Maple Questions and Posts

These are Posts and Questions associated with the product, Maple

On a calculus 2 test I was given to review the students were asked to find the derivative of arccosh(x)*sqrt(1-x^2).  Maple gives the answer -arccosh(x)*x/sqrt(1-x^2)+sqrt(1-x^2)/(sqrt(x-1)*sqrt(x+1)).   This is the same answer, in a slightly...

maplematrix.mw

Hi all,

I am stuck again in a simple problem of creating a M*1 Matrix.  I have attached a Maple file for your kind consideration.

I shall be looking forward to your reply.

Best Regards

A.Q

 

Hi,

> assume(y::prime)

> about(y);
Originally y, renamed y~:
  is assumed to be: prime

I don't understand this answer:

> is(sqrt(y)>0)

      FAIL

I want to solve a set of ODE equations numerically,there is 5 equations with certain boundary conditions,please help me,what kind of dsolve order could i use? when i use dsolve({sys,bcs}type=numeric) i get an error that say me:system must be entered as a set of equations! how can i solve it?

Interesting behavior!!

> restart
> N := 150; L := LinearAlgebra[RandomVector](N);

                              150

> st := time(); for j to 10^4 do ArrayTools[SearchArray](`~`[`=`](L, max(L))) end do; time()-st;

             ...

Hi everyone, 

In my research project, I needed to evaluate a multi-variable integration. I'm trying to do this in Maple, and seems no matter I use Int or int, it failed to evaluate the integration. 

Here's my code:

I'm integrating a joint probability density function which is basically a multiplication of four PDFs of four Gaussian distributions:

 
> mu := 0:                                                    ...

 

I have problems with the time delay the procedure for computing the Hough transform of the image that Annex. Delay 5534.875 seconds. How to improve, optimize the procedure, to be more efficient at runtime?

Hough.mw 

Hi,

I have a system consisting of a multi-body system and various modelica/maple custom components. The problem is whenever I re-run the simulation even though all the simulation settings are same, the simulation results are inconsistent. There should be no difference between each simulation as all the parameters/settings are same. I am attaching two pictures which are both obtained from two successive simulations

Hello everybody! I have a question that how to show the number of roots of Eqs automatically. Followings are part of my program: 

>U:=solve({-2/phi^3*u[0]^2*diff(phi,x)-4/phi^3*w[0]*diff(phi,x)-2*u[0]/phi^3*diff(phi,x)^2, -6/phi^4*u[0]*diff(phi,x)*v[0]+12*v[0]/phi^4*diff(phi,x)^2, -2/phi^3*v[0]*diff(phi,x)+2/phi^3*w[0]*diff(phi,y)},{u[0],v[0],w[0]});

I can obtain three items roots. My question is how can I obtain the number of roots automatically by using the program!

Hello!

I have a strange issue:   I have a procedure with signum, square roots, I and float numbers. First I optimize it and then compile.  (or just run compile with option optimize=true).  As a result I get a error:

Error, (in TargetLanguageTools:-GetExprType) Analysis is not a command in the _EnvCGEngine package

Trying to understand, what is happening, I manually copy-paste the optimised procedure to the argument of compile. Then it works!!!

I have a compiled function and want to integrate it numerically.  The integration procedure first tries to evaluate the integrand with symbolic values and return a error, since the compiled function accepts only real values.  So I have to write a STUPID workaround  for manual typechecking:

integrand2 := proc (kF1, kF2, m, k, omega, q) if type(kF1, numeric) and type(q, numeric) and type(kF2, numeric) and type(omega, numeric) and type(m, numeric) and type(k, numeric...

Hello,

How can I use assign(...) inside in proc in order to affect the local variables and not the globals.

 

Thanks

Consider the following:

 

with(Physics);

 

Setup(noncommutativeprefix = z);

 

(z1*z2)*z1;

 

gives z1 z2 z1 as it should but

 

z1*z2*z1*z1;

 

gives z1^3 z2. Thus noncommutativity has not been respected?

 

What can I do?

> with(CurveFitting); data := [[2, 10], [3, 1], [5, 4], [7, 5]];
               [[2, 10], [3, 1], [5, 4], [7, 5]]
> PolynomialInterpolation(data, y);
                    3  3       2   199     143
      ...

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