Although DADiSP typically operates on constant time interval data, DADiSP can also produce XY graphs. XY graphs with independent X and Y axes introduce a little more complexity into the world of 2-D plotting. XY graphs are commonly used to produce scatter plots or to plot data series that do not have a constant x-axis interval.
Consider an experiment which yields two interval series, pressure and temperature, over time. If the pressure data is displayed in W1 and the temperature data in W2, you can display pressure vs. temperature by typing:
xy(w2, w1)
W1: gexp(1000, .001, 2)
W2: gnorm(1000, .001)
W3: xy(w1, w2)
The XY function creates an XY series. In this case, the X values change exponentially.
xy(gsin(1000,.001,4),gsin(1000,.001,5))
Creates an interesting spiral graph.
XY graphs are usually end results; they can be created, displayed, plotted and graphically manipulated. However, in general DADiSP cannot operate on them quantitatively without some priming. For example, if you multiply two Windows that each contain an XY graph, DADiSP can only multiply the y values of each graph. Some routines such as DERIV or operating arithmetically on the XY data by a scalar will result in new XY data.
W1: xy(gsin(1000,.001,4),gsin(1000,.001,5))
W2: W1*10 + 3
W2 contains an XY series where the Y values are derived by linearly scaling the Y values of W1 and the X values are the same as the X values of W1.
If the X values of your data have a constant interval, DADiSP can optimize processing by if the interval is simply specified rather than carrying around the X values. For example:
t = 0..0.01..1
f = 3
s1 = sin(2*pi*f*t)
s2 = xy(t, s1)
The series s2 is an XY series that contains explicit X values. The series s1 is essentially equivalent to s2 from a graphing perspective, but the X values of s1 are implicit. Series s1 is an interval series, the X values increase by a constant value. In this case, s1 inherited the explicit deltax from the series t.