src/random-numbers.lisp @ 56edfdd18674
Poke at colors
| author | Steve Losh <steve@stevelosh.com> |
|---|---|
| date | Tue, 30 Aug 2016 12:04:52 +0000 |
| parents | 175fccc805fc |
| children | 184af4c4e8fc |
(in-package #:sand.random-numbers) ;;;; Types, etc ; (declaim (optimize (speed 1) (safety 1) (debug 3))) ; (declaim (optimize (speed 3) (safety 0) (debug 0))) (deftype positive-fixnum () `(integer 1 ,most-positive-fixnum)) (deftype negative-fixnum () `(integer ,most-negative-fixnum -1)) (deftype nonnegative-fixnum () `(integer 0 ,most-positive-fixnum)) (deftype nonpositive-fixnum () `(integer ,most-negative-fixnum 0)) ;;;; Utils (declaim (ftype (function (nonnegative-fixnum nonnegative-fixnum nonnegative-fixnum) nonnegative-fixnum) mod+) (inline mod+)) (defun mod+ (x y m) (if (<= x (- m 1 y)) (+ x y) (- x (- m y)))) ;;;; Random Number Generators (defun make-linear-congruential-rng-java (modulus multiplier increment seed) (declare (type nonnegative-fixnum seed) (type positive-fixnum modulus multiplier increment)) (let ((val (mod (logxor seed multiplier) modulus))) (dlambda (:next () (ldb (byte 32 16) ; java's j.u.Random only gives out 32 high-order bits (setf val (mod (+ (* val multiplier) increment) modulus)))) (:modulus () modulus)))) (defun make-linear-congruential-rng (modulus multiplier increment seed) (declare (type nonnegative-fixnum seed) (type positive-fixnum modulus multiplier increment)) (let ((val (mod (logxor seed multiplier) modulus))) (dlambda (:next () (setf val (mod (+ (* val multiplier) increment) modulus))) (:modulus () modulus)))) (declaim (inline rng-next rng-modulus)) (defun rng-next (generator) (funcall generator :next)) (defun rng-modulus (generator) (funcall generator :modulus)) (defparameter *generator* (make-linear-congruential-rng (expt 2 48) 25214903917 11 0)) (defun rand () (rng-next *generator*)) (defun rand-float () (float (/ (rng-next *generator*) (rng-modulus *generator*)))) ;;;; Mapping ;;; The Monte Carlo method is bad because it's biased, but it's fast. ;;; ;;; Basically we take our generator that generates say 1-8, and map the range ;;; ABC onto it: ;;; ;;; 1 2 3 4 5 6 7 8 ;;; A B C A B C A B ;;; ;;; Notice that it's not uniform. (defun monte-carlo (width) (mod (rng-next *generator*) width)) ;;; The Las Vegas method is a bit slower, but unbiased. We group the random ;;; numbers into contiguous buckets, with the last "partial bucket" being ;;; excess. If we hit that one we just loop and try again: ;;; ;;; 1 2 3 4 5 6 7 8 ;;; A A B B C C retry (defun las-vegas (width) (let* ((modulus (rng-modulus *generator*)) (bucket-width (truncate (/ modulus width)))) (iterate (for bucket = (truncate (/ (rng-next *generator*) bucket-width))) (finding bucket :such-that (< bucket width))))) (defun rand-range-bad (min max) (+ min (monte-carlo (- max min)))) (defun rand-range (min max) (+ min (las-vegas (- max min)))) ;;;; Spectral Test (defun spectral () (spit "data" (iterate (repeat 1000) (for i = (rand)) (for j :previous i) (for k :previous j) (when k (format t "~d ~d ~d~%" i j k))))) ;;;; Distributions (defun prefix-sums (list) (iterate (for i :in list) (sum i :into s) (collect s :result-type vector))) (defun frequencies (seq &key (test 'eql)) (iterate (with result = (make-hash-table :test test)) (for i :in-whatever seq) (incf (gethash i result 0)) (finally (return result)))) (defun random-weighted-list (weights n) (iterate (with sums = (prefix-sums weights)) (with max = (elt sums (1- (length sums)))) (repeat n) (collect (iterate (with r = (rand-range 0 max)) (for s :in-vector sums :with-index i) (finding i :such-that (< r s)))))) (defun random-weighted (weights) (first (random-weighted-list weights 1))) ;;;; Scratch ; (spectral)