Add python improvement examples

Author: stefpiatek

improvement/boids.py

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+"""
+A deliberately bad implementation of 
+[Boids](http://dl.acm.org/citation.cfm?doid=37401.37406)
+for use as an exercise on refactoring.
+
+This code simulates the swarming behaviour of bird-like objects ("boids").
+"""
+
+from matplotlib import pyplot as plt
+from matplotlib import animation
+
+import random
+
+boids_x=[random.uniform(-450,50.0) for x in range(50)]
+boids_y=[random.uniform(300.0,600.0) for x in range(50)]
+boid_x_velocities=[random.uniform(0,10.0) for x in range(50)]
+boid_y_velocities=[random.uniform(-20.0,20.0) for x in range(50)]
+boids=(boids_x,boids_y,boid_x_velocities,boid_y_velocities)
+
+def update_boids(boids):
+    xs,ys,xvs,yvs=boids
+    # Fly towards the middle
+    for i in range(len(xs)):
+        for j in range(len(xs)):
+            xvs[i]=xvs[i]+(xs[j]-xs[i])*0.01/len(xs)
+    for i in range(len(xs)):
+        for j in range(len(xs)):
+            yvs[i]=yvs[i]+(ys[j]-ys[i])*0.01/len(xs)
+    # Fly away from nearby boids
+    for i in range(len(xs)):
+        for j in range(len(xs)):
+            if (xs[j]-xs[i])**2 + (ys[j]-ys[i])**2 < 100:
+                xvs[i]=xvs[i]+(xs[i]-xs[j])
+                yvs[i]=yvs[i]+(ys[i]-ys[j])
+    # Try to match speed with nearby boids
+    for i in range(len(xs)):
+        for j in range(len(xs)):
+            if (xs[j]-xs[i])**2 + (ys[j]-ys[i])**2 < 10000:
+                xvs[i]=xvs[i]+(xvs[j]-xvs[i])*0.125/len(xs)
+                yvs[i]=yvs[i]+(yvs[j]-yvs[i])*0.125/len(xs)
+    # Move according to velocities
+    for i in range(len(xs)):
+        xs[i]=xs[i]+xvs[i]
+        ys[i]=ys[i]+yvs[i]

improvement/trees.py

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+"""This code produces a tree-like plot."""
+
+from math import sin, cos
+from matplotlib import pyplot as plt
+s=1
+d=[[0,1,0]]
+plt.plot([0,0],[0,1])
+for i in range(5):
+    n=[]
+    for j in range(len(d)):
+        n.append([d[j][0]+s*sin(d[j][2]-0.1), d[j][1]+s*cos(d[j][2]-0.1), d[j][2]-0.1])
+        n.append([d[j][0]+s*sin(d[j][2]+0.1), d[j][1]+s*cos(d[j][2]+0.1), d[j][2]+0.1])
+        plt.plot([d[j][0], n[-2][0]],[d[j][1], n[-2][1]])
+        plt.plot([d[j][0], n[-1][0]],[d[j][1], n[-1][1]])
+    d=n
+    s*=0.6
+plt.savefig('tree.png')