Gnuplotting

Multiple lines with different colors

February 20, 2012 | No comments

Most of you will probably know the problem of visualizing more than two dimensions of data. In the past we have seen some solutions to this problem by using color maps, or pseudo 3D plots. Here is another solution which will just plot a bunch of lines, but varying their individual colors.

Fig. 1 Plot of interaural time differences for different frequency channels, indicated by different colors (code to produce this figure, data)

For this we first define the colors we want to use. Here we create a transition from blue to green by varying the hue in equal steps. The values can be easily calculated with GIMP or any other tool that comes with a color chooser.

set style line 2  lc rgb '#0025ad' lt 1 lw 1.5 # --- blue
set style line 3  lc rgb '#0042ad' lt 1 lw 1.5 #      .
set style line 4  lc rgb '#0060ad' lt 1 lw 1.5 #      .
set style line 5  lc rgb '#007cad' lt 1 lw 1.5 #      .
set style line 6  lc rgb '#0099ad' lt 1 lw 1.5 #      .
set style line 7  lc rgb '#00ada4' lt 1 lw 1.5 #      .
set style line 8  lc rgb '#00ad88' lt 1 lw 1.5 #      .
set style line 9  lc rgb '#00ad6b' lt 1 lw 1.5 #      .
set style line 10 lc rgb '#00ad4e' lt 1 lw 1.5 #      .
set style line 11 lc rgb '#00ad31' lt 1 lw 1.5 #      .
set style line 12 lc rgb '#00ad14' lt 1 lw 1.5 #      .
set style line 13 lc rgb '#09ad00' lt 1 lw 1.5 # --- green

Then we plot our data with these colors and get Figure 1 as a result.

plot for [n=2:13] 'itd.txt' u 1:(column(n)*1000) w lines ls n

There the interaural time difference (ITD) between the right and left ear for different frequency channels ranging from 236 Hz to 1296 Hz is shown. As can be seen the ITD varies depending on the incident angle (azimuth angle) of the given sound.

Another possibility to indicate the frequency channels given by the different colors is to add a colorbox to the graph as shown in Figure 2.

Fig. 2 Plot of interaural time differences for different frequency channels, indicated by different colors as shown in the colorbox (code to produce this figure, data)

To achieve this we have to set the origin and size of the colorbox ourselves. Note, that the notation is not the same as for a rectangle object and uses only the screen coordinates which is a little bit nasty. In addition we have to define our own color palette, as has been discussed already in another colorbox entry. In a last step we add a second phantom plot to our plot command by plotting 1/0 using the image style in order to get the colorbox drawn onto the graph.

set colorbox user horizontal origin 0.32,0.385 size 0.18,0.035 front
set cbrange [236:1296]
set cbtics ('236 Hz' 236,'1296 Hz' 1296) offset 0,0.5 scale 0
set palette defined (\
    1  '#0025ad', \
    2  '#0042ad', \
    3  '#0060ad', \
    4  '#007cad', \
    5  '#0099ad', \
    6  '#00ada4', \
    7  '#00ad88', \
    8  '#00ad6b', \
    9  '#00ad4e', \
    10 '#00ad31', \
    11 '#00ad14', \
    12 '#09ad00' \
    )
plot for [n=2:13] 'itd.txt' u 1:(column(n)*1000) w lines ls n, \
   1/0 w image

Tags: colormap, data, for, label, lines, palette

Animation II – video

February 3, 2012 | No comments

In the first post regarding animations we have created a bunch of png files and combined them to a single gif animation. Now we want to generate again a bunch of png files, but combine them to a movie.

Fig. 1 Video animation of Huygens principle (code to produce this figure, loop function)

We create the png files in analogy to the gif example, hence we will discuss only the generation of the movie here. In order to compose a avi file from the png files we are using Mencoder. Gnuplot is able to directly start Mencoder by its system command.

# Create movie with mencoder
ENCODER = system('which mencoder');
if (strlen(ENCODER)==0) print '=== mencoder not found ==='; exit
CMD = 'mencoder mf://animation/*.png -mf fps=25:type=png -ovc lavc -lavcopts vcodec=mpeg4:mbd=2:trell -oac copy -o huygen.avi'
system(CMD)

The first two lines check if Mencoder is available and quit gnuplot if not. The Mencoder command itselfs gets the directory containing the png files mf://animation/*.png, frames per second and input type-mf fps=25:type=png, video -ovc and audio -oac options, and finally of course the output file -o huygen.avi.

In order to generate a webm video file for a web site, ffmpeg can be used to convert the video.

$ ffmpeg -i huygen.avi huygen.webm

Tags: animation, if, load, reread, system

Adding arrows to the axes

January 22, 2012 | No comments

Fig. 1 Plot of a sinusoid with arrows on the axes (code to produce this figure, data)

You can easily add arrows to the end of the x- and y-axis using the set arrow command. The two last values of the size option determines the opening and closing angles of the arrows.

set arrow from graph 1,0 to graph 1.05,0 size screen 0.025,15,60 \
    filled ls 11
set arrow from graph 0,1 to graph 0,1.05 size screen 0.025,15,60 \
    filled ls 11

Tags: arrow, axes, border

Matlab colorbar with Gnuplot

January 5, 2012 | No comments

This time another colormap plot. If you are using Matlab or Octave you are probably be familiar with Matlabs nice default colormap jet.

Fig. 1 Photoluminescence yield plotted with the jet colormap from Matlab (code to produce this figure, data)

In Fig.1, you see a photoluminescence yield in a given region, and as you can see Gnuplot is able to apply the jet colormap from Matlab. This can be achieved by defining the palette as follows.

set palette defined ( 0 '#000090',\
                      1 '#000fff',\
                      2 '#0090ff',\
                      3 '#0fffee',\
                      4 '#90ff70',\
                      5 '#ffee00',\
                      6 '#ff7000',\
                      7 '#ee0000',\
                      8 '#7f0000')

The numbers 0..8 are automatically rescaled to 0..1, which means you can employ arbitrary numbers here, only their difference counts.

If you want to use this colormap regularly, you can store it in the Gnuplot config file as a macro.

# ~/.gnuplot
set macros
MATLAB = "defined (0  0.0 0.0 0.5, \
                   1  0.0 0.0 1.0, \
                   2  0.0 0.5 1.0, \
                   3  0.0 1.0 1.0, \
                   4  0.5 1.0 0.5, \
                   5  1.0 1.0 0.0, \
                   6  1.0 0.5 0.0, \
                   7  1.0 0.0 0.0, \
                   8  0.5 0.0 0.0 )"

Here we defined the colors directly as rgb values in the range of 0..1, which can be alternatively used a color definition.
In order to apply the colormap, we now can simple write

set palette @MATLAB

Tags: colormap, macros, palette, rgb

Equipotential lines

December 18, 2011 | No comments

In physics equipotential lines describe lines in space which are at the same potential, for example of the electric field.

Fig. 1 Equipotential lines of a plate with electric charges (code to produce this figure)

In Fig. 1 equipotential lines for the electric field of six charges equally spaced on a plate are shown. In order to get these lines we need the function of the potential v(x,y) and make a contour plot with splot to a file to save the positions of the lines.

# calculate and save equipotential lines
set view map
unset surface
set contour base
# distance between contour lines according to 1/r
# => equal distance between lines
set cntrparam levels discrete 4,5,6.67,10
set isosam 31,31
set table 'equipotential_lines.txt'
splot v(x,y) w l ls 1
unset table

plot 'equipotential_lines.txt' u 1:2 w l ls 1

The positions of the lines are given by the cntrparam levels which are chosen in a way, to get equally spaced lines in the far field. The set table command stores the contour lines to a file, and finally the last command plots the stored lines.

In addition to the equipotential lines the value of the contour is stored as a third column in the equipotential_lines.txt file and can be plotted on the graph, too. This is shown in Fig. 2.

Fig. 2 Equipotential lines of a plate with electric charges with labels (code to produce this figure)

To get the label of the contour we have to choose a x-position which is given by lx0 in the following. The labels(x,y) function sets a string to the value of the third column, if the right x-position is given and we are above the plate. The function f(x,y) checks if we are near the point where a label should be drawn and undefines the contour line around this point. The size of this area is given by eps.

lx0 = 1.14899
eps = 0.15
labels(x,y) = (x==lx0 && y>y0) ? stringcolumn(3) : ""
f(x,y) = (abs(lx0-x)<eps && y>y0) ? 1/0 : y

Tags: cntrparam, contour, label, rectangle, table

Invert order of entries in the legend

November 14, 2011 | No comments

Sometimes it can be useful to be able to invert the entries of the legend. For example in Fig. 1 we have a plot of two frequency responses with the black one plotted as second one in order to stay in front of the gray one.

Fig. 1 Plot of two frequency responses (code to produce this figure, data)

In order to make the order of the entries in the legend more intuitive we can simple tell Gnuplot to invert them. The result is shown in Fig. 2.

set key invert

Fig. 2 Plot of two frequency responses (code to produce this figure, data)

Tags: invert, key, legend

Animation I – gif

October 21, 2011 | No comments

For presentation or teaching purposes it can be useful to show not only a figure, but an animation to illustrate something more clear. There exists different possibilities to do this in Gnuplot. Today we will have a look at how to create a gif animation.

Fig. 1 Animation of Bessel function (code to produce this figure, loop)

Fig. 1 shows a gif animation of a Bessel function of first kind and zeroth order. Gnuplot has a gif output terminal, but the result will be smoother if we first create png files with Gnuplot and then the animated gif file with another program. In order to create a set of png files we have to loop through the time value t and different output files.

# initializing values for the loop and start the loop
t = 0
end_time = 1
system('mkdir -p animation')
load 'bessel.plt'

The above code sets a start value for the running time variable t and the end_time variable at which the looping should be stopped. Then a folder for the output png files is created and the loop file bessel.plt is loaded. The content of this loop file is shown below.

# bessel loop
t = t + 0.02
outfile = sprintf('animation/bessel%03.0f.png',50*t)
set output outfile
splot u*sin(v),u*cos(v),bessel(u,t) w pm3d ls 1
if(t<end_time) reread;

Here we update the time t, create a file name with a different number and plot out Bessel function. Finally the last line checks if our time t is smaller than the end_time variable, and executes the loop again if this is the case.

After we have created the png files in the animation folder, we start GIMP and load all the files as layers (File > Open as Layers). After this we save all layers together as an animated gif file.

Tags: animation, bessel, gif, if, load, reread

Creating pseudo 3D plots

October 10, 2011 | No comments

In the last entry we have seen how to use a color map to represent matrix data. Another way to visualize such kind of data is to code their values not as color, but as height information using so called pseudo 3D plots.

Fig. 1 Pseudo 3D plot of basilar membrane activity (code to produce this figure, data)

Suppose we have some data like spectra with different parameters, slightly shifted and plotted into the same figure, or different oscillations over time as shown in Fig. 1. There, the movement of the basilar membrane to an input stimuli dependent on the center frequency in ERB is plotted over time. The movement on the basilar membrane is dependent on the frequency of the incoming stimulus, with different frequencies acting on different places along the membrane. In order to plot this kind of data the for command of Gnuplot can be used to iterate through the data. The pseudo 3D effect is realized by shifting the data in every iteration one ERB by the +ii part and the usage of filledcurves to overwrite not visible parts of the plot with white color.

set style fill solid 1.0 border rgb 'black'
plot for [ii=25:1:-1] 'bmm.txt' u (f(column(ii))+ii) \
    w filledcu y1=-2 ls 1

The amplitude of the data was originally stored in order to fit in a plot given in Hz. Hence, we have to convert the data into ERB. This is done by the function f. As arguments to the function the values of each column are given in the iteration. Therefore, the column number is indexed by the column function.

Tags: data, filledcurves, for, iteration

Color maps and the scale of axes

September 26, 2011 | No comments

If you have not only some data points or a line to plot but a whole matrix, you could plot its values using different colors as shown in the example plot in Fig. 1. Here a 2D slice of the 3D modulation transfer function of a digital breast tomosynthesis system is presented, thanks to Nicholas Marshall from UZ Gasthuisberg (Leuven) for sharing the data.

Fig. 1 A simple color map (code to produce this figure, data)

All we need to create such a plot is the image plot style, and of course the data have to be in a proper format. Suppose the following matrix which represents z-values of a measurement.

0 1 2 3 4 3 2 1 0
0 1 2 3 4 3 2 1 0
0 1 2 3 4 3 2 1 0
0 1 2 3 4 3 2 1 0
0 1 2 3 4 3 2 1 0
0 1 2 3 4 3 2 1 0
0 1 2 3 4 3 2 1 0
0 1 2 3 4 3 2 1 0
0 1 2 3 4 3 2 1 0

In order to plot these values in different gray color tones, we specify the corresponding palette. In addition we apply the above mentioned image plot style and the matrix format option. The result is shown in Fig. 2.

set palette grey
plot 'color_map.dat' matrix with image

Fig. 2 A simple color map (code to produce this figure, data)

One remaining problem with Fig. 2 is, that the values on the x- and y-axis are probably not the one which you want, but the corresponding row and column numbers. One way to get the desired values is the use command, which can also be used with image. See Fig. 3 for the result.

plot 'color_map.dat' u (($1-4)/10):2:3 matrix w image

Fig. 3 A color map with a scaled x-axis (code to produce this figure, data)

Another way is to store the axes vectors together with the data. Therefore the data has to be stored as a binary matrix. The format of this matrix has to be the following:

<M>  <y1>   <y2>   <y3>   ... <yN>
<x1> <z1,1> <z1,2> <z1,3> ... <z1,N>
<x2> <z2,1> <z2,2> <z2,3> ... <z2,N>
 :      :      :      :   ...    :
<xM> <zM,1> <zM,2> <zM,3> ... <zM,N>

In Matlab/Octave the binary matrix can be stored using this m-file. The stored binary matrix can then be plotted by adding the binary indicator to the plot command.

plot 'color_map.bin' binary matrix with image

Note that in principle a color map can also be created by the splot command:

set pm3d map
splot 'data.dat' matrix

But if you create vector graphics with this command you will get a really big output file, because every single point will be drawn separately. For example check the graph from Fig. 1 as pdf created with plot and image and as pdf created with splot and pm3d map.

Tags: binary, colormap, image, Matlab, matrix

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