def calcAction(self):
vec.normalize(vec.randomVec(self.action.direction), self.action.direction)
self.action.speed = util.clamp(util.uniform(), 0.25, 1.0)
def calcAction(self):
vec.normalize(vec.randomVec(self.action.direction), self.action.direction)
self.action.speed = util.clamp(util.uniform(), 0.25, 1.0)
def main():
nump,n,lower,upper = 10,2,-10,10
points = []
print "\nPOINTS\n"
for i in range(nump):
invalid = True
while invalid:
v = vec.randomVec(n,lower,upper)
if v.norm() != 0 and v not in points:
points.append(v)
print str(points[i]) + ",",
invalid = False
print ""
print "\nLEADER ALGORITHM\n"
t = 0.65
print "Cosine Similarity, t = " + str(t),
cleader0 = leader(points, t, vec.cos, 1, True)
print ""
for c in cleader0:
print "C:" + str(c)
t = 7
print "Euclidean Distance, t = " + str(t),
cleader1 = leader(points, t, vec.euclid, -1, True)
print ""
for c in cleader1:
print "C:" + str(c)
print "\nK-MEANS\n"
k = 4
print "Cosine Similarity",
ckmeans0 = kmeans(points,k,vec.cos,1,True)
print ""
for c in ckmeans0:
print "C:" + str(c)
print "Euclidean Distance",
ckmeans1 = kmeans(points,k,vec.euclid,-1,True)
print ""
for c in ckmeans1:
print "C:" + str(c)
print "\nAGGLOMORATIVE\n"
t = threshold(points, .4, vec.cos)
link = 's'
print "Cosine Similarity, " + link + ", t = " + str(t),
cagglo0 = agglomorate(points,link,t,vec.cos,1, True)
print ""
for c in cagglo0:
print "C:" + str(c)
t = threshold(points, .5, vec.euclid)
link = 'c'
print "Euclidean Distance, " + link + ", t = " + str(t),
cagglo1 = agglomorate(points,link,t,vec.euclid,-1, True)
print ""
for c in cagglo1:
print "C:" + str(c)
print "\nAGGREGATION\n"
t = threshold(points, .9, vec.euclid)
combined = aggregate(ckmeans1, cagglo1, t, vec.euclid, -1, True)
print ""
for c in combined:
print "C:" + str(c)
print "\nAGGREGATION2\n"
combined2 = aggregate2(ckmeans1, cagglo1, t, vec.euclid, -1, True)
print ""
for c in combined2:
print "C:" + str(c)
print "\nPRUNE\n"
pruned = prune(points,combined2, vec.euclid, -1)
for c in pruned:
print "C:" + str(c)
return points, [ cleader0, cleader1, ckmeans0, ckmeans1, cagglo0, cagglo1 ], combined