Can you store symbolic functions in a matrix/vector?

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KieranSQ
KieranSQ el 4 de Feb. de 2019
Comentada: Walter Roberson el 6 de Sept. de 2020
I am trying to write a finite element code. I want to consider the basis functions .
So I need to be able to store them in a matrix/vector such as: . In matlab I tried the following ,
phi=@(x,y)1/h.*[1-x-y;x;y]
but I either get an error for variables not being defined (which is the point at this stage). From here I want to do something like the following, but I can't see how. Any help would be appreciated!
phi(1)=1/h[1-x-y]

Respuesta aceptada

Walter Roberson
Walter Roberson el 4 de Feb. de 2019
Symbolic functions cannot be stored in a regular vector or array. If you concatenate symbolic functions, then what you get back is not a vector of symbolic functions but rather a single symbolic function that returns a vector. This is because the () indexing operation for symbolic functions is always interpreted as invocation of the function, never as indexing.
This is also part of the same reason that function handles cannot be stored in a regular vector or array, because () for function handles always means invocation, never indexing.
You can store symbolic functions as elements of a cell array.
Symbolic expressions can be stored in a vector or array. Most of the time it is easier to work with symbolic expressions rather than symbolic functions. However if you need to express differentiation of a symbolic function whose definition is not fully known, such as a differential equation, then you need a symbolic function.

Más respuestas (1)

Sebastian Pakula
Sebastian Pakula el 6 de Sept. de 2020
There is a way of picking one of the function from matrix (or vector) of functions. Try this:
syms x y
h=10;
phi=(1/h)*[1-x-y;x;y];
% if you need second function write:
f2=[0 1 0]*phi;
% if you need third one:
f3=[0 0 1]*phi;
  1 comentario
Walter Roberson
Walter Roberson el 6 de Sept. de 2020
You do not show any functions, only expressions.
For expressions you can just index directly, phi(2) for example.
You also need to be careful about 0 times infinity, which would normally be nan.

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