The worksheet below has two examples using your data.  There are other ways to do this, by reading in your data from an external file.  For help on the commands used, look at plot, display, Scatterplot commands from the Help menu.

Download dataplotvec.mws

The command modp in Maple can be used the same way that mod can in Matlab.  The mod command will give you the same answer, but the usage is different.

For example, in Matlab

mod(13,5)
ans =
     3

mod([1:5],3)
ans =
     1     2     0     1     2 

In Maple

> modp(13,5);
                                  3

> modp([1,2,3,4,5],3);
                           [1, 2, 0, 1, 2]

> [1,2,3,4,5] mod 3;
                           [1, 2, 0, 1, 2]

The DynamicSystems package was built in.  I do not remember which version started to use it, but you can check to see if ver 11 has it by typing the following:

with(DynamicSystems);

If it was part of ver 11, then you will see all of the functions that are supported.  If it is not a part of ver 11, then you will get an error message, similar to the one below:

Error, invalid input: with expects its 1st argument, pname, to be of type {package, module}, but received DynamicSystems

Hope this helps.

pds:-value(t=0.5)(0);
pds:-value(t=0.5)(1);

The above will give you values for t=0.5 with z=0 and then with z=1 and so on. 

Look at the help pages for the assign command:

?assign

For example: 

>ans:=solve( {x+y=1, 2*x+y=3}, {x, y} );

                    {x = 2, y = -1}

>assign(ans);

>x,y;

                     2, -1                   

restart:

f:=x/sqrt(1-cos(x));

limit(f,x=0,complex);

From the help files:

If dir is complex, the limit point infinity denotes complex infinity, that is, all infinities in the complex plane. If dir is real, the limit point infinity denotes both positive and negative infinity, and the limit is done bidirectionally. Otherwise, the limit point infinity denotes positive infinity, and -infinity denotes negative infinity.

restart: with(plots):

deq := (diff(y(x), x, x))*y(x)-1+x*y(x)^2 = cos(x);

sol := dsolve({deq, y(0) = 1, (D(y))(0) = 1}, numeric,range=-2..2);

p1:=odeplot(sol):

p2:=plot(x->op(2,op(2,sol(x))),-1..1,color=blue,style=point,symbol=circle):

display(p1,p2);

The plot looks like cos(x) over a small range.

This should clear it up a little.

plots:-display(DEplot(ode1, q(t), t = 0 .. 8760, q(t) = 0 .. 10000, [q(0) = 0], title = "contaminant accumulation and dissipation",linecolor=red,color=red), DEplot(ode2, q(t), t = 8760 .. 17520, q(t) = 0 .. 10000, [q(8760) = 9278],linecolor=blue,color=blue));

The method below works using odeplot.  

restart: with(plots):

p1:= dsolve({diff(q(t), t) = 3-3*q(t)/10^4, q(0)=0}, type=numeric, range=0..16000):

plot1:=odeplot(p1):

p2:=dsolve({diff(q(t), t) = -3*q(t)/10^4, q(0)=17520}, type=numeric, range=0..17520):

plot2:=odeplot(p2,color=blue):

display(plot1,plot2,title = "contaminant accumulation in the first year(red) and second year(blue)");
 

restart:

t:=[1,-1,0,1/2,3,3/2,sqrt(8)];

sort(t);

x:=evalf(t);

sort(x);

identify(%);

For your example as you posted it, you can do this after your t.

identify( sort(evalf(t)) );

Can you provide more details as to what you are trying to do, with an example, if possible?

restart:

x:=[Pi,sqrt(2), sqrt(3), sqrt(5), sqrt(10), sqrt(7)];

[x=Pi, 2^(1/2), 3^(1/2), 5^(1/2), 10^(1/2), 7^(1/2)]

identify(sort(evalf(x)));

[2^(1/2), 3^(1/2), 5^(1/2), 7^(1/2), Pi, 10^(1/2)]

This book looks like it covers the topics of intererest.  An advantage is the available code for you to try.

NonlinearFit from the Statistics package does not return a very good match to your data, using the model function y=ax^n+bx+c that you supplied.  Your might try another model function.  Otherwise, look into LSSolve, which is part of the Optimization package.

Download 221_Fit_from_data.mws

restart:

with(Student[Calculus1]):

Roots(cos(2*theta)=1/2,theta=0..2*Pi,numeric):

identify(%);

The help page for the Fit command has an example using X,Y data.

?Fit to bring it up.