Running ‘testthat.R’ [393s/409s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(dgo)
  Loading required package: dgodata
  Loading required package: rstan
  Loading required package: StanHeaders
  Loading required package: ggplot2
  rstan (Version 2.19.3, GitRev: 2e1f913d3ca3)
  For execution on a local, multicore CPU with excess RAM we recommend calling
  options(mc.cores = parallel::detectCores()).
  To avoid recompilation of unchanged Stan programs, we recommend calling
  rstan_options(auto_write = TRUE)
  > 
  > # https://stackoverflow.com/questions/12410694/rbundler-build-error-cannot-open-file-startup-rs-no-such-file-or-directory#27994299
  > Sys.setenv("R_TESTS" = "")
  > test_check("dgo")
  
  SAMPLING FOR MODEL '2017_01_04' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 1 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0 seconds (Warm-up)
  Chain 1:                0 seconds (Sampling)
  Chain 1:                0 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL '2017_01_04' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 1 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0 seconds (Warm-up)
  Chain 1:                0.000991 seconds (Sampling)
  Chain 1:                0.000991 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL '2017_01_04' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 1 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0 seconds (Warm-up)
  Chain 1:                0 seconds (Sampling)
  Chain 1:                0 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL '2017_01_04' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.000991 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 9.91 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 1 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0 seconds (Warm-up)
  Chain 1:                0 seconds (Sampling)
  Chain 1:                0 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL '2017_01_04' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 1 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0 seconds (Warm-up)
  Chain 1:                0 seconds (Sampling)
  Chain 1:                0 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL '2017_01_04' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 1 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0 seconds (Warm-up)
  Chain 1:                0 seconds (Sampling)
  Chain 1:                0 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL '2017_01_04' NOW (CHAIN 2).
  Chain 2: 
  Chain 2: Gradient evaluation took 0.000319 seconds
  Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 3.19 seconds.
  Chain 2: Adjust your expectations accordingly!
  Chain 2: 
  Chain 2: 
  Chain 2: WARNING: No variance estimation is
  Chain 2:          performed for num_warmup < 20
  Chain 2: 
  Chain 2: Iteration: 1 / 1 [100%]  (Sampling)
  Chain 2: 
  Chain 2:  Elapsed Time: 0 seconds (Warm-up)
  Chain 2:                0.000993 seconds (Sampling)
  Chain 2:                0.000993 seconds (Total)
  Chain 2: 
  
  SAMPLING FOR MODEL '2017_01_04' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.000989 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 9.89 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 1 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0 seconds (Warm-up)
  Chain 1:                0.00099 seconds (Sampling)
  Chain 1:                0.00099 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL '2017_01_04' NOW (CHAIN 2).
  Chain 2: 
  Chain 2: Gradient evaluation took 0 seconds
  Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
  Chain 2: Adjust your expectations accordingly!
  Chain 2: 
  Chain 2: 
  Chain 2: WARNING: No variance estimation is
  Chain 2:          performed for num_warmup < 20
  Chain 2: 
  Chain 2: Iteration: 1 / 1 [100%]  (Sampling)
  Chain 2: 
  Chain 2:  Elapsed Time: 0 seconds (Warm-up)
  Chain 2:                0 seconds (Sampling)
  Chain 2:                0 seconds (Total)
  Chain 2: 
  ── 1. Failure: dgirt_plot and plot can be called (@test-plot.r#4)  ─────────────
  `plot(toy_dgirtfit)` produced warnings.
  
  ── 2. Failure: dgirt_plot and plot can be called (@test-plot.r#5)  ─────────────
  `dgirt_plot(toy_dgirtfit)` produced warnings.
  
  ── 3. Failure: plots can be amended (@test-plot.r#10)  ─────────────────────────
  `dgirt_plot(toy_dgirtfit) %+% ylab("foo")` produced warnings.
  
  ── 4. Failure: plot_rhats handles parameters (@test-plot.r#22)  ────────────────
  `plot_rhats(toy_dgirtfit, pars = "xi", color_var = "year")` produced warnings.
  
  ── 5. Failure: dispatch seems to work (@test-poststratify.r#5)  ────────────────
  `poststratify(...)` produced warnings.
  
  ── 6. Failure: omitted arguments produce errors (@test-poststratify.r#44)  ─────
  `poststratify(...)` produced warnings.
  
  ── 7. Failure: poststratify works for gamma, gamma_raw, and theta_bar (@test-pos
  `poststratify(...)` produced warnings.
  
  ── 8. Failure: poststratify works for gamma, gamma_raw, and theta_bar (@test-pos
  `poststratify(...)` produced warnings.
  
  ── 9. Failure: poststratification is by iteration for dgirtfit-class objects (@t
  `... <- NULL` produced warnings.
  
  ── 10. Failure: poststratifying posterior means gives the same result as averagi
  `... <- NULL` produced warnings.
  
  ══ testthat results  ═══════════════════════════════════════════════════════════
  [ OK: 374 | SKIPPED: 1 | WARNINGS: 66 | FAILED: 10 ]
  1.  Failure: dgirt_plot and plot can be called (@test-plot.r#4) 
  2.  Failure: dgirt_plot and plot can be called (@test-plot.r#5) 
  3.  Failure: plots can be amended (@test-plot.r#10) 
  4.  Failure: plot_rhats handles parameters (@test-plot.r#22) 
  5.  Failure: dispatch seems to work (@test-poststratify.r#5) 
  6.  Failure: omitted arguments produce errors (@test-poststratify.r#44) 
  7.  Failure: poststratify works for gamma, gamma_raw, and theta_bar (@test-poststratify.r#77) 
  8.  Failure: poststratify works for gamma, gamma_raw, and theta_bar (@test-poststratify.r#77) 
  9.  Failure: poststratification is by iteration for dgirtfit-class objects (@test-poststratify.r#128) 
  10. Failure: poststratifying posterior means gives the same result as averaging poststratified posterior samples (@test-poststratify.r#148) 
  
  Error: testthat unit tests failed
  Execution halted