class GoldenSectionLS extends AnyRef
The GoldenSectionLS class performs a line search on f(x) to find a maximal
value for 'f'. It requires no derivatives and only one functional evaluation
per iteration. A search is conducted from 'x1' (often 0) to 'xmax'. A guess
for 'xmax' must be given, but can be made larger during the expansion phase,
that occurs before the recursive golden section search is called. It works on
scalar functions (see GoldenSectionLSTest). If starting with a vector function
'f(x)', simply define a new function 'g(y) = x0 + direction * y' (see GoldenSectionLSTest2).
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- new GoldenSectionLS(f: FunctionS2S)
- f
the scalar objective function to maximize
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- def gsection(left: Boolean, x1: Double, x2: Double, x3: Double, f2: Double): Double
A recursive golden section search requiring only one functional evaluation per call.
A recursive golden section search requiring only one functional evaluation per call. It works by comparing two center points x2 (given) and x4 computed.
- left
whether to search left (true) or right (false) side of last interval
- x1
the left-most point
- x2
the center point (.618 across for left and .382 across for right)
- x3
the right-most point
- f2
the functional value for the x2 center point
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- def printGolden(): Unit
Print the golden ratio and the golden section.
- def search(xmax: Double = 2.0, x1: Double = 0.0): Double
Perform a Line Search (LS) using the Golden Search Algorithm.
Perform a Line Search (LS) using the Golden Search Algorithm. Two phases are used: an expansion phase (moving the end-point) to find a down-up pattern, followed by a traditional golden section search.
- xmax
a rough guess for the right end-point of the line search
- x1
the left (smallest) anchor point for the search (usually 0)
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