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Hi all,

 i have a problem with the equation generation in MapleSim, when using spring/damper elements in a Multibody-System. As an example, I've created a model of a mass-spring-damper system:

 

 


 

Hello everybody,

I have this equation J:

> J := Matrix(2, 6, [[j41, j42, j43, j44, j45, j46], [j51, j52, j53, j54, j55, j56]]);

it's a 2 times 6 matrix made with the results of other equation, each one of those small j's are long analytical terms.

Later I want to generate a Matlab code of J using this:

> Matlab(J, resultname = "j4", output = "file.m", optimize);

I use the optimize code at the end because then I avoid getting...

I keep getting this error although the code is running fine in maple 14 , Help is greatly appreciated Thanks alot

> restart; with(LinearAlgebra);
> A[0] := Vector(3, {(1) = 0, (2) = 0, (3) = -g});
> type(a[0], Vector);
                             false
> omega[0] := Vector(3, {(1) = 0, (2) = 0, (3) = 0});

I am using MapleNet14 on Mac OS X Server 10.6.4. 

 

I tried to draw 3D plot by the use of MapleNet's Image Generation.

But the following URL that is sample code from document does not 

produce 3D plot.

http://localhost:8080/maplenet/imaging/image?maple=plot3d(x^2%2By^2,x=-1..1,y=-1..1)&width=400&height=400

 

Error messages are

  MapleNet JSP Error

  com.sun.opengl.impl.macosx.CGL.createPBuffer...

 

This is the fourth and final part of a blog post, the first three parts of which can be found here: Generating Samples from Custom Probability Distributions (I)

This is the third post in a four-part series; the earlier posts are Generating...

This is the second post in a four-part series that started with this post: Generating...

Maple's Statistics package contains many predefined probability distributions; well-known ones such as the normal distribution and lesser-known ones such as the Gumbel distribution. For these distributions, we ship efficient algorithms that can quickly generate a large number of sample points. To generate a sample of size 106 of both of these distributions, and print the time it took to do this (in seconds), you can run the following:

with(Statistics):
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