def get_disagreement(self, ock):
ndotdot = sum([
sum([ock[f1][f2] for f2 in self.flat_data])
for f1 in self.flat_data
])
distanced_ock_sum = sum([
sum([ock[f1][f2] * Util.distance(f1, f2) for f2 in self.flat_data])
for f1 in self.flat_data
])
return distanced_ock_sum / ndotdot
def test_distance(self):
print
print "{0}testing distance{0}".format("*" * 6)
d1 = ()
print "distance({{}}, {{}}) = {0}".format(Util.distance(d1, d1))
self.assertEquals(Util.distance(d1, d1), 0, "distance({Empty}, {Empty}) = 0")
d2 = ("Funk", "Rock")
print "distance({{Funk}}, {{Rock}}) = {0}".format(Util.distance(d1, d2))
self.assertEquals(Util.distance(d1, d2), 1.0, "distance({Empty}, {Rock, Funk}) = 1")
d3 = ("Funk", "Rock")
d4 = ("Funk", "Jazz", "Rock")
print "distance({{Funk, Rock}}, {{Funk, Rock, Jazz}}) = {0}".format(Util.distance(d3, d4))
self.assertAlmostEqual(Util.distance(d3, d4), 0.2, 5, "distance({Funk, Rock}, {Funk, Rock, Jazz}) = 0.2")
self.assertEquals(Util.distance(d3, d4), Util.distance(d4, d3), "distance is symmetric")
print "{0}tested distance{0}".format("*" * 6)
print
def get_single_case_ed(self, item1, item2, p, n, d):
"""
@param item1: multi-value item1
@param item2: multi-value item2
@param p: output of get_num_p
@param n: output of get_single_item_n
@param d: output of get_ways_of_pair
@return: expected disagreement of item1 and item2 (note: this is not symmetric, i.e., get_single_case_ed(item1, item2) != get_single_case_ed(item2, item1)
"""
def get_complementary_set(t):
return [x for x in n.iterkeys() if x not in t]
def intersection(t, s):
return [tt for tt in t if tt in s]
if not p.has_key(len(item1)):
return 0
else:
ratio1 = p[len(item1)]
if not p.has_key(len(item2)):
return 0
else:
ratio2 = p[len(item2)]
if d[len(item1)][len(item2)] == 0:
denominator = 1
else:
denominator = d[len(item1)][len(item2)]
if item1 == () and item2 == ():
numerator = n[()] * (n[()] - 1)
elif item1 == ():
numerator = n[()] * Util.prod([n[x] for x in item2])
elif item2 == ():
numerator = Util.prod([n[x] for x in item1]) * n[()]
else:
numerator = Util.prod([n[x] for x in item1]) * Util.prod([
n[x] for x in intersection(item2, get_complementary_set(item1))
]) * Util.prod([(n[x] - 1) for x in intersection(item1, item2)])
delta = Util.distance(item1, item2)
return ratio1 * ratio2 * numerator * delta / denominator
def get_single_case_ed(self, item1, item2, p, n, d):
"""
@param item1: multi-value item1
@param item2: multi-value item2
@param p: output of get_num_p
@param n: output of get_single_item_n
@param d: output of get_ways_of_pair
@return: expected disagreement of item1 and item2 (note: this is not symmetric, i.e., get_single_case_ed(item1, item2) != get_single_case_ed(item2, item1)
"""
def get_complementary_set(t):
return [x for x in n.iterkeys() if x not in t]
def intersection(t, s):
return [tt for tt in t if tt in s]
if not p.has_key(len(item1)):
return 0
else:
ratio1 = p[len(item1)]
if not p.has_key(len(item2)):
return 0
else:
ratio2 = p[len(item2)]
if d[len(item1)][len(item2)] == 0:
denominator = 1
else:
denominator = d[len(item1)][len(item2)]
if item1 == () and item2 == ():
numerator = n[()] * (n[()] - 1)
elif item1 == ():
numerator = n[()] * Util.prod([n[x] for x in item2])
elif item2 == ():
numerator = Util.prod([n[x] for x in item1]) * n[()]
else:
numerator = Util.prod([n[x] for x in item1]) * Util.prod([n[x] for x in intersection(item2, get_complementary_set(item1))]) * Util.prod([(n[x] - 1) for x in intersection(item1, item2)])
delta = Util.distance(item1, item2)
return ratio1 * ratio2 * numerator * delta / denominator
def test_distance(self):
print
print "{0}testing distance{0}".format("*" * 6)
d1 = ()
print "distance({{}}, {{}}) = {0}".format(Util.distance(d1, d1))
self.assertEquals(Util.distance(d1, d1), 0,
"distance({Empty}, {Empty}) = 0")
d2 = ("Funk", "Rock")
print "distance({{Funk}}, {{Rock}}) = {0}".format(Util.distance(
d1, d2))
self.assertEquals(Util.distance(d1, d2), 1.0,
"distance({Empty}, {Rock, Funk}) = 1")
d3 = ("Funk", "Rock")
d4 = ("Funk", "Jazz", "Rock")
print "distance({{Funk, Rock}}, {{Funk, Rock, Jazz}}) = {0}".format(
Util.distance(d3, d4))
self.assertAlmostEqual(
Util.distance(d3, d4), 0.2, 5,
"distance({Funk, Rock}, {Funk, Rock, Jazz}) = 0.2")
self.assertEquals(Util.distance(d3, d4), Util.distance(d4, d3),
"distance is symmetric")
print "{0}tested distance{0}".format("*" * 6)
print
def get_disagreement(self, ock):
ndotdot = sum([sum([ock[f1][f2] for f2 in self.flat_data]) for f1 in self.flat_data])
distanced_ock_sum = sum([sum([ock[f1][f2] * Util.distance(f1, f2) for f2 in self.flat_data]) for f1 in self.flat_data])
return distanced_ock_sum / ndotdot
