from qstkutil import timeutil as tu
from qstkutil import pseries as ps
import pandas
# Set the list of stocks for us to look at
# symbols= list()
# symtoplot = 'VZ'
# symbols.append(symtoplot)
# symbols.append('IBM')
# symbols.append('GOOG')
symbols = list(np.loadtxt('allsyms.csv',dtype='str',delimiter=',',
comments='#',skiprows=0))
# Set start and end boundary times. They must be specified in Unix Epoch
tsstart = tu.ymd2epoch(2008,1,1)
tsend = tu.ymd2epoch(2008,12,31)
# Get the data from the data store
storename = "Norgate" # get data from our daily prices source
fieldname = "close" # adj_open, adj_close, adj_high, adj_low, close, volume
closes = ps.getDataMatrixFromData(storename,fieldname,symbols,tsstart,tsend)
cldata = closes.values
cldata[cldata<=4.0] = 1.0
cldata[cldata>4.0] = 0
cldata[isnan(cldata)]= 0
lows = sum(cldata,axis=0)
lownames = array(closes.cols())[lows>0]
from qstkutil import timeutil as tu
from qstkutil import pseries as ps
import pandas
# Set the list of stocks for us to look at
# symbols= list()
# symtoplot = 'VZ'
# symbols.append(symtoplot)
# symbols.append('IBM')
# symbols.append('GOOG')
symbols = list(np.loadtxt('allsyms.csv',dtype='str',delimiter=',',
comments='#',skiprows=0))
# Set start and end boundary times. They must be specified in Unix Epoch
tsstart = tu.ymd2epoch(2008,1,1)
tsend = tu.ymd2epoch(2008,12,31)
# Get the data from the data store
storename = "Norgate" # get data from our daily prices source
fieldname = "close" # adj_open, adj_close, adj_high, adj_low, close, volume
closes = ps.getDataMatrixFromData(storename,fieldname,symbols,tsstart,tsend)
cldata = closes.values
cldata[cldata<=4.0] = 1.0
cldata[cldata>4.0] = 0
cldata[isnan(cldata)]= 0
lows = sum(cldata,axis=0)
lownames = array(closes.cols())[lows>0]
# imports
import matplotlib.pyplot as plt
from pylab import *
from qstkutil import DataAccess as da
from qstkutil import timeutil as tu
from qstkutil import timeseries as ts
# Set the list of stocks for us to look at
symbols= list()
symbols = list(np.loadtxt('example-syms.csv',dtype='str',delimiter=',',
comments='#',skiprows=0))
symbols.append("IBM")
#symbols.append("BLAH") # uncomment this line to see what happens
# Set start and end boundary times. They must be specified in Unix Epoch
tsstart = tu.ymd2epoch(2008,1,1)
tsend = tu.ymd2epoch(2010,1,1)
# Get the data from the data store
storename = "Norgate" # get data from our daily prices source
fieldname = "adj_close" # adj_open, adj_close, adj_high, adj_low, close, volume
adjcloses = ts.getTSFromData(storename,fieldname,symbols,tsstart,tsend)
# Print out a bit of the data
print "The prices are: "
print symbols
print adjcloses.values
# Convert the timestamps to dates for the plot
dates = []
for ts in adjcloses.timestamps:
# Set the list of stocks for us to look at
symbols= list()
symbols = list(np.loadtxt('example-syms.csv',dtype='str',delimiter=',',
comments='#',skiprows=0))
symbols.append("IBM")
#symbols.append("BLAH") # uncomment this line to see what happens
# Set the directories from which we will read data
QSDATA = os.environ.get('QSDATA')
listOfPaths=list()
listOfPaths.append(QSDATA + "/Processed/Norgate/Equities/US_NASDAQ/")
listOfPaths.append(QSDATA + "/Processed/Norgate/Equities/US_NYSE/")
listOfPaths.append(QSDATA + "/Processed/Norgate/Equities/US_NYSE Arca/")
# Set start and end boundary times. They must be specified in Unix Epoch
start_bound = tu.ymd2epoch(2008,1,1)
end_bound = tu.ymd2epoch(2010,1,1)
# Create the data object. Once the dates are set, this object can not give you
# data from outside this range even though it might be present in the hdf file
data= da.DataAccess(True, listOfPaths, "/StrategyData", "StrategyData",
False, symbols, start_bound, end_bound)
# Find the actual first and last timestamps
timestamps = data.getTimestampArray()
start_time = timestamps[0]
end_time = timestamps[-1]
print "first timestamp:" + str(tu.epoch2date(start_bound)) + " mapped to " + str(tu.epoch2date(start_time))
print "last timestamp:" + str(tu.epoch2date(end_bound)) + " mapped to " + str(tu.epoch2date(end_time))
