1.1 What is KUPLOT ?

KUPLOT is an interactive plotting program controlled by a command language. KUPLOT is part of the diffuse scattering simulation package DISCUS, however it can be used totally independent of the DISCUS software.

The program can produce graphical output for X-Windows screens and TEK4014 terminals. However, all options of KUPLOT such as using bitmaps are only supported for X11 screens. Any plot can be saved or printed directly as POSTSCRIPT or HPGL file. Again only the POSTSCRIPT output supports the use of bitmaps. As mentioned before, the program is controlled by a command language which includes a FORTRAN style interpreter which allows the use of variables, loops and conditional statements. This results in a high degree of flexibility and allows the creation of quite complex graphics. It also allows KUPLOT to be used to process large numbers of data files and produce the desired plots automatically.

KUPLOT can process simple 1d date files. The program supports normal line graphs, marker, error bars as well as spline interpolation between the data points. Line colour, marker colour, line type, line width and various other parameters can be adjusted. KUPLOT allows one to plot 3D data sets using contour lines, coloured bitmaps or both. The colourmap for the bitmap can be freely changed using the FORTRAN interpreter (see section 5.1). The program also allows one to define different contour line sets for one data set, e.g. finer spaced lines for diffuse scattering and larger space lines in a different colour for the Bragg peaks.

A page can be divided into different plot areas (see chapter 4). Each frame can contain graphs or the contents of a text file. Frames can have different background colours. Each frame has its own parameter set like e.g. title, axis labels, fonts.

Loaded data sets can be manipulated using the FORTRAN style interpreter or a variety of build-in functions. An integrated FIT sublevel, which allows to fit the following functions to a given 1D data set: polynom, n Gaussians and n Lorentzians. Furthermore 2D data sets can be fitted using a set of 2D Gaussians. Additionally $\star$]$\star$KUPLOT allows fitting a user defined function to a loaded data set.