虽然我以前在函数式语言中做了一些少量的编程,但我刚开始玩Clojure。由于在学习一门新语言时做同样的“Hello World”程序会变老,我决定通过Cinder“Hello,Cinder”教程,将其翻译成Clojure和Quil 。在本教程的Chapter 5中,您遇到了这个C ++片段来计算粒子列表的加速度:
void ParticleController::repulseParticles() {
for( list<Particle>::iterator p1 = mParticles.begin(); p1 != mParticles.end(); ++p1 ) {
list<Particle>::iterator p2 = p1;
for( ++p2; p2 != mParticles.end(); ++p2 ) {
Vec2f dir = p1->mLoc - p2->mLoc;
float distSqrd = dir.lengthSquared();
if( distSqrd > 0.0f ){
dir.normalize();
float F = 1.0f/distSqrd;
p1->mAcc += dir * ( F / p1->mMass );
p2->mAcc -= dir * ( F / p2->mMass );
}
}
}
}
在我看来,这段代码有一个非常重要的特征:它正在对粒子对进行比较并更新两个粒子,然后在将来跳过相同的组合。这对于性能原因非常重要,因为这段代码每帧执行一次,并且在任何给定时间屏幕上可能有数千个粒子(比我更了解大O的人可能会告诉你这个方法之间的区别并多次迭代每个组合。)
作为参考,我将展示我的想法。你应该注意到下面的代码一次只更新一个粒子,所以我做了很多“额外”的工作,比较相同的粒子两次。 (注意:为简洁起见,省略了一些方法,例如“normalize”):
(defn calculate-acceleration [particle1 particle2]
(let [x-distance-between (- (:x particle1) (:x particle2))
y-distance-between (- (:y particle1) (:y particle2))
distance-squared (+ (* x-distance-between x-distance-between) (* y-distance-between y-distance-between))
normalized-direction (normalize x-distance-between y-distance-between)
force (if (> distance-squared 0) (/ (/ 1.0 distance-squared) (:mass particle1)) 0)]
{:x (+ (:x (:accel particle1)) (* (first normalized-direction) force)) :y (+ (:y (:accel particle1)) (* (second normalized-direction) force))}))
(defn update-acceleration [particle particles]
(assoc particle :accel (reduce #(do {:x (+ (:x %) (:x %2)) :y (+ (:y %) (:y %2))}) {:x 0 :y 0} (for [p particles :when (not= particle p)] (calculate-acceleration particle p)))))
(def particles (map #(update-acceleration % particles) particles))
更新:所以这就是我最终提出的,万一有人感兴趣:
(defn get-new-accelerations [particles]
(let [particle-combinations (combinations particles 2)
new-accelerations (map #(calculate-acceleration (first %) (second %)) particle-combinations)
new-accelerations-grouped (for [p particles]
(filter #(not (nil? %))
(map
#(cond (= (first %) p) %2
(= (second %) p) (vec-scale %2 -1))
particle-combinations new-accelerations)))]
(map #(reduce (fn [accum accel] (if (not (nil? accel)) (vec-add accel accum))) {:x 0 :y 0} %)
new-accelerations-grouped)))
基本上,这个过程是这样的:
现在的问题是,这比我之前做的更快吗? (我还没有测试过,但我最初的猜测是没办法的。)
更新2: 这是我提出的另一个版本。我认为这个版本在各个方面都比我上面发布的版本好得多:它使用瞬态数据结构来提高新列表的性能/易变性,并使用loop / recur。它应该比我上面发布的示例快得多,但我还没有测试过验证。
(defn transient-particle-accelerations [particles]
(let [num-of-particles (count particles)]
(loop [i 0 new-particles (transient particles)]
(if (< i (- num-of-particles 1))
(do
(loop [j (inc i)]
(if (< j num-of-particles)
(let [p1 (nth particles i)
p2 (nth particles j)
new-p1 (nth new-particles i)
new-p2 (nth new-particles j)
new-acceleration (calculate-acceleration p1 p2)]
(assoc! new-particles i (assoc new-p1 :accel (vec-add (:accel new-p1) new-acceleration)))
(assoc! new-particles j (assoc new-p2 :accel (vec-add (:accel new-p2) (vec-scale new-acceleration -1))))
(recur (inc j)))))
(recur (inc i) new-particles))
(persistent! new-particles)))))
答案 0 :(得分:3)
def
- 粒子似乎不太正确 - 我猜测使用ref存储世界状态,然后在循环之间更新ref ,会更有意义。
对于算法问题,对我来说这是clojure.math.combinatorics的用例。如下所示:
(require '[clojure.math.combinatorics :as combinatorics])
(defn update-particles [particles]
(apply concat
(for [[p1 p2] (combinatorics/combinations particles 2)
:let [x-distance-between (- (:x p1) (:x p2))
y-distance-between (- (:y p1) (:y p2))
distance-squared (+ (* x-distance-between x-distance-between)
(* y-distance-between y-distance-between))
normalized-direction (normalize x-distance-between y-distance-between)
p1-force (if (> distance-squared 0)
(/ (/ 1.0 distance-squared) (:mass p1))
0)]]
[{:x (+ (:x (:accel p1)) (* (first normalized-direction) p1-force))
:y (+ (:y (:accel p1)) (* (first normalized-direction) p1-force))}
{:x (+ (:x (:accel p2)) (* (first normalized-direction) p2-force))
:y (+ (:y (:accel p2)) (* (first normalized-direction) p2-force))}]))
...你仍然需要减少,但这样我们就会将两个粒子的更新值拉出循环。
答案 1 :(得分:1)
因此,基本上,您想要选择所有大小为2的子集,然后对每个这样的对进行操作?
这是一个带有
的组合数据库http://richhickey.github.com/clojure-contrib/combinatorics-api.html combinations
function
Usage: (combinations items n) All the unique
ways of taking n different elements from items
使用它来生成列表,然后迭代它。