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Справка Scilab >> Optimization and Simulation > Simplex > optimsimplex_gradientfv


Returns the simplex gradient of the function.


g = optimsimplex_gradientfv(opt, [fun, [method]])
[g, data] = optimsimplex_gradientfv(opt, fun, method, data)



The current simplex object of TSIMPLEX type (tlist).


The function to compute at vertices (optional).

The fun function is expected to have the following input and output arguments:

y = myfunction (x)

The method to use to compute the simplex gradient (optional).

Two methods are available:

  • The "forward" method used the current simplex to compute the simplex gradient.

  • The "centered" method creates an intermediate reflected simplex and computes the average.

If not provided, the default method is "forward".


User-defined data passed to the function (optional).

If data is provided, it is passed to the callback function both as an input and output argument. In that case, the function must have the following header :

[y, data] = myfunction (x, data)

The data input parameter may be used if the function uses some additional parameters. It is returned as an output parameter because the function may modify the data while computing the function value. This feature may be used, for example, to count the number of times that the function has been called.


A column vector of doubles.


The optimsimplex_gradientfv function returns the simplex gradient of the function.


s1 = optimsimplex_new ();
simplex = [
3.  0.  0.
4.  1.  0.
5.  0.  2.
s1 = optimsimplex_setall ( s1 , simplex );
g = optimsimplex_gradientfv ( s1 );

s1 = optimsimplex_destroy(s1);

See also

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Last updated:
Mon Jan 03 14:39:57 CET 2022