Chapter 1. Prelude: Understanding data with gnuplot
Figure 1.1. Number of finishers versus time to complete (in minutes)
Figure 1.2. A DLA cluster of N=30,000 particles, drawn with gnuplot
Figure 1.3. Time required to grow a DLA cluster
Figure 1.4. Time required to grow a DLA cluster in a double-logarithmic plot, together with an approximate mathematical model
Chapter 2. Essential gnuplot
Figure 2.1. Our first plot: plot sin(x)
Figure 2.2. An unsuitable default plot range: plot sin(x), x, x-(x**3)/6
Figure 2.3. Using explicit plot ranges: plot [][-2:2] sin(x), x, x-(x**3)/6
Figure 2.4. Plotting from a file: plot "prices" using 1:2, "prices" using 1:3
Figure 2.5. Introducing styles and the title keyword: plot "prices" using1:2 title "PQR" with lines, "prices" using 1:3 title "XYZ" with linespoints
Figure 2.6. Any column can be used for either x or y axis: plot "prices" using 2:3 with points
Chapter 3. Working with data
Figure 3.1. Plotting a messy datafile: plot "jumbled" using 1:2 with linespoints
Figure 3.2. Using smooth unique lets us sort x values on the fly: plot "jumbled" u 1:2 smooth unique with linespoints
Figure 3.3. Using smooth unique can also find the averages for multi-valued data sets: plot [1989:1994][25:34] "messy" using 1:2 smooth unique with linespoints, "" using 1:2 with points
Figure 3.4. Using the smooth directive: plot "prices" using 1:2 with linesp, "" using 1:2 title "bezier" smooth bezier, "" using 1:2 title "csplines" smooth csplines