Occasionally it is necessary to temporarily assign a global flag to perform an action. Consider, for illustration, a procedure that returns the inert form of a procedure. We want it to be able to work with procedures that are local to modules. To do that, we need to temporarily assign the kernel flag opaquemodules to false.

GetInert1 := proc(p::uneval)
local opacity,inert;
    opacity := kernelopts('opaquemodules'=false);
    inert := ToInert(eval(p));
    kernelopts('opaquemodules'=opacity);
    inert;
end proc:

Here is a small module to test this on:

Hi folks! Does anybody know if Matlab and Maple and Mathematica works well and stable on Vista? How about speed on Vista? Thanks!

I have been attempting to use Maple 8 to compute the limit of a function defined by a procedure (rather than as a piecewise function). For example, consider the following procedure. f := proc(x) if is(x,numeric) then if x > 1 then 1; elif x <> returns undefined. limit( f(x),x=1,right) --> returns undefined. When I use a piecewise definition, all is well: f := x->piecewise( x>1, 1, x

Sorry, but I don't understand why Maple produces two different answers. (I make many analysis calculations, some expressions [math functions] come directly, e.g. 5x-3, some by Maple e.g. by series command.)

s:=x-1/2*x^2+1/3*x^3+O(x^4);

                               1  2   1  3    / 4\
                           x - - x  + - x  + O\x /
                               2      3           
t:=series(ln(1+x),x,4);

                               1  2   1  3    / 4\
                           x - - x  + - x  + O\x /
                               2      3           
nops(s);

My laptop is broken and I am seriously considering purchasing a new laptop. I mainly use the laptop to do all kinds of programming, including Matlab, C/C++, Fortran, Maple, Mathematica, etc. I am wondering if anybody can tell some experiences about speed performance of Maple on Core Duo Dual Core processors? Are the computations on these computers really faster? I recall a few months ago I had tested a Monte Carlo program in Matlab on my friend's new Intel Quad Core (4 cpus). He paid $6000 for a desktop like that. The speed was not improved at all.

This one? int(log(c*exp(k*s)-d), s= 0 .. t) assuming (t>0, c>0, k>0, d>0) Thanks!

I'm trying to get the simple form of sum{k=1 to n} _2k C _k... I've tried to use Pascal's triangle, the gamma function, etc... but I couldn't get it... Somebody help~ My guess is _2k C _k is equal to binomial(2k,k). I used Maple... and the answer is ... as I see, a complex number!

F:=binomial(2*k,k);
                              binomial(2 k, k)
DefiniteSummation(F,k=1..n);

         (1/2)                                                               
    4 I 3                                            /[       3]            \
- -------------- - binomial(2 n + 2, n + 1) hypergeom|[1, n + -], [n + 2], 4|

Hello, I´m trying to create a maplets, but crash out with problem, I don´t now how to create in a smart way a method for count the number of varibles, I did that in the following lines: for Num from 1 to 1E6 do > A[Num]:=assigned(u[Num]): > if A[Num]=true then > N:=Num > end if; > end do: u[k] is a vector, and N, obviously the number of them. because I guess that the user, don´t want introduce more than a million of vectors, I don´t like that way. If somebody know the answer to my (maybe silly) question, please, explain it. Please replace this text with the link to your file.

I am trying to write a procedure which takes a list of (linear) expressions in two variables and a list of assumptions on the two variables and returns all of the possible orderings of those expressions. To my dismay, the assuming facility does not seem to be working properly. I using Maple 9 on a Windows System. The following input illustrates the problem. coulditbe(mU > 1-u) assuming mU true Maple returns true! The first assumption alone eliminates the possibility of this being true. What's going wrong and how do I get this to work? If you wish, you can plot these assumptions and though at least two are redundant, there is a feasible region.

Hello, I need to find relative extrema of an expression with inequalities. e.g. extrema(xi^2-x1^2-x2^2-xp^2-y^2,{xi-x1-x2+xp^2<=y^2},y); extrema command is not able to compute with inequalities constraints. Could you help me please? Thank you. Vladimir

Hi I am looking for eigenvectors of a messy jacobian matrix, maple is taking its sweet time with this (but still probably faster than me ;)) I have access to a 250 node(dual and quad opteron) cluster, is there anyway to run maple in parallel? If not will maple see a speed up when run on a dual proc or dual core workstation?

Hi I have the following command: > LinearSolve(E0,Z,free=R) assuming real; when I execute this I get: Error, (in assuming) when calling 'LinearAlgebra:-LinearSolve'. Received: 'unexpected argument(s): free = R, LinearAlgebra:-LinearSolve' I am not sure why? can anyone explain? Without free=R it works fine...

I have used Maple 7 under Windows 2000. Now I want to port it to Windows Vista. It seems to work well, but only when instructions are introduced onto the Maple screen by drag and drop from an external text file. When I try to type numbers or literals nothing appears on the screen. This peculiar behaviour is not observed with other programs, Mathematica (4.2), for example. Additionally, when I try to save a file, the Maple screen disappears immediately. There must be a simple solution of these problems, but I have not yet found it. Any help will be welcome. Thanks! Willy

It appears that Maple uses N as the denominator and not N-1 in calculating a covariance matrix in the Statistics package. Why? Harry Garst

To read data from file and fit it to a known equation,for example y a*x+b I used the commands: fs := ImportMatrix("C:\\Fit\\test.dat"): with(Statistics):eq:=Fit(BesselK(a*x+b,fs[1....200,1],fs[1...200,2],x); but I do not know how to let Maple calclate the values of y for each x after I knew the parameters a and b from the fitting.and how I can plot the fitting equation to compare it with the plot of the data to know is the fitting is good or know.