Pretty simple, and I thought I knew what I was doing, but apparently not. Anyways.
I need to find the first element in a vector that is less than a specific value. Here is the code that I have been using:
t = 0:0.01:5;
u = ((2)*exp(-10.*t).*cos((4.*sqrt(6)).*t) + ((5)./sqrt(6)).*exp(-10.*t).*sin((4.*sqrt(6)).*t));
for a = 1:size(u)
if u(a) < (0.05)
disp(a)
break
end
end
The value that I'm trying to find is the first element less than 0.05, however, when I run my code, I don't get anything.
What could I be doing wrong?
Thanks!
#user2994291 has correctly pointed out where your loop based solution is going wrong (+1).
However I would also add that what you are trying to do can simply be accomplished by:
find(u < 0.05, 1, 'first')
Technically, the third input is not necessary - you could just use:
find(u < 0.05, 1)
However, I seem to recall reading at some point that find will work faster if you provide the third input.
The upper bound of your for loop is probably equal to 1.
In your case, u is a row vector (can't say 100% for sure in MATLAB as I only have access to GNU Octave right now), but calling size(u) will probably give back [1 501] as an answer. Your for-loop will select 1 as upper bound.
Try replacing size(u) with size(u,2) or, even better, with length(u). I get a = 24 as an answer.
Edit:
from your questions I assume you are a MATLAB beginner, therefore I strongly advise you to look into the built-in debugger (you can add breakpoints by clicking on the left vertical bar next to the desired line of code), this would have helped you identify the error with ease and will save you a lot of time in the future.
Related
I'd like to declare first of all, that I'm a mathematician. This might be a stupid stupid question; but I've gone through all the matlab tutorials--they've gotten me nowhere. I imagine I could code this in C (it'd be exhausting); but I need matlab for this particular function. And I don't get exactly how to do it.
Here is the pasted Matlab code of where I'm running into trouble:
function y = TAU(z,n)
y=0;
for i =[1,n]
y(z) = log(beta(z+1,i) + y(z+1)) - beta(z,i);
end
end
(beta is an arbitrary "float" to "float" function with an index i.)
I'm having trouble declaring y as a function, in which we call the function at a different argument. I want to define y_n(z) with something something y_{n-1}(z+1). This is all done in a recursive process to create the function. I really feel like I'm missing something stupid.
As a default function it assigns y to be an array (or whatever you call the default index assignment). But I don't want an array. I want y to be assigned as a "function" class (i.e. takes "float" to "float"). And then I'm defining a sequence of y_n : "float" to "float". So that z to z+1 is a map on "float" to "float".
I don't know if I'm asking too much of matlab...
Help a poor mathematician who hasn't coded since the glory days of X-box mods.
...Please don't tell me I have to go back to Pari-GP/C drawing boards over something so stupid.
Please help!
EDIT: At rahnema1 & mimocha's request, I'll describe the math, and of what I am trying to do with my program. I can't see how to implement latex in here. So I'll write the latex code in a generator and upload a picture. I'm not so sure if there even is a work around to what I want to do.
As to the expected output. We'd want,
beta(z+1,i) + TAU(z+1,i) = exp(beta(z,i) + TAU(z,i+1))
And we want to grow i to a fixed value n. Again, I haven't programmed in forever, so I apologize if I'm speaking a little nonsensically.
EDIT2:
So, as #rahnema1 suggests; I should produce a reproducible example. In order to do this, I'll write the code for my beta function. It's surprisingly simple. This is for the case where the "multiplier" variable is set to log(2); but you don't need to worry about any of that.
function f = beta(z,n)
f=0;
for i = 0:n-1
f = exp(f)/(1+exp(log(2)*(n-i-z)));
end
end
This will work fine for z a float no greater than 4. Once you make z larger it'll start to overflow. So for example, if you put in,
beta(2,100)
1.4242
beta(3,100)
3.3235
beta(3,100) - exp(beta(2,100))/(1/4+1)
0
The significance of the 100, is simply how many iterations we perform; it converges fast so even setting this to 15 or so will still produce the same numerical accuracy. Now, the expected output I want for TAU is pretty straight forward,
TAU(z,1) = log(beta(z+1,1)) - beta(z,1)
TAU(z,2) = log(beta(z+1,2) + TAU(z+1,1)) - beta(z,2)
TAU(z,3) = log(beta(z+1,3) + TAU(z+1,2)) - beta(z,3)
...
TAU(z,n) = log(beta(z+1,n) + TAU(z+1,n-1)) -beta(z,n)
I hope this helps. I feel like there should be an easy way to program this sequence, and I must be missing something obvious; but maybe it's just not possible in Matlab.
At mimocha's suggestion, I'll look into tail-end recursion. I hope to god I don't have to go back to Pari-gp; but it looks like I may have to. Not looking forward to doing a deep dive on that language, lol.
Thanks, again!
Is this what you are looking for?
function out = tau(z,n)
% Ends recursion when n == 1
if n == 1
out = log(beta(z+1,1)) - beta(z,1);
return
end
out = log(beta(z+1,n) + tau(z+1,n-1)) - beta(z,n);
end
function f = beta(z,n)
f = 0;
for i = 0:n-1
f = exp(f) / (1 + exp(log(2)*(n-i-z)));
end
end
This is basically your code from the most recent edit, but I've added a simple catch in the tau function. I tried running your code and noticed that n gets decremented infinitely (no exit condition).
With the modification, the code runs successfully on my laptop for smaller integer values of n, where 1e5 > n >= 1; and for floating values of z, real and complex. So the code will unfortunately break for floating values of n, since I don't know what values to return for, say, tau(1,0) or tau(1,0.9). This should easily be fixable if you know the math though.
However, many of the values I get are NaNs or Infs. So I'm not sure if your original problem was Out of memory error (infinite recursion), or values blowing up to infinity / NaN (numerical stability issue).
Here is a quick 100x100 grid calculation I made with this code.
Then I tested on negative values of z, and found the imaginary part of the output to looks kinda cool.
Not to mention I'm slightly geeking out over the fact that pi is showing up in the imaginary part as well :)
tau(-0.3,2) == -1.45179335740446147085 +3.14159265358979311600i
I've got a Subscripted assignment dimension mismatch problem.
I've already localized the issue, and know exactly what is going on, I just don't know why.
Here's the problematic piece of code:
mFrames(:,i) = vSignal(round(start:1:frameLength*samplingRate));
start=start+frameShift*samplingRate;
frameLength = frameLength+frameShift;
I've already checked what's going on in debugmode; usually my resulting column length of mFrames is 128, this stays the same until i=1004. Then, my column length changes to 127.
I've checked the values involved while in debug mode, and it simply does not make sense what is going on. At i==1004 start=32097 and frameLength*samplingRate=32224.
That's a difference of 127 meaning 128 points, that should work.
BUT when i assign a vector A=round(start:1:frameLength*samplingRate)
OR B=start:1:frameLength*samplingRate
In both cases I get a vector going from 32097 to 32223. This ALTHOUGH when I give in frameLength*samplingRate matlab is giving me 32224.
In other words, matlab is telling me it's using one number, but when I test I find it's using a different one.
Any help appreciated.
I suspect your 32224 is not actually 32224. MATLAB's default format only displays so many decimal places, so when dealing with floating point numbers, what is printed on screen is not necessarily the "exact" value.
Let's go back a step and look at how the synatx x = start:step:end works.
1:1:10 should give us numbers in steps of 1 from 1 to 10. Fair enough, that makes sense. What if we set the end value to something that's slightly above 10?
e.g.:
1:1:10.1
Well, it still gives us 1:1:10, (or 1:10, 1 being the default step) because we can't have values higher than the end-point, so 11 isn't a correct step.
So what about this:
1:1:9.99
Spoiler: it's the same as 1:9
And this?
1:1:9.9999999
Yep, still 1:9
But if we do this:
a = 9.9999999;
Then with default format, the value of a will be shown on the command line and in your list of workspace variables as 10.0000.
Now, if frameLength and samplingRate are both stored as floating point numbers, it's possible that the number you see as 32224 is not 32224 but very slightly below that. You can check this by changing your default format - e.g. format long at the command line - to show more decimal places.
The simplest solution is probably to do something like:
B=start:1:round(frameLength*samplingRate)
Or try to store the relevant values as integers (e.g., uint32).
I am having difficulty achieving sufficient accuracy in a root-finding problem on Matlab. I have a function, Lik(k), and want to find the value of k where Lik(k)=L0. Basically, the problem is that various built-in Matlab solvers (fzero, fminbnd, fmincon) are not getting as close to the solution as I would like or expect.
Lik() is a user-defined function which involves extensive coding to compute a numerical inverse Laplace transform, etc., and I therefore do not include the full code. However, I have used this function extensively and it appears to work properly. Lik() actually takes several input parameters, but for the current step, all of these are fixed except k. So it is really a one-dimensional root-finding problem.
I want to find the value of k >= 165.95 for which Lik(k)-L0 = 0. Lik(165.95) is less than L0 and I expect Lik(k) to increase monotonically from here. In fact, I can evaluate Lik(k)-L0 in the range of interest and it appears to smoothly cross zero: e.g. Lik(165.95)-L0 = -0.7465, ..., Lik(170.5)-L0 = -0.1594, Lik(171)-L0 = -0.0344, Lik(171.5)-L0 = 0.1015, ... Lik(173)-L0 = 0.5730, ..., Lik(200)-L0 = 19.80. So it appears that the function is behaving nicely.
However, I have tried to "automatically" find the root with several different methods and the accuracy is not as good as I would expect...
Using fzero(#(k) Lik(k)-L0): If constrained to the interval (165.95,173), fzero returns k=170.96 with Lik(k)-L0=-0.045. Okay, although not great. And for practical purposes, I would not know such a precise upper bound without a lot of manual trial and error. If I use the interval (165.95,200), fzero returns k=167.19 where Lik(k)-L0 = -0.65, which is rather poor. I have been running these tests with Display set to iter so I can see what's going on, and it appears that fzero hits 167.19 on the 4th iteration and then stays there on the 5th iteration, meaning that the change in k from one iteration to the next is less than TolX (set to 0.001) and thus the procedure ends. The exit flag indicates that it successfully converged to a solution.
I also tried minimizing abs(Lik(k)-L0) using fminbnd (giving upper and lower bounds on k) and fmincon (giving a starting point for k) and ran into similar accuracy issues. In particular, with fmincon one can set both TolX and TolFun, but playing around with these (down to 10^-6, much higher precision than I need) did not make any difference. Confusingly, sometimes the optimizer even finds a k-value on an earlier iteration that is closer to making the objective function zero than the final k-value it returns.
So, it appears that the algorithm is iterating to a certain point, then failing to take any further step of sufficient size to find a better solution. Does anyone know why the algorithm does not take another, larger step? Is there anything I can adjust to change this? (I have looked at the list under optimset but did not come up with anything useful.)
Thanks a lot!
As you seem to have a 'wild' function that does appear to be monotone in the region, a fairly small range of interest, and not a very high requirement in precision I think all criteria are met for recommending the brute force approach.
Assuming it does not take too much time to evaluate the function in a point, please try this:
Find an upperbound xmax and a lower bound xmin, choose a preferred stepsize and evaluate your function at
xmin:stepsize:xmax
If required (and monotonicity really applies) you can get another upper and lower bound by doing this and repeat the process for better accuracy.
I also encountered this problem while using fmincon. Here is how I fixed it.
I needed to find the solution of a function (single variable) within an optimization loop (multiple variables). Because of this, I needed to provide a large interval for the solution of the single variable function. The problem is that fmincon (or fzero) does not converge to a solution if the search interval is too large. To get past this, I solve the problem inside a while loop, with a huge starting upperbound (1e200) with the constraint made on the fval value resulting from the solver. If the resulting fval is not small enough, I decrease the upperbound by a factor. The code looks something like this:
fval = 1;
factor = 1;
while fval>1e-7
UB = factor*1e200;
[x,fval,exitflag] = fminbnd(#(x)function(x,...),LB,UB,options);
factor = factor * 0.001;
end
The solver exits the while when a good solution is found. You can of course play also with the LB by introducing another factor and/or increase the factor step.
My 1st language isn't English so I apologize for any mistakes made.
Cheers,
Cristian
Why not use a simple bisection method? You always evaluate the middle of a certain interval and then reduce this to the right or left part so that you always have one bound giving a negative and the other bound giving a positive value. You can reduce to arbitrary precision very quickly. Since you reduce the interval in half each time it should converge very quickly.
I would suspect however there is some other problem with that function in that it has discontinuities. It seems strange that fzero would work so badly. It's a deterministic function right?
Keeping simple, take a matrix of ones i.e.
U_iso = ones(72,37)
and some parameters
ThDeg = 0:5:180;
dtheta = 5*pi/180;
dphi = 5*pi/180;
Th = ThDeg*pi/180;
Now the code is
omega_iso = 0;
for i = 1:72
for j=1:37
omega_iso = omega_iso + U_iso(i,j)*sin(Th(j))*dphi*dtheta;
end
end
and
D_iso = (4 * pi)/omega_iso
This code is fine. It take a matrix with dimension 72*37. The loop is an approximation of the integral which is further divided by 4pi to get ONE value of directivity of antenna.
Now this code gives one value which will be around 1.002.
My problem is I dont need 1 value. I need a 72*37 matrix as my answer where the above integral approximation is implemented on each cell of the 72 * 37 matrix. and thus the Directviity 'D' also results in a matrix of same size with each cell giving the same value.
So all we have to do is instead of getting 1 value, we need value at each cell.
Can anyone please help.
You talk about creating a result that is a function essentially of the elements of U. However, in no place is that code dependent on the elements of U. Look carefully at what you have written. While you do use the variable U_iso, never is any element of U employed anywhere in that code as you have written it.
So while you talk about defining this for a matrix U, that definition is meaningless. So far, it appears that a call to repmat at the very end would create a matrix of the desired size, and clearly that is not what you are looking for.
Perhaps you tried to make the problem simple for ease of explanation. But what you did was to over-simplify, not leaving us with something that even made any sense. Please explain your problem more clearly and show code that is consistent with your explanation, for a better answer than I can provide so far.
(Note: One option MIGHT be to use arrayfun. Or the answer to this question might be more trivial, using simple vectorized operations. I cannot know at this point.)
EDIT:
Your question is still unanswerable. This loop creates a single scalar result, essentially summing over the entire array. You don't say what you mean for the integral to be computed for each element of U_iso, since you are already summing over the entire array. Please learn to be accurate in your questions, otherwise we are just guessing as to what you mean.
My best guess at the moment is that you might wish to compute a cumulative integral, in two dimensions. cumtrapz can help you there, IF that is your goal. But I'm not sure it is your goal, since your explanation is so incomplete.
You say that you wish to get the same value in each cell of the result. If that is what you wish, then a call to repmat at the end will do what you wish.
I have been happily using MATLAB to solve some project Euler problems. Yesterday, I wrote some code to solve one of these problems (14). When I write code containing long loops I always test the code by running it with short loops. If it runs fine and it does what it's supposed to do I assume this will also be the case when the length of the loop is longer.
This assumption turned out to be wrong. While executing the code below, MATLAB ran out of memory somewhere around the 75000th iteration.
c=1;
e=1000000;
for s=c:e
n=s;
t=1;
while n>1
a(s,t)=n;
if mod(n,2) == 0
n=n/2;
else
n=3*n+1;
end
a(s,t+1)=n;
t=t+1;
end
end
What can I do to prevent this from happening? Do I need to clear variables or free up memory somewhere in the process? Will saving the resulting matrix a to the hard drive help?
Here is the solution, staying as close as possible to your code (which is very close, the main difference is that you only need a 1D matrix):
c=1;
e=1000000;
a=zeros(e,1);
for s=c:e
n=s;
t=1;
while n>1
if mod(n,2) == 0
n=n/2;
else
n=3*n+1;
end
t=t+1;
end
a(s)=t;
end
[f g]=max(a);
This takes a few seconds (note the preallocation), and the result g unlocks the Euler 14 door.
Simply put, there's not enough memory to hold the matrix a.
Why are you making a two-dimensional matrix here anyway? You're storing information that you can compute just as fast as looking it up.
There's a much better thing to memoize here.
EDIT: Looking again, you're not even using the stuff you put in that matrix! Why are you bothering to create it?
The code appears to be storing every sequence in a different row of a matrix. The number of columns of that matrix will be equal to the length of the longest sequence currently found. This means that a sequence of two numbers will be padded with a bunch of right hand zeros.
I am sure you can see how this is incredibly inefficient. That may be the point of the exercise, or it will be for you in this implementation.
Better is to keep a variable like "Seed of longest solution found" which would store the seed for the longest solution. I would also keep a "length of longest solution found" keep the length. As you try every new seed, if it wins the title of longest, then update those variables.
This will keep only what you need in memory.
Short Answer:Use a 2d sparse matrix instead.
Long Answer: http://www.mathworks.com/access/helpdesk/help/techdoc/ref/sparse.html