@@ -882,7 +882,8 @@ setMethod("plotRPC",

         diffMeansByK$L <- as.factor(diffMeansByK$L)

         diffMeansByK$rollmean <- data.table::frollmean(

             diffMeansByK$meanperpdiffK, n = n, align = "center")

-

+        diffMeansByK <- diffMeansByK[complete.cases(diffMeansByK),]

+        

         if (nlevels(dt$L) > 1) {

             plot <- ggplot2::ggplot(dt[!is.na(perpdiffK), ],

                 ggplot2::aes_string(x = "K",

@@ -890,7 +891,7 @@ setMethod("plotRPC",

                 ggplot2::geom_jitter(height = 0, width = 0.1, alpha = alpha,

                     ggplot2::aes_string(color = "L")) +

                 ggplot2::scale_color_discrete(name = "L") +

-                ggplot2::geom_path(data = diffMeansByK[!is.na(meanperpdiffK), ],

+                ggplot2::geom_path(data = diffMeansByK,

                     ggplot2::aes_string(x = "K", y = "rollmean", group = "L",

                         color = "L"), size = 1) +

                 ggplot2::ylab("Rate of perplexity change") +

@@ -908,7 +909,7 @@ setMethod("plotRPC",

                 ggplot2::geom_jitter(height = 0, width = 0.1,

                     color = "grey", alpha = alpha) +

                 ggplot2::scale_color_manual(name = "L", values = "black") +

-                ggplot2::geom_path(data = diffMeansByK[!is.na(meanperpdiffK), ],

+                ggplot2::geom_path(data = diffMeansByK,

                     ggplot2::aes_string(x = "K", y = "rollmean", group = "L",

                         color = "L"), size = 1) +

                 ggplot2::ylab("Rate of perplexity change") +

@@ -938,14 +939,15 @@ setMethod("plotRPC",

         diffMeansByL$L <- as.factor(diffMeansByL$L)

         diffMeansByL$rollmean <- data.table::frollmean(

             diffMeansByL$meanperpdiffL, n = n, align = "center")

-

+        diffMeansByL <- diffMeansByL[complete.cases(diffMeansByL),]

+        

         plot <- ggplot2::ggplot(dt[!is.na(perpdiffL), ],

             ggplot2::aes_string(x = "L", y = "perpdiffL")) +

             ggplot2::geom_jitter(height = 0, width = 0.1,

                 color = "grey", alpha = alpha) +

             ggplot2::scale_color_manual(name = "K", values = "black") +

             ggplot2::geom_path(

-                data = diffMeansByL[!is.na(meanperpdiffL), ],

+                data = diffMeansByL,

                 ggplot2::aes_string(

                     x = "L", y = "rollmean", group = "K", color = "K"),

                 size = 1) +

@@ -1000,13 +1002,14 @@ setMethod("plotRPC",

         diffMeansByK$K <- as.factor(diffMeansByK$K)

         diffMeansByK$rollmean <- data.table::frollmean(

             diffMeansByK$meanperpdiffK, n = n, align = "center")

-

+        diffMeansByK <- diffMeansByK[complete.cases(diffMeansByK),]

+        

         plot <- ggplot2::ggplot(dt[!is.na(perpdiffK), ],

             ggplot2::aes_string(x = "K",

                 y = "perpdiffK")) +

             ggplot2::geom_jitter(height = 0, width = 0.1,

                 color = "grey", alpha = alpha) +

-            ggplot2::geom_path(data = diffMeansByK[!is.na(meanperpdiffK), ],

+            ggplot2::geom_path(data = diffMeansByK,

                 ggplot2::aes_string(x = "K", y = "rollmean", group = 1),

                 size = 1) +

             ggplot2::ylab("Perplexity difference compared to previous K") +

@@ -1059,13 +1062,14 @@ setMethod("plotRPC",

         diffMeansByL$L <- as.factor(diffMeansByL$L)

         diffMeansByL$rollmean <- data.table::frollmean(

             diffMeansByL$meanperpdiffL, n = n, align = "center")

-

+        diffMeansByL <- diffMeansByL[complete.cases(diffMeansByL),]

+        

         plot <- ggplot2::ggplot(dt[!is.na(perpdiffL), ],

             ggplot2::aes_string(x = "L",

                 y = "perpdiffL")) +

             ggplot2::geom_jitter(height = 0, width = 0.1,

                 color = "grey", alpha = alpha) +

-            ggplot2::geom_path(data = diffMeansByL[!is.na(meanperpdiffL), ],

+            ggplot2::geom_path(data = diffMeansByL,

                 ggplot2::aes_string(x = "L", y = "rollmean", group = 1),

                 size = 1) +

             ggplot2::ylab("Perplexity difference compared to previous L") +