Gnuplot .gnu files

As you can see you can write in your data set in floating point notation. Now everything is ready to make the data plot: by typing only. The default settings will use the first two columns of your data file, respectively x and y. To specify the columns to be plotted use the using specifier. In the case your data set is a tridimensional file just use splot ad add the z-column. First of all, before plotting, you must be sure to be under the same directory where the data file is, otherwise you'll eventually get a warning.

As you can see you can write in your data set in floating point notation. Now everything is ready to make the data plot: by typing only. The default settings will use the first two columns of your data file, respectively x and y.

To specify the columns to be plotted use the using specifier. In the case your data set is a tridimensional file just use splot ad add the z-column. There are also different style see gnuplot documentation or Selecting a plotting style for further infos for plotting points.

Here we must use x as the independent variable. The next part, "cavendish. The using tells gnuplot to take columns 1, 2, and 3 from the data file and use them as the x, y, and uncertainties, respectively. If this part is left out, then the experimental uncertainties will not be used for the curve fit. See below for a greater discussion of the extremely powerful using qualifier.

Finally, we must tell gnuplot what variables it can adjust to get a better fit. For this case, we say via a, tau, phi, T, theta0.

Important quantities to note are the reduced chi square variance of residuals , which in this case is 1. Each fitting parameter also has an uncertainty listed.

The correlation matrix at the end can ususually be ignored. The using qualifier used in the fitting command above is an extremely powerful tool in gnuplot. With it, you can exercise almost limitless control over your data as it is plotted. Usually, only two columns are used: the independent variable and the dependent variable.

With error bars, one or two more columns may be used. Usually, these columns are taken out of the datafile directly. Sometimes, it's necessary to exercise a little more control. That's where using comes in. Say you need to swap the two data columns, since that the dependent variable comes first, followed by the independent variable in the data file. You can produce this plot with the command:.

The using command expects several values, one for each column of data required, with each value separated by a colon. If the value is simply a number, gnuplot will take that data piece from the specified column in the datafile.

In this case, we tell gnuplot to take the independent variable from column 2, and the dependent variable from column 1. The previous example was a bit contrived. But there's a very common case where using is used: when there are multiple data sets in an input. Suppose you have a datafile with three columns: an independent variable, and two dependent variables.

You'd like to plot both dependet variables as a separate set of points. You can use:. In our fitting example above, by specifying using , we were forcing the fit command to take three columns as input, instead of the usual two to include the error information , but we did not perform any reordering on them.

This is still just scratching the surface of what using can do. Instead of giving a column number, you can also specify a complete expression, which must be surrounded in parentheses. As an example, if we wanted to plot the natural logarithm of our dependent variable, we could use:. To understand this section, you'll need to have understood the section "Using using " above.

A little explanation of the using statement is perhaps in order. We're producing a plot with y error bars, so we need three data columns. Hence, the using qualifier has three parts, separated by colons. The first, 1 , says the first part, the independent variable, is simply the first column from the input file.

The third column, 3 , simply says to use the existing uncertainty stored in column 3 of the data file with no modification.

It would be even better if we could put the residuals on the same graph as the fitted curve. To make this look good, we'll use a different scale for the residuals, so they can be separated from the rest of the graph.

There's another syntax for defining the ranges for each of the axes, which is necessary for using more than one scale at a time. First, let's shift the graph of our data and fitted curve up a bit, to make room. This is like specifying the range as part of the plot command, but the settings will stick around until they are overridden, and we can specify a y-range without an x-range.