Failed test, "Wishart can use a choleskied Sigma"

The following test fails...sometimes:

test_that("Wishart can use a choleskied Sigma", {
  skip_if_not(check_tf_version())

  sig <- lkj_correlation(3, dim = 3)
  w <- wishart(5, sig)
  m <- model(w, precision = "double")
  # expect_ok(draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE))
  expect_success(draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE))
})

Example:

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
sig <- lkj_correlation(3, dim = 3)
#> ℹ Initialising python and checking dependencies, this may take a moment.
#> ✓ Initialising python and checking dependencies ... done!
#> 
w <- wishart(5, sig)
m <- model(w, precision = "double")
# one in 5 seems to fail
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)
#> Error: Could not find reasonable starting values after 20 attempts.
#> Please specify initial values manually via the `initial_values` argument
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)
#> Error: Could not find reasonable starting values after 20 attempts.
#> Please specify initial values manually via the `initial_values` argument
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)

# not sure how to better specify initial values though, since
# this synax doesn't work?
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE,
              initial_values = initials(w = 0.1))
#> only one set of initial values was provided, and was used for all chains
#> Error: initial values can only be set for variable <greta_array>s
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE,
              initial_values = initials(sig = 0.1))
#> only one set of initial values was provided, and was used for all chains
#> Error: initial values can only be set for variable <greta_array>s

^{Created on 2022-02-22 by the reprex package (v2.0.1)}

Session info

``` r sessioninfo::session_info() #> ─ Session info ─────────────────────────────────────────────────────────────── #> setting value #> version R version 4.1.2 (2021-11-01) #> os macOS Big Sur 10.16 #> system x86_64, darwin17.0 #> ui X11 #> language (EN) #> collate en_AU.UTF-8 #> ctype en_AU.UTF-8 #> tz Australia/Brisbane #> date 2022-02-22 #> pandoc 2.17.1.1 @ /Applications/RStudio.app/Contents/MacOS/quarto/bin/ (via rmarkdown) #> #> ─ Packages ─────────────────────────────────────────────────────────────────── #> package * version date (UTC) lib source #> abind 1.4-5 2016-07-21 [1] CRAN (R 4.1.0) #> 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 4.1.2) #> crayon 1.4.2 2021-10-29 [1] CRAN (R 4.1.0) #> 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 0.14 2019-05-28 [1] CRAN (R 4.1.0) #> 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 1.23.0 2021-10-31 [1] CRAN (R 4.1.0) #> globals 0.14.0 2020-11-22 [1] CRAN (R 4.1.0) #> glue 1.6.0 2021-12-17 [1] CRAN (R 4.1.0) #> greta * 0.4.0 2022-02-16 [1] local #> 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 1.7.2 2020-12-09 [1] CRAN (R 4.1.0) #> knitr 1.37 2021-12-16 [1] CRAN (R 4.1.0) #> lattice 0.20-45 2021-09-22 [1] CRAN (R 4.1.2) #> 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 2.0.1 2020-11-17 [1] CRAN (R 4.1.0) #> Matrix 1.3-4 2021-06-01 [1] CRAN (R 4.1.2) #> parallelly 1.29.0 2021-11-21 [1] CRAN (R 4.1.0) #> pillar 1.6.4 2021-10-18 [1] CRAN (R 4.1.0) #> 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 2022-01-13 [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 0.4.12 2021-10-18 [1] CRAN (R 4.1.0) #> 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 2021-12-06 [1] CRAN (R 4.1.1) #> 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 2.4.3 2021-11-30 [1] CRAN (R 4.1.0) #> xfun 0.29 2021-12-14 [1] CRAN (R 4.1.0) #> yaml 2.2.1 2020-02-01 [1] CRAN (R 4.1.0) #> #> [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 #> #> ────────────────────────────────────────────────────────────────────────────── ```

As @goldingn suggested, changing the dim to 2 gave a smaller space to explore so a better result:

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
sig <- lkj_correlation(2, dim = 2)
#> ℹ Initialising python and checking dependencies, this may take a moment.
#> ✓ Initialising python and checking dependencies ... done!
#> 
w <- wishart(5, sig)
m <- model(w, precision = "double")
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)

# one in 5 seems to fail
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)
draws <- mcmc(m, warmup = 0, n_samples = 5, verbose = FALSE)

^{Created on 2022-02-22 by the reprex package (v2.0.1)}

Session info

greta-dev / greta

Failed test, "Wishart can use a choleskied Sigma" #502