When trying to compute this sequence I get an error
syms n
limit(((-3)^n)/factorial(n),inf)
Error using factorial (line 17)
N must be a matrix of non-negative integers.
Error in (line 9)
How do you fix this or specify the matrix they want?
The factorial function wasn't designed for use of symbolic references, and often chokes on them. It might work if you have a new enough version (2012b claims it works), but I don't think it'll necessarily work with older versions, I've found some documents claiming it won't in fact. The following two methods have been suggested to work around the problem.
limit((-3)^n/sym('n!'),n,inf)
limit((-3)^n/gamma(n+1),n,inf)
Related
I am trying to run code similar to the following, I replaced the function I had with one much smaller, to provide a minimum working example:
clear
syms k m
n=2;
symsum(symsum(k*m,m,0,min(k,n-k)),k,0,n)
I receive the following error message:
"Error using sym/min (line 86)
Input arguments must be convertible to floating-point numbers."
I think this means that the min function cannot be used with symbolic arguments. However, I was hoping that MATLAB would be substituting in actual numbers through its iterations of k=0:n.
Is there a way to get this to work? Any help much appreciated. So far I the most relevant page I found was here, but I am somewhat hesitant as I find it difficult to understand what this function does.
EDIT following #horchler, I messed around putting it in various places to try and make it work, and this one did:
clear
syms k m
n=2;
symsum(symsum(k*m,m,0,feval(symengine, 'min', k,n-k)),k,0,n)
Because I do not really understand this feval function, I was curious to whether there was a better, perhaps more commonly-used solution. Although it is a different function, there are many pieces online advising against the eval function, for example. I thought perhaps this one may also carry issues.
I agree that Matlab should be able to solve this as you expect, even though the documentation is clear that it won't.
Why the issue occurs
The problem is due the inner symbolic summation, and the min function itself, being evaluated first:
symsum(k*m,m,0,min(k,n-k))
In this case, the input arguments to sym/min are not "convertible to floating-point numbers" as k is a symbolic variable. It is only after you wrap the above in another symbolic summation that k becomes clearly defined and could conceivably be reduced to numbers, but the inner expression has already generated an error so it's too late.
I think that it's a poor choice for sym/min to return an error. Rather, it should just return itself. This is what the sym/int function does when it can't evaluate an integral symbolically or numerically. MuPAD (see below) and Mathematica 10 also do something like this as well for their min functions.
About the workaround
This directly calls a MuPAD's min function. Calling MuPAD functions from Matlab is discussed in more detail in this article from The MathWorks.
If you like, you can wrap it in a function or an anonymous function to make calling it cleaner, e.g.:
symmin = #(x,y)feval(symengine,'min',x,y);
Then, you code would simply be:
syms k m
n = 2;
symsum(symsum(k*m,m,0,symmin(k,n-k)),k,0,n)
If you look at the code for sym/min in the Symbolic Math toolbox (type edit sym/min in your Command Window), you'll see that it's based on a different function: symobj::maxmin. I don't know why it doesn't just call MuPAD's min, other than performance reasons perhaps. You might consider filing a service request with The MathWorks to ask about this issue.
I've just updated to Matlab 2014a finally. I have loads of scripts that use the Symbolic Math Toolbox that used to work fine, but now hit the following error:
Error using mupadmex
Error in MuPAD command: Division by zero. [_power]
Evaluating: symobj::trysubs
I can't post my actual code here, but here is a simplified example:
syms f x y
f = x/y
results = double(subs(f, {'x','y'}, {1:10,-4:5}))
In my actual script I'm passing two 23x23 grids of values to a complicated function and I don't know in advance which of these values will result in the divide by zero. Everything I can find on Google just tells me not to attempt an evaluation that will result in the divide by zero. Not helpful! I used to get 'inf' (or 'NaN' - I can't specifically remember) for those it could not evaluate that I could easily filter for when I do the next steps on this data.
Does anyone know how to force Matlab 2014a back to that behaviour rather than throwing the error? Or am I doomed to running an older version of Matlab forever or going through the significant pain of changing my approach to this to avoid the divide by zero?
You could define a division which has the behaviour you want, this division function returns inf for division by zero:
mydiv=#(x,y)x/(dirac(y)+y)+dirac(y)
f = mydiv(x,y)
results = double(subs(f, {'x','y'}, {1:10,-4:5}))
I'm evaluating a series of theoretical (not necessarily functional) circuits in matlab. I have been trying to get the transfer function of the circuits and during the process I use the sym2poly function. Sometimes, sym2poly works and returns the transfer function. Sometimes it does not.
This is what the code looks like:
[n,d] = numden(eval(v_3/V));
transH = tf(sym2poly(n),sym2poly(d))
n and d are symbolic cell arrays. The error I get is:
Error using sym/sym2poly (line 28)
Not a polynomial.
Error in CircuitGA (line 349)
n = sym2poly(n);
This looks similar to several questions posted a long time ago, but all of those were solved by a bug fix in an updated version of the symbolic math toolbox. Does it mean that what I am giving it is impossible to turn into a polynomial?
Is there a fix?
Any suggestions of a method that will work for all my circuit arrays?
Maybe a try and catch for if it can return a transfer function?
I have to carry out the following operation
R=[0,0.5,-0.25;-0.25,0,0.25;0,0,0.25];
B=[0,k21,k31;k12,0,k32;0,0,k];
G=inv(R).*B;
g=det(G);
but Matlab is showing the following error
??? Error using ==> horzcat
CAT arguments dimensions are not consistent.
Error in ==> g at 60
B=[0,k21,k31;k12,0,k32;0,0,k];
K21,K31,K12,K32 and k all have dimensions of 923334 by 1. Can anyone help me how can I carry out the following operation.
Your code works well for me. Check that the k-values (k12,k31,k32...) are scalars (or 1x1 dimension)
EDIT :
For the case you mention, k's are nx1, one simple way is to perform a loop:
R=[0,0.5,-0.25;-0.25,0,0.25;0,0,0.25];
for ii=1:length(k)
B=[0,k21(ii),k31(ii);k12(ii),0,k32(ii);0,0,k(ii)];
G=inv(R).*B;
g(ii)=det(G);
end
There is also a "vectorized" way to do that, but it seems to be good enough...
I am working on a project that needs to use hidden markov models. I downloaded Kevin Murphy's toolbox. I have some problems about the usage. In the toolbox webpage, he says that first input of dhmm_em and dhmm_logprob are symbol sequence data. On their examples, they give row vectors as data. So, when I give my symbol sequence as row vector, I get error;
??? Error using ==> assert at 9
assertion violated:
Error in ==> fwdback at 105
assert(approxeq(sum(alpha(:,t)),1))
Error in ==> dhmm_logprob at 17
[alpha, beta, gamma, ll] = fwdback(prior,
transmat, obslik, 'fwd_only', 1);
Error in ==> mainCourseProject at 110
loglik(train_act) =
dhmm_logprob(orderedSymbols,
hmm{train_act}.prior,
hmm{train_act}.trans,
hmm{act}.emiss);
However, before giving this error, code works for some symbol vectors. When I give my data as column vector, functions work fine, no errors. So why exactly am I getting this error?
You might say that I should be giving not single vectors, but vector sets, I also tried to collect my feature vectors in a struct and give row vectors as such, but nothing changed, I still get assertion error.
By the way, my symbol sequence does not have any zeros, I am doing everything almost the same as they showed in their examples, so I would be greatful if anyone could help me please.
Im not sure, but from the function call stack shown above, shouldn't the last line be hmm{train_act}.emiss instead of hmm{act}.emiss.
In other words when you computing the log-probability of a sequence, you should pass components that belong to the same HMM model (transition matrix, emission matrix, and prior probabilities).
By the way, the ASSERT in the code is a sanity check that a vector of probabilities should sum to 1. Oftentimes, when working with very small values (log-probabilities), numerical stability issues can creep in... You could edit the APPROXEQ function to relax the comparison a bit, by giving it a bigger margin of error
This error message and the code it refers to are human-readable. An assertion is a guard put in by the programmer, to ensure that certain conditions are met. In this case, what is the condition? approxeq(sum(alpha(:,t)),1) I'd venture to say that approxeq wants the values to be approximately equal, so this boils down to: sum(alpha(:,t)) ~= 1
Without knowing anything about the code, I'd also guess that these refer to probabilities. The probabilities of a node's edges must sum to one. Hopefully this starts you down a productive debugging path. If you can't figure out what's wrong with your input that produces this condition, start wading into the code a bit to see where this alpha vector comes from, and how it ended up invalid.