Sep 032011
 

When plotting my typing performance, I wanted to demonstrate my baseline typing performance as well as the number of errors. For this, I discovered some quite useful capabilities in the CRAN package ggplot2.

DVORAK typing performance on Kinesis Contour Keyboard

results<-read.csv("./dvorak_vs_qwerty_typing_test_results.csv", header = TRUE);
png(filename="kinesis_dvorak.png", width=640, height=440, bg="#070707");
ggplot(results, aes(x=Trial, y=Kinesis.DVORAK)) + scale_x_continuous(name="Trial #", limits=c(1, 15), breaks=seq(1,15)) + scale_y_continuous(name="Words per Minute", limits=c(0,100), breaks=seq(0,100,by=10)) + geom_point(aes(x=results$Trial, y=(results$Kinesis.DVORAK + results$Errors)), color="#7b0000", pch=19) + geom_area(color="#004088", fill="#004088", alpha=0.5) + opts(title="Kinesis Keyboard - DVORAK Layout") + theme_bb() + opts(plot.title=theme_text(colour="#ffffff", size=14, vjust=1), axis.title.x=theme_text(colour="#ffffff",size=12,vjust=0), axis.title.y=theme_text(angle=90,colour="#ffffff",size=12), plot.background=theme_rect(colour="#070707", fill="#070707"), panel.background=theme_rect(colour="#666666"), panel.grid.major=theme_line(colour="#444444"), panel.grid.minor=theme_line(colour="#070707"));
dev.off();

Required packages: ggplot2, ggExtra

Download Data File

DVORAK vs QWERTY Typing Performance Results

 Posted by on 2011/09/03  Tip  Tags:
Apr 172010
 

Basic feature comparisons (e.g. amount of L3 cache):
Plot of Xeon 7500-series L3 Cache size

png( filename="plot.png", width=640, height=440, bg="#070707" );
par(bg="#070707", fg="white", col.axis="white", col.main="white", col.lab="white", mar=c(3,4,2,2) + 0.1);
plot(xeon$Model, xeon$L3.Cache, ylab="L3 Cache", border=brewer.pal(8, "Dark2"), cex.axis=1.3, cex.lab=1.5);
dev.off();

Two-factor comparisons (e.g. with and without turbo boost):
Plot of Xeon 7500-series Processor Frequency and Turbo Boost

png( filename="plot.png", width=640, height=440, bg="#070707" );
par(bg="#070707", fg="white", col.axis="white", col.main="white", col.lab="white", mar=c(3,4,2,2) + 0.1);
plot(xeon$Model, xeon$Frequency, ylab="Processor Frequency", ylim=c(1.8,2.8), border=brewer.pal(8, "Dark2"), cex.axis=1.3, cex.lab=1.5)
points(xeon$Model, xeon$Frequency..Turbo., col=brewer.pal(8, "Dark2"), pch=19)
dev.off();

Required packages: RColorBrewer

Download Data File

Intel Xeon 7500-series model lineup

 Posted by on 2010/04/17  Tip  Tags:
Apr 172010
 

I’ve loved R since the first time I used it in statistics class. I went several years without using it, but I probably should have pulled it out a few times. It’s incredibly powerful and ends up being quite fun for data visualization geeks. Unfortunately, it’s not intuitive to a lot of users.

Further, even those of us comfortable with it seem to quickly forget exactly how we displayed the data just the way we wanted last time. I’m going to post the tricks/scripts I write whenever I use R – both for others and myself to re-use. Just click on the tag R.

 Posted by on 2010/04/17  Tip  Tags: