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Hi! I need help with my project I dont know where to even start!

Question:

Consider a simple polymer , which consist of long chains of simple molecules attached to each other, e.g:

....-CH₂-CH₂-CH₂-...

If the interaction energy between consecutive sections ca be ignored or is low enough, the chain can be bend around at varios places to form varios configurations. One can start by  fixing the first section...

I frequently have a list of numbers and what I want is a sorted list of unique elements with a count of how many times each element appears.  Is there some way to do this with ListTools?

Here is my code:

listhist := proc(L)
local S, T, i;
T := table(sparse):
for i in L do T[i] := T[i]+1; end do;
S := sort(map(op,[indices(T)]));
[seq([i,T[i]], i=S)];
end proc:

I'm using Maple to simulate particle collision and interaction (absorption and scattering) and keep tracking its energy until each particle either get absorbed or leaked (Energy less than predefined minimum energy). I also use Maple statistical pacakge. I also need to call MATLAB link to generate histogram in a logarithmically spaced bin, a feature that I could not find anywhere in Maple and I think it is one of the reasons for calculation performance issue.

The problem...

I have some data that requires a logarithmic y-axis for its histogram, but I want the y-axis to start at y=10^0. In my histogram, the y-axis starts near 10^-2, seemingly because I have 0-points in my data. How can I restrict the y-axis to start at 10^0? 

Hi,

My question is fairly straight-forward, I hope someone has an equally straight-forward solution. I would like to be able to illustrate the convergence of the distribution on the mean of i.i.d random variables to the normal distribution. For example, I'd like to visualize (by way of a histogram plot) that as n increases arbitrarily, the mean of n i.i.d. exponential random variables with mean 10 converges to a normal distribution.

Thanks!

Hi, 

I am relatively new to Maple and I am seeking an efficient way to create a probability histogram for a discrete probability distribution. For example,

x:      1     3   5    7

p(x): 1/8 1/4 1/2 1/8

I would like rectangles with height corresponding to the probabilities with bases centered at each x value, allowing for the possibility of gaps in the distribtuion.

Hey folks, I'll give you the actual problem I'm trying to solve before I show you my code in case anyone can think of a better idea...

Long read but you can ignore the examples and additional info if you don't need it.

Take the doubling map,

f(x) = 2x if 0 <= x <= 1/2

f(x) = 2x - 1 if 1/2 < x <= 1.

Or in maple code, f := x -> piecewise(x<=1/2, 2*x, 2*x - 1):

This looks...

I have an BW image, which i can read in with ImageTools. now i simply want a histogram of it. the plothistogram function works, but i am not sure that it does right, because the numbers in the plot seem far to big. so i am trying to use the histogram function but i am only able to plot a histogram for a single vector of my image. is there an easy way to use the histogram function for the entire array? as the next step, i would like to compute the variance of the histogram....

If you work with Maple on a daily basis sometimes you come across
things that seem impossible to do. Yesterday I tried to have two colors
in a histogram ie -3..-1 = red and -1..3 =blue but I could not figure
out how to do it...hummm.....any suggestions?

restart:
with(Statistics):
with(plots):

n:=5000:
A:=Sample(RandomVariable(Normal(0,1)),n):

Histogram(A,bincount=100, color=blue);

For fun, I have created a sweet and short small animation procedure, which I must say is one of my biggest programs yet (gasp!) as much as I have played with Maple I should have at least created a few more ... In any case, it is a procedure of a random set of numbers chosen and displayed in a histogram on the left with a running total tallied on the right. It is by no means efficient (but feel free to fix up my code and tweak it a little bit, and let me know so I can learn more...

In all versions prior to and including Maple 13 the Histogram default incorrectly displays the data.  Has this been fixed in 14?

eg.

a:=[1,2,3,4,5,6,7,8,9,8,9,7,6,5,4,2,2]

with(Statistics):
Histogram(a,frequencyscale=absolute,binwidth=1)

Clearly the...

Depending on the number of bars in a histogram.  The bars vary their width. 

Why is it not consistent?