def compute_alpha(annotations, extract=get_doc, value=lambda x:int(x)):
n = 0
d = defaultdict(list)
all_values = []
d = defaultdict(list)
for a in annotations:
for k, v in extract(a, value):
d[k].append(v)
all_values.append(v)
n += 1
return _compute_alpha(n, d, all_values)
def compute_alpha(annotations, key=get_query, value=get_score):
def iter_pairs(l):
size = len(l)
if size >= 2:
for i in range(size - 1):
for j in range(i + 1, size):
yield l[i], l[j]
def dist(x, y):
return (x - y) * (x - y)
annotations = list(annotations)
n = 0
d = defaultdict(list)
all_values = []
for a in annotations:
query = key(a)
d[query].append(value(a))
all_values.append(value(a))
n += 1
return _compute_alpha(n, d, all_values)
def compute_alpha(annotations, key=get_query, value=get_score):
def iter_pairs(l):
size = len(l)
if size >= 2:
for i in range(size-1):
for j in range(i+1, size):
yield l[i], l[j]
def dist(x, y):
return (x - y) * (x - y)
annotations = list(annotations)
n = 0
d = defaultdict(list)
all_values = []
for a in annotations:
query = key(a)
d[query].append(value(a))
all_values.append(value(a))
n += 1
return _compute_alpha(n, d, all_values)
