Large or involved projects may involve Maple modules which rely upon each other. Routines in one module may call routines in another module. Interdependence of modules can have a direct bearing on the available means of successfully utilizing the `use` functionality. In certain situations, some of the ways to utilize the `use` statement can be problematic.

Some such situations, and workarounds, are illustrated below.

The basic description of the `use` statement functionality is,

Math is boring. Math isn’t useful. You’ll never need to use math again after school. It isn’t necessary to learn math, now that we have cash registers, calculators and computers. Math is just plain boring.

After ?invtrig:

For real arguments x, y, the two-argument function arctan(y, x), computes the principal value of the argument of the complex number x+I*y, so -Pi < arctan(y, x) <= Pi.

For any point in C or R^2 (x,y)<>(0,0) the geometrical meaning of this result is clear: the angle that the segment/vector from (0,0) to (x,y) forms with the x-axis. But this angle is undefined if this point is the origin.

So, what is arctan(0,0)?, and what it should be?

If x -1 is regarded as the difference of two cubes, can Maple factor it?

Alla

 

The attached work sheet teaches you the fundamental concepts behind the antiderivative.

The examples in this worksheet are entirely done in an interactive video tutorial - follow the link below:

 (Ctrl+Click on the link to view the video)

Antiderivatives - Video Tutorial

 

Enjoy!

 

The attached worksheet is a wonderful introduction to the concept of obtaining the area under a curve.

You'll see how easy it is to learn how to find the limit of the sum of a series using Maple.

An interactive video tutorial that shows you how to do Riemann sums really fast is linked below:

(Ctrl+Click on the link to view the video)

Riemann Sums...

f := proc (x) options operator, arrow; cos(x)-x*sin(x)+1 end proc

_EnvAllSolutions := true

solutions := [solve(f(x) = 0, x)]

evalf({%})

 

What is up with that solution at zero?  And if this function is plotted, there is clearly a solution at around x=1.3.  Maple does not see this, is there a setting I missed?  Thanks.

 

 

GMP is now deeply integrated into Maple - which I consider to be a good thing.  But it appears that compiler writers are doing a bad job (see the first paragraph on GMP's home page)  In other words, unless you carefully make sure that you have compile GMP properly, it is entirely possible that you end up with a buggy library.  Very scary stuff.

It’s not the fault of my world-famous professors at M.I.T. who gave me a M.Sc. degree in Electrical Engineering, but it’s a fact – I know less about engineering than most (if not all) of you.

Way back then, “Computer Science” was a fledgling field of study, and in many schools it was an offshoot of either math or engineering.  In my case it was an offshoot of engineering, and ergo my inappropriate degree.

So much for my sordid past.

Can Maple graph the Dirichlet function?

f(x) =   {0,   if x is rational
            {1,   if x is irrational

Alla

 

Yesterday I watched a demonstration of Maple being applied to the modeling and simulation of the internal deformations of human bones. The researcher was a mathematician working primarily in the biomedical modeling fields. The actual technique was to utilize the symbolic mathematical power of Maple to formulate the necessary equation pieces for a finite element model (FEM) of the internals of the bone. The equations are then fed into the legendary FEM solver ABAQUS.

Due to the notoriously non-linear qualities of human flesh and bone, traditional formulation methods developed for modeling beams and metals simply do not work. So as in the case of so many impressive engineering applications, the power of Maple is being deployed in the formulation or the pre-solution phase of modeling and in doing so, previously infeasible models now become feasible.

 

Please.. Anybody explained this plot?

 

Thanks & Regards

Ravikanth Aluri

Everything below is "as far as Maple is concerned".

The following indicates that infinity does not satisfy the property of being real.

> is(infinity,real);
                                     false

But this next pair indicates that infinity is real. They show that infinity satisfies the nonstrict inequality relation equivalent to the 'real' RealRange, from which it would follow that infinity is in the 'real' RealRange.

Hello

i have a question regarding the Compiler:-Compile Command in Maple12
under linux i got this error message when trying to compile the example:
> y := proc( x :: float ) 2.3 * x end proc:
> cy := Compiler:-Compile( y):
Error, (in Compiler:-Compile) possible installation problem:
GNU C compiler (gcc) not found in your command search
path (PATH). You will need to restart Maple after ensuring that gcc
is installed and adjusting your PATH environment variable.
>
> cy( 1.1 );
cy(1.1)
but the compiler is installed in /usr/bin and maple knows the path:
> getenv(PATH);

That’s a mantra I need to have drummed into me, and perhaps tattooed on the inside of my car so I’m reminded every morning.  But I keep on making the same mistakes. 

 I seem to think that if I’ve “optimized” my portfolio with a few flashy calculations that I’ve done my due diligence, and the next stop is financial independence.  It’s the black box syndrome – trusting the output of a computer program without truly understanding the real issues.  Most portfolio analyses, for example, hinge on historical data, which of course doesn’t predict the sub-prime blow-up in the US or whether Brazilian coffee growers are on strike.  They’re all backward looking.

 However, in the absence of a neighbourhood scryer, historical analyses are a good indication of how to position a portfolio for the long term.

 Being a geek (however much I strenuously deny it), I tend leverage my tech skills wherever I can.  I wrote the attached worksheet to import stock quotes, including historical data, from Yahoo using the Sockets package.  Simply type in the appropriate NYSE stock tickers into the appropriate text boxes, check the quantities you want to download, and click the big gray button.

 All the stock quotes and historical data can be manipulated on the command-line and can be accessed via command-completion. 

 It then finds the best distribution of stocks in a portfolio by maximizing its Sharpe Ratio (through the Optimization package). 

The Sharpe ratio quantifies how effectively a portfolio of risky assets utilises risk to maximise return.  It’s defined as follows.

 

 

It essentially measures how effectively a portfolio uses risk to maximize return – the higher the ratio the better.  The expected portfolio return is predicted from historic data, the portfolio standard deviation is traditionally used as a proxy for risk, and the risk free return is the return that can be expected from a zero-risk investment (i.e. the interest on US Treasury Bills or the redemption yield on UK gilts).

What I find particularly fascinating is how Maple is now the centre of my technical desktop.  Through the combination of the interface and its math tools, I now use it for everything from the simplest calculations through to making wild guesses about my financial future.  If any of the developers are reading this, I want you to know there’s a lot riding on you...