(v1.6.0.9023) new unit test flow

R/resistance_predict.R

@@ -347,6 +347,20 @@ plot.resistance_predict <- function(x, main = paste("Resistance Prediction of",
          col = "grey40")
 }
 
+
+#' @method ggplot resistance_predict
+#' @rdname resistance_predict
+# will be exported using s3_register() in R/zzz.R
+ggplot.resistance_predict <- function(x,
+                               main = paste("Resistance Prediction of", x_name),
+                               ribbon = TRUE,
+                               ...) {
+  x_name <- paste0(ab_name(attributes(x)$ab), " (", attributes(x)$ab, ")")
+  meet_criteria(main, allow_class = "character", has_length = 1)
+  meet_criteria(ribbon, allow_class = "logical", has_length = 1)
+  ggplot_rsi_predict(x = x, main = main, ribbon = ribbon, ...)
+}
+
 #' @rdname resistance_predict
 #' @export
 ggplot_rsi_predict <- function(x,
@@ -360,14 +374,14 @@ ggplot_rsi_predict <- function(x,
   stop_ifnot_installed("ggplot2")
   stop_ifnot(inherits(x, "resistance_predict"), "`x` must be a resistance prediction model created with resistance_predict()")
   
-  
   if (attributes(x)$I_as_S == TRUE) {
     ylab <- "%R"
   } else {
     ylab <- "%IR"
   }
   
-  p <- ggplot2::ggplot(x, ggplot2::aes(x = year, y = value)) +
+  p <- ggplot2::ggplot(as.data.frame(x, stringsAsFactors = FALSE),
+                       ggplot2::aes(x = year, y = value)) +
     ggplot2::geom_point(data = subset(x, !is.na(observations)),
                         size = 2) +
     scale_y_percent(limits = c(0, 1)) +