Gnuplot Error Bars Style
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Gnuplot Set Bars
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Gnuplot Boxerrorbars
to specifying yerrorbar style from gnuplot up vote 3 down vote favorite emphasized textPlotting script that used to work for the previous version of gnuplot (v4.2.6) no longer work for the latest version (v4.4.0) and produces error messages for the following script line. plot "data_file" u ($1+0.5):2 title "legend1" w boxes fs solid 0.85, "" u ($1+0.5):2:3 notitle w yerrorbars 1, .... The error candlesticks gnuplot goes away as I change "yerrorbars 1" to "yerrorbars". However, this prohibits the customization of the errorbar style. Can anyone tell me how can I do this right? I'm attaching test code that causes the error and the error message. #!/opt/local/bin/gnuplot set term postscript monochrome enhanced set output "test.eps" set grid x y set xtics nomirror set ytics 1.5 font "Helvetica, 18" set yrange [0:10] set xrange [0:10] set boxwidth 1 set bmargin 3 set key top left plot "test.dat" u ($1+0.5):2 title "test0" \ w boxes fs solid 0.85, \ "" u ($1+0.5):2:3 notitle w yerrorbars 1, \ "" u ($1+1.5):4 title "test1" w boxes fs solid 0.7, \ "" u ($1+1.5):4:5 notitle w yerrorbars 1 I ran above script with the following data. $ cat test.dat 1 1.315119617 0.131 1.199138756 0.136 7 5.382161114 0.002 4.818144427 0.003 and it generated the following error messages. $ gnuplot test.plt plot "test.dat" .... ^ "test.plt", line 17: ';' expected As I mentioned from above, the error goes away when I change yerrorbar 1 to yerrorbar but this prevent me from specifying error bar style. gnuplot share|improve this question edited Jan 14
by the various errorbar styles. In the default situation, gnuplot expects to see three, four, or six numbers on each line
Gnuplot Standard Deviation
of the data file -- either (x, y, ydelta), (x, y,
Gnuplot 5
ylow, yhigh), (x, y, xdelta), (x, y, xlow, xhigh), (x, y, xdelta, ydelta), or (x, y, xlow, gnuplot fit xhigh, ylow, yhigh). The x coordinate must be specified. The order of the numbers must be exactly as given above, though the using qualifier can manipulate the order and http://stackoverflow.com/questions/8055383/how-to-specifying-yerrorbar-style-from-gnuplot provide values for missing columns. For example, plot 'file' with errorbars plot 'file' using 1:2:(sqrt($1)) with xerrorbars plot 'file' using 1:2:($1-$3):($1+$3):4:5 with xyerrorbars The last example is for a file containing an unsupported combination of relative x and absolute y errors. The using entry generates absolute x min and max from the relative error. The y error bar http://gnuplot.sourceforge.net/docs_4.2/node140.html is a vertical line plotted from (x, ylow) to (x, yhigh). If ydelta is specified instead of ylow and yhigh, ylow = y - ydelta and yhigh = y + ydelta are derived. If there are only two numbers on the record, yhigh and ylow are both set to y. The x error bar is a horizontal line computed in the same fashion. To get lines plotted between the data points, plot the data file twice, once with errorbars and once with lines (but remember to use the notitle option on one to avoid two entries in the key). Alternately, use the errorlines command (see errorlines (p.)). The error bars have crossbars at each end unless set bars is used (see set bars (p.) for details). If autoscaling is on, the ranges will be adjusted to include the error bars. See also http://gnuplot.sourceforge.net/demo/mgr.htmlerrorbar demos. See plot using (p.), plot with (p.), and set style (p.) for more information. Next: Errorlines Up: Plot Previous: Zticlabels Contents Index Ethan Merritt 2007-03-03
the last entry we had mean and standard variation data for five different conditions. Now let us assume that we have only two different conditions, but have measured with three different instruments A, B and C. We have used a ANOVA to verify that the data for the two conditions are significant different. As a result the plot in Fig. 1 should http://www.gnuplotting.org/tag/errorbars/ be created. Fig. 1 Plot the mean and variance of the given data (code to produce this figure) Therefore we store our data in a format, that can be used by the index command in Gnuplot. Note that the data have two empty lines between the blocks in the real data file: # mean std # A 0.77671 0.20751 0.33354 0.30969 # B 0.64258 0.22984 0.19621 0.22597 # C 0.49500 0.31147 0.14567 0.21857 Now every instrument is stored in a different data block containing both conditions as columns. The color definitions and axes settings error bars are done in a similar way as in the previous blog entry. Note that we have to define two more colors for the boxes, because we use three different colors. Also we define a black line to plot the significance indicator (arrow). set style line 1 lc rgb 'gray30' lt 1 lw 2 set style line 2 lc rgb 'gray40' lt 1 lw 2 set style line 3 lc rgb 'gray70' lt 1 lw 2 set style line 4 lc rgb 'gray90' lt 1 lw 2 set style line 5 lc rgb 'black' lt gnuplot error bars 1 lw 1.5 set style fill solid 1.0 border rgb 'grey30' The significance indicator is created by three black arrows and a text label: # Draw line for significance test set arrow 1 from 0,1 to 1,1 nohead ls 5 set arrow 2 from 0,1 to 0,0.95 nohead ls 5 set arrow 3 from 1,1 to 1,0.95 nohead ls 5 set label '**' at 0.5,1.05 center For the plot the index command is used to plot first condition A, then B and then C by using block 0,1, and 2 respectively. The x-position of the boxes for instrument A are slightly shifted to the left, the ones for C to the right by subtracting or adding the value of bs. The value of bs has the width of one box in order to plot the boxes side by side. # Size of one box bs = 0.2 # Plot mean with variance (std^2) as boxes with yerrorbar plot 'statistics.dat' i 0 u ($0-bs):1:($2**2) notitle w yerrorb ls 1, \ '' i 0 u ($0-bs):1:(bs) t 'A' w boxes ls 2, \ '' i 1 u 0:1:($2**2) notitle w yerrorb ls 1, \ '' i 1 u 0:1:(bs) t 'B' w boxes ls 3, \ '' i 2 u ($0+bs):1:($2**2) notitle w yerrorb ls 1, \ '' i 2 u ($0+bs):1:(bs) t 'C' w boxes ls 4 Tags: ANOVA, border, boxes, data, errorbars, index Plotting simple statistical data September 9th, 2010 | No Comments If we have done a experiment in order to apply a significance test like a ANOVA to our measured data, we are interested in presenting our statistical data in a familiar way. Let us assume we have