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)