)
                x += 1
    outfile.write("</edges>\n")
    outfile.write("</graph></gexf>\n")
    outfile.close()


# Get TFIDF table list
tfidf_tblist = obj_db.getTFIDFTableList()

# Get Segmented table list
seg_tblist = obj_db.getTableList()
print seg_tblist
for i in range(5):
    dict_tfidf = {}
    results = mysql.queryrows("SELECT * FROM `" + tfidf_tblist[i] + "`")
    for row in results:
        list_pairs = row[1].split("|")
        for pair in list_pairs:
            term_tfidf = pair.split("@")
            term = term_tfidf[0]
            tfidf = float(term_tfidf[1])
            if term in dict_tfidf:
                continue
            else:
                dict_tfidf[term] = tfidf

    # Remove number and not english word in dictionary
    for key, val in dict_tfidf.items():
        if verifyEngNum(key) == 1 or verifyEngNum(key) == 3:
            dict_tfidf.pop(key)
            continue
        else:
            # Init ang reset feature and category dataset
            avg_feature = []
            avg_category = []
            max_feature = []
            max_category = []

            # Rest All value to 0.0 in dictionary
            dict_avg_zero = dict.fromkeys(dict_flted_avgchi, 0.0)
            dict_max_zero = dict.fromkeys(dict_flted_maxchi, 0.0)

            sql_getContent = "SELECT `ClsNo1`, `ScoreContent` FROM `" + tfidf_viewlist[view_num] + "`"

            # Get All result
            view_result = mysql.queryrows(sql_getContent)

            for view_row in view_result:
                view_content = view_row[1]
                term_tfidf_list = view_content.split("|")
                avg_tfidf_score_vactor = getTFIDFScoreVector(dict_avg_zero, term_tfidf_list)
                max_tfidf_score_vextor = getTFIDFScoreVector(dict_max_zero, term_tfidf_list)

                avg_feature.append(avg_tfidf_score_vactor)
                avg_category.append(int(view_row[0]))
                max_feature.append(max_tfidf_score_vextor)
                max_category.append(int(view_row[0]))

            print 'AVG Feature dataset: ' + str(len(avg_feature))
            print 'AVG Category dataset: ' + str(len(avg_category))
            print 'MAX Feature dataset: ' + str(len(max_feature))
def pairReliablility(user1, user2, coder_clsfi):
    len_n = len(coder_clsfi)
    M = 0
    for key, value in coder_clsfi.items():
        if value[user1] == value[user2]:
            M += 1
    rebilty = (2.0 * M) / (2.0 * len_n)
    print "User: "******", " + str(user2)
    print "M (Number of totally agreement): " + str(M)
    print "N1,N2 (Should agree with number): " + str(len_n)
    print "Mutual consent degree = 2M/(N1+N2): " + str(rebilty) + "\n\n"

sql_get = "SELECT `SamplingNo`, `ClsNo1`, `UserId` FROM `CoderCompare` ORDER BY `CoderCompare`.`SamplingNo` ASC"

result = mysql.queryrows(sql_get)

coder_clsfi = {}

for row in result:
    sno = int(row[0])
    cls = int(row[1])
    user = int(row[2])
    if sno in coder_clsfi:
        coder_clsfi[sno][user] = cls
    else:
        coder_clsfi[sno] = {}
        coder_clsfi[sno][user] = cls

print coder_clsfi