I'm learning to handle the output of pdsolve. It is a module and I'm quite new to that. The objective is to plot the solution for different values of, say, time t, in a fairly systematic way. I'll consign here my progress for reference. Feel free to comment if you have suggestions.

 sol := pdsolve
  ( diff(u(x, t), t) = (1/10)*(diff(u(x, t), x, x))
  , {u(0, t) = 0, u(x, 0) = 1, (D[1](u))(1, t) = 0}
  , numeric
  );

Introduction

The Magma package introduced in Maple 15 includes the command Enumerate. This routine allows you to count, or list, isomorphism class representatives of magmas of a given (small) order satisfying a selection of properties that...

A Plot Component (on the right below) can act as a kind of 2-dimensional "slider" for inputing values of two parameters at once.

The polar plot (on the left below) makes use of both values.

If you click in the right Plot, and drag around the mouse cursor for a while, then the left Plot will be continuously updated.

Make sure to execute the collapsed code-edit region, to initialize it. (Just click on it, to execute. Or expand, look, and right-click on it.)

Download plotslider1.mw

This is in response to a Question about the speed and memory use of an animated DEplot. The problems are that the example's animation was slow to create, and prohibitively expensive to save in a Document.

An alternative approach is to combine multiple calls to plots:-odeplot with a call to plots:-fieldplot to supply the background flow arrows. This is a lot faster. It takes less memory to create and run, but the GUI may still consume too much resources saving it. The good news is that it's so much faster that it's not inconvenient to re-run the entire thing from scratch. And so it's quite feasible to remove all the expensive output from the Document prior to saving and thus avoid the whole resources problem.

The original questioner also wanted to visualize with resect to two varying parameters. So I've also done an implementation of that using Embedded Components and two Sliders.

Here is the old DEplot animation. It takes about 40 sec to create it animation on an Intel i7.

Here is the new combined odeplot+fieldplot animation. It takes a second or two to create its animation on an Intel i7.

Here is the DEplot in Embedded Components. It's very slow, and the image doesn't change smoothly with the sliders.

Here is the new combined odeplot+fieldplot in Embedded Components. Its image changes pretty smoothly with the sliders.

I encourage completely quitting the GUI (not just restart, or close Document and re-Open) between comparison runs of these implementations, of you want to get a really good feel for the effects of both running them as well as saving them (with and without all output).

For the Embedded Component documents, the functioning code resides inside the "initialize" button. (right-click, go to Component Properties, Action When Clicked, only if you want to inspect it.) To run those two  Documents, execute all the commands (use the triple-exclam from the menubar if you like), and then press the "initialize" button, and then move the sliders.

The difference in performance is related partly to the use of hardware datatype Arrays in the PLOT structures generated by odeplot and fieldplot. (But an `arrow` primitive would help even more!)

And (I think) there is improvement by virtue of using dsolve/numeric/parameters in the use of `odeplot`. That saves overhead from repeated cold invocations of dsolve/numeric. And DEplot doesn't support that, since it expects as argument the system of DEs and ICs. The newer `odeplot` command accepts the procedure returned by dsolve/numeric, and thus allows for efficient repeated setting of parameter values. The `fieldplot` command doesn't need the solution of the DE system at all: it just needs the DEs.

I would have considered wrapping the whole combined approach up into a single command, but it might have to accept separate options for the view ranges, in order to always look its best. A smart version might be able to deduce the computed ranges from the odeplot output, and then create the background fieldplot based on that.

The Magma package in Maple 15 includes the command IsSubMagma.  This tests whether a specified subset of a magma is closed under the binary operation that defines the magma.  For example, consider the following Cayley table for a group of order four.

> with( Magma ):
> m := << 1, 2, 3, 4 |

Inside a procedure, local variables are evaluated only one level. Of what good is this, one might ask?

Well, for one thing it allows you to do checks or manipulations of an unevaluated function call without having that function call be evaluated over again. I mean, for function calls to routines which don't happen to remember earlier results.

This is a revision of an Answer

There have been some recent posts about interpolating data.

Attached below is a worksheet that shows some possibilities, with the functionality centering on the CurveFitting:-ArrayInterpolation command.

This is quick summary of parts of a broader document which covers both 2-d and 3-d methods (for regular grids), where I've left out the higher-efficiency methods and instead roughed in some examples involving integration and differentiation.

I've elected not to follow the 3-d Example from the ArrayInterpolation command's help-page, although using a pre-formed grid is a very fast approach to obtain just an interpolated 3-d plot. I also prefer to use the plots:-surfdata command rather than the plots:-matrixplot command, since the former let's one get the axes' tickmarks correct for the x- and y-data ranges.

The scenario is that you have a grid of data points in two dimensions (x- and y, or P- and T-, or what have you).

For each point (ie, for each 2-d pair of values) you have an associated value (or height in z, say). Hence you actually have data points in 3-d space.

How you obtained the associated (z) values depends on your own particular data collection method, or your own program. How you got the data is irrelevant here. What matters is that you have the finite number of data values, and no other easy way to generate data values at more points (let alone data for arbitrary new points). Below, we'll just create the data (once, at the start) for this example using an entirely made-up formula.

The presumption is that you might wish to plot a smooth surface that connects the 3-d data.

But you might also wish to write some program which requires interpolated (z) values at some new (x,y) 2-d points.  And you do not yet know what these 2-d point pairs are. So a pre-formed Array of points  at which to interpolate may not suffice.

Instead of using a pre-formed Array of output points, we'll contruct a procedure named `B` which can be supplied with a new (x,y) 2-d output point and (if that point lies within the original range) return an interpolated (z) value.

This procedure `B` can also be plotted, using the usual `plot3d` comamnd. It won't plot quite as fast as would a pre-computed and pre-interpolated finer grid of (x,y) values, but it should plot nicely. And the surface can be made quite smooth, by merely increasing the number of plotted points using plot3d's usual numpoints option. (Maple does not currently do "adaptive" 3-d plotting, so there's also no advantage in that respect.) But `B` does solve the secondary task, of being able to compute for any subsequent (x,y) point.

We can even integrate and differentiate `B` numerically. Of course we should keep in mind that this is somewhat error prone, since on top of usual issues with numerical differentiation there is also fact that we make the choice of interpolation method! The entire interpolated surface will differ considerably according to whether a spline, cubic (or other) interpolating scheme is chosen!

We'll use P and T as the x- and y- grid points, below, since "a name is just a name" and our choice of variables is arbitarary.

plot_interp.mw

One useful feature of the `evalf` command is that it remembers previous results. But it also stores the current value of Digits as well as its input argument, to be associated with the remembered result.

There are two reasons for this. The fancier reason is so that, when Digits is reduced from that of an earlier successful computation, `evalf` can simply round off the earlier result to the desired number of decimal digits. The more basic reason is that `evalf` might...

Now that Maple 15 is out, I thought I should share this little application I made: GoalTracker.mw. It is an application partially inspired by the BMI tracker in Nintendo's WiiFit application; you could easily use it to track a weight loss goal. But it could also be used to track other quantifiable goals. I am posting it here mostly because it takes advantage of two new features in Maple 15.

The (new, Maple 15) Programming Guide is available for download from the Documentation Center.

In a recent blog post, I discussed five "gems" in my Little Red Book of Maple Magic, a notebook I use to keep track of the Maple wisdom I glean from interactions with the Maple programmers in the building. Here are five more such "gems" that appeared in a Tips & Techniques column in a recent issue of the ...

This is just a programmatic twist on Robert Lopez's very nice original post on this topic.

I'd rather be able to control such declarations with code, than to have to manipulate the palettes or context menus in order to get what are -- in essence -- additional programming and authoring tools. Such code can be dynamic and flexible, and could be inserted in Code- or Startup regions.

Download atomicpartials.mw

This post will explain how to configure the compiler and other tools that will be necessary for you to build the External Calling examples that will come in later posts.  This is an advanced topic and so this post is fairly complex.

First, I am going to be using the compilers via the command line, so you will need to familarize yourself with the terminal program on your particular OS.  You'll have to do this for yourself, but here are a few starting points:

Windows

Apple

I am going to assume that Linux and Solaris users are familar with using the terminal.

For Linux, Apple and Solaris, I am going to use gcc as the compiler.  For Linux you should use your distribution's package management system to get it, for Apple you need to install Xcode and for Solaris, well, gcc is probably already installed or you'll want to talk to you sys admin to have it installed (or if you are your own sys admin, you probably know how to install gcc for yourself).  For Windows, you need to install the Windows Software Development Kit.  If you already have a copy of Visual Studio C++ (Express or Professional) installed, then you already have these tools.

I am also going to use the "make" program to manage the building of the examples, thus you will need to install a version of make as well (you won't need to learn how make works unless you want to modify the examples).  I will be using gnu make, which should be easy to install on Linux and Solaris (similar to how you installed gcc) and it is included in Xcode for Apple.  For Windows, use this:

http://gnuwin32.sourceforge.net/packages/make.htm

Installing 32 bit make on 64 bit windows is fine.

Now you'll need to launch a terminal.  For Linux, Apple and Solaris this should be easy, on Windows go to the Windows SDK folder (or Windows Visual Studio folder) on the Start menu, there should be an icon for Windows SDK Command Prompt.  Click that to launch the terminal.  This version of the terminal has the environment configured to run the compiler.

On Windows you'll also have to add the location you installed make to your path, which can be done on 32 bit windows like this:

path=%PATH%;C:\Program Files\GnuWin32\bin

and on 64 bit Windows like this:

path=%PATH%;C:\Program Files (x86)\GnuWin32\bin

assuing you used the default install location for make.

You can test this by running "make" in the terminal.  If everything is set up correctly, make should run but not find a Makefile and it will raise an error.  If the path is not set properly, make won't be found you'll get a message saying that.

Path not set properly:

C:\Program Files\Microsoft SDKs\Windows\v7.1>make
'make' is not recognized as an internal or external command,
operable program or batch file.

Set the path:

C:\Program Files\Microsoft SDKs\Windows\v7.1>path=%PATH%;"C:\Program Files (x86)
\GnuWin32\bin"

Make is now found, but there is no makefile in the current directory

C:\Program Files\Microsoft SDKs\Windows\v7.1>make
make: *** No targets specified and no makefile found.  Stop.

As a final test, I've attached a small example (test.zip) that contains a Makefile and a simple source file.  If you extract the files to a new directory, go to that new directoy in the terminal and run make (with make added to the path as described above) it should build an executable (test or test.exe).  You can run the executable by executing "test" on the command line.

By default the Makefile is configured for Windows, so Windows users won't need to change it, however other users will need to comment out the

WINDOWS=true

line in Makefile by changing it to

#WINDOWS=true

I know this is a little confusing, especially if you are not familar with the command line interface, therefore I encourage you post replies if you have problems.  Hopefully we will be able to answer your questions.  Once everyone has figured out how to get this simple example to compile and run on their system, the upcoming external calling examples will be (relatively) easy.

Good Luck!

Darin

Maple T.A.  7 and Maple T.A. MAA Placement Test Suite 7 are now available.

Maple T.A. 7 provides new options for analyzing grades and gaining a deep understanding of how students are performing, including:

• Instructors can view all responses to an assignment question, to easily look for patterns
• The grading scheme for the entire course can be defined inside Maple T.A., with appropriate weightings and flexible policies for dealing with missed, repeated, and worst assignments...