> processx 3.5.2 2021-04-30 [1] CRAN (R 4.1.0) #> progress 1.2.2 2019-05-16 [1] CRAN (R 4.1.0) #> ps 1.6.0 2021-02-28 [1] CRAN (R 4.1.0) #> purrr 0.3.4 2020-04-17 [1] CRAN (R 4.1.0) #> R.cache 0.15.0 2021-04-30 [1] CRAN (R 4.1.0) #> R.methodsS3 1.8.1 2020-08-26 [1] CRAN (R 4.1.0) #> R.oo 1.24.0 2020-08-26 [1] CRAN (R 4.1.0) #> R.utils 2.11.0 2021-09-26 [1] CRAN (R 4.1.0) #> R6 2.5.1 2021-08-19 [1] CRAN (R 4.1.0) #> Rcpp 1.0.8.2 2022-03-11 [1] CRAN (R 4.1.2) #> reprex 2.0.1 2021-08-05 [1] CRAN (R 4.1.0) #> reticulate 1.24 2022-01-26 [1] CRAN (R 4.1.2) #> rlang 1.0.2 2022-03-04 [1] CRAN (R 4.1.2) #> rmarkdown 2.11 2021-09-14 [1] CRAN (R 4.1.0) #> rprojroot 2.0.2 2020-11-15 [1] CRAN (R 4.1.0) #> rstudioapi 0.13 2020-11-12 [1] CRAN (R 4.1.0) #> sessioninfo 1.2.2.9000 2022-03-01 [1] Github (r-lib/sessioninfo@d70760d) #> stringi 1.7.6 2021-11-29 [1] CRAN (R 4.1.0) #> stringr 1.4.0 2019-02-10 [1] CRAN (R 4.1.0) #> styler 1.6.2 2021-09-23 [1] CRAN (R 4.1.0) #> tensorflow 2.8.0 2022-02-09 [1] CRAN (R 4.1.2) #> tfruns 1.5.0 2021-02-26 [1] CRAN (R 4.1.0) #> tibble 3.1.6 2021-11-07 [1] CRAN (R 4.1.0) #> utf8 1.2.2 2021-07-24 [1] CRAN (R 4.1.0) #> vctrs 0.3.8 2021-04-29 [1] CRAN (R 4.1.0) #> whisker 0.4 2019-08-28 [1] CRAN (R 4.1.0) #> withr 2.5.0 2022-03-03 [1] CRAN (R 4.1.2) #> xfun 0.30 2022-03-02 [1] CRAN (R 4.1.2) #> yaml 2.3.5 2022-02-21 [1] CRAN (R 4.1.2) #> #> [1] /Library/Frameworks/R.framework/Versions/4.1/Resources/library #> #> ─ Python configuration ─────────────────────────────────────────────────────── #> python: /Users/njtierney/Library/r-miniconda/envs/greta-env/bin/python #> libpython: /Users/njtierney/Library/r-miniconda/envs/greta-env/lib/libpython3.7m.dylib #> pythonhome: /Users/njtierney/Library/r-miniconda/envs/greta-env:/Users/njtierney/Library/r-miniconda/envs/greta-env #> version: 3.7.12 | packaged by conda-forge | (default, Oct 26 2021, 05:59:23) [Clang 11.1.0 ] #> numpy: /Users/njtierney/Library/r-miniconda/envs/greta-env/lib/python3.7/site-packages/numpy #> numpy_version: 1.16.4 #> tensorflow: /Users/njtierney/Library/r-miniconda/envs/greta-env/lib/python3.7/site-packages/tensorflow #> #> NOTE: Python version was forced by use_python function #> #> ────────────────────────────────────────────────────────────────────────────── ```

I think sd should be included, I'm not sure why it wasn't, I'll just need to check a few things first with Nick Golding, but I'll add this to the next milestone in the meantime.

Cheers!

Nick

[njtierney]

Intriguingly, there is no defined method for sd and var because sd and var are not generic methods in R

(learnt from: https://stackoverflow.com/questions/4728342/using-sd-as-a-generic-function-in-r)

I have started implementing this in #506