I used MATLAB coder to covert M-file to cpp-file.
There generated problem when is building.
Expected either a logical, char, int, fi, single, or double. Found an
mxArray. MxArrays are returned from calls to the MATLAB
interpreter and are not supported inside expressions. They may only be
used on the right-hand side of assignments and as arguments to
extrinsic functions.
MATLAB code :
nms = sum(transpose(X).^2);
nms0=-1 * nms;
nms2=transpose(nms0);
nms3=transpose(X);
nms4=nms2*ones(1,n);
nms5=ones(n,1)*nms;
nms6=2*X*nms3;
nms7=zeros(150,150);
nms7=nms4-nms5; //This line is wrong
nms8=nms7 + nms6;
K = exp(nms8);
I want to know why code has been run correct in MATLAB,but it has error when is building
This error happens when you try to use result of extrinsic functions in expressions. In the code you provided is "n" or "X" the result of an extrinsic function? Even if they are not directly a result of an extrinsic function, they may have been computed based on data from other extrinsic functions.
One way to fix the problem is to help MATLAB coder convert these extrinsic data to known types. You can do that by pre-defining them with known data. For example,
coder.extrinsic('some_extrinsic_fcn');
y = zeros(10,1);
y = some_extrinsic_fcn();
y = y * 2;
In this case some_extrinsic_fcn should return a double precision vector with 10 elements. This resulting mxArray will be auto-converted and stored in y. Without the line "y = zeros(10,1);" y will be of mxArray type and the line "y = y * 2;" will cause an error.
Related
I want to use the stats::swGOFT function in MuPAD. I have a numerical vector called r. I used
feval(symengine, 'stats::swGOFT', r);
The error was
Error using mupadengine/feval (line 157)
MuPAD error: Error: Some data are of invalid type.
So I tried a more direct way, which worked:
feval(symengine, 'stats::swGOFT', 1,2,3,4);
But this didn't work:
feval(symengine, 'stats::swGOFT', [1,2,3,4]);
My variable r is a 1146-by-1 double vector. Obviously I can't manually input all the numbers. So, how to pass the vector variable r to the MuPAD function stats::swGOFT?
MuPAD is not Matlab. From the current version documentation for stats::swGOFT, it appears that this function requires a list, as opposed to an array (what Matlab uses). Many MuPAD functions automatically coerce inputs to the desired format, but that doesn't seem to occur in this case. You have several options if you want to call this function from Matlab using numeric values – here's a simple one that will work for both floating point and symbolic numeric values:
r = randn(1146,1);
rStr = char(sym(r(:).'));
feval(symengine, 'stats::swGOFT', rStr(9:end-2))
This one should perform the string conversion more quickly for large datasets of floating point values using sprintf:
r = randn(1146,1);
rStr = ['[' sprintf('%.17g', r(1)) sprintf(',%.17g', r(2:end)) ']'];
feval(symengine, 'stats::swGOFT', rStr)
Since you're converting to a string yourself, you might as well convert the above to use evalin directly:
r = randn(1146,1);
rStr = [ sprintf('%.17g', r(1)) sprintf(',%.17g', r(2:end)) ];
evalin(symengine, ['stats::swGOFT([' rStr '])'])
I want to evaluate the simple example of integral
a = max(solve(x^3 - 2*x^2 + x ==0 , x));
fun = #(x) exp(-x.^2).*log(x).^2;
q = integral(fun,0,a)
and the error is
Error using integral (line 85)
A and B must be floating-point scalars.
Any tips? The lower limit of my integral must be a function, not a number.
The Matlab command solve returns symbolic result. integral accepts only numeric input. Use double to convert symbolic to numeric. As your code is written now, already max should throw an error due to symbolic input. The following works.
syms x;
a = max(double(solve(x^3 - 2*x^2 + x)));
fun = #(x) exp(-x.^2).*log(x).^2;
q = integral(fun,0,a)
Output: 1.9331.
the lower limit of my integral must be a function, not a number
integral is a numeric integration routine; the limits of integration must be numeric.
Check values of a by mouse over in breakpoint or removing the ; from the end of the line so it prints a. Based on the error, a is not a scalar float. You might need another max() or double() statement to transform the vector to a single value.
Solve Help : http://www.mathworks.com/help/symbolic/solve.html
Integral Help : http://www.mathworks.com/help/ref/integral.html
I tryed to write an Matlab function in Simulink.
My first func like this:
function y = fcn(u, v)
coder.extrinsic('detectSURFFeatures');
boxPoints = detectSURFFeatures(u);
%scenePoints = detectSURFFeatures(v);
vBoxPoints = boxPoints.selectStrongest(100);
y = 0;
y = vBoxPoints;
But I see errors:
1. Attempt to extract field 'selectStrongest' from 'mxArray'.
2.Undefined function or variable 'vBoxPoints'. The first assignment to a local variable determines its class.
3. Error in port widths or dimensions. Output port 1 of 'detecting_cross/MATLAB Function/v' is a [400x239] matrix.
Pls, help.
The data returned from extrinsic functions are mxArray types. If you want to get the values from these mxArrays you need to pre-declare them so that the result of extrinsic function can be auto-converted to that type. You can use something like
boxPoints = struct('selectStrongest',zeros(100,1));
before calling detectSUTFFeatures. If the mxArray does not match the one from the function, you will get a run-time error. Your errors 2 and 3 are because of the first problem.
I am trying to use Octave's fminsearch function, which I have used in MATLAB before. The function seems not sufficiently documented (for me at least), and I have no idea how to set to options such that it would actually minimize.
I tried fitting a very simple exponential function using the code at the end of this message. I want the following:
I want the function to take as input the x- and y-values, just like MATLAB would do. Furthermore, I want some control over the options, to make sure that it actually minimizes (i.e. to a minimum!).
Of course, in the end I want to fit functions that are more complicated than exponential, but I want to be able to fit exponentials at least.
I have several problems with fminsearch:
I tried handing over the x- and y-value to the function, but a matlab-style thing like this:
[xx,fval]=fminsearch(#exponential,[1000 1],x,y);
or
[xx,fval]=fminsearch(#exponential,[33000 1],options,x,y)
produces errors:
error: options(6) does not correspond to known algorithm
error: called from:
error: /opt/local/share/octave/packages/optim-1.0.6/fmins.m at line 72, column 16
error: /opt/local/share/octave/packages/optim-1.0.6/fminsearch.m at line 29, column 4
Or, respectively (for the second case above):
error: `x' undefined near line 4 column 3
error: called from:
error: /Users/paul/exponential.m at line 4, column 2
error: /opt/local/share/octave/packages/optim-1.0.6/nmsmax.m at line 63, column 6
error: /opt/local/share/octave/packages/optim-1.0.6/fmins.m at line 77, column 9
error: /opt/local/share/octave/packages/optim-1.0.6/fminsearch.m at line 29, column 4
Apparently, the order of arguments that fminsearch takes is different from the one in MATLAB. So, how is this order??
How can I make fminsearch take values and options?
I found a workaround to the problem that the function would not take values: I defined the x- and y values as global. Not elegant, but at least then the values are available in the function.
Nonetheless, fminsearch does not minimize properly.
This is shown below:
Here is the function:
function f=exponential(coeff)
global x
global y
X=x;
Y=y;
a= coeff(1);
b= coeff(2);
Y_fun = a .* exp(-X.*b);
DIFF = Y_fun - Y;
SQ_DIFF = DIFF.^2;
f=sum(SQ_DIFF);
end
Here is the code:
global x
global y
x=[0:1:200];
y=4930*exp(-0.0454*x);
options(10)=10000000;
[cc,fval]=fminsearch(#exponential,[5000 0.01])
This is the output:
cc =
4930.0 5184.6
fval = 2.5571e+08
Why does fminsearch not find the solution?
There is an fminsearch implementation in the octave-forge package "optim".
You can see in its implementation file that the third parameter is always an options vector, the fourth is always a grad vector, so your ,x,y invocations will not work.
You can also see in the implementation that it calls an fmins implementation.
The documentation of that fmins implementation states:
if options(6)==0 && options(5)==0 - regular simplex
if options(6)==0 && options(5)==1 - right-angled simplex
Comment: the default is set to "right-angled simplex".
this works better for me on a broad range of problems,
although the default in nmsmax is "regular simplex"
A recent problem of mine would solve fine with matlab's fminsearch, but not with this octave-forge implementation. I had to specify an options vector [0 1e-3 0 0 0 0] to have it use a regular simplex instead of a 'right-angled simplex'. The octave default makes no sense if your coefficients differ vastly in scale.
The optimization function fminsearch will always try to find a minimum, no matter what the options are. So if you are finding it's not finding a minimum, it's because it failed to do so.
From the code you provide, I cannot determine what goes wrong. The solution with the globals should work, and indeed does work over here, so something else on your side must be going awry. (NOTE: I do use MATLAB, not Octave, so those two functions could be slightly different...)
Anyway, why not do it like this?
function f = exponential(coeff)
x = 0:1:200;
y = 4930*exp(-0.0454*x);
a = coeff(1);
b = coeff(2);
Y_fun = a .* exp(-x.*b);
f = sum((Y_fun-y).^2);
end
Or, if you must pass x and y as external parameters,
x = [0:1:200];
y = 4930*exp(-0.0454*x);
[cc,fval] = fminsearch(#(c)exponential(c,x,y),[5000 0.01])
function f = exponential(coeff,x,y)
a = coeff(1);
b = coeff(2);
Y_fun = a .* exp(-x.*b);
f = sum((Y_fun-y).^2);
end
How can I make a function from a symbolic expression? For example, I have the following:
syms beta
n1,n2,m,aa= Constants
u = sqrt(n2-beta^2);
w = sqrt(beta^2-n1);
a = tan(u)/w+tanh(w)/u;
b = tanh(u)/w;
f = (a+b)*cos(aa*u+m*pi)+a-b*sin(aa*u+m*pi); %# The main expression
If I want to use f in a special program to find its zeroes, how can I convert f to a function? Or, what should I do to find the zeroes of f and such nested expressions?
You have a couple of options...
Option #1: Automatically generate a function
If you have version 4.9 (R2007b+) or later of the Symbolic Toolbox you can convert a symbolic expression to an anonymous function or a function M-file using the matlabFunction function. An example from the documentation:
>> syms x y
>> r = sqrt(x^2 + y^2);
>> ht = matlabFunction(sin(r)/r)
ht =
#(x,y)sin(sqrt(x.^2+y.^2)).*1./sqrt(x.^2+y.^2)
Option #2: Generate a function by hand
Since you've already written a set of symbolic equations, you can simply cut and paste part of that code into a function. Here's what your above example would look like:
function output = f(beta,n1,n2,m,aa)
u = sqrt(n2-beta.^2);
w = sqrt(beta.^2-n1);
a = tan(u)./w+tanh(w)./u;
b = tanh(u)./w;
output = (a+b).*cos(aa.*u+m.*pi)+(a-b).*sin(aa.*u+m.*pi);
end
When calling this function f you have to input the values of beta and the 4 constants and it will return the result of evaluating your main expression.
NOTE: Since you also mentioned wanting to find zeroes of f, you could try using the SOLVE function on your symbolic equation:
zeroValues = solve(f,'beta');
Someone has tagged this question with Matlab so I'll assume that you are concerned with solving the equation with Matlab. If you have a copy of the Matlab Symbolic toolbox you should be able to solve it directly as a previous respondent has suggested.
If not, then I suggest you write a Matlab m-file to evaluate your function f(). The pseudo-code you're already written will translate almost directly into lines of Matlab. As I read it your function f() is a function only of the variable beta since you indicate that n1,n2,m and a are all constants. I suggest that you plot the values of f(beta) for a range of values. The graph will indicate where the 0s of the function are and you can easily code up a bisection or similar algorithm to give you their values to your desired degree of accuracy.
If you broad intention is to have numeric values of certain symbolic expressions you have, for example, you have a larger program that generates symbolic expressions and you want to use these expression for numeric purposes, you can simply evaluate them using 'eval'. If their parameters have numeric values in the workspace, just use eval on your expression. For example,
syms beta
%n1,n2,m,aa= Constants
% values to exemplify
n1 = 1; n2 = 3; m = 1; aa = 5;
u = sqrt(n2-beta^2);
w = sqrt(beta^2-n1);
a = tan(u)/w+tanh(w)/u;
b = tanh(u)/w;
f = (a+b)*cos(aa*u+m*pi)+a-b*sin(aa*u+m*pi); %# The main expression
If beta has a value
beta = 1.5;
eval(beta)
This will calculate the value of f for a particular beta. Using it as a function. This solution will suit you in the scenario of using automatically generated symbolic expressions and will be interesting for fast testing with them. If you are writing a program to find zeros, it will be enough using eval(f) when you have to evaluate the function. When using a Matlab function to find zeros using anonymous function will be better, but you can also wrap the eval(f) inside a m-file.
If you're interested with just the answer for this specific equation, Try Wolfram Alpha, which will give you answers like:
alt text http://www4c.wolframalpha.com/Calculate/MSP/MSP642199013hbefb463a9000051gi6f4heeebfa7f?MSPStoreType=image/gif&s=15
If you want to solve this type of equation programatically, you probably need to use some software packages for symbolic algebra, like SymPy for python.
quoting the official documentation:
>>> from sympy import I, solve
>>> from sympy.abc import x, y
Solve a polynomial equation:
>>> solve(x**4-1, x)
[1, -1, -I, I]
Solve a linear system:
>>> solve((x+5*y-2, -3*x+6*y-15), x, y)
{x: -3, y: 1}