def distance(screen1, screen2, weights):
"""
Compute the distance between two screens (from Newman et al. 2010).
:param screen screen1: First screen
:param screen screen2: Second screen
:param array weights: weights
:returns: The distance score between 0 and 1
"""
sum1 = 0.0
for c1 in screen1.cocktails:
mini = 100000000
for c2 in screen2.cocktails:
distance = metric.distance(c1, c2, weights)
if mini > distance:
mini = distance
sum1 += mini
sum2 = 0.0
for c1 in screen2.cocktails:
mini = 100000000
for c2 in screen1.cocktails:
distance = metric.distance(c1, c2, weights)
if mini > distance:
mini = distance
sum2 += mini
score = ( (sum1/float(len(screen1))) + (sum2/float(len(screen2))) )/2.0
return score
def internal_similarity(s, weights):
"""
Compute the internal diversity within a screen (from Newman et al. 2010).
:param screen s: The screen
:param array weights: weights
:returns: The diversity score between 0 and 1
"""
sum_avg = 0
for c1 in s.cocktails:
isum = 0
n = 0
for c2 in s.cocktails:
isum += metric.distance(c1, c2, weights)
n += 1
sum_avg += isum / n
return sum_avg / len(s)
