Annonymouse

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7 years, 40 days

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These are questions asked by Annonymouse

HI

I am using a simple piece of code to generate Lie derivatives, and I am interested in adapting it so that I can use it with vector Fields where that include RootOf expressions. 

LieDer_with_rootof.mw

The above includes an example where it works, and an example where RootOf appears in the vector field and it does not work. 

Hi

I have been making a 3d graph of the level sets of a function. Here is the code for the 3d graph:

display(seq(seq(plot3d([i/sin(u), u, j], u = 0 .. 3/2, t = 0 .. 10, view = [0 .. 10, 0 .. Pi/2, 0 .. 10], color = i*j), i = 1 .. 10), j = 1 .. 10))

Each curve is a different level set- and I'd liketo colour them all individually -so people can tell tham appart. Any variation of the code I've made makes each of the curves black.


 

Hi

I am new to parallel computing, but as my current desktop is struggling with caclulating Groebner bases (i've been locked out for most of a week), I've contacted my universities center for scientific computing in the hope that they could do the caclulations.

However, I've been told that maple doesn't run in a distributed-memory parallel sense; as parallelisation in maple is very new - and i couldn't find discussion of this in the documentation - I thought it would be best to ask here if it does.

Secondarily can commands from the GB package be implemented in a way that would benefit?
if not can other similar commands like solve or eliminate?

Hi

I am woking on a pharmo model for a freind, and it includes a variable called depot that needs to jump up by 150 every 24 hours.
currently I have written it as:

diff(Depot(t), t) = piecewise(t = 0, -Ka*Depot(t)+150, t = 24, -Ka*Depot(t)+150, -Ka*Depot(t))

clearly thats wrong though, as the +150 s don't make it jump up by 150 because of the small step size.


(at t=0, it adds 150*a small step size, at 24 it looks like it adds 150* a vastly smaller step size, what I want would be much closer to a series of pulses each decaying to almost 0 and then getting boosted to just over 150)

My intuition is that i need to use the dirac delta function but in such a way that its integral adds 150 instantaneoulsy every 24 hours. I have no idea how to do that!

Lindas_signal_transduction_model_2.mw

[Edit:
I've just realised that this ode has an obvious solution, so you can trivially make a function that adds 150 every 24 hours and exponentially decays in between.  However there are other models that hopefully i'll being doing similar work on, that don't have nice solutions]

 

Hi i was trying to numerically integrate my freinds model with dsolve, and i am sure that I have put all the right components in the command as described in the help page, but it doesn't work. (Here is a worksheet with the model Lindas_signal_transduction_model.mw )

What is the problem with the way I have called the function?
Does anyone have a mental checklist that they use for dsolve commands? because I often struggle with making them work.

 

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