(use srfi-4 cmaes)

(define (minimize f N)
  (let-values (((h funvals) (init `((N .  ,N) ;; Problem dimension

				    (initialX 0.5e0)  ;; Initial search point
				    
				    (typicalX 0.0) ;; Typical search point (useful for restarts)
				    
				    (initialStandardDeviations  0.3)
				    ;; numbers should not differ by orders of magnitude
				    ;; should be roughly 1/4 of the search interval
				    ;; this number essentially influences the global 
				    ;; search ability (ie. the horizon where to search
				    ;; at all) on multimodal functions
				    
				    (stopMaxFunEvals   . 1e299) ;; max number of f-evaluations, 900*(N+3)*(N+3) is default
				    (stopMaxIter       . 1e299) ;; max number of iterations (generations), inf is default
				    
				    (stopTolFun . 1e-12) ;; stop if function value differences are 
				    ;; smaller than stopTolFun, default=1e-12
				    
				    (stopTolFunHist . 1e-13) ;; stop if function value differences of best values are 
				    ;; smaller than stopTolFunHist, default was 0
				    
				    (stopTolX . 1e-11) ;; stop if step sizes/steps in x-space are 
				    ;; smaller than TolX, default=0
				    
				    (stopTolUpXFactor . 1e3) ;; stop if std dev increases more than by TolUpXFactor, default 1e3
				    
				    (seed . 0) 
				    ))))
    
    (pp 
     (run f h funvals 
	  `((print  fewinfo    200) ;; print every 200 seconds
	    (print  few+clock  2  ) ;; clock: used processor time since start
	    (write "iter+eval+sigma+0+0+xmean"                           outcmaesxmean.dat )
	    (write "iter+eval+sigma+0+fitness+xbest"                     outcmaesxrecentbest.dat )
	    )))
    ))


;; an objective (fitness) function to be minimized 
(define (f1 x)
  (let ((N (f64vector-length x)))
    (let recur ((i 2) (sum (+ (* 1e4 (f64vector-ref x 0) (f64vector-ref x 0)) 
			      (* 1e4 (f64vector-ref x 1) (f64vector-ref x 1)) )))
      (if (< i N)
	  (recur (+ 1 i) (+ sum (* (f64vector-ref x i) (f64vector-ref x i))))
	  sum))
    ))

(minimize f1 22)