I'm writing a function which have one value constant and others are derived in Matlab, I'm currently on that stage in which first argument is constant and others are derived,, but I want auto detection of constant and derived arguments.
Sample run is myfunc(7, #(b) -b,#(c) -c)
My function:
function p = myfunc(varargin)
a=varargin{1};
b=varargin{2};
c=varargin{3};
res = a-1;
p = [a b(a) c(a)];
end
What I wants is to input like myfunc(#(a) -a, 7,#(c) -c) or myfunc(#(a) -a, #(c) -c,7) are also possible.
You can see if a variable is an anonymous function using
isa(a,'function_handle')
or see if it is a number using
isa(a,'numeric')
so you could set up a switch or a series of if's based on what you get.
Related
I have code which is in multiple function files, input to these functions are stored in one file called inputfile.m(script file), in which I assigned some constant values to the inputs. These values act as a input to several function files named degree_eq.m(function file).
How I can write the code so that every time of execution, function files takes the required inputs from the inputfile.m.
Let's say you have two functions, one with your inputs (inputfile) and one where you do stuff (do_stuff).
function [a,b,c] = inputfile()
%define your constants
a=10;
b=100;
c=8.3;
function z = do_stuff()
[a, b, c] = inputfile() %takes the inputs from inputfile.m
z = a*c - b;
You can exploit the fact that matlab variables are persistent outside their scope. Lets say you have 6 constants a,b,c,d,e,f defined in input file. So what can be done is, write a top script called top.m which would be something like
inputfile
degree_eq1(a,b,c)
degree_eq2(c,d,e)
A third approach (combining Nirvedh Meshram and qbzenker answers) is to call an input script inside your MATLAB functions.
The advantage is that you do not have to specify which parameters are needed from or specified in your input script, but this is a disadvantage too, because the needed inputs are not made explicit. So, it is much more error prone. I only recommend this approach for a large number of input variables.
inputfile.m:
a = 5;
b = 8;
c = 10;
degree_eq.m:
function d = degree_eq()
inputfile;
d = a + b + c;
end
As an alternative, you can specify which input file to use:
degree_eq.m:
function d = degree_eq(inputFilename)
eval(inputFilename);
d = a + b + c;
end
and call it as follows:
degree_eq('inputfile');
I am trying to use this function in my m file but I get an error(mentioned in question). Everything seems correct and a, b and c are defined in my m file. Any thoughts?
Error:
Error in modal2 (line 8)
[v,an]=eig(a);
Output argument "am" (and maybe others) not assigned during call to "C:\Users\Cena\Desktop\Thesis\My Codes\SMC\modal2.m>modal2".
function [r,am,bm,cm] = modal2(a,b,c)
% this function determines the modal representation 2(am,bm,cm)
%given a generic state-space representation (a,b,c)
%and the transformation r to the modal representation
%such that am=inv(r)*a*r, bm=inv(r)*b and cm=c*r
%transformation to complex-diagonal form:
[v,an]=eig(a);
bn=inv(v)*b;
cn=c*v;
%transformation to modal form 2:
i = find(imag(diag(an))');
index = i(1:2:length(i));
j=sqrt(-1);
t = eye(length(an));
if isempty(index)
am=an;bm=bn;cm=cn;
else
for i=index
t(i:i+1,i:i+1)=[j 1;-j 1];
end
%Modal transformation
r=v*t;
end
The problem is likely in
if isempty(index)
am=an;bm=bn;cm=cn;
The assignment to those variables is only being done if the conditional passes. If it doesn't , there is no assignment.
You need to modify your code to assign to those variables under all conditions if they are going to be output arguments.
I have been using MATLAB fminunc function to solve my optimization problem. I want to try the minFunc package :
http://www.di.ens.fr/~mschmidt/Software/minFunc.html
When using fminunc, I defined a function funObj.m which gives me the objective value and the gradient at any point 'x'. It also takes in several external inputs say, {a,b,c} which are matrices. So the function prototype looks like :
function [objVal,G] = funObj(x,a,b,c)
I want to use the same setup in the minFunc package. From the examples, I figured this should work :
options.Method='lbfgs';
f = #(x)funObj(x,a,b,c);
x = minFunc(f,x_init,options);
But when I call this way, I get an error as:
Error using funObj
Too many output arguments.
What is the correct way to call minFunc for my case?
**EDIT : Alright, here is a sample function that I want to use with minFunc. Lets say I want to find the minimum of a*(b-x)^2, where a,b are scalar parameters and x being a scalar too. The MATLAB objective function will then look like :
function obj = testFunc(x,a,b)
obj = a*(b-x)^2;
The function call to minimize this using fminunc (in MATLAB ) is simply:
f = #(x)testFunc(x,a,b);
x = fminunc(f,x_init);
This gives me the minimum of x = 10. Now, How do I do the same using minFunc ?
"Note that by default minFunc assumes that the gradient is supplied, unless the 'numDiff' option is set to 1 (for forward-differencing) or 2 (for central-differencing)."
The error is because only one argument is returned by the function. You can either return the gradient as a second argument or turn on numerical differencing.
Agree with Mark. I think the simplest way to solve it is
minFunc(#testFunc, x_init, a, b, c)
In MATLAB temporary function can only have one return value. So f = #(x)testFunc(x,a,b); let your method drop gradient part every time. Because minFunc can accept extra paramters, you can pass a, b and c after x_init. I think this would work.
A lot of MATLAB functions have an input structure such as:
output = function MyFun(a,b,c,'-setting1',s1,'-setting2',s2,'-setting3',s3)
I am wondering how I should implement this kind of functionality in my own functions. To be precise, I would like to find out how I can create a function such that:
The function has a variable number of inputs N + M
The first N inputs are ordered and unlabeled. In the example above, N = 3. The first input is always a, second input is always b, third input is always c. The function input is variable in that users do not necessarily need to send b, c; when they do not then these can take on default (hardcoded) values. As far as I know, this type of functionality is generally handled via varargin.
The remaining M inputs are unordered, but labeled. In the example above, M = 3, the variables are s1,s2,s3 and their labels are setting1,setting2 and setting3 respectively, I would like for users to be able to specify these variables in whatever order they want. If users choose not to specify one of these inputs (i.e. setting1), then I would like my function to assign default values for s1.
One example of such a function is the dlmwrite function.
Ideally, I am looking for an approach that is typically used by MATLAB developers so that my code is easy to understand.
The InputParser class addresses all of these issues. You can specify any number of:
Required parameters (ordered, unlabeled)
Optional parameters (ordered, unlabeled)
String parameter-value pairs in any order (unordered, labeled)
A very clear tutorial with examples is provided by MathWorks. For a function defined as function printPhoto(filename,varargin), the example boils down to the following.
Create the inputParser:
p = inputParser;
Specify defaults and define validation criteria:
defaultFinish = 'glossy';
validFinishes = {'glossy','matte'};
checkFinish = #(x) any(validatestring(x,validFinishes));
defaultColor = 'RGB';
validColors = {'RGB','CMYK'};
checkColor = #(x) any(validatestring(x,validColors));
defaultWidth = 6;
defaultHeight = 4;
Define required/optional/parameter input names, set their default values and validation functions:
addRequired(p,'filename',#ischar);
addOptional(p,'finish',defaultFinish,checkFinish);
addOptional(p,'color',defaultColor,checkColor);
addParameter(p,'width',defaultWidth,#isnumeric);
addParameter(p,'height',defaultHeight,#isnumeric);
Parse the inputs into a struct:
parse(p,filename,varargin{:});
Then you have the input arguments and their values in p.Results.
The InputParser class is used throughout newer MathWorks functions, so don't be afraid to use it yourself!
Working on an assignment involving Genetic Algorithms (loads of headaches, loads of fun). I need to be able to test differing crossover methods and differing mutation methods, to compare their results (part of the paper I have to write for the course). As such, I want to just pass the function names into the Repopulate method, as function handles.
function newpop = Repopulate(population, crossOverMethod, mutationMethod)
...
child = crossOverMethod(parent1, parent2, #mutationMethod);
...
function child = crossOverMethod(parent1, parent2, mutationMethod)
...
if (mutateThisChild == true)
child = mutationMethod(child);
end
...
The key point here is like 3, parameter 3: how do I pass mutationMethod down another level? If I use the # symbol, I get told:
"mutationMethod" was previously used as a variable,
conflicting with its use here as the name of a function or command.
If I don't use the # symbol, then mutationMethod gets called, with no parameters, and is quite unhappy.
While I am aware that yes, I could just rewrite my code to make it work differently, I'm now curious as to how to make it actually work.
Any help is greatly appreciated.
Actually just dont use the # symbol, use it when you call the Repopulate function instead.
Example:
function x = fun1(a,m)
x = fun2(a,m);
end
function y = fun2(b,n)
y = n(b);
end
which we call as:
> fun1([1 2 3], #sum)
6
Refer to the documentation for Passing Function Handle Arguments
Note you can check if the argument is a function handle by: isa(m,'function_handle'). Therefore you can make your function Repopulate more flexible by accepting both a function handle and a function name as a string:
function x = fun(a,m)
if ischar(m)
f = str2func(m);
elseif isa(m,'function_handle')
f = m;
else
error('expecting a function')
end
x = fun2(a,f);
end
which now can be called both ways:
fun1([1 2 3], #sum)
fun1([1 2 3], 'sum')