def getZscore(conn,cur_date,stock_index,cur_diff,duration): cur = conn.cursor() scores = [] sql = "select one_day_change from t_enriched_bloomberg_prices where post_date<? and name = ? order by post_date desc limit ?" cur.execute(sql,(cur_date,stock_index,duration)) rows = cur.fetchall() for row in rows: scores.append(row[0]) zscore = calculator.calZscore(scores, cur_diff) return zscore
def getZscore(curDate,stockIndex,curDiff,duration): con = common.getDBConnection() cur = con.cursor() scores = [] sql = "select one_day_change from t_daily_stockindices where date<? and stock_index = ? order by date desc limit ?" cur.execute(sql,(curDate,stockIndex,duration)) rows = cur.fetchall() for row in rows: scores.append(row[0]) zscore = calculator.calZscore(scores, curDiff) return zscore
def getZscore(curDate,stockIndex,curDiff,duration): global con global cur scores = [] sql = "select one_day_difference from t_daily_stockindex where date<? and stock_index = ? order by date desc limit ?" cur.execute(sql,(curDate,stockIndex,duration)) rows = cur.fetchall() for row in rows: scores.append(row[0]) zscore = calculator.calZscore(scores, curDiff) return zscore
import json import numpy import nltk import sys from Util import calculator import sqlite3 as lite news = open('D:/filterBloombergArray.json') jsonNews = json.load(news,encoding='ISO-8859-1') print calculator.calZscore([1,1,1,1,1],1) clusterDis = json.load(open("d:/embers/financemodel/clusterDistribution.json")) print clusterDis result = open("d:/embers/financemodel/TestPredict.txt") lines = result.readlines() for line in lines: # print line tokens = [token.replace("\t","") for token in line.strip().split("\t")] date = tokens[1] pClusster = tokens[4] print date,pClusster con = None try: con = lite.connect("d:/sqlite/embers.db") cur = con.cursor() cur.execute('select sqlite_version()')
import json import numpy import nltk import sys from Util import calculator import sqlite3 as lite news = open('D:/filterBloombergArray.json') jsonNews = json.load(news, encoding='ISO-8859-1') print calculator.calZscore([1, 1, 1, 1, 1], 1) clusterDis = json.load(open("d:/embers/financemodel/clusterDistribution.json")) print clusterDis result = open("d:/embers/financemodel/TestPredict.txt") lines = result.readlines() for line in lines: # print line tokens = [token.replace("\t", "") for token in line.strip().split("\t")] date = tokens[1] pClusster = tokens[4] print date, pClusster con = None try: con = lite.connect("d:/sqlite/embers.db") cur = con.cursor() cur.execute('select sqlite_version()') data = cur.fetchone() print "Sqlite Version: %s" % data