I am starting to get used to Maple. I have an old copy of it (Maple 7). I am trying to simplify an equation using the simplify command by typing something like this:
simplify(eqn1, {x[1]^2+y[1]^2 = 1});
I want to make life easier for the case when I have several equations in my equation expression of simplify (or other maple commands). I want something like this:
simplify(eqn1, {for i from 1 to 10 do: x[i]^2 + y[i]^2 = 1 end do:})
I don't know if this is possible. So I am asking here if someone knows if something like this is possible in Maple.
Jose
Try it as,
simplify( eqn1, { seq( x[i]^2 + y[i]^2 = 1 , i = 1 .. 10 ) } )
Related
I'm coding the matrix for the 2-dimensional graph, now.
Although it's so simple equation, it takes a lot of time for performing. I think it could get faster.
especially, "for - command term" could be simplified I think.
How can I simplify this?
q=1:1:30
x(q)=330+q*0.3
F=1:30:8970
T=x(1)-0.3:0.001:x(30)+0.3
n=size(T,2)
k=1:1:n
for a=1:1:30
I(a,k)=F(a)*exp(-2.*(T(:,k)))
end
happy=sum(I)
plot(k,I)
I would say that the time is used to print results. Try to use ; at the end of each line, it will fasten computation.
You can also replace the for loop by the following element by element computation:
a = (1:1:30).';
aux = repmat(exp(-2.*(T(:,k))), length(a), 1);
a = repmat(a, 1, length(k));
I = a.'.*aux.';
I'm trying to make Maple solve a complex equation, but it produces an incorrect result.
The following images tells it all :
At (3) I would expect to get something close to 1 (as (2) shows), yet it gives me something that doesn't make any sense. Is it that the || (to express the complex number modulus) operator has another significance in the solve() function?
The more appropriate function here is fsolve.
Example 1
restart:
G:=(w,L)->(5+I*L*2*Pi*w)/(150+I*L*2*Pi*w);
evalf(5*abs(G(10,1)));
fsolve(5*abs(G(10,L))=%,L=0..10)
Example 2
As above, you need to specify the interval L=0..1 where the solution might be.
G:=(f,L)->(256.4+I*L*2*Pi*f)/(256.4+9845+I*L*2*Pi*f);
evalf(5*abs(G(20000,0.03602197444)));
fsolve(5*abs(G(20000,L))=%,L=0..1);
If you are facing difficulties to specify the interval then you should plot it first, it will give you an idea about it?
plot(5*abs(G(20000,L)),L=0..1)
Restrict the values of L in the solve command with the assuming command.
Example 1:
G:= (w,L) -> (50+I*L*2*Pi*w)/(150+I*L*2*Pi*w);
result := evalf(5*abs(G(10,1)));
solve({5*abs(G(10,L)) = result},L) assuming L::real;
{L = 1.000000000}, {L = -1.000000000}
Example 2:
G:=(f,L) -> (256.4+I*2*Pi*L*f)/(256.4+9845+I*2*Pi*L*f);
result := 5*abs(G(20000,0.03602197444));
solve({5*abs(G(20000,L)) = result},L) assuming L::real;
{L = 0.03602197445}, {L = -0.03602197445}
my Problem is the following:
I have about 300 Struct files given.
They are set up like this:
DSC_0001 has about 250 other struct files in it:
-> like this: DSC_0001.marker_1
And this one has 10 Numbers in it.
Like that:
DSC_0001.marker_1.flow_angle = 90
and now I want to iterate through all the Struct files
Something like that:
for i = 1:300
for j = 1:250
flow_angle = DSC_**i**.marker_**j**
end
end
Is there a way to do this?
I have the feeling that it could be really easy but I just can't find the solution...
I hope my question is clear enough...
Thanks for your help!
If possible don't use eval.
It depends on how your data is stored, but one possiblity is that it is in a .mat file. In that case it can be loaded using
DSC_structs = load('My_DSC_struct_file.mat');
and then you can access the values like so:
for i = 1:300
for j = 1:250
flow_angle(i,j) = DSC_structs.(['DSC_' sprintf('%04d',i)]).(['marker_' sprintf('%d',j)]);
end
end
Why avoid the eval function
Edit: You say that each struct is in a different file. That's a bit messier. I would probably do something like this to load them:
DSC_structs = cell(1,300);
for i = 1:300
%Note: I'm guess at your file names here
DSC_structs{i} = load(['DSC_' sprintf('%04d',i) '.mat'];
end
and then access the values as
DSC_structs{i}.(['DSC_' sprintf('%04d',i)]).(['marker_' sprintf('%d',j)]);
I guess this is a use case for the dreaded eval function:
for i = 1:300
for j = 1:250
eval (['flow_angle = DSC_', sprintf('%04d',i), '.marker_', num2str(j)]);
end
end
BUT NB there are 2 problems with my code above
You haven't told us where you want to store your angle, so my code doesn't :/ but you'd want something like this if you just want to store them in a matrix: eval (['flow_angle(', num2str(i), ',', num2str(j), ') = DSC_', sprintf('%04d',i), '.marker_', num2str(j)])
eval is a horrible way of doing things but you're forced to because someone saved your data in a horrible. Sort yourself out now for the future by re-saving your data in a smarter way! so something like:
.
for i = 1:300
eval ( ['DSC(', num2str(i), ') = DSC_', sprintf('%04d',i)]);
end
%// then save DCS!
And now your can iterate through this matrix of structs rather than having a 300 structs polluting your workspace and forcing you to use eval
I need to substitute a value for s in a transfer function. For example:
G(s)= 1/ (s+3)
I need to substitute
s = -2.118 +2.221j
What code should I use for this?
PS: Unfortunately, I only have control system toolbox in MATLAB.
What's wrong with saving m-file with
function g = transferFun( s )
g = 1 ./ ( s + 3 )
And then calling the function
>> transferFun( -2.118 + 2.221*j )
As shai mentioned you can simply create an m file with the function.
However, if you are just doing some quick calculations here is a way to just do it on the command line. You can define an anonymous function like this:
G = #(s) 1/(s+3)
Now you can simply call it like this:
G(-2.118 +2.221j)
Note that Matlab is case sensitive.
I've been given the task of translating a piece of MATLAB code into IDL and have
hit a roadblock when I came across the MATLAB function accumarry(). The
function, described here
is used to sum elements in one array, based on indices given in another. Example
1 perhaps explains this better than the actual function description at the top
of the page. In trying to reproduce Example 1 in IDL, I haven't been able to avoid a for loop, but I'm confident that it is possible. My best attempt is the following:
vals = [101,102,103,104,105]
subs = [0,1,3,1,3]
n = max(subs)+1
accum = make_array(n)
for i = 0, n-1 do begin
wVals = where(subs eq i,count)
accum[i] = count eq 0 ? 0 : total(vals[wVals])
endfor
print,accum
; 101.000 206.000 0.00000 208.000
Any advice on improving this would be greatly appreciated! I expected IDL to have a similar built-in function, but haven't been able to track one down. Perhaps some magic with histogram binning?
I found a number of possible solutions to this problem on Coyote's IDL site (not surprisingly.)
http://www.idlcoyote.com/code_tips/drizzling.html
I ended up using the following, as a compromise between performance and readability:
function accumarray,data,subs
mx = max(subs)
accum = fltarr(mx+1)
h = histogram(subs,reverse_indices=ri,OMIN=om)
for j=0L,n_elements(h)-1 do if ri[j+1] gt ri[j] then $
accum[j+om] = total(vals[ri[ri[j]:ri[j+1]-1]])
return,accum