I got an odd behaviour of my functions and since i'm not so used to matlab coding i guess is due to something really easy that i don't get.
I can't understand how this could print something different
fx(Punti(1,:),Punti(2,:))
fx(Punti(2,:),Punti(3,:))
fx(Punti(3,:),Punti(4,:))
fx(Punti(4,:),Punti(5,:))
from this
for i_unic=1:4
fx(Punti(i_unic,:),Punti(i_unic+1,:))
end
Consider fx as a generic function.
Is it possible that fx uses some variables that for some reason are erased at the end of each iteration?
EDIT
-->"Punti" is just matrix containing the points a SCARA robot should follow
-->fx is the function "Retta" and it's the following
function retta(PuntoA,PuntoB,Asse_A,q_ini,rot,contaerro,varargin)
global SCARA40
global inizio XX YY ZZ
global seg_Nsteps
npassi = seg_Nsteps;
ipuntofin = inizio + npassi;
for ipunto = inizio : ipuntofin
P4 = PuntoA + (ipunto-inizio)*(PuntoB-PuntoA)/npassi;
q = kineinversa(Asse_A,P4,q_ini,rot);
Mec = SCARA40.fkine(q);
Pec = Mec(:,4);
if (dot((P4-Pec),(P4-Pec),3)>0.0001)
fprintf(1,'\n P4 Desid. = [%9.1f %9.1f %9.1f %9.1f ] \n',P4);
fprintf(1,'\n P4 Attuato = [%9.1f %9.1f %9.1f %9.1f ] \n',Pec);
contaerro = contaerro + 1;
else
q_ini = q;
end
SCARA40.plot(q);
XX(ipunto) = Pec(1);
YY(ipunto) = Pec(2);
ZZ(ipunto) = Pec(3);
if(nargin>6)
color = varargin{1};
else
color = 'r';
end
plot3(XX,YY,ZZ,color,'LineWidth',1 );
drawnow;
hold on
end
end
the test function with the results
Punti = [ 10,10,0,1 ;10,-10,0,1 ;-10,-10,0,1 ; -10,10,0,1 ] ;
%inizio=1
%retta(Punti(1,:)',Punti(2,:)',Asse_A,q_ini,rot,contaerro)
%inizio=21
%retta(Punti(2,:)',Punti(3,:)',Asse_A,q_ini,rot,contaerro)
%inizio=41
%retta(Punti(3,:)',Punti(4,:)',Asse_A,q_ini,rot,contaerro)
%inizio=61
inizio=1
for i=1:length(Punti)-1
retta(Punti(i,:)',Punti(i+1,:)',Asse_A,q_ini,rot,contaerro)
inizio=inizio+20;
end
the two images have been generated restarting Matlab
Addressing the question in the most general sense (since there is no sample given for the function fx or the function/variable Punti) then the reason you are getting different results is likely that the state of your variables/workspace is different when you test one case versus the other. How could this happen? Here are some obvious ways...
Your functions (or possibly other functions they call) are making use of the random number generator, and the starting state of the RNG is different when you test the loop versus unrolled loop case.
Your functions are sharing global variables that aren't reset to some default value at the start of each test case. You mention in a comment that the functions use global variables, so this is likely your problem.
Your functions aren't really functions, but scripts. Scripts all share a common workspace (the base workspace), whereas a function (and specifically each call to a function) will have its own unique workspace. If fx is actually a script, each call may change any or all of the variables in the base workspace. Furthermore, any other scripts, or anything you type into the command line, can change things as well. The contents of the base workspace may therefore be different when you test the loop versus unrolled loop case.
If I were to hazard a guess, I'd say that if you were to exit and restart MATLAB before each test case (i.e. reset everything to the same default starting state) you would probably get the same exact result for the loop versus unrolled loop case.
Related
I have a segment of code where a composition of nested loops needs to be run at various times; however, each time the operations within the nested loops are different. Is there a way to make the outer portion (loop composition) somehow a functional piece, so that the internal operations are variable. For example, below, two code blocks are shown which both use the same loop introduction, but have different purposes. According to the principle of DRY, how can I improve this, so as not to need to repeat myself each time a similar loop needs to be used?
% BLOCK 1
for a = 0:max(aVec)
for p = find(aVec'==a)
iDval = iDauVec{p};
switch numel(iDval)
case 2
r = rEqVec(iDval);
qVec(iDval(1)) = qVec(p) * (r(2)^0.5 / (r(1)^0.5 + r(2)^0.5));
qVec(iDval(2)) = qVec(p) - qVec(iDval(1));
case 1
qVec(iDval) = qVec(p);
end
end
end
% BLOCK 2
for gen = 0:max(genVec)-1
for p = find(genVec'==gen)
iDval = iDauVec{p};
QinitVec(iDval) = QinitVec(p)/numel(iDval);
end
end
You can write your loop structure as a function, which takes a function handle as one of its inputs. Within the loop structure, you can call this function to carry out your operation.
It looks as if the code inside the loop needs the values of p and iDval, and needs to assign to different elements of a vector variable in the workspace. In that case a suitable function definition might be something like this:
function vec = applyFunctionInLoop(aVec, vec, iDauVec, funcToApply)
for a = 0:max(aVec)
for p = find(aVec'==a)
iDval = iDauVec{p};
vec = funcToApply(vec, iDval, p);
end
end
end
You would need to put the code for each different operation you want to carry out in this way into a function with suitable input and output arguments:
function qvec = myFunc1(qVec, iDval, p)
switch numel(iDval)
case 2
r = rEqVec(iDval); % see note
qVec(iDval(1)) = qVec(p) * (r(2)^0.5 / (r(1)^0.5 + r(2)^0.5));
qVec(iDval(2)) = qVec(p) - qVec(iDval(1));
case 1
qVec(iDval) = qVec(p);
end
end
function v = myFunc2(v, ix, q)
v(ix) = v(q)/numel(ix);
end
Now you can use your loop structure to apply each function:
qvec = applyFunctionInLoop(aVec, qVec, iDauVec, myFunc1);
QinitVec = applyFunctionInLoop(aVec, QinitVec, iDauVec, myFunc2);
and so on.
In most of the answer I've kept to the same variable names you used in your question, but in the definition of myFunc2 I've changed the names to emphasise that these variables are local to the function definition - the function is not operating on the variables you passed in to it, but on the values of those variables, which is why we have to pass the final value of the vector out again.
Note that if you want to use the values of other variables in your functions, such as rEqVec in myFunc1, you need to think about whether those variables will be available in the function's workspace. I recommend reading these help pages on the Mathworks site:
Share Data Between Workspaces
Dynamic Function Creation with Anonymous and Nested Functions
Let's say I have a simulation set up in Simulink, which consists of three blocks: Input (From Workspace block), model calculation (S-function block) and results (Outport).
In my class, I do a lot of preprocessing on the input data, which is not shown here. Then, I point the Input block to use the inputArray, which is a property of my class.
classdef SimulationClass < handle
%SimulationClass Simulate process using model
properties
inputArray double = ones(101, 11)
modelFilename char
simOpts struct
simulationTime double
simulationResultsArray double
end
methods
function obj = SimulationClass(simulationTime)
obj.simulationTime = simulationTime;
end
function prepareSimulation(obj, modelFilename)
obj.modelFilename = modelFilename;
open_system(obj.modelFilename);
set_param([obj.modelFilename '/fromWorkspaceBlock'],...
'VariableName', 'obj.inputArray');
obj.simOpts = simset('SrcWorkspace', 'current');
end
function runSimulation(obj)
[~, ~, obj.simulationResultsArray] = sim(obj.modelFilename,...
obj.simulationTime, obj.simOpts);
end
end
end
I can easily start the simulation run from the command prompt.
mySim = SimulationClass(1:10);
mySim.prepareSimulation('mySimulinkSheet');
mySim.runSimulation;
But, if I play around with some settings (e.g., different solvers) and press Run in Simulink, it doesn't work, since the data is not in the base workspace. I.e., I lose the interactivity with Simulink.
Any ideas on how to resolve this issue? The only workaround I have figured out so far would be to write an additional method (like writePropertiesToBaseWorkspace) which would convert the classes properties into variables, using assignin().
We have a script that defines values to names similar to #define in c. For example:
script.m:
ERR_NOERROR = 0;
ERR_FATAL = 1;
This script already exists and is used for value replacement when reading data from files.
Now we have a function (or more) that does some analysis and we would like to use the same definition in this function to avoid magic numbers. But when the script is called from the function we get an error.
Attempt to add "ERR_NOERROR" to a static workspace.
See MATLAB Programming, Restrictions on Assigning to Variables for details.
And this does not help much in the understanding of the problem.
The question is how can we make these definitions visible/usable in the functions with having to copying it every time.
Example:
function foo = bar(a)
run(script.m) %also tried running it without the run command
if a == ERR_NOERROR
foo = 5;
else
foo = 6;
end
end
edit:
There was a nested function,below in the function which I was not aware of. This explains the problem.
This kind of scoping error happens when you use nested or anonymous function within a function. The solution is well documented.
To your case, you can avoid nested function, or "Convert the script to a function and pass the variable using arguments", as the documentation suggests.
EDIT: I should have made it clear that the error occurs even if the script is not called within the nested function. Similar scenario is that, in debug mode (by setting up a break point), it will be an error if one tries to create a temporal variable to test something.
This is not a direct answer, rather a recommendation to switch to another method, which will not be mixing scope and workspace.
Instead of defining your constant in a script, you could make a class containing only constant properties. ex: code for error_codes.m:
classdef error_codes
% ---------------------------------------------------------------------
% Constant error code definition
% ---------------------------------------------------------------------
properties (Constant = true)
noerror = 0 ;
fatal = 1 ;
errorlvl2 = 2 ;
errorlvl3 = 3 ;
warning = -1 ;
% etc ...
end
end
I use this style for many different type of constants. For tidiness, I groups them all in a Matlab package directory (The directories which starts with a + character.
The added benefit of using constant class properties is the safety that the values cannot be changed in the middle of the code (your variables defined in a script could easily be overwritten by a careless user).
So assuming my file error_codes.m is placed in a folder:
\...somepath...\+Constants\error_codes.m
and of course the folder +Constants is on the MATLAB path, then to use it as in your example, instead of calling the script, just initialise an instance of the class, then use the constant values when you need them:
function foo = bar(a)
ERR = Constants.error_codes ;
if a == ERR.noerror
foo = 5;
else
foo = 6;
end
or it can works in switch statement too:
switch a
case ERR.noerror
foo = 5 ;
case ERR.warning
foo = 42 ;
case ERR.fatal
foo = [] ;
end
function [ muln, varargout ] = my_mul( varargin )
%MY_MUL This function is used to multiply numbers.
% My_mul function multiplies array of entered numbers, and outputs single
% solution.
% For example: my_mul(12, 2, 3, 5) gives ans = 360
if nargout >=1
disp('Error, wrong number of output arguments');
varargout{1} = 0;
return
end
if nargin <= 1
disp('Error, small number of input argumnets');
return
else
muln = 1;
for i = 1:nargin
muln = muln*varargin{i};
end
end
end
Hi, everyone, I'm just doing my assignment for uni and have a qiuck question.
How can I make this function to give an error if it is called with more than one output.(It meant to give only one) Thanks!
In your function definition, you have defined your function to allow for an unlimited number of outputs. The keyword varargout is a place-holder for a variable number of outputs.
As you have stated in your question, you only want one possible output which in your case looks to be muln. So if you simply remove varargout from your function definition, MATLAB should automatically throw an error if too many outputs are requested
function muln = my_mul(varargin)
If you ever do need to use varargout but want to place constraints on how many outputs are provided for any given scenario, you can check the number of output arguments that were requested using nargout and then throw an error with the error function.
if nargout > 4
error('my_mul:TooManyOutputs', 'Too many outputs requested');
end
My opinion is that if a return value is expected the function needs to throw. Otherwise the caller (function calling this function) will expect everything to be ok. Note that disp('Error') gives information to the developer, but it does not give the program any indication on what happens. More importantly, the information does not give any indication of where the error occurs. This can force the developer to do heavy debugging just to find the error, which is completely unnecessary.
The use of variable output arguments should only be used in case a different number of output arguments should be expected. An example is some customized plot function
function varargout = myplot(varargin)
filename = '';
idx = find(strcmp(varargin,'filename'));
if (~isempty(idx) && length(varargin)<idx+1 && ~ischar(varargin{idx+1}))
error('filename property must be followed by a directory');
elseif(~isempty(idx))
filename = varargin{idx+1};
varargin([idx,idx+1]) = [];
end
h = plot(varargin{:});
varagout{1} = h;
if (~isempty(idx))
save(filename, h);
end
varagout{2} = filename;
This function works as plot except it saves the figure to file in case a filename is specified. In case the developer needs the handle it will be returned and in case the developer wants the save directory it can be returned as well. None of these arguments are necessary though. The developer may want to use this function as a standard plot function and this means that the user may want to call myplot as myplot(x,y);which does not return a value. Further note that even if 'filename' is not specified, the function can still return 2 outputs. The second output may be an empty array of char, but two outputs for the caller will never cause a crash.
Also, note that no further error handling is required. The only unchecked crashes are in plot and save. How this is handled may be different for different users and this means that it only is reasonable to let the user catch the error and handle it (as he would have done if save or plot would have thrown).
Apart from this you may also want to have a check so that the number of output variables are within the correct range (in this case 0,1 or 2 outputs).
Suppose the matrix is A which is in a m file new1.m . Now I want to access this matrix to another m file new2.m . How can it be done ?
Your question is a little nonspecific, but I'll try to answer.
There are several ways to do this,
Assuming that you have a m-file (script) named 'new1' with (for example) A = rand(4) in it. You could just run it in new2.m before you want to use A
new1;
B = 2*A;
Note that new1 will return all the other variables assigned in it, flooding your workspace. Perhaps not a problem, but if so, you could just clear them with
clear var1 var2 var2 etc.
Another way is to make new1 into a function and return (only) A
function A = new1()
but I'm guessing that might ruin some other purposes of new1.
In that case you could return A only if the function is called with a special input argument (for example 'getA')
function new1(varargin)
...
... % some code
...
if nargin && strcmp(varargin{1},'getA')
assignin('caller','A',A);
end
And so from new2, just call the function.
new1('getA');