From c95eb0dcd94e0cc16a08dcbd8d5bc367c80ca673 Mon Sep 17 00:00:00 2001
From: Ryan Nazareth <ryankarlos@gmail.com>
Date: Thu, 3 Oct 2019 17:45:37 +0100
Subject: [PATCH] Disabling calculation of uncertainties if uncertainty.samples
 is not True

---
 R/R/prophet.R | 26 ++++++++++++++++++--------
 1 file changed, 18 insertions(+), 8 deletions(-)

diff --git a/R/R/prophet.R b/R/R/prophet.R
index 92ae3fa..b49e17d 100644
--- a/R/R/prophet.R
+++ b/R/R/prophet.R
@@ -62,7 +62,8 @@ globalVariables(c(
 #'  If mcmc.samples>0, this will be integrated over all model parameters,
 #'  which will include uncertainty in seasonality.
 #' @param uncertainty.samples Number of simulated draws used to estimate
-#'  uncertainty intervals.
+#'  uncertainty intervals. Settings this value to 0 or False will disable
+#'  uncertainty estimation and speed up the calculation.
 #' @param fit Boolean, if FALSE the model is initialized but not fit.
 #' @param ... Additional arguments, passed to \code{\link{fit.prophet}}
 #'
@@ -1343,7 +1344,12 @@ predict.prophet <- function(object, df = NULL, ...) {
   df$trend <- predict_trend(object, df)
   seasonal.components <- predict_seasonal_components(object, df)
   intervals <- predict_uncertainty(object, df)
-
+  if uncertainty.samples{
+    intervals <- predict_uncertainty(object, df)
+  } else {
+    intervals <- NULL
+    }
+ 
   # Drop columns except ds, cap, floor, and trend
   cols <- c('ds', 'trend')
   if ('cap' %in% colnames(df)) {
@@ -1453,8 +1459,10 @@ predict_seasonal_components <- function(m, df) {
   m <- out$m
   seasonal.features <- out$seasonal.features
   component.cols <- out$component.cols
-  lower.p <- (1 - m$interval.width)/2
-  upper.p <- (1 + m$interval.width)/2
+  if uncertainty.samples{
+    lower.p <- (1 - m$interval.width)/2
+    upper.p <- (1 + m$interval.width)/2
+  }
 
   X <- as.matrix(seasonal.features)
   component.predictions <- data.frame(matrix(ncol = 0, nrow = nrow(X)))
@@ -1466,10 +1474,12 @@ predict_seasonal_components <- function(m, df) {
       comp <- comp * m$y.scale
     }
     component.predictions[[component]] <- rowMeans(comp, na.rm = TRUE)
-    component.predictions[[paste0(component, '_lower')]] <- apply(
-      comp, 1, stats::quantile, lower.p, na.rm = TRUE)
-    component.predictions[[paste0(component, '_upper')]] <- apply(
-      comp, 1, stats::quantile, upper.p, na.rm = TRUE)
+    if (uncertainty.samples){
+      component.predictions[[paste0(component, '_lower')]] <- apply(
+        comp, 1, stats::quantile, lower.p, na.rm = TRUE)
+      component.predictions[[paste0(component, '_upper')]] <- apply(
+        comp, 1, stats::quantile, upper.p, na.rm = TRUE)
+    }
   }
   return(component.predictions)
 }