def updateInfo(self, item, newlinks, oldlinks):
		'''爬虫爬完之后对数据库内容进行更新'''
		cur = self.conn.cursor()
		cur.execute("SELECT wid,did FROM Websites WHERE url=?", (item['url'],))
		wid, did = cur.fetchone()
		# website记录更新
		cur.execute("UPDATE Websites SET title=?,visited=1 WHERE wid=?", (item['title'], wid,))
		# 对应的domain记录中出度也需要更新
		cur.execute("UPDATE Domains SET outdegree=outdegree+? WHERE did=?", (len(item['links']), did,))

		# 对该网页中所有链接涉及的记录进行更新
		# 外部判断未出现过的链接
		for link,domain in newlinks:
			self.insertWebsite(link, domain)

		# 外部判断出现过的链接
		for link,domain in oldlinks:
			# 对对应的domain记录入度增加
			cur.execute("UPDATE Domains SET outdegree=outdegree+1 WHERE domain=?", (domain,))
		# 写入到文件
		self.conn.commit()
def gerrity_score(self):
        """
        Gerrity Score, which weights each cell in the contingency table by its observed relative frequency.
        :return:
        """
        k = self.table.shape[0]
        n = float(self.table.sum())
        p_o = self.table.sum(axis=0) / n
        p_sum = np.cumsum(p_o)[:-1]
        a = (1.0 - p_sum) / p_sum
        s = np.zeros(self.table.shape, dtype=float)
        for (i, j) in np.ndindex(*s.shape):
            if i == j:
                s[i, j] = 1.0 / (k - 1.0) * (np.sum(1.0 / a[0:j]) + np.sum(a[j:k - 1]))
            elif i < j:
                s[i, j] = 1.0 / (k - 1.0) * (np.sum(1.0 / a[0:i]) - (j - i) + np.sum(a[j:k - 1]))
            else:
                s[i, j] = s[j, i]
        return np.sum(self.table / float(self.table.sum()) * s)