MaplePrimes Questions

I got an MS Excel file where the matrix (7054x60) is created and the last row of the matrix is used for optimization of its (the matrix) values. In Maple you can create the matrix as follows:

M := Matrix(7054, 60):
for i to 10 do M[1, i] := 1 end do:

Mat_proc := proc(x)
  local i, j;
  global M;
  for i from 2 to 7054 do

How does this  function  work:

rtable_scanblock( M, [rtable_dims(M)],

    (val,ind,res) -> `if`(val > res[2],[ind,val],res),



Please could comment on each statement.

Taken from


The attached worksheet (, first-order non-linear ODE system) is ~x100 (one hundred) times slower that the "same" program in Mathematica 8. Both give the same/satisfactory numerical results and have similar/identical structure (I can supply the Mathematica 8 notebook, if requested).

I assume that my attached worksheet must be sub-optimally programmed and would be grateful...

Like this! Some error. How to do it


I have the function which I run well in Maple V
but in maple 15 .It's wrong. How can it be? and please help me to edit it.

for i from 0 to 15 do

Hi everyone,

I guess the question I am asking is quite common, however I am still not able to figure it out. I have several (right now three) non-linear inequalities. Given these inequalities, I try to plot them in one graph and then color the different areas with different colors. It would be also ok, if just the area where all inequalities hold is plotted. To do this I have already tried several things. With implicitplot and transparency it is generally working, but...


I am tring to do if–then–else in the do-loop for the parameter A[1]. Example: when k=3 we want to use A[1]=B[3] insted of B[1] but it seems my if–then–else did not do what I want. Any ideas?

Thank you

This is maple code:

> restart;
> k := 0; B[1] := 0.001/365: B[2] :=0.002/365:B[3] :=0.005/365:
> ode := diff(U(t), t) = -(A[1]+A[2]*U(t))*U(t);
> ic[0] := U(365*k) = 1000;

I have a 6 x 6 matrix. I want to employ Cramer's rule to solve Gx=Θ. I need to sequently substitute column Vector Θ into the matrix columns. I can't get this to work. I have only being using Maple for a couple of weeks so still finding my way.



This plot was never created. I think it's taking too long to evaluate it when it's divegent.


Hi all,

For my research purpose, I need to integrate this function. I understand that there maybe values for which this integration is divegent. But is there a way to look into it? Say creat...

how to write a procedure to ceiling a number such as 3.5 to 4

HI everyone, im currently using maple 15 and im trying to animate at least the mass of my pendulum. My problem is that the  coordinate of each mass would be the solution of two numerical ODE and I can't animate this. I am able to plot the solution of my ODE (wich correpond to the two angle in the pendulum), but when it comes to animating... its an another piece of work. So here is what I tried: the code would correspond to the animation two masses... no rope yet.

I have a set of multi variate polynomial  equations. I need to setup a matrix [G][x]=[Θ]  Θ is a function of c1 and c2 up to 4th order terms

 My problem x=[c15, c14c2 , c13c22 , c12c23 , c1c24 , c25 ] these 6 5th order terms...



I'm trying to plot a few phase portraits for this four equation system but maple wont let me...

> restart;

> s := 10; d[T] := 0.2e-1; k1 := 2.4*10^(-5); k2 := 3*10^(-3);
> N := 5; delt := .24; c := 2.4; T0 := 1; 


Can someone please help me? Thanks


Hi everyone, im trying to solve the following system of ode (motion of a double pendulum) where im trying to plot numerical solution for T1(t) and T2(t). Been searching for a while... found nothing :) Here is my code , i also loaded the library plots, DEtools. . Im using maple 15

> Systeme := [2*(diff(T1(t), x, x))+cos(T1(t)-T2(t))*(diff(T2(t), x, x))+sin(T1(t)-T2(t))*(diff(T2(t), x))^2+19.6*sin(T1(t)) = 0, diff(T2(t), x, x...

Hi everyone,


I want to create a Gaussian PDF so I need to calculate Determinant(sigma) with sigma the covariance matrix of a gaussian variable.

If we call this variable alpha (which is a 12 dimension vector and represents the noise in a discrete dynamical equation), then sigma_ij=ExpectedValue(alpha_i*alpha_j)-ExpectedValue(alpha_i)*ExpectedValue(alpha_j)

and this is zero most of the time! So the covariance matrix is singular and the determinant is zero. 

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