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removed cruft
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@ -25,32 +25,6 @@ namespace dlib
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const matrix<double,0,1>& x_upper,
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const funct& f
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)
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/*!
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requires
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- f(x) must be a valid expression that evaluates to a double
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- x.size() == x_lower.size() == x_upper.size()
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- x.size() > 0
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- 0 < eps < initial_search_radius
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- max_f_evals > 1
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- min(x_upper - x_lower) > 0
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- min(x - x_lower) >= 0 && min(x_upper - x) >= 0
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(i.e. the given x should be within the bounds defined by x_lower and x_upper)
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ensures
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- Performs a constrained minimization of the function f() starting from
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the initial point x.
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- This function does not require derivatives of f(). Instead, it uses
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derivative free methods to find the best setting of x. In particular, it
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will begin by searching within a sphere of radius initial_search_radius
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around x and will continue searching until either f() has been called
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max_f_evals times or the search area has been shrunk to less than eps radius.
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- #x == the value of x (within the bounds defined by x_lower and x_upper) that
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was found to minimize f(). More precisely, it will always be true that:
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- min(#x - x_lower) >= 0 && min(x_upper - #x) >= 0
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- returns f(#x).
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throws
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- No exception is thrown for executing max_f_evals iterations. This function
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will simply output the best x it has seen if it runs out of iterations.
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!*/
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{
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DLIB_CASSERT(x.size() == x_lower.size() && x_lower.size() == x_upper.size() && x.size() > 0,
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"\t double find_optimal_parameters()"
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