**'cern.jet.math.tdouble.DoubleFunctions'**Java class

## Class DoubleFunctions

- java.lang.Object
- cern.jet.math.tdouble.DoubleFunctions

public class DoubleFunctionsextends Object

Function objects to be passed to generic methods. Contains the functions of`Math`

as function objects, as well as a few more basic functions.Function objects conveniently allow to express arbitrary functions in a generic manner. Essentially, a function object is an object that can perform a function on some arguments. It has a minimal interface: a method

`apply`that takes the arguments, computes something and returns some result value. Function objects are comparable to function pointers in C used for call-backs.Unary functions are of type

`DoubleFunction`

, binary functions of type`DoubleDoubleFunction`

. All can be retrieved via`public static final`variables named after the function. Unary predicates are of type`DoubleProcedure`

, binary predicates of type`DoubleDoubleProcedure`

. All can be retrieved via`public static final`variables named`isXXX`.Binary functions and predicates also exist as unary functions with the second argument being fixed to a constant. These are generated and retrieved via factory methods (again with the same name as the function). Example:

`Functions.pow`gives the function`a`.^{b}`Functions.pow.apply(2,3)==8`.`Functions.pow(3)`gives the function`a`.^{3}`Functions.pow(3).apply(2)==8`.

`bindArg1(DoubleDoubleFunction,double)`

and`bindArg2(DoubleDoubleFunction,double)`

. The order of arguments can be swapped so that the first argument becomes the second and vice-versa. See method`swapArgs(DoubleDoubleFunction)`

. Example:`Functions.pow`gives the function`a`.^{b}`Functions.bindArg2(Functions.pow,3)`gives the function`x`.^{3}`Functions.bindArg1(Functions.pow,3)`gives the function`3`.^{x}`Functions.swapArgs(Functions.pow)`gives the function`b`.^{a}

Even more general, functions can be chained (composed, assembled). Assume we have two unary functions

`g`and`h`. The unary function`g(h(a))`applying both in sequence can be generated via`chain(DoubleFunction,DoubleFunction)`

:`Functions.chain(g,h);`

`f`. The binary function`g(f(a,b))`can be generated via`chain(DoubleFunction,DoubleDoubleFunction)`

:`Functions.chain(g,f);`

`f(g(a),h(b))`can be generated via`chain(DoubleDoubleFunction,DoubleFunction,DoubleFunction)`

:`Functions.chain(f,g,h);`

`sin(a) + cos`can be specified as follows:^{2}(b)`chain(plus,sin,chain(square,cos));`

new DoubleDoubleFunction() { public final double apply(double a, double b) { return Math.sin(a) + Math.pow(Math.cos(b), 2); } }

For aliasing see

`functions`

. Try this// should yield 1.4399560356056456 in all cases double a = 0.5; double b = 0.2; double v = Math.sin(a) + Math.pow(Math.cos(b), 2); System.out.println(v); Functions F = Functions.functions; DoubleDoubleFunction f = F.chain(F.plus, F.sin, F.chain(F.square, F.cos)); System.out.println(f.apply(a, b)); DoubleDoubleFunction g = new DoubleDoubleFunction() { public double apply(double a, double b) { return Math.sin(a) + Math.pow(Math.cos(b), 2); } }; System.out.println(g.apply(a, b));

### Performance

Surprise. Using modern non-adaptive JITs such as SunJDK 1.2.2 (java -classic) there seems to be no or only moderate performance penalty in using function objects in a loop over traditional code in a loop. For complex nested function objects (e.g.`F.chain(F.abs,F.chain(F.plus,F.sin,F.chain(F.square,F.cos)))`) the penalty is zero, for trivial functions (e.g.`F.plus`) the penalty is often acceptable.Iteration Performance [million function evaluations per second]

Pentium Pro 200 Mhz, SunJDK 1.2.2, NT, java -classic,30000000 iterations

3000000 iterations (10 times less) `F.plus``a+b``F.chain(F.abs,F.chain(F.plus,F.sin,F.chain(F.square,F.cos)))``Math.abs(Math.sin(a) + Math.pow(Math.cos(b),2))`10.8 29.6 0.43 0.35

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