feat: add clusters information to one-pagers, fix metric notes, reduce texts sizes, no ng check to recreate + fix: RNG warning

R/DESCRIPTION

@@ -1,7 +1,7 @@
 Package: Robyn
 Type: Package
 Title: Semi-Automated Marketing Mix Modeling (MMM) from Meta Marketing Science 
-Version: 3.10.5.9015
+Version: 3.10.5.9016
 Authors@R: c(
     person("Gufeng", "Zhou", , "gufeng@meta.com", c("cre","aut")),
     person("Leonel", "Sentana", , "leonelsentana@meta.com", c("aut")),

R/R/clusters.R

@@ -114,6 +114,7 @@ robyn_clusters <- function(input, dep_var_type,
       dim_red = dim_red, quiet = TRUE, seed = seed
     )
   )
+  cls$df <- group_by(cls$df, .data$cluster) %>% mutate(n = n()) %>% ungroup()
 
   # Select top models by minimum (weighted) distance to zero
   all_paid <- setdiff(names(cls$df), c(ignore, "cluster"))

R/R/json.R

@@ -74,7 +74,7 @@ robyn_write <- function(InputCollect,
       OutputCollect$OutputModels$trials
     collect$conv_msg <- gsub("\\:.*", "", OutputCollect$OutputModels$convergence$conv_msg)
     if ("clusters" %in% names(OutputCollect)) {
-      collect$clusters <- OutputCollect$clusters$n_clusters
+      collect$n_clusters <- OutputCollect$clusters$n_clusters
     }
 
     skip <- which(unlist(lapply(OutputCollect, function(x) is.list(x) | is.null(x))))
@@ -106,6 +106,14 @@ robyn_write <- function(InputCollect,
         select(order(colnames(.))) %>%
         as.list()
       outputs$hyper_updated <- OutputCollect$hyper_updated
+      if ("clusters" %in% names(OutputCollect)) {
+        outputs$clusters <- list(
+          data = OutputCollect$clusters$data %>%
+            group_by(.data$cluster) %>% mutate(n = n()) %>%
+            filter(.data$solID == select_model) %>%
+            select(any_of(c("solID", "cluster", "n")))
+        )
+      }
       ret[["ExportedModel"]] <- outputs
     } else {
       select_model <- "models"

R/R/model.R

@@ -229,6 +229,11 @@ robyn_run <- function(InputCollect = NULL,
     output <- robyn_outputs(InputCollect, OutputModels, clusters = FALSE, ...)
   }
 
+  # Created with assign from JSON file
+  if (exists("clusters"))
+    if (!is.integer(get("clusters")))
+      output$clusters <- get("clusters")
+
   # Check convergence when more than 1 iteration
   if (!hyper_collect$all_fixed) {
     output[["convergence"]] <- robyn_converge(OutputModels, ...)
@@ -300,7 +305,7 @@ Pareto-front ({x$pareto_fronts}) All solutions ({nSols}): {paste(x$allSolutions,
 {clusters_info}
 ",
       nSols = length(x$allSolutions),
-      clusters_info = if ("clusters" %in% names(x)) {
+      clusters_info = if ("models" %in% names(x[["clusters"]])) {
         glued(
           "Clusters (k = {x$clusters$n_clusters}): {paste(x$clusters$models$solID, collapse = ', ')}"
         )
@@ -451,17 +456,19 @@ robyn_mmm <- function(InputCollect,
                       trial = 1L,
                       seed = 123L,
                       quiet = FALSE, ...) {
-  if (reticulate::py_module_available("nevergrad")) {
-    ng <- reticulate::import("nevergrad", delay_load = TRUE)
-    if (is.integer(seed)) {
-      np <- reticulate::import("numpy", delay_load = FALSE)
-      np$random$seed(seed)
+  if (iterations > 1) {
+    if (reticulate::py_module_available("nevergrad")) {
+      ng <- reticulate::import("nevergrad", delay_load = TRUE)
+      if (is.integer(seed)) {
+        np <- reticulate::import("numpy", delay_load = FALSE)
+        np$random$seed(seed)
+      }
+    } else {
+      stop(
+        "You must have nevergrad python library installed.\nPlease check our install demo: ",
+        "https://github.com/facebookexperimental/Robyn/blob/main/demo/install_nevergrad.R"
+      )
     }
-  } else {
-    stop(
-      "You must have nevergrad python library installed.\nPlease check our install demo: ",
-      "https://github.com/facebookexperimental/Robyn/blob/main/demo/install_nevergrad.R"
-    )
   }
 
   ################################################

R/R/plots.R

@@ -257,6 +257,7 @@ robyn_onepagers <- function(
     baseline_level = 0, ...) {
   check_class("robyn_outputs", OutputCollect)
   if (TRUE) {
+    window <- c(InputCollect$window_start, InputCollect$window_end)
     pareto_fronts <- OutputCollect$pareto_fronts
     hyper_fixed <- OutputCollect$hyper_fixed
     resultHypParam <- as_tibble(OutputCollect$resultHypParam)
@@ -315,7 +316,7 @@ robyn_onepagers <- function(
     uniqueSol <- unique(plotMediaShare$solID)
 
     # parallelResult <- for (sid in uniqueSol) { # sid = uniqueSol[1]
-    parallelResult <- foreach(sid = uniqueSol) %dorng% { # sid = uniqueSol[1]
+    parallelResult <- foreach(sid = uniqueSol, .options.RNG = OutputCollect$seed) %dorng% { # sid = uniqueSol[1]
 
       if (TRUE) {
         plotMediaShareLoop <- plotMediaShare[plotMediaShare$solID == sid, ]
@@ -354,7 +355,7 @@ robyn_onepagers <- function(
       plotMediaShareLoopLine <- temp[[sid]]$plot1data$plotMediaShareLoopLine
       ySecScale <- temp[[sid]]$plot1data$ySecScale
       plotMediaShareLoopBar$variable <- stringr::str_to_title(gsub("_", " ", plotMediaShareLoopBar$variable))
-      type <- ifelse(InputCollect$dep_var_type == "conversion", "CPA", "ROI")
+      type <- ifelse(InputCollect$dep_var_type == "conversion", "CPA", "ROAS")
       plotMediaShareLoopLine$type_colour <- type_colour <- "#03396C"
       names(type_colour) <- "type_colour"
       p1 <- ggplot(plotMediaShareLoopBar, aes(x = .data$rn, y = .data$value, fill = .data$variable)) +
@@ -386,7 +387,7 @@ robyn_onepagers <- function(
         scale_fill_brewer(palette = 3) +
         scale_color_identity(guide = "legend", labels = type) +
         labs(
-          title = paste0("Share of Sum of Spend, Sum of Effect & Total ", type, " in Modeling Window*"),
+          title = paste0("Share of Total Spend, Effect & ", type, " in Modeling Window*"),
           x = NULL, fill = NULL, color = NULL
         )
 
@@ -589,7 +590,14 @@ robyn_onepagers <- function(
 
       ## 8. Bootstrapped ROI/CPA with CIs
       if ("ci_low" %in% colnames(xDecompAgg)) {
-        metric <- ifelse(InputCollect$dep_var_type == "conversion", "CPA", "ROI")
+        cluster_txt <- ""
+        if ("clusters" %in% names(OutputCollect)) {
+          temp <- OutputCollect$clusters$data
+          if (!"n" %in% colnames(temp)) temp <- group_by(temp, .data$cluster) %>% mutate(n = n())
+          temp <- filter(temp, .data$solID == sid)
+          cluster_txt <- sprintf(" %s (%s IDs)", temp$cluster, temp$n)
+        }
+        title <- sprintf("In-cluster%s bootstrapped %s [95%% CI & mean]", cluster_txt, type)
         p8 <- xDecompAgg %>%
           filter(!is.na(.data$ci_low), .data$solID == sid) %>%
           select(.data$rn, .data$solID, .data$boot_mean, .data$ci_low, .data$ci_up) %>%
@@ -599,10 +607,10 @@ robyn_onepagers <- function(
           geom_text(aes(y = .data$ci_low, label = signif(.data$ci_low, 2)), hjust = 1.1, size = 2.8) +
           geom_text(aes(y = .data$ci_up, label = signif(.data$ci_up, 2)), hjust = -0.1, size = 2.8) +
           geom_errorbar(aes(ymin = .data$ci_low, ymax = .data$ci_up), width = 0.25) +
-          labs(title = paste("In-cluster bootstrapped", metric, "with 95% CI & mean"), x = NULL, y = NULL) +
+          labs(title = title, x = NULL, y = NULL) +
           coord_flip() +
           theme_lares(background = "white", )
-        if (metric == "ROI") {
+        if (type == "ROAS") {
           p8 <- p8 + geom_hline(yintercept = 1, alpha = 0.5, colour = "grey50", linetype = "dashed")
         }
       } else {
@@ -614,8 +622,12 @@ robyn_onepagers <- function(
       rver <- utils::sessionInfo()$R.version
       onepagerTitle <- sprintf("One-pager for Model ID: %s", sid)
       onepagerCaption <- sprintf("Robyn v%s [R-%s.%s]", ver, rver$major, rver$minor)
-      onepagerCaption <- paste0(onepagerCaption,
-                                "\n*Total ROI = sum of response / sum of spend in the modeling window")
+      calc <- ifelse(type == "ROAS",
+                     "Total ROAS = sum of response / sum of spend",
+                     "Total CPA = sum of spend / sum of response")
+      onepagerCaption <- paste0(
+        "*", calc, " in modeling window ", paste0(window, collapse = ":"),
+        "\n", onepagerCaption)
       get_height <- length(unique(plotMediaShareLoopLine$rn)) / 5
       pg <- (p2 + p5) / (p1 + p8) / (p3 + p7) / (p4 + p6) +
         patchwork::plot_layout(heights = c(get_height, get_height, get_height, 1)) +
@@ -676,8 +688,8 @@ allocation_plots <- function(
     "* Mean CPA = raw spend / mean response | mCPA =  marginal spend / marginal response"
   )
   formulax1 <- paste0(
-    "The allocator 'mean response' = curve response of adstocked mean spend in date range, ",
-    "while the model onepager 'sum of effect' = sum of curve responses of all adstocked spends in modeling window\n",
+    "Allocator's mean response = curve response of adstocked mean spend in date range, ",
+    "while\n Model's sum of effect = sum of curve responses of all adstocked spends in modeling window\n",
     formulax1)
   formulax2 <- sprintf("When reallocating budget, m%s converges across media within respective bounds", metric)