def test_addtick4(self):
""" simulate the processing of a large period of ticks
the corresponding number of candles for each timeframe should
be generated
"""
# candleCountKnown = {"M1": 6, "M5": 1,
# "M15": 1, "H1": 1, "H4": 1, "D": 1}
candleCountKnown = {"M1": 927, "M5": 187,
"M15": 63, "H1": 16, "H4": 5, "D": 2}
candleCountReal = {}
for G in candleCountKnown.keys():
cf = CandleFactory("DE30_EUR", G)
n = 0
with open(TICKDATA) as I:
for tick in I:
if tick[0] == '#':
continue
r = cf.processTick(StreamRecord(tick))
if r:
n += 1
candleCountReal.update({G: n})
self.assertEqual(candleCountKnown, candleCountReal)
def test_numerical_granularity(self):
""" initialize a timeframe, diff between end - start should
correspond with the numerical equivalent of the granularity
"""
cft = 0
grt = 0
for G in ["M1", "M5", "M15", "H1"]:
testdata = test_ticks[G]
cf = CandleFactory("DE30_EUR", G)
r = cf.processTick(StreamRecord(testdata[0]))
cft += (cf.end - cf.start)
grt += granularity_to_time(G)
self.assertEqual(cft, grt)
def test_frames(self):
""" ticks that make a timeframe : atEndOfTimeFrame
candle data should be returned
perform this for given granularities
"""
self.maxDiff = None
for F in ["M1", "M5", "M15", "H1"]:
testdata = test_ticks[F]
candle_factory = CandleFactory("DE30_EUR", F,
processingMode='atEndOfTimeFrame')
res = []
for T in testdata:
r = candle_factory.processTick(StreamRecord(T))
res.append(r)
self.assertEqual(res, [None, None, None, None, None, candles[F]])