monads+probabilities: added an -m suffix to all monad names

2 files changed, 17 insertions, 18 deletions

diff --git a/src/clojure/contrib/probabilities/dist.clj b/src/clojure/contrib/probabilities/dist.clj
index 4f9100fd..4c1d321f 100644
--- a/src/clojure/contrib/probabilities/dist.clj
+++ b/src/clojure/contrib/probabilities/dist.clj
@@ -1,7 +1,7 @@
 ;; Finite probability distributions
 
 ;; by Konrad Hinsen
-;; last updated January 30, 2009
+;; last updated February 18, 2009
 
 ;; Copyright (c) Konrad Hinsen, 2009. All rights reserved.  The use
 ;; and distribution terms for this software are covered by the Eclipse
@@ -12,7 +12,6 @@
 ;; remove this notice, or any other, from this software.
 
 (ns clojure.contrib.probabilities.dist
-  (:refer-clojure :exclude (sequence))
   (:use clojure.contrib.monads clojure.contrib.macros
 	clojure.contrib.monads clojure.contrib.def))
 
@@ -20,12 +19,12 @@
 ; distributions (e.g. there is a finite number of possible value), which
 ; are represented as maps from values to probabilities.
 
-(defmonad dist
+(defmonad dist-m
   "Monad describing computations on fuzzy quantities, represented by a finite
    probability distribution for the possible values. A distribution is
    represented by a map from values to probabilities."
   [m-result (fn m-result-dist [v]
-       {v 1})
+	      {v 1})
    m-bind   (fn m-bind-dist [mv f]
 	      (letfn [add-prob [dist [x p]]
 		        (assoc dist x (+ (get dist x 0) p))]
@@ -40,8 +39,8 @@
 ; The function normalize takes this probability out of the distribution and
 ; re-distributes its weight over the valid values.
 
-(defvar cond-dist
-  (maybe-t dist)
+(defvar cond-dist-m
+  (maybe-t dist-m)
   "Variant of the dist monad that can handle undefined values.")
 
 ; Normalization
@@ -100,7 +99,7 @@
 		  :else (assoc dist v p))]
     (reduce add-choice {} (partition 2 choices))))
 
-(with-monad dist
+(with-monad dist-m
 
   (defn certainly
     "Returns a distribution in which the single value v has probability 1."
@@ -119,7 +118,7 @@
    the predicate pred."
   [pred dist]
   (normalize-cond
-    (with-monad cond-dist
+    (with-monad cond-dist-m
       (m-bind dist (fn [v] (m-result (when (pred v) v)))))))
 
 ; Select (with equal probability) N items from a sequence
@@ -130,7 +129,7 @@
   (let [[h t] (split-at n xs)]
     (list (first t) (concat h (rest t)))))
 
-(with-monad dist
+(with-monad dist-m
 
   (defn- select-n [n xs]
     (letfn [select-1 [[s xs]]
diff --git a/src/clojure/contrib/probabilities/dist/examples.clj b/src/clojure/contrib/probabilities/dist/examples.clj
index 6fb1b5be..947f5366 100644
--- a/src/clojure/contrib/probabilities/dist/examples.clj
+++ b/src/clojure/contrib/probabilities/dist/examples.clj
@@ -27,13 +27,13 @@
 
 ; The sum of two dice using a monad comprehension
 (assert (= two-dice
-	   (domonad dist
+	   (domonad dist-m
 		    [d1 die
 		     d2 die]
 		    (+ d1 d2))))
 
 ; The two values separately, but as an ordered pair
-(domonad dist
+(domonad dist-m
   [d1 die
    d2 die]
   (if (< d1 d2) (list d1 d2) (list d2 d1)))
@@ -42,7 +42,7 @@
 (cond-prob odd? two-dice)
 
 ; A two-step experiment: throw a die, and then add 1 with probability 1/2
-(domonad dist
+(domonad dist-m
   [d die
    x (choose (/ 1 2)  d
 	     :else    (inc d))]
@@ -50,7 +50,7 @@
 
 ; The sum of n dice
 (defn dice [n]
-   (domonad dist
+   (domonad dist-m
       [ds (m-seq (replicate n die))]
       (apply + ds)))
 
@@ -84,7 +84,7 @@
 (def doors #{:A :B :C})
 
 ; A simulation of the game, step by step:
-(domonad dist
+(domonad dist-m
   [; The prize is hidden behind one of the doors.
    prize  (uniform doors)
    ; The player make his initial choice.
@@ -126,7 +126,7 @@
 
 ; Multiple evolution steps can be chained together with m-chain,
 ; since each step's input is the output of the previous step.
-(with-monad dist
+(with-monad dist-m
   (defn evolve [n tree]
     ((m-chain (replicate n evolve-1)) tree)))
 
@@ -136,7 +136,7 @@
 (evolve 2 new-tree)
 
 ; We can also get a distribution of the height only:
-(with-monad dist
+(with-monad dist-m
   ((m-lift 1 :height) (evolve 2 new-tree)))
 
 
@@ -170,7 +170,7 @@
 ; 4) Normalize the distribution for the non-nil values.
 (defn add-observation [prior observation]
   (normalize-cond
-    (domonad cond-dist
+    (domonad cond-dist-m
       [die    prior
        number (get dice die)]
       (when (= number observation) die))))
@@ -188,7 +188,7 @@
 ; With Bayesian inference, it is most efficient to eliminate choices
 ; as early as possible.
 (defn add-observations [prior observations]
-  (with-monad cond-dist
+  (with-monad cond-dist-m
     (let [n-nums #(m-seq (replicate (count observations) (get dice %)))]
       (normalize-cond
         (domonad