more tests.

npoExamples.R

@@ -186,7 +186,7 @@ graph = dag_create() %>%
 
 graph %>% dag_render()
 graph %>% dag_render(shortLabel = TRUE)
-drawsDF = graph %>% dag_numpyro()
+drawsDF = graph %>% dag_numpyro(mcmc = FALSE)
 drawsDF %>% dagp_plot()
 
 ### greta example #5: Multiple Categorical Regression

tests/testthat/test-dag_numpyroGamma.R

@@ -0,0 +1,20 @@
+test_that("gamma Dist in Use", {
+ graph = dag_create() %>%
+ dag_node("Tree Height","x",
+ rhs = student(nu,mu,sigma),
+ data = trees$Height) %>%
+ dag_node("Degrees Of Freedom","nu",
+ rhs = gamma(2,0.1),
+ child = "x") %>%
+ dag_node("Avg Cherry Tree Height","mu",
+ rhs = normal(50,24.5),
+ child = "x") %>%
+ dag_node("StdDev of Observed Height","sigma",
+ rhs = uniform(0,50),
+ child = "x") %>%
+ dag_plate("Observation","i",
+ nodeLabels = "x")
+ mcmcCode = graph %>% dag_numpyro(mcmc = FALSE)
+ expect_type(mcmcCode, "character")
+})
+

tests/testthat/test-distributions.R

@@ -7,5 +7,11 @@ test_that("distributions have good output", {
  expect_equal(uniformString, "dist.Uniform(0,8)")
  studentString = causact::student(df=3,mu=8,sigma=7)
  expect_equal(studentString, "dist.StudentT(3,8,7)")
+ poissonString = causact::poisson(lambda = 9)
+ expect_equal(poissonString, "dist.Poisson(9)")
+ logNorm = causact::lognormal(meanlog = 9, 10)
+ expect_equal(logNorm, "dist.LogNormal(9,10)")
+ binomStr = causact::binomial("numTrials","succProb")
+ expect_equal(binomStr, "dist.Binomial(numTrials,succProb)")
 })