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OSADL HOWTOs

HOWTO: Create a pseudo 3D long-term latency graphic derived from a large number of consecutive latency plots

Create a set of test data

In a first step, we need to create some test data that must be formatted in the same way as the actual plot data:

<Number (µs)> <space> <frequency core #0> <tabulator> <frequency core #1> <tabulator> <frequency core #N>

To do so, we run the following script:

#!/bin/bash

echo=`which echo`

for i in `seq 1 180`
do
core0=`expr 90000000 - $i \* 360000`
core1=`expr 80000000 - $i \* 360000`
core2=`expr 70000000 - $i \* 360000`
core3=`expr 80000000 - $i \* 360000`
rm -f latency-$i
for j in `seq 0 399`
do
$echo -e `printf %06d $j` $core0\\t$core1\\t$core2\\t$core3 >>latency-`printf %03d $i`
core0=`expr $core0 - 500000`; if test $core0 -lt 0; then core0=0; fi;
core1=`expr $core1 - 500000`; if test $core1 -lt 0; then core1=0; fi;
core2=`expr $core2 - 500000`; if test $core2 -lt 0; then core2=0; fi;
core3=`expr $core3 - 500000`; if test $core3 -lt 0; then core3=0; fi;
done
done

sed -i "s/200 0/200 1/" latency-090

which will create a total of 180 simulated data files named latency-001 to latency-180 in the same format as if they had been obtained form cyclictest running in histogram mode on a 4-core processor. An artificial single outlier with a latency of 200 µs occurring at latency plot #90 is inserted.

Create the pseudo 3D graphic with R

This R script will read the data, select the highest value per line, transform them to a 3D matrix and call the persp() routine to generate the graphic.

read.matrix <-
function(file, header = FALSE, sep = "", skip = 0)
{
  row.lens <- count.fields(file, sep = sep, skip = skip)
  if(any(row.lens != row.lens[1]))
    stop("number of columns is not constant")
  if(header) {
    nrows <- length(row.lens) - 1
    ncols <- row.lens[2]
    col.names <- scan(file, what = "", sep = sep, nlines = 1, quiet = TRUE, skip = skip)
    x <- scan(file, sep = sep, skip = skip + 1, quiet = TRUE)
  }
  else {
    nrows <- length(row.lens)
    ncols <- row.lens[1]
    x <- scan(file, sep = sep, skip = skip, quiet = TRUE)
    col.names <- NULL
  }
  x <- as.double(x)
  if(ncols > 1) {
    dim(x) <- c(ncols,nrows)
    x <- t(x)
    colnames(x) <- col.names
  }
  else if(ncols == 1)
    x <- as.vector(x)
  else
    stop("wrong number of columns")
  return(x)
}

read.latencyplots <-
function(dir = ".")
{
  i <- 1
  files <- dir(".")
  files <- sort(files, decreasing = TRUE)
  r = read.delim(files[1], sep = "\n")
  rows = dim(r)[1] + 1
  z <- matrix(nrow = rows, ncol = length(files))
  for (file in files) {
    m <- read.matrix(file=file)
    m[,1] <- 0
    m <- apply(m, 1, max, na.rm = TRUE)
    z[,i] <- m
    i <- i + 1
  }
  return(z)
}

data = read.latencyplots(dir = ".")
data <- data + 0.1
data <- log10(data)
z <- data

x <- 1:nrow(z)
x <- c(min(x) - 1e-10, x, max(x) + 1e-10)

y <- 1:ncol(z)
y <- c(min(y) - 1e-10, y, max(y) + 1e-10)

z0 <- min(z)
z <- rbind(z0, cbind(z0, z, z0), z0)
fill <- matrix("green3", nrow = nrow(z)-1, ncol = ncol(z)-1)
fill[ , i2 <- c(1,ncol(fill))] <- "gray"
fill[i1 <- c(1,nrow(fill)) , ] <- "gray"
par(bg = "slategray")
fillfunc <- colorRampPalette(c("green", "yellow", "red"), space = "Lab",  interpolate = "spline")
fcol <- fill ; fcol[] <- fillfunc(nrow(fcol))

pdf("../3Dplot.pdf", paper = "special", width = 11.69, height = 8.26)
par(fin = c(10.69, 7.26), mai = c(0.5, 0.5, 0.5, 0.5), ps = 12, pty = "m")
persp(x, y, z, theta = 30, phi = 25, col = fcol, scale = FALSE, expand = 10 * nrow(z) / 200, nticks = 10, ticktype = "detailed",
  ltheta = -70, shade = 0.4, border = NA, box = TRUE, axes = TRUE, xlab = "Latency (us)", r = sqrt(3),
  zlab = "Frequency (log10)", ylab = "Repetitions")
title(main = "3D plot", font.main = 4)

Run the scripts and display the result

Output of the R script
Output of the R script (click on the image to show the PDF file)

To download and run the scripts type

cd /tmp
wget https://www.osadl.org/uploads/media/mkplotdata.bash
chmod +x mkplotdata.bash
wget https://www.osadl.org/uploads/media/mk3dplot.R
mkdir 3D
cd 3D
../mkplotdata.bash
R -f ../mk3dplot.R
cd ..
evince 3Dplot.pdf

and a graphic similar to the one at the right will be displayed. It may then further be processed with usual image converters to create bitmap files in a desired format.

Note that – due to the logarithmic vertical scale – the single outlier in the amount of 200 µs is distinguishable out of the many million recordings at latency plot #90.

Download the scripts

mkplotdata.bash

Bash script to create simulated plot data

699

mk3dplot.R

R script to generate the 3D graphic

2.2 K

Animated 3D

Finally, you may wish to create an animated sequence in order to allow for a better inspection of the whole of the results – particularly not to overlook single latency outliers. For this purpose, the R script is repeated with different view angles, and the resulting images are combined in an animated gif.

First frame of the animation
Click on the image to show the animation

Optional video clips

If you really wanted, you may even produce short video clips from the animated GIF that have considerably shorter files sizes, but a less good resolution.

latency.avi

Video clip in AVI format

851 K

latency.ogv

Video clip in Ogg-Vorbis format

1.8 M