MaplePrimes Questions

I have a function that refuses to allow "fsolve" to compute a root for.  I'm trying to use a brute force Newton (or secant) algorithm to find the root.  This is successful 

But I'm new enough in Maple Flow (and Maple) that I can't build an automatic recursion method.  All ideas welcome.

EqBIS := proc(P, U, V)
local a, eq1, M1, t, PU, PV, bissec1;
a := (P - U)/LinearAlgebra:-Norm(P - U, 2) + (P - V)/LinearAlgebra:-Norm(P - V, 2);
M1 := P + a*t;
eq1 := op(eliminate({x = M1[1], y = M1[2]}, t));
RETURN(op(eq1[2])); end proc;
EqBIS*([4, 5], [11, 7/3], [11, 5]);
why such a procedure gives no result Thabk you.


Trying to use the jets package from (file jets.s) for calculus of variations.

Test example -

vg:=variation(g,f);                  # first variation of g (from line 4354 of jets.s)

Now I want to find g from vg - inverse problem. The code for this starts on line 4367 of jets.s, command is lagrangian.

Tried -


but all give syntax errors.

The authors of the package don't respond to query and the manual does't help.

Does anyone know what the correct syntax of lagrangian is. Or is there a better package to use for inverse problem.

Thank you.

I am doing some error I dont know where in the usage

T := [[1, 2], [3, 4]];
convert(T, set, nested);

{[1, 2], [3, 4]}

But I expected internal lists also to be converted to sets like {{1,2},{3,4}}  my list may be a big list just taken a example

This a simple question I know i tried somewhere i am going wrong please help

what i am trying to do is 



not making all nested all as set as mentioned in the simple example.

some simple program and fast kind help

I'm trying to figure out how to represent 100 people where each one has a 30% probablity of getting sick.

I think sample can be used but not I'm exactly sure how to achieve that. Basically how many people are sick?

The computer on which I have been executing Maple worksheets for the past six years (CPU: i7 - 5820K, 6 core, 3.3 GHz, 5th generation) is now significantly slower than new machines.

I don't know how to interpret public specifications of potential replacement machines into their actual future performance with Maple.

Please give me or direct me to any advice which would enable me to knowledgeably purchase a much faster processor of Maple code.


Hello there, 

Is there any chance to see that the 'eq_5_22_desired' expression shown below can be derived from a collection of the commands. similar to what's given in the 'eq_5_22a'? In other words, is it possible to make Maple aware of the point that 'L__ad/(L__ad + L__fd)' can be interpreted as 'L__ad*L__fd/(L__ad + L__fd) * 1/L__fd'?




eq_5_22 := Psi__ad = -L__ad*L__fd*i__d*1/(L__ad + L__fd) + L__ad*Psi__fd*1/(L__ad + L__fd);

Psi__ad = -L__ad*L__fd*i__d/(L__ad+L__fd)+L__ad*Psi__fd/(L__ad+L__fd)


eq_5_23x := L__ad__p = 1 / (1/L__ad + 1/L__fd);

L__ad__p = 1/(1/L__ad+1/L__fd)


eq_5_23 := L__ad__p = evala(rhs(eq_5_23x));

L__ad__p = L__ad*L__fd/(L__ad+L__fd)


eq_5_22a := Psi__ad = collect(expand(solve(eq_5_18x, Psi__ad)), rhs(eq_5_23)); # error

Error, invalid input: expand expects 1 argument, but received 0


eq_5_22_desired := Psi__ad = -L__ad__p*i__d + L__ad__p*Psi__fd/L__fd;

Psi__ad = -L__ad__p*i__d+L__ad__p*Psi__fd/L__fd







assume(delta:: real)



f:= g->e^(-1/2*(C*g*(1-g^2))^2*(1+delta^2)-C*g*(1-g^2)*alpha)/(g*(1-g^2));

proc (g) options operator, arrow; e^(-(1/2)*C^2*g^2*(1-g^2)^2*(delta^2+1)-C*g*(1-g^2)*alpha)/(g*(1-g^2)) end proc





f1:= g->-e^(-1/2*(C*g*(1-g^2))^2*(1+delta^2)-C*g*(1-g^2)*alpha)/(2*(g+1));

proc (g) options operator, arrow; -e^(-(1/2)*C^2*g^2*(1-g^2)^2*(delta^2+1)-C*g*(1-g^2)*alpha)/(2*g+2) end proc


f2 := g->e^(-1/2*(C*g*(1-g^2))^2*(1+delta^2)-C*g*(1-g^2)*alpha)/g;

proc (g) options operator, arrow; e^(-(1/2)*C^2*g^2*(1-g^2)^2*(delta^2+1)-C*g*(1-g^2)*alpha)/g end proc


f3:= g->-e^(-1/2*(C*g*(1-g^2))^2*(1+delta^2)-C*g*(1-g^2)*alpha)/(2*(g-1));

proc (g) options operator, arrow; -e^(-(1/2)*C^2*g^2*(1-g^2)^2*(delta^2+1)-C*g*(1-g^2)*alpha)/(2*g-2) end proc



int(-e^(-(1/2)*C^2*g^2*(-g^2+1)^2*(delta^2+1)-C*g*(-g^2+1)*alpha)/(2*g+2), g = 0 .. infinity)





I do not know why eq(6) does not evaluate. Could you help me?

When trying to construct objects like SU(3)xSU(2)xU(1), one needs parameters to satisfy SU(n,q)xSU(n,q)xU(n,q).  What are the values of 'q' for these group constructions using the group theory package?  


in Maple 2022.1 on windows 10


`Standard Worksheet Interface, Maple 2022.1, Windows 10, May 26 2022 Build ID 1619613`


`The "Physics Updates" version in the MapleCloud is 1288 and is the same as the version installed in this computer, created 2022, August 6, 16:9 hours Pacific Time.`



Error, (in gcdex) invalid arguments


Why it happens and is there a workaround?

Does it happen on earlier versions? I do not have an earlier Maple installed on my current PC as it is new to check. 


When I use rsolve() to obtain the direct formula for calculating the mean `u` from its recursive definition:

u(n + 1) = u(n) + (x[n + 1] - u(n))/(n + 1)

u(1) = x[1]

and plug it into rsolve() then I receive the output:

rsolve({ u(n + 1) = u(n) + (x[n + 1] - u(n))/(n + 1), u(1) = x[1]}, u(n))

which is correct, but I would like to see it further simplified to:

sum(x[n1], n1 = 1 .. n)/n

Further calls to simplify() don't achieve this. Is there a way to do this, or did I hit some kind of limitation of rsolve() and is this as good as can be expected?


I want to change the output of the mtaylor command, eg for 3 series terms



ftaylor := f(0,0)+D[1](f)(0,0)*x+D[2](f)(0,0)*y+1/2*D[1,1](f)(0,0)*x^2+D[1,2](f)(0,0)*x*y+1/2*D[2,2](f)(0,0)*y^2;

I want the output as ftaylor := g(x,y) + D[1](g(x,y)) *x + D[2](g(x,y))*y + .... etc for all the terms in ftaylor.

Later on g(x,y) can be defined and terms like D[1](g(x,y)) evaluated.

I tried


but it doesn't work. Using eval doesn't work either.

Is there a way to do this?

Thank you in advance.

I want to modify the code such that it works with


How to do that? What is radical? 

A := matrix(2, 2, [0, a, b, 0]);
v := eigenvects(map(eval, A), 'radical');
q := ev[1][3][1];
et := eigenvects(map(eval, transpose(A)), 'radical');
P := et[2][3][1];

A simple tutorial task on optimization from one of the forums. We need to find the minimum of the function 
g1 = (x1-x2)*(x2-x3)*(x3-x4)*(x4-x1) with the following constraint g2 = x1^2+x2^2+x3^2+x4^2-1
It reduces to solving polynomial equations.  
Minimum = - 0.25. It's  solution:
[x1 = .683012702, x2 = .183012702, x3 = -.183012702, x4 = -.683012702],
[x1 = .183012702, x2 = .683012702, x3 = -.683012702, x4 = -.183012702],
[x1 = -.183012702, x2 = .183012702, x3 = .683012702, x4 = -.683012702],
[x1 = -.683012702, x2 = .683012702, x3 = .183012702, x4 = -.183012702],
[[x1 = .683012702, x2 = -.683012702, x3 = -.183012702, x4 = .183012702],
[x1 = .183012702, x2 = -.183012702, x3 = -.683012702, x4 = .683012702],
[x1 = -.183012702, x2 = -.683012702, x3 = .683012702, x4 = .183012702],
[x1 = -.683012702, x2 = -.183012702, x3 = .183012702, x4 = .683012702]
when x5 =0 .25

But so far I have not found an easy way to solve it using Maple. First we need to be able to successfully use fsolve, and only then "polynomial" functions.

restart; with(RootFinding):
g1 := (x1-x2)*(x2-x3)*(x3-x4)*(x4-x1); 
g2 := x1^2+x2^2+x3^2+x4^2-1;
 g :=g1+x5*g2; 
f1 := diff(g, x1); 
f2 := diff(g, x2); 
f3 := diff(g, x3); 
f4 := diff(g, x4); 
f5 := diff(g, x5); 
#solve([f1, f2, f3, f4, f5], [x1, x2, x3, x4, x5]);
Isolate([f1, f2, f3, f4, f5], [x1, x2, x3, x4, x5]); 
S := fsolve([f1, f2, f3, f4, f5], {x1, x2, x3, x4, x5}, maxsols = 8); 
x5 := rhs(op(5, S));
Isolate([f1, f2, f3, f4], [x1, x2, x3, x4]); 
solve([f1, f2, f3, f4], [x1, x2, x3, x4])

The optimization package doesn't help much either.
The task itself is of no interest, it is interesting to look at its simplest solution in Maple.
(By the way, Draghilev's method works well, but, of course, this is not the easiest way).

Hellow maple users, I am getting an error while solving system of differential equations analytically. Please help to recify the error. Thanks in advance. Here is my codes;

# S, N  are constant
combine(dsolve(desys union ics,{u(y),T(y),C(y)}));

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