tidy_step is dead, long live declare_step with no default handler.

NAMESPACE

@@ -40,7 +40,6 @@ export(reveal_outcomes_handler)
 export(run_design)
 export(simulate_design)
 export(tidy_estimator)
-export(tidy_step)
 importFrom(estimatr,difference_in_means)
 importFrom(fabricatr,add_level)
 importFrom(fabricatr,fabricate)

R/construct_design.R

@@ -38,11 +38,13 @@
 #' my_estimand <- declare_estimand(ATE = mean(Y_Z_1 - Y_Z_0))
 #'
 #' my_estimator <- declare_estimator(Y ~ Z, estimand = my_estimand)
+#' 
+#' my_mutate <- declare_step(dplyr::mutate, noise_sq = noise^2)
 #'
 #' my_reveal <- declare_reveal()
 #'
 #' design <- my_population + my_potential_outcomes + my_sampling + 
-#'          my_estimand + tidy_step(dplyr::mutate(noise_sq = noise^2)) + 
+#'          my_estimand + my_mutate + 
 #'          my_assignment + my_reveal + my_estimator
 #'
 #' design
@@ -93,7 +95,7 @@
   } else{
 
     if (!inherits(rhs, "dd") & !inherits(rhs, "function")) {
-      stop("The right hand side does not appear to be a DeclareDesign object. Can you wrap the step with `tidy_step()`?", call. = FALSE)
+      stop("The right hand side does not appear to be a DeclareDesign object or a function", call. = FALSE)
     }
 
     if (inherits(lhs, "design")) {

R/declare_step.R

@@ -1,15 +1,17 @@
 #' Declare a custom step
+#' 
+#' With declare_step, you can include any function that takes data as one of its arguments and returns data in a design declaration. The first argument is always a "handler", which is the name of the data-in, data-out function. 
+#' 
 #' @inheritParams declare_internal_inherit_params
 #' @return a function that returns a data.frame
 #' @export
-#' @importFrom fabricatr fabricate
 #' @examples
 #'
 #' N <- 50
 #' my_population <- declare_population(N = N, noise = rnorm(N))
 #' my_assignment <- declare_assignment(m = 25)
-#' my_step <- declare_step(Z2 = Z, q = 5)
+#' my_step <- declare_step(fabricate, Z2 = Z, q = 5)
 #'
 #' design <- my_population + my_assignment + my_step
 #'
-declare_step <- make_declarations(fabricate, "custom")
+declare_step <- make_declarations(function(data, ...f, ...) ...f(data, ...), "custom")

R/design_helper_functions.R

@@ -9,7 +9,7 @@
 #'   declare_potential_outcomes(Y ~ noise + Z * rnorm(N, 2, 2)) +
 #'   declare_sampling(n = 250) +
 #'   declare_estimand(ATE = mean(Y_Z_1 - Y_Z_0)) +
-#'   tidy_step(dplyr::mutate(noise_sq = noise^2)) +
+#'   declare_step(dplyr::mutate, noise_sq = noise^2) +
 #'   declare_assignment(m = 25) +
 #'   declare_reveal() +
 #'   declare_estimator(Y ~ Z, estimand = "my_estimand")
@@ -353,14 +353,16 @@ print.design <- function(x, verbose = TRUE, ...) {
 #' my_estimand <- declare_estimand(ATE = mean(Y_Z_1 - Y_Z_0))
 #'
 #' my_estimator <- declare_estimator(Y ~ Z, estimand = my_estimand)
+#' 
+#' my_mutate <- declare_step(dplyr::mutate, noise_sq = noise ^ 2)
 #'
 #' my_reveal <- declare_reveal()
 #'
 #' design <- my_population +
 #'   my_potential_outcomes +
 #'   my_sampling +
 #'   my_estimand +
-#'   tidy_step(dplyr::mutate(noise_sq = noise ^ 2)) +
+#'   my_mutate +
 #'   my_assignment +
 #'   my_reveal +
 #'   my_estimator

tests/testthat/test-allow-custom-functions.R

@@ -37,25 +37,3 @@ test_that("a dplyr pipeline can be used in a design", {
 
 })
 
-
-# case 3
-
-test_that("a function call can be used in a design", {
-
-  `%dd%` <- DeclareDesign:::`+.dd`
-
-  my_func <- function(data, my_n = 50){
-    data %>% sample_n(n = my_n)
-  }
-
-  # errors before sending to our operator function
-  my_pop + my_func(my_n = 50)
-
-  # sends into our operator function
-  my_pop %dd% my_func(my_n = 50)
-
-  dat <- draw_data(des)
-
-  expect_equal(nrow(dat), 50)
-
-})

tests/testthat/test-declare-design.R

@@ -18,13 +18,15 @@ test_that(
 
     my_estimator <- declare_estimator(Y ~ Z, estimand = my_estimand)
 
+    my_mutate <- declare_step(dplyr::mutate, noise_sq = noise^2)
+
     my_reveal <- declare_reveal()
 
     design <- my_population +
       my_potential_outcomes +
       my_sampling +
       my_estimand +
-      tidy_step(dplyr::mutate(q = 5)) +
+      my_mutate +
       my_assignment +
       my_reveal +
       my_estimator
@@ -59,13 +61,3 @@ test_that("No estimators / estimands", {
 
 })
 
-
-
-
-test_that("Declare a bare function", {
-
-  expect_error(tidy_step(function(foo) foo), "The arguments of the tidy'd function do not include data or .data.")
-
-})
-
-

tests/testthat/test-declare-step.R

@@ -3,7 +3,7 @@ context("declare step")
 test_that("test declare step ", {
   my_population <- declare_population(N = 50, noise = rnorm(N))
   my_assignment <- declare_assignment(m = 25)
-  my_step <- declare_step(Z2 = Z, q = 5)
+  my_step <- declare_step(fabricate, Z2 = Z, q = 5)
 
   design <- my_population + my_assignment + my_step
   df <- draw_data(design)

tests/testthat/test-demo.R

@@ -97,7 +97,7 @@ test_that("demo runs", {
   design <- my_population + 
     my_potential_outcomes + 
     my_estimand + 
-    tidy_step(dplyr::mutate(big_income = 5*income)) + 
+    declare_step(dplyr::mutate, big_income = 5*income) + 
     my_sampling + 
     my_assignment + 
     reveal_outcomes + 

tests/testthat/test-design-summary.R

@@ -20,7 +20,7 @@ test_that("Basic design summary", {
     my_potential_outcomes + 
     my_sampling + 
     my_estimand + 
-    tidy_step(dplyr::mutate(q = 5)) + 
+    declare_step(dplyr::mutate, q = 5) + 
     my_assignment + 
     reveal_outcomes + 
     my_estimator

tests/testthat/test-diagnose-design.R

@@ -24,7 +24,7 @@ test_that("allow design functions to be sent to simulate design and diagnose_des
       my_potential_outcomes +
       my_sampling +
       my_estimand +
-      tidy_step(dplyr::mutate(q = 5)) +
+      declare_step(dplyr::mutate, q = 5) +
       my_assignment +
       my_reveal +
       my_estimator

tests/testthat/test-factorial.R

@@ -24,10 +24,11 @@ test_that("Factorial", {
       my_potential_outcomes + 
       my_estimand + 
       my_assignment + 
-      tidy_step(dplyr::mutate(Z1 = as.numeric(Z %in% c("T2", "T4")),
-             Z2 = as.numeric(Z %in% c("T3", "T4")))) +
-      reveal_outcomes +
-      my_estimator
+    declare_step(dplyr::mutate, 
+                 Z1 = as.numeric(Z %in% c("T2", "T4")),
+                 Z2 = as.numeric(Z %in% c("T3", "T4"))) +
+    reveal_outcomes +
+    my_estimator
 
   expect_equal(my_design %>% draw_data %>% nrow, 2000)
   expect_equal(my_design %>% run_design %>% names, c("estimates_df", "estimands_df"))

tests/testthat/test-modify-design.R

@@ -13,7 +13,7 @@ test_that("test modify declare design ", {
 
   design <- my_population +
     my_potential_outcomes +
-    tidy_step(dplyr::mutate(q = 5)) +
+    declare_step(dplyr::mutate, q = 5) +
     my_assignment
 
   my_assignment_2 <- declare_assignment(m = 25, assignment_variable = "Z2")

tests/testthat/test-multiple-estimators.R

@@ -12,7 +12,7 @@ test_that("Two estimators, Two estimands (matched)",{
                      subset = ID %in% 1:5) +
     declare_estimand(CATE_6_10 = mean(extra[group == 2]) - mean(extra[group == 1]),
                      subset = ID %in% 6:10) +
-    declare_step(extra = extra + rnorm(N)) +
+    declare_step(fabricate, extra = extra + rnorm(N)) +
     declare_estimator(
       extra ~ group,
       subset = ID %in% 1:5,

tests/testthat/test-noncompliance.R

@@ -46,7 +46,7 @@ test_that("Noncompliance", {
   design <- my_population +
     POS_Y +
     POS_Z +
-    declare_step(complier = as.numeric(D_Z_0 == 0 & D_Z_1 == 1)) +
+    declare_step(fabricate, complier = as.numeric(D_Z_0 == 0 & D_Z_1 == 1)) +
     ITT_d +
     CACE +
     my_assignment +