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