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#!/usr/bin/env python
# Some functions to load a return data for the plot demos
from numpy import fromstring, argsort, take, array, resize
import matplotlib.cbook as cbook
def get_two_stock_data():
"""
load stock time and price data for two stocks The return values
(d1,p1,d2,p2) are the trade time (in days) and prices for stocks 1
and 2 (intc and aapl)
"""
ticker1, ticker2 = 'INTC', 'AAPL'
file1 = cbook.get_sample_data('INTC.dat', asfileobj=False)
file2 = cbook.get_sample_data('AAPL.dat', asfileobj=False)
M1 = fromstring( file(file1, 'rb').read(), '<d')
M1 = resize(M1, (M1.shape[0]/2,2) )
M2 = fromstring( file(file2, 'rb').read(), '<d')
M2 = resize(M2, (M2.shape[0]/2,2) )
d1, p1 = M1[:,0], M1[:,1]
d2, p2 = M2[:,0], M2[:,1]
return (d1,p1,d2,p2)
def get_daily_data():
"""
return stock1 and stock2 instances, each of which have attributes
open, high, low, close, volume
as numeric arrays
"""
class C: pass
def get_ticker(ticker):
vals = []
datafile = cbook.get_sample_data('%s.csv'%ticker, asfileobj=False)
lines = file(datafile).readlines()
for line in lines[1:]:
vals.append([float(val) for val in line.split(',')[1:]])
M = array(vals)
c = C()
c.open = M[:,0]
c.high = M[:,1]
c.low = M[:,2]
c.close = M[:,3]
c.volume = M[:,4]
return c
c1 = get_ticker('intc')
c2 = get_ticker('msft')
return c1, c2
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