we also need lattice

[don.git] / posts / bug_reporting_rate.mdwn

diff --git a/posts/bug_reporting_rate.mdwn b/posts/bug_reporting_rate.mdwn
index 8cf225c5626e0f33bc8af1927f804023c27bbc4a..4266c45253aaceb363439dbc32b185508af6fcf2 100644 (file)
--- a/posts/bug_reporting_rate.mdwn
+++ b/posts/bug_reporting_rate.mdwn
@@ -16,6 +16,7 @@ Now, lets get the data into R and plot it.
 [For clarity, I'm not showing the R code, but it's available in the source cdoe for this post.]
 
 [[!sweavealike results="hide" fig=1 echo=0 code="""
+require(lattice)
 reporting.rate <- read.table("data/bug_reporting_rate.txt")
 colnames(reporting.rate) <- c("bug","epoch")
 reporting.rate <- data.frame(reporting.rate)
@@ -27,13 +28,13 @@ reporting.rate$rate <- c(NA,(reporting.rate$bug[-1] - reporting.rate$bug[-nrow(r
        (reporting.rate$epoch[-1]-reporting.rate$epoch[-nrow(reporting.rate)]))
 reporting.rate$day <- as.POSIXct(reporting.rate$epoch,origin="1970-01-01")
 ### show the reporting rate from 2003 onward with a lowess line
-xyplot(rate~day,reporting.rate[reporting.rate$epoch >= 1041408000,],
+print(xyplot(rate~day,reporting.rate[reporting.rate$epoch >= 1041408000,],
        panel=function(x,y,col,...){
             panel.xyplot(x,y,col="cyan",...);
                 panel.loess(x,y,col="red",...);},
       ylim=c(0,0.005),
          ylab="Bugs per Second",
-         xlab="Time")
+         xlab="Time"))
 """]]
 
 From the plot (Bugs reported per second over time with a red loess fit