To process data in MATLAB I have to execute a certain function, let's call it function(). Since there is much data to be processed, like large array Time or Voltage (but many more) I execute those one by one like this:
TimeNew = function(Time);
VoltageNew = function(Voltage);
... etc
So this is done around 10 times. Moreover, I have to do such a thing multiple times, resulting in around 30 lines of code which all do the same thing but to a different variable.
Is there a way to optimize this? I am using the most recent version of MATLAB (2015b) and have all toolboxes installed.
A possible solution could be to store the input array into a struct, them use that struct as input of the function.
In the function you can identify the number and content of each field by using fieldnames and getfiled built-in function.
The function could return a structure as output whose names can be made the same as the ones of the input struct.
In the example below, three arrays are generated and the function siply compute their square.
var_1=1:10;
var_2=11:20;
var_3=21:30;
str_in=struct('var_1',var_1,'var_2',var_2,'var_3',var_3)
str_out=my_function(str_in)
The function
function [str_out]=my_function(str_in)
f_names=fieldnames(str_in)
n_fields=length(f_names);
for i=1:n_fields
x=getfield(str_in,f_names{i})
str_out.(f_names{i})=x.^2;
end
Hope this helps.
Qapla'
You could try cellfun
allResultsAsACell = cellfun(#function, {Time,Voltage,...,varN});
This is equivalent to
allResultsAsACell{1} = function(Time);
allResultsAsACell{2} = function(Voltage);
...
allResultsAsACell{N} = function{VarN};
The issue is just matching up the indices with the values. I'm sure you could code those in as well if you needed (e.g. timeInd = 1; voltageInd =2; ...)
To see more on the cellfun method, type
help cellfun
into your MATLAB terminal.
Related
Suppose we have an 3-D array (tensor) and we want to apply in each slice a function, e.g., myFun = #(x)mean(x). Is there any way to do this without for loop using build-in functions (possibly withbsxfun, or arrayfun, or accumarray)?
For loop example:
inputA = rand(10,5,20);
for sl = 1:size(A,3)
inputB = myFun(inputA(:,:,sl));
end
Thank you.
EDIT:
inputB = arrayfun(#(iterSlice) myFun(inputA(:,:,iterSlice), 1:size(inputA,3))
PS: I would like to mention, that the handler function applied is more complicated in each slice, mean was an example included in the handler function.
A for loop is already the best possibility to iterate. The only way to further improve the performance is to get rid of the iteration and have a single function call of myFun which processes all data in a vectorized way. For your example function that very simple:
myFun=#(x)permute(mean(x,1),[3,2,1])
Now it accepts 3d inputs and in the rows you find the results of the previous iterative code. You have to modify your function, there is no generic wrapper on top which can do this for you.
Regarding your edit: arrayfun is known to be slow
I am a beginner in Matlab and have not been able to find an answer to my question so far. Your help will definitely be very much appreciated.
I have 70 matrices (100x100), named SUBJ_1, SUBJ_2 etc. I would like to create a loop so that I would calculate some metrics (i.e. max and min values) for each matrix, and save the output in a 70x2 result matrix (where each row would correspond to the consecutively named SUBJ_ matrix).
I am struggling with both stages - how to use the names of individual variables in a 'for' loop and how to properly save individual outputs in a combined array.
Many thanks and all the best!
Don't use such variable names, create a big cell array named SUBJ and put each Matrix in it.
r=zeros(numel(SUBJ),2)
for idx=1:numel(SUBJ)
r(idx,1)=min(min(SUBJ{idx}))
r(idx,2)=max(max(SUBJ{idx}))
end
min and max are called twice because first call creates maximum among rows, second call among columns.
Even though this is in principle possible in Matlab, I would not recommend it: too slow and cumbersome to implement.
You could instead use a 3-D matrix (100x100x70) SUBJ which would contain all the SUBJ_1 etc. in one matrix. This would allow you to calculate min/max etc. with just one line of code. Matlab will take care of the loops internally:
OUTPUT(:,1) = min(min(SUBJ,[],1)[],2);
OUTPUT(:,2) = max(max(SUBJ,[],1)[],2);
Like this, OUTPUT(1,1) contains min(min(SUBJ(:,:,1))) and so on...
As to how to use the names of individual variables in a 'for' loop, here gives an example:
SUBJ = [];
for idx = 1:70
term = eval(['SUBJ_',num2str(idx)]);
SUBJ = [SUBJ; max(max(term)),min(min(term))];
end
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.
When using a multiple-output matlab function, do i need to callback all variables? or can I just take the first two variables? (if so..is it not recommended?)
lets say in function.m
[a, b, c] = function( )
in main.m
[var1, var2] = function;
When calling (almost) any function in matlab you can request fewer outputs than it specifies. So, yes the example you give should work perfectly fine.
There are some clever things you can do with this, such as using nargout within a function to see how many output arguments have been requested and only calculating the values that have been requested as an optimisation trick.
It depends on the definition of the function, and exactly which of the outputs you want to get.
Not all the function allow to do it, you can find all the options for each function in the beginning of the help documentation on the specific function.
If you want only the 2nd, or 3rd outputs, and you want also to save the computation-time of the results that does not interesting, you can use ~ option, like this (for versions 2009b and later):
[~, var1, var2]=function
Many functions allow for options to passed that change how the function behaves. I used/wrote various numerical solving functions a bit and one that nice amount of option, for instance is the LSMR function(s).
Otherwise, if you can manipulate the original either introduce an input(s) to do so before or at the end with an inline subroutine to generate the outputs you want.
Or if you can't it will return as either a cell array or a vector and you can pass an anonymous function to generate the desired outputs that way.
Really, can be done many ways. Very contextual.
I am trying to use MATLAB in order to generate a variable whose elements are either 0 or 1. I want to define this variable using some kind of concatenation (equivalent of Java string append) so that I can add as many 0's and 1's according to some upper limit.
I can only think of using a for loop to append values to an existing variable. Something like
variable=1;
for i=1:N
if ( i%2==0)
variable = variable.append('0')
else
variable = variable.append('1')
i=i+1;
end
Is there a better way to do this?
In MATLAB, you can almost always avoid a loop by treating arrays in a vectorized way.
The result of pseudo-code you provided can be obtained in a single line as:
variable = mod((1:N),2);
The above line generates a row vector [1,2,...,N] (with the code (1:N), use (1:N)' if you need a column vector) and the mod function (as most MATLAB functions) is applied to each element when it receives an array.
That's not valid Matlab code:
The % indicates the start of a comment, hence introducing a syntax error.
There is no append method (at least not for arrays).
Theres no need to increment the index in a for loop.
Aside of that it's a bad idea to have Matlab "grow" variables, as memory needs to be reallocated at each time, slowing it down considerably. The correct approach is:
variable=zeros(N,1);
for i=1:N
variable(i)=mod(i,2);
end
If you really do want to grow variables (some times it is inevitable) you can use this:
variable=[variable;1];
Use ; for appending rows, use , for appending columns (does the same as vertcat and horzcat). Use cat if you have more than 2 dimensions in your array.