Merge pull request #746 from njtierney/master

tweaks for CRAN 0.5.0 release

Author: njtierney

inst/WORDLIST

@@ -3,7 +3,9 @@ AVX
 AdagradDAOptimiser
 CMD
 CRAN's
+Cmd
 Codecov
+Ctrl
 DAGs
 DiagrammeR
 GPUs
@@ -18,6 +20,7 @@ Hermann
 Hessians
 JIT
 Jupyter
+LKJ
 Lmax
 Lmin
 McMahan
@@ -45,16 +48,20 @@ acyclic
 al
 analysed
 args
+automagically
 bayesplot
 behaviour
+bijection
 broadcastable
 broadcasted
+chol
+choleskied
 cholesky
 cli
 colour
 colours
 conda
-cran
+dependences
 deps
 devtools
 dlkjcorr
@@ -66,6 +73,7 @@ equalling
 et
 extraDistr
 generalises
+geweke
 gfortran
 github
 greta's
@@ -80,7 +88,9 @@ joss
 labelled
 libxml
 linux
+lkj
 logfile
+logfiles
 maximise
 mcmc
 md
@@ -90,6 +100,7 @@ modelled
 modelling
 multisession
 nd
+normalisation
 normalised
 optimisation
 optimisations
@@ -123,8 +134,10 @@ softmax
 specialised
 summarise
 tensorflow
+tensorflows
 tf
 tfp
+tril
 tuh
 unadjusted
 uncentered
@@ -133,4 +146,5 @@ vectorising
 visualise
 warmup
 winbuilder
+wishart
 zhang

tests/testthat/_snaps/print_calculate.md

@@ -7,40 +7,48 @@
       , , 1
       
                   [,1]
-       [1,]  0.4559286
-       [2,] -0.9169700
-       [3,]  0.2051770
-       [4,] -1.7940580
-       [5,]  1.2063919
-       [6,] -0.1103080
-       [7,]  0.5195801
-       [8,] -0.7110114
-       [9,]  1.0908014
-      [10,] -1.0610485
+       [1,] -1.3716505
+       [2,] -0.3086943
+       [3,] -1.2029317
+       [4,] -0.7109460
+       [5,] -0.4889447
+       [6,]  1.1541374
+       [7,]  0.8869046
+       [8,] -0.3983025
+       [9,]  0.4208952
+      [10,] -1.1759923
       
       
 
 ---
 
     Code
-      x_draws_10
-    Output
-      $x
-      , , 1
-      
-                   [,1]
-       [1,] -0.64461997
-       [2,] -1.89567086
-       [3,] -1.32104850
-       [4,]  0.07416449
-       [5,] -1.33409029
-       [6,] -1.88981759
-       [7,] -0.32234742
-       [8,]  0.42244656
-       [9,] -0.11780999
-      [10,] -1.11090368
+      x_draws_values
+    Message
       
+      -- MCMC draws from greta -------------------------------------------------------
+      * Iterations = 10
+      * Chains = 4
+      * Thinning = 1
       
+      -- Chain 1 (iterations 1...5) --------------------------------------------------
+    Output
+                     x
+      [1,] -0.08002652
+      [2,] -1.83388724
+      [3,] -0.16133841
+      [4,] -0.01941975
+      [5,] -0.43649773
+    Message
+      i 5 more draws
+      Use `print(n = ...)` to see more draws
+      --------------------------------------------------------------------------------
+      i View greta draw chain i with:
+      `greta_draws_object[[i]]`. 
+      E.g., view chain 1 with: 
+      `greta_draws_object[[1]]`.
+      i To see a summary of draws, run:
+      `summary(greta_draws_object)`
 
 ---
 
@@ -50,17 +58,17 @@
       $x
       , , 1
       
-                   [,1]
-       [1,] -0.64461997
-       [2,] -1.89567086
-       [3,] -1.32104850
-       [4,]  0.07416449
-       [5,] -1.33409029
-       [6,] -1.88981759
-       [7,] -0.32234742
-       [8,]  0.42244656
-       [9,] -0.11780999
-      [10,] -1.11090368
+                  [,1]
+       [1,]  0.1224691
+       [2,]  1.6876720
+       [3,] -2.0192331
+       [4,] -1.2172102
+       [5,]  0.8676729
+       [6,] -0.1613384
+       [7,] -1.0970895
+       [8,] -2.0362168
+       [9,]  0.9766937
+      [10,]  0.9396561
       
       
 

tests/testthat/test-print_calculate.R

@@ -6,12 +6,13 @@ test_that("calculate print method is different for different inputs", {
 
   x <- normal(0,1)
   m <- model(x)
-  tensorflow::set_random_seed(2024-07-30-1057)
-  draws <- mcmc(m, n_samples = 10, warmup = 10, verbose = FALSE)
-  x_sim_10 <- calculate(x, nsim = 10, seed = 2024-08-1004)
-  x_draws_10 <- calculate(x, values = draws, seed = 2024-08-1004)
-  x_draws_10 <- calculate(x, values = draws, nsim = 10, seed = 2024-08-1004)
+  new_seed <- 2024-11-07-14-01
+  x_sim_10 <- calculate(x, nsim = 10, seed = new_seed)
   expect_snapshot(x_sim_10)
-  expect_snapshot(x_draws_10)
+  set.seed(new_seed)
+  draws <- mcmc(m, n_samples = 10, warmup = 10, verbose = FALSE)
+  x_draws_values <- calculate(x, values = draws, seed = new_seed)
+  expect_snapshot(x_draws_values)
+  x_draws_10 <- calculate(x, values = draws, nsim = 10, seed = new_seed)
   expect_snapshot(x_draws_10)
 })