I'm writing a program in MATLAB to solve integrals, and I have my function in a .M-file. Now I wonder how I can write a program in the .MAT-file that lets the user set a value that exists in the both files. The .M-file looks like this:
function fh = f(y)
fh = 62.5.*(b-y).*(40-20.*exp(-(0.01.*y).*(0.01.*y)));
and as you can see, the function depends on two variables, y and b. I want the user to set b. I tried putting b = input('Type in the value of b: ') in the .M-file but for some reason the user would then have to put in the same value four times.
Can I ask for the value of b in the .MAT-file?
Firstly, m-files store code (i.e. functions), while MAT-files store data (i.e. variables). You can save workspace variables to a MAT-file using the function SAVE and load them into a workspace from a file using the function LOAD. If you have a user choose a value for b, then save it to a MAT-file ('b_value.mat', for example), you can simply load the value from the MAT-file inside your m-file function like so:
function fh = f(y)
load('b_value.mat','b');
fh = 62.5.*(b-y).*(40-20.*exp(-(0.01.*y).*(0.01.*y)));
However, this is not a very good way to handle the larger problem I think you are having. It requires that you hardcode the name of the MAT-file in your function f, plus it will give you an error if the file doesn't exist or if b isn't present in the file.
Let's address what I think the larger underlying problem is, and how to better approach a solution...
You mention that you are solving integrals, and that probably means you are performing numerical integration using one or more of the various built-in integration functions, such as QUAD. As you've noticed, using these functions requires you to supply a function for the integrand which accepts a single vector argument and returns a single vector argument.
In your case, you have other additional parameters you want to pass to the function, which is complicated by the fact that the integration functions only accept integrand functions with a single input argument. There is actually a link in the documentation for QUAD (and the other integration functions) that shows you a couple of ways you can parameterize the integrand function without adding extra input arguments by using either nested functions or anonymous functions.
As an example, I'll show you how you can do this by writing f as an anonymous function instead of an m-file function. First you would have the user choose the parameter b, then you would construct your anonymous function as follows:
b = input('Type in the value of b: ');
f = #(y) 62.5.*(b-y).*(40-20.*exp(-(0.01.*y).^2));
Note that the value of b used by the anonymous function will be fixed at what it was at the time that the function was created. If b is later changed, you would need to re-make your anonymous function so that it uses the new value.
And here's an example of how to use f in a call to QUAD:
q = quad(f,lowerLimit,upperLimit);
In your m file declare b as a global
function fh = f(y)
global b
fh = 62.5.(b-y).(40-20.*exp(-(0.01.y).(0.01.*y)));
This allows the variable to be accessed from another file without having to create another function to set the value of b. You could also add b to the arguments of your fh function.
Related
Let the variables A and B be n x 1 doubles and c be a scalar. My goal is to sum the values in A corresponding to indices for which the optimization variable x is greater than B. I have written this up below:
x = optimvar('x',n); % Creates optimization variable
objfun = sum(x); % Creates objective function
constraint = sum(A(x>=B))>=c; % Constraint based on logical indexing
The third line in the code above returns an error message because optimization variables are not compatible with inequality indexing. Specifically, x>=B cannot be input as indexes into A. Is there a way around this? Or am I thinking about this the wrong way?
Thank you!
You need to use function handles for both, the objective function as well as the constraint-function:
objfun = #(var) sum(var);
constraint = #(var) sum(A(var>=B)) >= c;
In fact, for the objective function objfun, you may also use objfun = #sum. This is a function handle. You can think of it as a pointer or reference to a certain function. Function, which work with one input can be used directly (with #). The optimizer calls the function and uses the optimization variable as input.
Now, if you have multiple inputs, you need to create a function, where you define all inputs but one. For this, you create an anonymous function handle, where you tell the handle what variables are placed where: #(var) sum(A(var>=B)) >= c. The variable var is the changing input and the other variables A, B, and c are taken from the workspace at the point of definition (i.e. the function handle is unaffected if you change the variables later or even delete them).
Considering we have a huge matrix called A and we pass it to the function func(A) wherein func I do a set of computations like:
func(A):
B=A;
%% a lot of processes will happen on B here
return B;
end
The fact is that as soon as I pass A to B I would not have anything to do with A anymore in my Matlab session so it takes an unnecessary space in memory. Is it possible to remove its instance in the scope of the script that called func?
Using evalin with the option caller you can evaluate expression clear A:
function A = func(A)
evalin('caller', 'clear A')
A(1) = 5;
end
However we usually don't know the name of the input variable so we can use inputname to get the actual name of the workspace variable:
function A = func(A)
name = inputname(1);
if ~isempty(name)
evalin('caller', ['clear ' name])
end
A(1)=4;
end
1.Here inputname(1) means the actual name of the first argument.
2.Work directly with A because if you copy A into B the function scope will have two copies of A.
If you write your function as
function A = func(A)
% Do lots of processing on A here
and call it as
A = func(A);
Then MATLAB will optimize it such that you work on A in-place, meaning that no copy is made. There is no need to delete A from the workspace.
This behavior is not expressly documented as far as I know, but it is well-known. See for example on Undocumented MATLAB, or on Loren's blog.
I have a statement in my MATLAB program:
f = #(A)DistanceGauss(A,x_axis,Y_target,Y_initial,numOf,modus);
I understood that f is defined as the function handle to the function distancegauss which contains the parameters/arg list present inside the parentheses.
What does the variable A in #(A) do? Does it have any importance? While browsing I found that the variables within parentheses after # would be the input arguments for an anonymous function..
Can anyone explain what does that A do? Will this handle work even without that A after the # symbol ? Because it is already present as an argument to be passed after the function name.
Your code will create an anonymous function f which accepts one input A. In particular f will call the function DistanceGauss(A,x_axis,Y_target,Y_initial,numOf,modus); where the value of A is whatever you input with f(A) and the other inputs must already exist in your workspace and will be passed to the function. Note: if the other variables don't exist you should get an error when calling f.
Now a reasonable question is why would you want to do this you could just call DistanceGauss(A,x_axis,Y_target,Y_initial,numOf,modus); directly with whatever values you want, without having to worry about whether some of them exist.
There are two main reasons I can think of why you would do this (I'm sure there are others). Firstly for simplicity where your other inputs don't change and you don't want to have to keep retyping them or have users accidentally change them.
The other reason where you would want this is when optimizing/minimizing a function, for example with fminsearch. The matlab optimization functions will vary all inputs. If you want only vary some of them you can use this sort of syntax to reduce the number of input variables.
As to what A actually is in your case this will depend on what it does in DistanceGauss, which is not a standard MATLAB function so I suggest you look at the code for that.
"f(A)" or "f of A" or "The function of A" here has the handle "f"
DistanceGauss() here is another function that was defined elsewhere in your code.
You would set x_axis, Y_target, Y_initial, numOf, & modus before creating the function f. These arguments would stay the same for Function f, even if you try and set them again later.
'A' though, is different. You don't set it before you make the function. You can later operate on all values of A, such as if you plot the function or get the integral of the function. In that case, it would be performing the DistanceGauss function on every value of 'A', (though we can't see here what DistanceGauss function does. )
Anonymous function should be defined such as:
sqr = #(x) x.^2;
in which x shows the variable of the the function and there is no name for it (it is called anonymous!).
Although you can do something like this:
c = 10;
mygrid = #(x,y) ndgrid((-x:x/c:x),(-y:y/c:y));
[x,y] = mygrid(pi,2*pi);
in which you are modifying an existing function ndgrid to make a new anonymous function.
In your case also:
f = #(A)DistanceGauss(A,x_axis,Y_target,Y_initial,numOf,modus);
This is a new anonymous function by modifying the function DistanceGauss that you may want to have a single variable A.
If you remove (A) from the code, then f would be a handle to the existing function DistanceGauss:
f = #DistanceGauss;
Now you can evaluate the function simply by using the handle:
f(A,x_axis,...)
For example in testinit.m I have the following
function [x, y, m] = testinit
x=4
y=3
m=2
When I run testinit in the console it correctly displays the value. However when I type x it says
error: 'x' undefined...
Just to add to the above answer, the reason you're getting this is because variables in a MatLab function are local variables, they are not passed to the workspace unless you use one of the functions in the above answer. You can read more about global and local variables here.
P.S If you wrote an m-file that is not a function, then the variables are global.
There's the assignin function (evalin is related). And also global.
The other answers are all possible solutions, but potentially more complicated than what you may be looking for. I think the first part of yuk's answer addresses the real problem you are having, but I think it deserves a more detailed explanation...
If you have a function that has output arguments, you need to actually capture those arguments in variables when you call the function. For example, if you typed this in the Command Window:
[x, y, m] = testinit;
Then you would have your three output values present for you to use. What you were probably doing was typing this:
testinit;
This would display the values (because you didn't end each line in the function with a semicolon to suppress displaying them), but it would not store them in variables in the Command Window for you to use later.
This is a result of how variables are stored in MATLAB, as described by the documentation on variable scope:
MATLAB stores variables in a part of memory called a workspace. The base workspace holds variables created during your interactive MATLAB session and also any variables created by running scripts. Variables created at the MATLAB command prompt can also be used by scripts without having to declare them as global.
Functions do not use the base workspace. Every function has its own function workspace. Each function workspace is kept separate from the base workspace and all other workspaces to protect the integrity of the data used by that function. Even subfunctions that are defined in the same file have a separate function workspace.
So, if you want to share variables between functions, the simplest way is to pass them back and forth via their input and output argument lists.
It should also be noted that the names you give variables in the output argument list of the function don't have to match the names of the variables you place those output values in. For example, given this function:
function [a, b, c] = testinit
a = 4;
b = 3;
c = 2;
You can make this call in the Command Window:
[x, y, m] = testinit;
And you will get x = 4, y = 3, and m = 2.
If you run [x, y, m] = testinit in the console you should get the variables. The output variables can have any allowed name, not necessary x, y and m.
In addition you should put ; after each variable assignment in the function to avoid their output to the console. You can control the console output while calling the function.
If you want simply initialize new variables just by typing testinit, use assignin as in #BenVoigt's answer.
assignin('base','x',4)
However, this is dangerous, since some variable may already exist in the calling environment and will be overwritten. You can avoid it adding EXIST tests (inside EVALIN):
function testinit
if ~evalin('base','exist(''x'',''var'')')
assignin('base','x',4)
end
if ~evalin('base','exist(''y'',''var'')')
assignin('base','y',3)
end
if ~evalin('base','exist(''m'',''var'')')
assignin('base','m',2)
end
You can also use 'caller' instead of 'base' if you plan to call the function from another function.
The variables are local to the function so you cannot access them from the command line. As #BenVoigt said, you can use asignin but it's very dirty, and I don't think that it's what you really want to do.
I advise you do go in debug mode
Add a break point or a keyboard to your function like that:
function [x, y, m] = testinit
x=4
y=3
m=2
keyboard
After execute your function, and the command line will remain in the environment of the function.
The usual >> kill be replaced by a K>>. At that point you can access all your local variables.
To quit the debug mode type dbquit, or press shift+F5
In short: is there an elegant way to restrict the scope of anonymous functions, or is Matlab broken in this example?
I have a function that creates a function handle to be used in a pipe network solver. It takes as input a Network state which includes information about the pipes and their connections (or edges and vertices if you must), constructs a large string which will return a large matrix when in function form and "evals" that string to create the handle.
function [Jv,...] = getPipeEquations(Network)
... %// some stuff happens here
Jv_str = ['[listConnected(~endNodes,:)',...
' .* areaPipes(~endNodes,:);\n',...
anotherLongString,']'];
Jv_str = sprintf(Jv_str); %// This makes debugging the string easier
eval(['Jv = #(v,f,rho)', Jv_str, ';']);
This function works as intended, but whenever I need to save later data structures that contain this function handle, it requires a ridiculous amount of memory (150MB) - coincidentally about as much as the entire Matlab workspace at the time of this function's creation (~150MB). The variables that this function handle requires from the getPipeEquations workspace are not particularly large, but what's even crazier is that when I examine the function handle:
>> f = functions(Network.jacobianFun)
f =
function: [1x8323 char]
type: 'anonymous'
file: '...\pkg\+adv\+pipe\getPipeEquations.m'
workspace: {2x1 cell}
...the workspace field contains everything that getPipeEquations had (which, incidentally is not the entire Matlab workspace).
If I instead move the eval statement to a sub-function in an attempt to force the scope, the handle will save much more compactly (~1MB):
function Jv = getJacobianHandle(Jv_str,listConnected,areaPipes,endNodes,D,L,g,dz)
eval(['Jv = #(v,f,rho)', Jv_str, ';']);
Is this expected behavior? Is there a more elegant way to restrict the scope of this anonymous function?
As an addendum, when I run the simulation that includes this function several times, clearing workspaces becomes painfully slow, which may or may not be related to Matlab's handling of the function and its workspace.
I can reproduce: anonymous functions for me are capturing copies of all variables in the enclosing workspace, not just those referenced in the expression of the anonymous function.
Here's a minimal repro.
function fcn = so_many_variables()
a = 1;
b = 2;
c = 3;
fcn = #(x) a+x;
a = 42;
And indeed, it captures a copy of the whole enclosing workspace.
>> f = so_many_variables;
>> f_info = functions(f);
>> f_info.workspace{1}
ans =
a: 1
>> f_info.workspace{2}
ans =
fcn: #(x)a+x
a: 1
b: 2
c: 3
This was a surprise to me at first. But it makes sense when you think about it: because of the presence of feval and eval, Matlab can't actually know at construction time what variables the anonymous function is actually going to end up referencing. So it has to capture everything in scope just in case they get referenced dynamically, like in this contrived example. This uses the value of foo but Matlab won't know that until you invoke the returned function handle.
function fcn = so_many_variables()
a = 1;
b = 2;
foo = 42;
fcn = #(x) x + eval(['f' 'oo']);
The workaround you're doing - isolating the function construction in a separate function with a minimal workspace - sounds like the right fix.
Here's a generalized way to get that restricted workspace to build your anonymous function in.
function eval_with_vars_out = eval_with_vars(eval_with_vars_expr, varargin)
% Assign variables to the local workspace so they can be captured
ewvo__reserved_names = {'varargin','eval_with_vars_out','eval_with_vars_expr','ewvo__reserved_names','ewvo_i'};
for ewvo_i = 2:nargin
if ismember(inputname(ewvo_i), ewvo__reserved_names)
error('variable name collision: %s', inputname(ewvo_i));
end
eval([ inputname(ewvo_i) ' = varargin{ewvo_i-1};']);
end
clear ewvo_i ewvo__reserved_names varargin;
% And eval the expression in that context
eval_with_vars_out = eval(eval_with_vars_expr);
The long variable names here hurt readability, but reduce the likelihood of collision with the caller's variables.
You just call eval_with_vars() instead of eval(), and pass in all the input variables as additional arguments. Then you don't have to type up a static function definition for each of your anonymous function builders. This'll work as long as you know up front what variables are actually going to be referenced, which is the same limitation as the approach with getJacobianHandle.
Jv = eval_with_vars_out(['#(v,f,rho) ' Jv_str],listConnected,areaPipes,endNodes,D,L,g,dz);
Anonymous functions capture everything within their scope and store them in the function workspace. See MATLAB documentation for anonymous functions
In particular:
"Variables specified in the body of the expression. MATLAB captures these variables and holds them constant throughout the lifetime of the function handle.
The latter variables must have a value assigned to them at the time you construct an anonymous function that uses them. Upon construction, MATLAB captures the current value for each variable specified in the body of that function. The function will continue to associate this value with the variable even if the value should change in the workspace or go out of scope."
An alternative workaround to your problem, is to use the fact that the matlab save function can be used to save only the specific variables you need. I have had issues with the save function saving way too much data (very different context from yours), but some judicial naming conventions, and use of wildcards in the variables list made all my problems go away.