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How to concatenate a number to a variable name in MATLAB?
MATLAB: How can I use a variables value in another variables name?
I want to name a variable using values of other variables given in a function.
So, if I have values for an x1,x2 I can make the new variable's name as:
x_(x1's value)_(x2's value) as a name.
I've checked out the eval, num2str, strcat functions, but as of yet I can't make it so that I have a variable with the name above which I can assign a value to.
Any help would be greatly appreciated.
Take a look at the following FAQ:
How can I create variables A1, A2,...,A10 in a loop?
It answers the "how" part of your question and recommends a better approach using arrays.
As Jonas suggests, if x1 and x2 are numbers this works:
x1 = 3;
x2 = 4;
newValue = 25;
eval(sprintf('x_%i_%i = newValue;',x1,x2));
If x1 and x2 are strings, this becomes:
x1 = 'foo';
x2 = 'bar';
newValue = 25;
eval(sprintf('x_%s_%s = newValue;',x1,x2));
or more simply (using concatenation instead of SPRINTF):
x1 = 'foo';
x2 = 'bar';
newValue = 25;
eval(['x_' x1 '_' x2 ' = newValue']);
I don't know what you're trying to accomplish, but this probably isn't the best way to go about it. EVAL should always be avoided. Creating variables in the using EVAL is (a.k.a. "poofing") is doubly bad.
If you're trying to associate parameters with values, structures are a much better solution:
x1 = 'foo';
x2 = 'bar';
newValue = 25;
x.([x1 '_' x2]) = newValue;
Assuming you have a really good reason why you'd want to do that (and assuming x1 and x2 have integer values), you can do this by combining EVAL and SPRINTF.
x1 = 3;
x2 = 4;
newValue = 25;
eval(sprintf('x_%i_%i = newValue;',x1,x2));
If x1 and x2 are floats, it'll be trickier since a variable name cannot have dots in it, though it would still be possible as long as you replace the dots with something else.
However, I really have to ask: Are you sure that you want to do that? Because at the moment I cannot imagine an application where would want to create variable names you don't know beforehand, which in turn makes it very hard to write an efficient program.
EDIT
There are many useful ways to store your data in arrays. If you really don't want that, you may be interested in accessing data via key/value pairs in a MAP, a feature which is available in more recent versions of Matlab. Thus, your key would become sprintf('%i_%i',x1,x2), and the corresponding value would be whatever it is you want to store.
You can also use dynamic field references. Loren at the Mathworks gives a writeup here:
Mathworks: use-dynamic-field-references
Related
I'd like to write a LP problem in the standard format with MatOptInterface, e.i.:
min c'*x
S.t A*x .== b
x >= 0
Now, how can one write this problem with MathOptInterface? I'm having many issues, one of them is how to define the variable "model". For example, if I try to run:
x = add_variables(model,3)
I first would need to declare this model variable. But I don't know how one is supposed to do this on MathOptInterface.
IIUC in your situation model has to be an argument to be specified by the user of your function.
The user can then pass GLPK.Optimizer(), Tulip.Optimizer() or any other optimizer inheriting from MathOptInterface.AbstractOptimizer.
See e.g. Manual#A complete example.
Alternatively you can look at MOI.Utilities.Model but I don't know how to get an optimizer to solve that model.
Here is how to implement the LP solver for standard Simplex format:
function SolveLP(c,A,b,model::MOI.ModelLike)
x = MOI.add_variables(model, length(c));
MOI.set(model, MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}(),
MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.(c, x), 0.0))
MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
for xi in x
MOI.add_constraint(model, MOI.SingleVariable(xi), MOI.GreaterThan(0.0))
end
for (i,row) in enumerate(eachrow(A))
row_function = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.(row, x), 0.0);
MOI.add_constraint(model, row_function, MOI.EqualTo(b[i]))
end
MOI.optimize!(model)
p = MOI.get(model, MOI.VariablePrimal(), x);
return p
end
For the model, just choose something like GLPK.Optimizer()
So I am trying to calculate the value of a parameter, beta, by minimizing the chi-square function. To do this, I'm using the scipy.optimize.minimize() function. I can't seem to get the code to do what I want. Is there a way to do this? I am open to other ways of approaching the problem.
For some background, the variables vr, rms and delta are both 1D tuples of the same length, and zeff, H and beta are parameters. I am trying to calculate an optimized beta value.
def chisq(beta,vr, delta,rvs,rms,zeff,H):
c = -(H/(1+zeff))*(beta/3)
model = c*np.multiply(rms,delta)
q = (vr-model)**2
p = model**-1
ratio = np.multiply(p,q)
chisq = np.sum(ratio)
return chisq
initial_guess = 0.47663662075855323
res = opt.minimize(chisq,initial_guess,args = (beta,delta,rvs,rms,zeff,H))
I usually get an error saying the dimensions of the function don't match the syntax for the minimize() function.
In your case beta is the optimization variable, so you don't need to pass it as an extra argument to the function chisq:
res = opt.minimize(chisq, x0=initial_guess, args=(vr, delta, rvs, rms, zeff, H))
I have defined the following:
typdef enum {
none = 0,
alpha = 1,
beta = 2,
delta = 4
gamma = 8
omega = 16,
} Greek;
Greek t = beta | delta | gammax
I would like to be able to pick one of the flags set in t randomly. The value of t can vary (it could be, anything from the enum).
One thought I had was something like this:
r = 0;
while ( !t & ( 2 << r ) { r = rand(0,4); }
Anyone got any more elegant ideas?
If it helps, I want to do this in ObjC...
Assuming I've correctly understood your intent, if your definition of "elegant" includes table lookups the following should do the trick pretty efficiently. I've written enough to show how it works, but didn't fill out the entire table. Also, for Objective-C I recommend arc4random over using rand.
First, construct an array whose indices are the possible t values and whose elements are arrays of t's underlying Greek values. I ignored none, but that's a trivial addition to make if you want it. I also found it easiest to specify the lengths of the subarrays. Alternatively, you could do this with NSArrays and have them self-report their lengths:
int myArray[8][4] = {
{0},
{1},
{2},
{1,2},
{4},
{4,1},
{4,2},
{4,2,1}
};
int length[] = {1,1,1,2,1,2,2,3};
Then, for any given t you can randomly select one of its elements using:
int r = myArray[t][arc4random_uniform(length[t])];
Once you get past the setup, the actual random selection is efficient, with no acceptance/rejection looping involved.
I am trying to follow the tutorial of using the optimization tool box in MATLAB. Specifically, I have a function
f = exp(x(1))*(4*x(1)^2+2*x(2)^2+4*x(1)*x(2)+2*x(2)+1)+b
subject to the constraint:
(x(1))^2+x(2)-1=0,
-x(1)*x(2)-10<=0.
and I want to minimize this function for a range of b=[0,20]. (That is, I want to minimize this function for b=0, b=1,b=2 ... and so on).
Below is the steps taken from the MATLAB's tutorial webpage(http://www.mathworks.com/help/optim/ug/nonlinear-equality-and-inequality-constraints.html), how should I change the code so that, the optimization will run for 20 times, and save the optimal values for each b?
Step 1: Write a file objfun.m.
function f = objfun(x)
f = exp(x(1))*(4*x(1)^2+2*x(2)^2+4*x(1)*x(2)+2*x(2)+1)+b;
Step 2: Write a file confuneq.m for the nonlinear constraints.
function [c, ceq] = confuneq(x)
% Nonlinear inequality constraints
c = -x(1)*x(2) - 10;
% Nonlinear equality constraints
ceq = x(1)^2 + x(2) - 1;
Step 3: Invoke constrained optimization routine.
x0 = [-1,1]; % Make a starting guess at the solution
options = optimoptions(#fmincon,'Algorithm','sqp');
[x,fval] = fmincon(#objfun,x0,[],[],[],[],[],[],...
#confuneq,options);
After 21 function evaluations, the solution produced is
x, fval
x =
-0.7529 0.4332
fval =
1.5093
Update:
I tried your answer, but I am encountering problem with your step 2. Bascially, I just fill the my step 2 to your step 2 (below the comment "optimization just like before").
%initialize list of targets
b = 0:1:20;
%preallocate/initialize result vectors using zeros (increases speed)
opt_x = zeros(length(b));
opt_fval = zeros(length(b));
>> for idx = 1, length(b)
objfun = #(x)objfun_builder(x,b)
%optimization just like before
x0 = [-1,1]; % Make a starting guess at the solution
options = optimoptions(#fmincon,'Algorithm','sqp');
[x,fval] = fmincon(#objfun,x0,[],[],[],[],[],[],...
#confuneq,options);
%end the stuff I fill in
opt_x(idx) = x
opt_fval(idx) = fval
end
However, it gave me the output is:
Error: "objfun" was previously used as a variable, conflicting
with its use here as the name of a function or command.
See "How MATLAB Recognizes Command Syntax" in the MATLAB
documentation for details.
There are two things you need to change about your code:
Creation of the objective function.
Multiple optimizations using a loop.
1st Step
For more flexibility with regard to b, you need to set up another function that returns a handle to the desired objective function, e.g.
function h = objfun_builder(x, b)
h = #(x)(objfun(x));
function f = objfun(x)
f = exp(x(1))*(4*x(1)^2+2*x(2)^2+4*x(1)*x(2)+2*x(2)+1) + b;
end
end
A more elegant and shorter approach are anonymous functions, e.g.
objfun_builder = #(x,b)(exp(x(1))*(4*x(1)^2+2*x(2)^2+4*x(1)*x(2)+2*x(2)+1) + b);
After all, this works out to be the same as above. It might be less intuitive for a Matlab-beginner, though.
2nd Step
Instead of placing an .m-file objfun.m in your path, you will need to call
objfun = #(x)(objfun_builder(x,myB));
to create an objective function in your workspace. In order to loop over the interval b=[0,20], use the following loop
%initialize list of targets
b = 0:1:20;
%preallocate/initialize result vectors using zeros (increases speed)
opt_x = zeros(length(b))
opt_fval = zeros(length(b))
%start optimization of list of targets (`b`s)
for idx = 1, length(b)
objfun = #(x)objfun_builder(x,b)
%optimization just like before
opt_x(idx) = x
opt_fval(idx) = fval
end
Lets say I have pre-defined 3 variables, x1, x2, and x3, each of which is a different co-ordinate on the screen. I have a whole chunk of code to decide whether another variable, a will equal 1, 2, or 3. Now, I want to include the value of a in a variable name, allowing me to 'dynamically' change between x1, x2, and x3.
E.g. a is set to 2. Now I want to move the mouse to xa, so if a=2, xa is x2, which is a predefined variable.
Its probably clear I am very new to Lua, I have tried googling the issue, but I'm not really sure what I am looking for, terminology wise and such.
Anyhow, is anyone able to help me out?
If you can change the code where x1, x2 and x3 are defined, a cleaner approach is to use arrays (i.e. array-like tables). This is the general approach when you need a sequence of variables indexed by a number.
Therefore, instead of x1, x2 and x3 you could define:
local x = {}
x[1] = 10 -- instead of x1
x[2] = 20 -- instead of x2
x[3] = 30 -- instead of x3
Now instead of using xa you simply use x[a].
If xa are global variables, you can use the table _G like this:
x1 = 42
x2 = 43
x3 = 44
local a = 2
print(_G['x' .. a])
Output:
43