I am trying to write a function in MATLAB that takes 1x3 vectors as input. My code looks something like this:
function myFunction=([x1, x2, x3], [y1, y2, y3], [z1, z2, z3])
where all inputs are numbers, and then in the body of the function I perform some calculations indexing through the numerical values in the vectors. i want the vectors to be user input, so the user will enter the vectors and their components (x1, x2, etc.) into the function argument. However, I am getting an error saying "Invalid expression. When calling a function or indexing a variable, use parentheses. Otherwise, check for mismatched delimiters." Therefore I believe I either have the syntax or something else wrong. I know MATLAB is supposed to be able to take vector input in functions, so please let me know what I am doing wrong. Thanks!
What you need to do is declare your function like this:
function myFunction(x,y,z)
% your function code here
end
Then within your function you can access the individual elements of the vectors using x(1), y(2), etc.
To call the function, including whatever number you like, you can enter on the Matlab command window (for example),
myFunction([1 2 3],[4 5 6],[7 8 9]) and the code in your function will be called with the x variable set to the vector [1,2,3], the y variable set to [4,5,6] and z to [7,8,9]. The use of commas to delineate values is optional. If your function then accesses y(2) it will get the second value of the y vector which will be 5 - it is important to note that indexing in Matlab is 1-based so the 1st element of x is obtained with x(1).
If you need to return values you can use:
function [a,b,c] = myFunction(x,y,z)
Then just assign the a, b or c in your code before the end statement.
See the offical Matlab documentation for more info.
I would add that much of the advantage of matlab is dealing with data in a vectorised form, so if you can avoid splitting out into separate elements I would do so. For example, if you need to add two vecors, you could do z = [x(1)+y(1), x(2)+y(2), x(3)+y(3)], but much better (more readable, more maintainable, faster) is z=x+y.
Related
Matlab plot requires the data to be of the same dimension. Meaning, you cannot plot a 1x10 vector with a 1x1x10 vector. This is sometimes necessary. For those purposes, you can use the squeeze function to get rid of the singleton dimensions.
However, this is kind of a hassle. For the plot function specifically, it would be useful to have the argument always squeezed. How would one go about creating a new function, lets call it splot which squeezes every input and passes it onto plot. Here is an attempt (that doesn't work)
function splot(varargin)
for i=1:length(varargin)
varargin{i}=squeeze(varargin{i});
end
plot(varargin)
end
plot(varargin) part fails, because that is simply not how matlab syntax works. But is there any way to achieve what I want? I guess I could write a long if elseif chain where I manually write the case with every possible number of input arguments like:
if length(varargin)==2
plot(varargin{1},varargin{2})
if length(varargin)==3
plot(varargin{1},varargin{2},varargin{3})
But this is going to be very annoying. Any better ideas.
This question is similar to Is there any mechanism to auto squeeze in Matlab / Octave , however, not similar enough, because the other question is for squeezing every vector, which is a bad idea. Here I am asking a way to squeeze only the inputs to the plot function and requiring syntax help.
From the docs there are several ways to call plot. Generally
Just numeric arrays, these can be on their own, or one or more pairs
plot(Y), plot(X,Y) or plot(X1,Y1,...,Xn,Yn)
Numeric arrays as before, with a char array giving the line spec
plot(X,Y,LineSpec) or plot(Y,LineSpec)
Either of the previous two, plus name-value pair options
plot(___,Name,Value)
In any of these cases, you want to squeeze the first N inputs which are numeric, since either of the optional additions have the first non-plottable input as a char.
We can achieve that with the following code, see the comments for details:
function h = splot( varargin )
% Check if there are any optional inputs, which will either be
% LineSpec (which is a char) or name-value pairs (which the
% first of will be a char)
bNumericArg = cellfun( #isnumeric, varargin );
% By default, assume all inputs are arrays to plot
lastArrayArg = numel(varargin);
if ~all(bNumericArg)
% In this case, there are some optional inputs, get last array index
lastArrayArg = find( ~bNumericArg, 1 ) - 1;
end
% Squeeze the arrays
for ii = 1:lastArrayArg
varargin{ii} = squeeze(varargin{ii});
end
% Plot with all inputs, optional output
if nargout > 0
h = plot( varargin{:} );
else
plot( varargin{:} );
end
end
There are two possible cases I've not handled here which the plot function can handle,
Having the first input as the target axes i.e. plot(ax,___), could be achieved by altering the loop slightly to start from 1 or 2 depending if the first input is an axes object
Having pairs of arrays each with their own line spec argument i.e. plot(X1,Y1,LineSpec1,...,Xn,Yn,LineSpecn). The later pairs will be ignored. This would be trickier to handle since you'd likely have to parse all inputs and check whether a char is just a line spec or if you're messing with name-value pairs. Maybe a heuristic to do with "two arrays then a char, repeated". I've never used this syntax so omitting the over-complication for now.
I'm trying to vectorize one function in Matlab, but I have a problem with assigning values.
function [val] = clenshaw(coeffs,x)
b=zeros(1,length(coeffs)+2);
for k=length(coeffs):-1:2
b(k)=coeffs(k)-b(k+2)+2*b(k+1).*x;
end
val=coeffs(1)-b(3)+b(2).*x;
The purpose of this function is to use Clenshaw's algorithm to compute a value of one polynomial with coefficients "coeffs" at point x.
It work fine when x is a single value, but I'd like it to work with vector of arguments too.
When I try to pass a vector I get an error:
Unable to perform assignment because the left
and right sides have a different number of
elements.
Error in clenshaw (line 7)
b(k)=coeffs(k)-b(k+2)+2*b(k+1).*x;
I understand that there is a problem, because I'm trying to assign vector to a scalar variable b(k).
I tried making b a matrix instead of a vector, however I still cannot get the return output I'd like to have which would be a vector of values of this function at points from vector x.
Thank you for helping and sorry if something isn't entirely clear, because English is not my native language.
The vectorized version of your function looks like this:
function [val] = clenshaw(coeffs,x)
b=zeros(length(x),length(coeffs)+2);
for k=length(coeffs):-1:2
b(:,k)=coeffs(k)-b(:,k+2)+2*b(:,k+1).*transpose(x);
end
val=coeffs(1)-b(:,3)+b(:,2).*transpose(x);
end
b needs to be a matrix. In your loop, you have to perform every operation per row of b. So you need to write b(:,k) instead of b(k). Since b(:,k) is a vector and not a scalar, you also have to be careful with the dimensions when using the .* operator. To get the correct results, you need to transpose x. The same goes for the calculation of val. If you don't like the transposition, just swap the rows and cols of b and you get this:
function [val] = clenshaw(coeffs,x)
b=zeros(length(coeffs)+2, length(x));
for k=length(coeffs):-1:2
b(k,:)=coeffs(k)-b(k+2,:)+2*b(k+1,:).*x;
end
val=coeffs(1)-b(3,:)+b(2,:).*x;
end
However, the first version returns a column vector and the second a row vector. So you might need to transpose the result if the vector type is important.
I am going to solve an inverse problem, AX=b, using conjugate gradient method in MATLAB. I want to use pcg function in MATLAB and as I know instead of matrix A I can use a function.
I have a function for example afun which has some entries. In the documents, I have seen that the afun function is entered in pcg function without entries, however, when I do the same, the error not enough input arguments appears. I use a code like this:
b = afun(ent1,ent2);
x = pcg(#afun,b,tol,max_iter);
How should I use my function in pcg?
According to the documentation, the function handle should the have the signature afun(x) and return A*x.
Your function apparently takes two inputs... You need to use a anonymous function to wrap the call, something like this:
% I dont know what these ent1/ent2 represent exactly,
% so you must complete the ".." part first
fcn = #(x) afun(x, ..)
% now you can call PCG
x = pcg(fcn, b, tol, maxiter);
There is a doc page explaining how to parameterize functions to pass extra args using function handles.
Good evening everyone,
I want to create a function
f(x) = [f1(x), f2(x), ... , fn(x)]
in MatLab, with an arbitrary form and number for the fi. In my current case they are meant to be basis elements for a finite-dimensional function space, so for example a number of multi variable polynomials. I want to able to be able to set form (e.g. hermite/lagrange polynomials, ...) and number via arguments in some sort of "function creating" function, so I would like to solve this for arbitrary functions fi.
Assume for now that the fi are fi:R^d -> R, so vector input to scalar output. This means the result from f should be a n-dim vector containing the output of all n functions. The number of functions n could be fairly large, as there is permutation involved. I also need to evaluate the resulting function very often, so I hope to do it as efficiently as possible.
Currently I see two ways to do this:
Create a cell with each fi using a loop, using something like
funcell{i}=matlabFunction(createpoly(degree, x),'vars',{x})
and one of the functions from the symbolic toolbox and a symbolic x (vector). It is then possible to create the desired function with cellfun, e.g.
f=#(x) cellfun(#(v) v(x), funcell)
This is relatively short, easy and what can be found when doing searches. It even allows extension to vector output using 'UniformOutput',false and cell2mat. On the downside it is very inefficient, first during creation because of matlabFunction and then during evaluation because of cellfun.
The other idea I had is to create a string and use eval. One way to do this would be
stringcell{i}=[char(createpoly(degree, x)),';']
and then use strjoin. In theory this should yield an efficient function. There are two problems however. The first is the use of eval (mostly on principle), the second is inserting the correct arguments. The symbolic toolbox does not allow symbols of the form x(i), so the resulting string will not contain them either. The only remedy I have so far is some sort of string replacement on the xi that are allowed, but this is also far from elegant.
So I do have ways to do what I need right now, but I would appreciate any ideas for a better solution.
From my understanding of the problem, you could do the straightforward:
Initialization step:
my_fns = cell(n, 1); %where n is number of functions
my_fns{1} = #f1; % Assuming f1 is defined in f1.m etc...
my_fns{2} = #f2;
Evaluation at x:
z = zeros(n, 1);
for i=1:n,
z(i) = my_fns{i}(x)
end
For example if you put it in my_evaluate.m:
function z = my_evaluate(my_fns, x)
z = zeros(n, 1);
for i=1:n,
z(i) = my_fns{i}(x)
end
How might this possibly be sped up?
Depends on if you have special structure than can be exploited.
Are there calculations common to some subset of f1 through fn that need not be repeated with each function call? Eg. if the common calculation step is costly, you could do y = f_helper(x) and z(i) = fi(x, y).
Can the functions f1...fn be vector / matrix friendly, allowing evaluation of multiple points with each function call?
The big issue is how fast your function calls f1 through fn are, not how you collect the results from those calls in a vector.
I am trying to understand the following commands of a MATLAB script :
global operatorObj
calcEVR_handles = operatorObj.calcEVR_handles;
m = operatorObj.nInputs
E = zeros(m,1);
V = zeros(m,1);
R = zeros(m,m);
for i=1:m
[E(i), V(i), R(i,i)] = calcEVR_handles{i}(t,x);
end
What can calcEVR_handles be, if t is a float and x is a vector?
calcEVR_handles (to me) looks like a cell array where each element is a handle to a function. Each element in calcEVR_handles is an anonymous function that takes in a single value t and a single vector x. As such, by doing calcEVR_handles{i}, you would access the corresponding function stored at the ith element in the cell array. Once you have access, you then pass your parameters to this function and it gives you those three outputs.
To show you an example of this working, consider the following cell array that works similarly to calcEVR_handles.
calcCellFunc = {#sin, #cos, #tan};
This is a three element cell array, where each element is a handle to a function. The # is a special character in MATLAB that denotes that you are creating a handle to a function. It's also used to create anonymous functions, but let's shelve that for this answer. You can read more about it here if you want to delve into more detail regarding this.
Back to our cell array of handles, we will make handles for sin, cos and tan. You can then iterate over your cell array by accessing the function you want by calcCellFunc{idx} where idx is the element you want in the cell array. This will ultimately give you the function stored at index idx. Once you do that, you can then call the function and specify whatever inputs you want (or none if it doesn't take any inputs). Here's a quick example for you. Let's create a random 5 x 5 matrix, and run through each function with this matrix serving as the input. We then take each of these outputs and store them into a corresponding slot in an output cell array. As such:
rng(123); %// Set seed for reproducibility
M = rand(5);
calcCellFunc = {#sin, #cos, #tan};
out = cell(1, numel(calcCellFunc)); %// To store the results for each function
for idx = 1 : numel(calcCellFunc)
out{idx} = calcCellFunc{idx}(M); %// Get the function, then pass
%// the matrix M to it
end
If you want to make things clear, you could split up the out statement to this instead:
func = calcCellFunc{idx}; %// Get access to the function
out{idx} = func(M); %// Pass M to this function
If you're new to handles / anonymous functions, you should probably use the above code first to make it explicitly clear on what MATLAB is doing. You are first getting access to the function you want that is stored in the cell array, and then you pass your arguments to this function.
If we display the output, we get:
>> celldisp(out)
out{1} =
0.6415 0.4106 0.3365 0.6728 0.5927
0.2823 0.8309 0.6662 0.1815 0.7509
0.2249 0.6325 0.4246 0.1746 0.6627
0.5238 0.4626 0.0596 0.5069 0.5737
0.6590 0.3821 0.3876 0.5071 0.6612
out{2} =
0.7671 0.9118 0.9417 0.7398 0.8054
0.9593 0.5564 0.7458 0.9834 0.6604
0.9744 0.7745 0.9054 0.9846 0.7489
0.8518 0.8866 0.9982 0.8620 0.8191
0.7522 0.9241 0.9218 0.8619 0.7502
out{3} =
0.8363 0.4503 0.3573 0.9094 0.7359
0.2942 1.4934 0.8932 0.1845 1.1370
0.2308 0.8167 0.4690 0.1773 0.8850
0.6149 0.5218 0.0597 0.5880 0.7004
0.8761 0.4135 0.4205 0.5884 0.8814
The first element of the output cell array has the output when you pass M to sin, the second when you pass M to cos, and the third when you pass M to tan.
So the next question you're asking... why is this useful?
Point #1 - Nix the copying and pasting
This kind of code writing is very useful because if you want to use the same inputs and supply them to many different functions, we would naturally be inclined to do some copying and pasting. Take each of your function names, and create a single line for each. Each line would call the corresponding function you want, followed by the input arguments. This can become quite tedious, and so one smart way to do it would be to place your function name as a handle into a cell array, and to write one for loop that goes over all of the functions dynamically. You could even explore cellfun and escape using the for loop to iterate over all of the function handles too, but I'll leave that for you to read up on.
In this way, you have very maintainable code and if you want to remove functions that don't need to be run, just remove the handles from the cell array rather than scrolling down to where the line that invokes this function is located and removing that.
This is actually a very common technique in computer science / software engineering in general. In fact, this is actually quite close to what are known as function pointers. This is MATLAB's cheap way of doing it, but the logic behind this is essentially the same.
Point #2 - Higher Order Functions
Another way this is useful is if you have a function where one (or more than one!) of the inputs is a function, and you also specify inputs into this function as additional parameters to this function. This is what is known as a higher order function. The outputs would be based on using this input function, and the additional inputs you specify to it and the outputs are based on using this input function and the inputs you specify for this function.
One very good example is the fzero function in MATLAB. The goal is to find the root of a non-linear function, and the first parameter is a handle to a function that you specify. The base behaviour behind how fzero works is the same no matter what the function is. All you have to do is specify the function you want to solve and the initial guess of where you think this root is.
All in all, anonymous functions are very useful.