Department of Mathematics

Math 300: Mathematical Computing

Maple Plot Options

Maple has very powerful plotting capabilities. It can plot points in the same way as Matlab, but it can also do adaptive plots of symbolic functions, in many different formats. We may (or may not) address these abilities elsewhere, but here we will discuss some options for enhancing ordinary plots.

Consider an ordinary plot of some data and a curve to pass through them.

plot([temppts, co[1]+co[2]*(x-temppts[1, 1])], x = temppts[1, 1] .. temppts[nyears, 1]);

which produces a plot that appears below.
Simple Plot

This is not really what we want to see. We should change the data to some kind of points, thicken the line, label the axes, and make a title and a legend. First, we change the data so that they show in a point style.

plot([temppts, co[1]+co[2]*(x-temppts[1, 1])], x = temppts[1, 1] .. temppts[nyears, 1],style=[point,line]);

This is an example of the way that Maple handles plot options that apply to individual data series. One puts such options in a an ordered list, so that there is a correspondence between the attributes in the option and the data series listed in the first argument of plot. If there are muliple data series but only one option attribute, then that attribute is applied to all data series. If there are different numbers of data series and attributes, then the attributes cycle. The command above produces this image.
Point Plot
We can change the symbol for the data points, as well as the size and color by adding the options symbol = box, symbolsize = 5, color = [blue, RGB(.8, .5, .3)]. This produces
Point Plot
The default symbol size is 10. By setting the size to 5, we made the data point symbols smaller. The symbols that are possible include asterisk, box, circle, cross, diagonalcross, diamond, point, solidbox, solidcircle, and soliddiamond. The default is diamond. Since colors are attributes of data series, we can set them in an ordered list again. The first is a built-in color blue, while for the second we specify our own color using the RGB() function. RGB takes three arguments for the amount of red, green, and blue, respectively. The arguments are numbers in the interval [0,1].

We can double the line thickness and make it dashed by adding the options thickness = 2, linestyle = dash. The default thickness is 1. The possible line styles include solid, dot, dash, dashdot, longdash, spacedash, and spacedot, with solid as the default.

Axis labels are added using an ordered list, this time indicating correspondence between the labels and the x and y axis in order. Finally we add a title and a legend, setting the location of the legend to the bottom, which is actually the default. The final plot command looks like this:

plot([temppts, co[1]+co[2]*(x-temppts[1, 1])], x = temppts[1, 1] .. temppts[nyears, 1], style = [point, line], \ symbol = box, symbolsize = 5, color = [blue, RGB(.8, .5, .3)], thickness = 2, linestyle = dash, \ labels = ["Year", "Temp."], title = "Temperature trends from 1995 to 2010", \ legend = ["Annual mean temp.", "Linear Fit"], legendstyle = [location = bottom]);

The result is shown below.
Final Plot

The last test will take place at the final exam time on Tuesday, 12 December, from 1:30-3:30. It will be written as a one-hour (not 50 minute) exam, but you may have the full two hours for it. In other respects it will be very like the other tests, but comprehensive - it will emphasize Python, but cover all the topics we have seen. There is a Sample Exam, but be aware that things will have changed somewhat with the advent of ChatGPT.

Assignment A is posted.

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